Legends Lecture Series

NASA Image and Video Library

2011-10-13

Stennis Space Center Director Patrick Scheuermann (right) welcomes former leaders to the fourth Legends Lecture Series presentation Oct. 13. Stennis launched the series in November 2010 as part of a yearlong 50th anniversary celebration. The recent session focused on past rocket engine test work. Visiting Stennis legends were: (l to r) Dave Geiger, Patrick Mooney, Boyce Mix, J. Stephens Dick, James Taylor and Marvin Carpenter.

Multiple Indicator Stationary Time Series Models.

ERIC Educational Resources Information Center

Sivo, Stephen A.

2001-01-01

Discusses the propriety and practical advantages of specifying multivariate time series models in the context of structural equation modeling for time series and longitudinal panel data. For time series data, the multiple indicator model specification improves on classical time series analysis. For panel data, the multiple indicator model…

Volatility of linear and nonlinear time series

NASA Astrophysics Data System (ADS)

Kalisky, Tomer; Ashkenazy, Yosef; Havlin, Shlomo

2005-07-01

Previous studies indicated that nonlinear properties of Gaussian distributed time series with long-range correlations, ui , can be detected and quantified by studying the correlations in the magnitude series ∣ui∣ , the “volatility.” However, the origin for this empirical observation still remains unclear and the exact relation between the correlations in ui and the correlations in ∣ui∣ is still unknown. Here we develop analytical relations between the scaling exponent of linear series ui and its magnitude series ∣ui∣ . Moreover, we find that nonlinear time series exhibit stronger (or the same) correlations in the magnitude time series compared with linear time series with the same two-point correlations. Based on these results we propose a simple model that generates multifractal time series by explicitly inserting long range correlations in the magnitude series; the nonlinear multifractal time series is generated by multiplying a long-range correlated time series (that represents the magnitude series) with uncorrelated time series [that represents the sign series sgn(ui) ]. We apply our techniques on daily deep ocean temperature records from the equatorial Pacific, the region of the El-Ninõ phenomenon, and find: (i) long-range correlations from several days to several years with 1/f power spectrum, (ii) significant nonlinear behavior as expressed by long-range correlations of the volatility series, and (iii) broad multifractal spectrum.

Harmonic Series Meets Fibonacci Sequence

ERIC Educational Resources Information Center

Chen, Hongwei; Kennedy, Chris

2012-01-01

The terms of a conditionally convergent series may be rearranged to converge to any prescribed real value. What if the harmonic series is grouped into Fibonacci length blocks? Or the harmonic series is arranged in alternating Fibonacci length blocks? Or rearranged and alternated into separate blocks of even and odd terms of Fibonacci length?

Analysis of series resonant converter with series-parallel connection

NASA Astrophysics Data System (ADS)

Lin, Bor-Ren; Huang, Chien-Lan

2011-02-01

In this study, a parallel inductor-inductor-capacitor (LLC) resonant converter series-connected on the primary side and parallel-connected on the secondary side is presented for server power supply systems. Based on series resonant behaviour, the power metal-oxide-semiconductor field-effect transistors are turned on at zero voltage switching and the rectifier diodes are turned off at zero current switching. Thus, the switching losses on the power semiconductors are reduced. In the proposed converter, the primary windings of the two LLC converters are connected in series. Thus, the two converters have the same primary currents to ensure that they can supply the balance load current. On the output side, two LLC converters are connected in parallel to share the load current and to reduce the current stress on the secondary windings and the rectifier diodes. In this article, the principle of operation, steady-state analysis and design considerations of the proposed converter are provided and discussed. Experiments with a laboratory prototype with a 24 V/21 A output for server power supply were performed to verify the effectiveness of the proposed converter.

Visibility Graph Based Time Series Analysis

PubMed Central

Stephen, Mutua; Gu, Changgui; Yang, Huijie

2015-01-01

Network based time series analysis has made considerable achievements in the recent years. By mapping mono/multivariate time series into networks, one can investigate both it’s microscopic and macroscopic behaviors. However, most proposed approaches lead to the construction of static networks consequently providing limited information on evolutionary behaviors. In the present paper we propose a method called visibility graph based time series analysis, in which series segments are mapped to visibility graphs as being descriptions of the corresponding states and the successively occurring states are linked. This procedure converts a time series to a temporal network and at the same time a network of networks. Findings from empirical records for stock markets in USA (S&P500 and Nasdaq) and artificial series generated by means of fractional Gaussian motions show that the method can provide us rich information benefiting short-term and long-term predictions. Theoretically, we propose a method to investigate time series from the viewpoint of network of networks. PMID:26571115

Visibility Graph Based Time Series Analysis.

PubMed

Stephen, Mutua; Gu, Changgui; Yang, Huijie

2015-01-01

Network based time series analysis has made considerable achievements in the recent years. By mapping mono/multivariate time series into networks, one can investigate both it's microscopic and macroscopic behaviors. However, most proposed approaches lead to the construction of static networks consequently providing limited information on evolutionary behaviors. In the present paper we propose a method called visibility graph based time series analysis, in which series segments are mapped to visibility graphs as being descriptions of the corresponding states and the successively occurring states are linked. This procedure converts a time series to a temporal network and at the same time a network of networks. Findings from empirical records for stock markets in USA (S&P500 and Nasdaq) and artificial series generated by means of fractional Gaussian motions show that the method can provide us rich information benefiting short-term and long-term predictions. Theoretically, we propose a method to investigate time series from the viewpoint of network of networks.

Smoothing of climate time series revisited

NASA Astrophysics Data System (ADS)

Mann, Michael E.

2008-08-01

We present an easily implemented method for smoothing climate time series, generalizing upon an approach previously described by Mann (2004). The method adaptively weights the three lowest order time series boundary constraints to optimize the fit with the raw time series. We apply the method to the instrumental global mean temperature series from 1850-2007 and to various surrogate global mean temperature series from 1850-2100 derived from the CMIP3 multimodel intercomparison project. These applications demonstrate that the adaptive method systematically out-performs certain widely used default smoothing methods, and is more likely to yield accurate assessments of long-term warming trends.

Graphical Data Analysis on the Circle: Wrap-Around Time Series Plots for (Interrupted) Time Series Designs.

PubMed

Rodgers, Joseph Lee; Beasley, William Howard; Schuelke, Matthew

2014-01-01

Many data structures, particularly time series data, are naturally seasonal, cyclical, or otherwise circular. Past graphical methods for time series have focused on linear plots. In this article, we move graphical analysis onto the circle. We focus on 2 particular methods, one old and one new. Rose diagrams are circular histograms and can be produced in several different forms using the RRose software system. In addition, we propose, develop, illustrate, and provide software support for a new circular graphical method, called Wrap-Around Time Series Plots (WATS Plots), which is a graphical method useful to support time series analyses in general but in particular in relation to interrupted time series designs. We illustrate the use of WATS Plots with an interrupted time series design evaluating the effect of the Oklahoma City bombing on birthrates in Oklahoma County during the 10 years surrounding the bombing of the Murrah Building in Oklahoma City. We compare WATS Plots with linear time series representations and overlay them with smoothing and error bands. Each method is shown to have advantages in relation to the other; in our example, the WATS Plots more clearly show the existence and effect size of the fertility differential.

Test Series 2. 4: detailed test plan

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

Not Available

Test Series 2.4 comprises the fourth sub-series of tests to be scheduled as a part of Test Series 2, the second stage of the combustion research program to be carried out at the Grimethorpe Experimental Pressurized Fluidized Bed Combustion Facility. Test Series 2.1, the first sub-series of tests, was completed in February 1983, and the first part of the second sub-series, Test Series 2.3, in October 1983. Test Series 2.2 was completed in February 1984 after which the second part of Test Series 2.3 commenced. The Plan for Test Series 2.4 consists of 350 data gathering hours to be completedmore » within 520 coal burning hours. This document provides a brief description of the Facility and modifications which have been made following the completion of Test Series 2.1. No further modifications were made following the completion of the first part of Test Series 2.3 or Test Series 2.2. The operating requirements for Test Series 2.4 are specified. The tests will be performed using a UK coal (Lady Windsor), and a UK limestone (Middleton) both nominated by the FRG. Seven objectives are proposed which are to be fulfilled by thirteen test conditions. Six part load tests based on input supplied by Kraftwerk Union AG are included. The cascade is expected to be on line for each test condition and total cascade exposure is expected to be in excess of 450 hours. Details of sampling and special measurements are given. A test plan schedule envisages the full test series being completed within a two month calendar period. Finally, a number of contingency strategies are proposed. 3 figures, 14 tables.« less

Kapteyn series arising in radiation problems

NASA Astrophysics Data System (ADS)

Lerche, I.; Tautz, R. C.

2008-01-01

In discussing radiation from multiple point charges or magnetic dipoles, moving in circles or ellipses, a variety of Kapteyn series of the second kind arises. Some of the series have been known in closed form for a hundred years or more, others appear not to be available to analytic persuasion. This paper shows how 12 such generic series can be developed to produce either closed analytic expressions or integrals that are not analytically tractable. In addition, the method presented here may be of benefit when one has other Kapteyn series of the second kind to consider, thereby providing an additional reason to consider such series anew.

Fourier Series Optimization Opportunity

ERIC Educational Resources Information Center

Winkel, Brian

2008-01-01

This note discusses the introduction of Fourier series as an immediate application of optimization of a function of more than one variable. Specifically, it is shown how the study of Fourier series can be motivated to enrich a multivariable calculus class. This is done through discovery learning and use of technology wherein students build the…

Summing Certain p-Series.

ERIC Educational Resources Information Center

Fay, Temple H.

1997-01-01

Presents an exercise suitable for beginning calculus students that may give insight into series representations and allow students to see some elementary application of these representations. The Fourier series is used to approximate by taking sums of trigonometric functions of the form sin(ns) and cos(nx) for n is greater than or = zero. (PVD)

76 FR 62470 - MFS Series Trust I, et al.

Federal Register 2010, 2011, 2012, 2013, 2014

2011-10-07

...] MFS Series Trust I, et al.; Notice of Application September 30, 2011. AGENCY: Securities and Exchange... Series Trust I, MFS Series Trust II, MFS Series Trust III, MFS Series Trust IV, MFS Series Trust V, MFS Series Trust VI, MFS Series Trust VII, MFS Series Trust VIII, MFS Series Trust IX, MFS Series Trust X...

Anterior mandibular apical base augmentation in the surgical orthodontic treatment of mandibular retrusion.

PubMed

Brusati, R; Giannì, A B

2005-12-01

The authors describe a surgical technique alternative to traditional pre-surgical orthodontics in order to increase the apical base in mandibular retrusion (class II, division I). This subapical osteotomy, optimizing inferior incisal axis without dental extractions and a long orthodontic treatment, associated to genioplasty permits to obtain an ideal labio-dento-mental morphology. This procedure avoids in some cases the need of a mandibular advancement and, if necessary, it reduces his entity with obvious advantages.

Network structure of multivariate time series.

PubMed

Lacasa, Lucas; Nicosia, Vincenzo; Latora, Vito

2015-10-21

Our understanding of a variety of phenomena in physics, biology and economics crucially depends on the analysis of multivariate time series. While a wide range tools and techniques for time series analysis already exist, the increasing availability of massive data structures calls for new approaches for multidimensional signal processing. We present here a non-parametric method to analyse multivariate time series, based on the mapping of a multidimensional time series into a multilayer network, which allows to extract information on a high dimensional dynamical system through the analysis of the structure of the associated multiplex network. The method is simple to implement, general, scalable, does not require ad hoc phase space partitioning, and is thus suitable for the analysis of large, heterogeneous and non-stationary time series. We show that simple structural descriptors of the associated multiplex networks allow to extract and quantify nontrivial properties of coupled chaotic maps, including the transition between different dynamical phases and the onset of various types of synchronization. As a concrete example we then study financial time series, showing that a multiplex network analysis can efficiently discriminate crises from periods of financial stability, where standard methods based on time-series symbolization often fail.

A Look at Infinite Series

ERIC Educational Resources Information Center

Basor, Estelle

1978-01-01

Sums for divergent series that were seriously considered by eighteenth century mathematicians are shown to have reappeared as result of new interpretations for divergent series that make these previous conclusions valid. (MN)

Series of Reciprocal Triangular Numbers

ERIC Educational Resources Information Center

Bruckman, Paul; Dence, Joseph B.; Dence, Thomas P.; Young, Justin

2013-01-01

Reciprocal triangular numbers have appeared in series since the very first infinite series were summed. Here we attack a number of subseries of the reciprocal triangular numbers by methodically expressing them as integrals.

Improving the Instruction of Infinite Series

ERIC Educational Resources Information Center

Lindaman, Brian; Gay, A. Susan

2012-01-01

Calculus instructors struggle to teach infinite series, and students have difficulty understanding series and related concepts. Four instructional strategies, prominently used during the calculus reform movement, were implemented during a 3-week unit on infinite series in one class of second-semester calculus students. A description of each…

A Review of Subsequence Time Series Clustering

PubMed Central

Teh, Ying Wah

2014-01-01

Clustering of subsequence time series remains an open issue in time series clustering. Subsequence time series clustering is used in different fields, such as e-commerce, outlier detection, speech recognition, biological systems, DNA recognition, and text mining. One of the useful fields in the domain of subsequence time series clustering is pattern recognition. To improve this field, a sequence of time series data is used. This paper reviews some definitions and backgrounds related to subsequence time series clustering. The categorization of the literature reviews is divided into three groups: preproof, interproof, and postproof period. Moreover, various state-of-the-art approaches in performing subsequence time series clustering are discussed under each of the following categories. The strengths and weaknesses of the employed methods are evaluated as potential issues for future studies. PMID:25140332

A review of subsequence time series clustering.

PubMed

Zolhavarieh, Seyedjamal; Aghabozorgi, Saeed; Teh, Ying Wah

2014-01-01

Clustering of subsequence time series remains an open issue in time series clustering. Subsequence time series clustering is used in different fields, such as e-commerce, outlier detection, speech recognition, biological systems, DNA recognition, and text mining. One of the useful fields in the domain of subsequence time series clustering is pattern recognition. To improve this field, a sequence of time series data is used. This paper reviews some definitions and backgrounds related to subsequence time series clustering. The categorization of the literature reviews is divided into three groups: preproof, interproof, and postproof period. Moreover, various state-of-the-art approaches in performing subsequence time series clustering are discussed under each of the following categories. The strengths and weaknesses of the employed methods are evaluated as potential issues for future studies.

Transient electromagnetic scattering by a radially uniaxial dielectric sphere: Debye series, Mie series and ray tracing methods

NASA Astrophysics Data System (ADS)

Yazdani, Mohsen

Transient electromagnetic scattering by a radially uniaxial dielectric sphere is explored using three well-known methods: Debye series, Mie series, and ray tracing theory. In the first approach, the general solutions for the impulse and step responses of a uniaxial sphere are evaluated using the inverse Laplace transformation of the generalized Mie series solution. Following high frequency scattering solution of a large uniaxial sphere, the Mie series summation is split into the high frequency (HF) and low frequency terms where the HF term is replaced by its asymptotic expression allowing a significant reduction in computation time of the numerical Bromwich integral. In the second approach, the generalized Debye series for a radially uniaxial dielectric sphere is introduced and the Mie series coefficients are replaced by their equivalent Debye series formulations. The results are then applied to examine the transient response of each individual Debye term allowing the identification of impulse returns in the transient response of the uniaxial sphere. In the third approach, the ray tracing theory in a uniaxial sphere is investigated to evaluate the propagation path as well as the arrival time of the ordinary and extraordinary returns in the transient response of the uniaxial sphere. This is achieved by extracting the reflection and transmission angles of a plane wave obliquely incident on the radially oriented air-uniaxial and uniaxial-air boundaries, and expressing the phase velocities as well as the refractive indices of the ordinary and extraordinary waves in terms of the incident angle, optic axis and propagation direction. The results indicate a satisfactory agreement between Debye series, Mie series and ray tracing methods.

Test Series 2. 2: Detailed Test Plan

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

Not Available

Test Series 2.2 comprises the third sub-series of tests to be scheduled as a part of Test Series 2, the second stage of the combustion research program to be carried out at the Grimethorpe Experimental Pressurized Fluidized Bed Combustion Facility. Test Series 2.1, the first sub-series of tests, was completed in February 1983, and the first half of the second sub-series, Test Series 2.3, in October 1983. Test Series 2.2 is to consist of 350 data gathering hours, which it is hoped to complete within 560 coal burning hours. This document provides a brief description of the Facility and modificationsmore » which have been made following the completion of Test Series 2.1. No further modifications were made following the completion of the first half of Test Series 2.3. The operating requirements are specified. The tests will be performed using a UK coal (Kiveton Park), and a UK limestone (Middleton) both nominated by the FRG. Nine objectives are proposed which are to be fulfilled by thirteen test conditions. Six part load tests are included, as defined by Kraftwerk Union AG. The cascade is expected to be on line for each test condition and total cascade exposure is expected to be in excess of 450 hours. Details of sampling and special measurements are given. A test plan schedule envisages the test series being completed within a two month calendar period. Finally, a number of contingency strategies are proposed.« less

Association mining of dependency between time series

NASA Astrophysics Data System (ADS)

Hafez, Alaaeldin

2001-03-01

Time series analysis is considered as a crucial component of strategic control over a broad variety of disciplines in business, science and engineering. Time series data is a sequence of observations collected over intervals of time. Each time series describes a phenomenon as a function of time. Analysis on time series data includes discovering trends (or patterns) in a time series sequence. In the last few years, data mining has emerged and been recognized as a new technology for data analysis. Data Mining is the process of discovering potentially valuable patterns, associations, trends, sequences and dependencies in data. Data mining techniques can discover information that many traditional business analysis and statistical techniques fail to deliver. In this paper, we adapt and innovate data mining techniques to analyze time series data. By using data mining techniques, maximal frequent patterns are discovered and used in predicting future sequences or trends, where trends describe the behavior of a sequence. In order to include different types of time series (e.g. irregular and non- systematic), we consider past frequent patterns of the same time sequences (local patterns) and of other dependent time sequences (global patterns). We use the word 'dependent' instead of the word 'similar' for emphasis on real life time series where two time series sequences could be completely different (in values, shapes, etc.), but they still react to the same conditions in a dependent way. In this paper, we propose the Dependence Mining Technique that could be used in predicting time series sequences. The proposed technique consists of three phases: (a) for all time series sequences, generate their trend sequences, (b) discover maximal frequent trend patterns, generate pattern vectors (to keep information of frequent trend patterns), use trend pattern vectors to predict future time series sequences.

Visibility graph approach to exchange rate series

NASA Astrophysics Data System (ADS)

Yang, Yue; Wang, Jianbo; Yang, Huijie; Mang, Jingshi

2009-10-01

By means of a visibility graph, we investigate six important exchange rate series. It is found that the series convert into scale-free and hierarchically structured networks. The relationship between the scaling exponents of the degree distributions and the Hurst exponents obeys the analytical prediction for fractal Brownian motions. The visibility graph can be used to obtain reliable values of Hurst exponents of the series. The characteristics are explained by using the multifractal structures of the series. The exchange rate of EURO to Japanese Yen is widely used to evaluate risk and to estimate trends in speculative investments. Interestingly, the hierarchies of the visibility graphs for the exchange rate series of these two currencies are significantly weak compared with that of the other series.

Convergence of a Catalan Series

ERIC Educational Resources Information Center

Koshy, Thomas; Gao, Zhenguang

2012-01-01

This article studies the convergence of the infinite series of the reciprocals of the Catalan numbers. We extract the sum of the series as well as some related ones, illustrating the power of the calculus in the study of the Catalan numbers.

Precision Tests of a Quantum Hall Effect Device DC Equivalent Circuit Using Double-Series and Triple-Series Connections

PubMed Central

Jeffery, A.; Elmquist, R. E.; Cage, M. E.

1995-01-01

Precision tests verify the dc equivalent circuit used by Ricketts and Kemeny to describe a quantum Hall effect device in terms of electrical circuit elements. The tests employ the use of cryogenic current comparators and the double-series and triple-series connection techniques of Delahaye. Verification of the dc equivalent circuit in double-series and triple-series connections is a necessary step in developing the ac quantum Hall effect as an intrinsic standard of resistance. PMID:29151768

Time series with tailored nonlinearities

NASA Astrophysics Data System (ADS)

Räth, C.; Laut, I.

2015-10-01

It is demonstrated how to generate time series with tailored nonlinearities by inducing well-defined constraints on the Fourier phases. Correlations between the phase information of adjacent phases and (static and dynamic) measures of nonlinearities are established and their origin is explained. By applying a set of simple constraints on the phases of an originally linear and uncorrelated Gaussian time series, the observed scaling behavior of the intensity distribution of empirical time series can be reproduced. The power law character of the intensity distributions being typical for, e.g., turbulence and financial data can thus be explained in terms of phase correlations.

Homogenising time series: Beliefs, dogmas and facts

NASA Astrophysics Data System (ADS)

Domonkos, P.

2010-09-01

For obtaining reliable information about climate change and climate variability the use of high quality data series is essentially important, and one basic tool of quality improvements is the statistical homogenisation of observed time series. In the recent decades large number of homogenisation methods has been developed, but the real effects of their application on time series are still not known entirely. The ongoing COST HOME project (COST ES0601) is devoted to reveal the real impacts of homogenisation methods more detailed and with higher confidence than earlier. As part of the COST activity, a benchmark dataset was built whose characteristics approach well the characteristics of real networks of observed time series. This dataset offers much better opportunity than ever to test the wide variety of homogenisation methods, and analyse the real effects of selected theoretical recommendations. The author believes that several old theoretical rules have to be re-evaluated. Some examples of the hot questions, a) Statistically detected change-points can be accepted only with the confirmation of metadata information? b) Do semi-hierarchic algorithms for detecting multiple change-points in time series function effectively in practise? c) Is it good to limit the spatial comparison of candidate series with up to five other series in the neighbourhood? Empirical results - those from the COST benchmark, and other experiments too - show that real observed time series usually include several inhomogeneities of different sizes. Small inhomogeneities seem like part of the climatic variability, thus the pure application of classic theory that change-points of observed time series can be found and corrected one-by-one is impossible. However, after homogenisation the linear trends, seasonal changes and long-term fluctuations of time series are usually much closer to the reality, than in raw time series. The developers and users of homogenisation methods have to bear in mind that

Legends Lecture Series III

NASA Image and Video Library

2011-07-27

Marina Benigno (far right) at Stennis Space Center, welcomes former administrative assistants and secretaries to the third Legends Lecture Series session. Lecture participants spoke about their work experiences with Stennis directors and deputy directors. Panel participants included Janet Austill (l to r), Mary Lou Matthews, Helen Paul, Wanda Howard, Ann Westendorf and Mary Gene Dick. The Legends Lecture Series is part of a yearlong celebration of the 50th anniversary of Stennis Space Center.

Expression Templates for Truncated Power Series

NASA Astrophysics Data System (ADS)

Cary, John R.; Shasharina, Svetlana G.

1997-05-01

Truncated power series are used extensively in accelerator transport modeling for rapid tracking and analysis of nonlinearity. Such mathematical objects are naturally represented computationally as objects in C++. This is more intuitive and produces more transparent code through operator overloading. However, C++ object use often comes with a computational speed loss due, e.g., to the creation of temporaries. We have developed a subset of truncated power series expression templates(http://monet.uwaterloo.ca/blitz/). Such expression templates use the powerful template processing facility of C++ to combine complicated expressions into series operations that exectute more rapidly. We compare computational speeds with existing truncated power series libraries.

Fuzzy Inference System Approach for Locating Series, Shunt, and Simultaneous Series-Shunt Faults in Double Circuit Transmission Lines

PubMed Central

Swetapadma, Aleena; Yadav, Anamika

2015-01-01

Many schemes are reported for shunt fault location estimation, but fault location estimation of series or open conductor faults has not been dealt with so far. The existing numerical relays only detect the open conductor (series) fault and give the indication of the faulty phase(s), but they are unable to locate the series fault. The repair crew needs to patrol the complete line to find the location of series fault. In this paper fuzzy based fault detection/classification and location schemes in time domain are proposed for both series faults, shunt faults, and simultaneous series and shunt faults. The fault simulation studies and fault location algorithm have been developed using Matlab/Simulink. Synchronized phasors of voltage and current signals of both the ends of the line have been used as input to the proposed fuzzy based fault location scheme. Percentage of error in location of series fault is within 1% and shunt fault is 5% for all the tested fault cases. Validation of percentage of error in location estimation is done using Chi square test with both 1% and 5% level of significance. PMID:26413088

Clustering of financial time series

NASA Astrophysics Data System (ADS)

D'Urso, Pierpaolo; Cappelli, Carmela; Di Lallo, Dario; Massari, Riccardo

2013-05-01

This paper addresses the topic of classifying financial time series in a fuzzy framework proposing two fuzzy clustering models both based on GARCH models. In general clustering of financial time series, due to their peculiar features, needs the definition of suitable distance measures. At this aim, the first fuzzy clustering model exploits the autoregressive representation of GARCH models and employs, in the framework of a partitioning around medoids algorithm, the classical autoregressive metric. The second fuzzy clustering model, also based on partitioning around medoids algorithm, uses the Caiado distance, a Mahalanobis-like distance, based on estimated GARCH parameters and covariances that takes into account the information about the volatility structure of time series. In order to illustrate the merits of the proposed fuzzy approaches an application to the problem of classifying 29 time series of Euro exchange rates against international currencies is presented and discussed, also comparing the fuzzy models with their crisp version.

Allan deviation analysis of financial return series

NASA Astrophysics Data System (ADS)

Hernández-Pérez, R.

2012-05-01

We perform a scaling analysis for the return series of different financial assets applying the Allan deviation (ADEV), which is used in the time and frequency metrology to characterize quantitatively the stability of frequency standards since it has demonstrated to be a robust quantity to analyze fluctuations of non-stationary time series for different observation intervals. The data used are opening price daily series for assets from different markets during a time span of around ten years. We found that the ADEV results for the return series at short scales resemble those expected for an uncorrelated series, consistent with the efficient market hypothesis. On the other hand, the ADEV results for absolute return series for short scales (first one or two decades) decrease following approximately a scaling relation up to a point that is different for almost each asset, after which the ADEV deviates from scaling, which suggests that the presence of clustering, long-range dependence and non-stationarity signatures in the series drive the results for large observation intervals.

17 CFR 270.18f-2 - Fair and equitable treatment for holders of each class or series of stock of series investment...

Code of Federal Regulations, 2010 CFR

2010-04-01

... for holders of each class or series of stock of series investment companies. 270.18f-2 Section 270.18f... or series of stock of series investment companies. (a) For purposes of this § 270.18f-2 a series...(f)(2) of the Act, issues two or more classes or series of preferred or special stock each of which...

17 CFR 270.18f-2 - Fair and equitable treatment for holders of each class or series of stock of series investment...

Code of Federal Regulations, 2013 CFR

2013-04-01

... for holders of each class or series of stock of series investment companies. 270.18f-2 Section 270.18f... or series of stock of series investment companies. (a) For purposes of this § 270.18f-2 a series...(f)(2) of the Act, issues two or more classes or series of preferred or special stock each of which...

17 CFR 270.18f-2 - Fair and equitable treatment for holders of each class or series of stock of series investment...

Code of Federal Regulations, 2012 CFR

2012-04-01

... for holders of each class or series of stock of series investment companies. 270.18f-2 Section 270.18f... or series of stock of series investment companies. (a) For purposes of this § 270.18f-2 a series...(f)(2) of the Act, issues two or more classes or series of preferred or special stock each of which...

17 CFR 270.18f-2 - Fair and equitable treatment for holders of each class or series of stock of series investment...

Code of Federal Regulations, 2014 CFR

2014-04-01

... for holders of each class or series of stock of series investment companies. 270.18f-2 Section 270.18f... or series of stock of series investment companies. (a) For purposes of this § 270.18f-2 a series...(f)(2) of the Act, issues two or more classes or series of preferred or special stock each of which...

17 CFR 270.18f-2 - Fair and equitable treatment for holders of each class or series of stock of series investment...

Code of Federal Regulations, 2011 CFR

2011-04-01

... for holders of each class or series of stock of series investment companies. 270.18f-2 Section 270.18f... or series of stock of series investment companies. (a) For purposes of this § 270.18f-2 a series...(f)(2) of the Act, issues two or more classes or series of preferred or special stock each of which...

Complex Landscape Terms in Seri

ERIC Educational Resources Information Center

O'Meara, Carolyn; Bohnemeyer, Jurgen

2008-01-01

The nominal lexicon of Seri is characterized by a prevalence of analytical descriptive terms. We explore the consequences of this typological trait in the landscape domain. The complex landscape terms of Seri classify geographic entities in terms of their material make-up and spatial properties such as shape, orientation, and merological…

Decoding divergent series in nonparaxial optics.

PubMed

Borghi, Riccardo; Gori, Franco; Guattari, Giorgio; Santarsiero, Massimo

2011-03-15

A theoretical analysis aimed at investigating the divergent character of perturbative series involved in the study of free-space nonparaxial propagation of vectorial optical beams is proposed. Our analysis predicts a factorial divergence for such series and provides a theoretical framework within which the results of recently published numerical experiments concerning nonparaxial propagation of vectorial Gaussian beams find a meaningful interpretation in terms of the decoding operated on such series by the Weniger transformation.

Winter Video Series Coming in January | Poster

Cancer.gov

The Scientific Library’s annual Summer Video Series was so successful that it will be offering a new Winter Video Series beginning in January. For this inaugural event, the staff is showing the eight-part series from National Geographic titled “American Genius.” 

A case of labio-facial necrotizing fasciitis complicating acne.

PubMed

Eltayeb, Amel Salah; Ahmad, Abdelnasir Gafar; Elbeshir, Elnour Ibrahim

2016-04-23

Facial necrotizing fasciitis is extremely rare. Most of the cases reported in literature are related to dental, sinus, tonsillar and salivary glands causes, but rarely as consequence of skin infection. We report a unique case of lower lip cellulitis, which was initially misdiagnosed as angioedema and subsequently progressed into lower lip necrotizing fasciitis. This is a case report of necrotizing fasciitis involving the lower lip as a consequence of infected skin acne in a 19 year old black female. The patient had been diagnosed earlier as a case of angioedema by a physician and treated accordingly. She was mildly anemic, hyponatremic and hypokalemic. Treatment was started immediately by incision, drainage and full debridement of the whole necrotic tissue. Triple antibiotic therapy was administered and daily irrigation and dressing were performed until full recovery. Complete healing occurred within a month by secondary intention. This case demonstrates the misdiagnosis of a lip swelling leading to the development of labiofacial necrotizing fasciitis, a serious and life threatening condition. Lip angioedema is a common condition; however, lip fasciitis is rare. A broad differential diagnosis in case of lower lip swelling is essential to avoid inappropriate treatment delay.

Constructing Weyl group multiple Dirichlet series

NASA Astrophysics Data System (ADS)

Chinta, Gautam; Gunnells, Paul E.

2010-01-01

Let Phi be a reduced root system of rank r . A Weyl group multiple Dirichlet series for Phi is a Dirichlet series in r complex variables s_1,dots,s_r , initially converging for {Re}(s_i) sufficiently large, that has meromorphic continuation to {{C}}^r and satisfies functional equations under the transformations of {{C}}^r corresponding to the Weyl group of Phi . A heuristic definition of such a series was given by Brubaker, Bump, Chinta, Friedberg, and Hoffstein, and they have been investigated in certain special cases by others. In this paper we generalize results by Chinta and Gunnells to construct Weyl group multiple Dirichlet series by a uniform method and show in all cases that they have the expected properties.

Assiniboine Series.

ERIC Educational Resources Information Center

Allen, Minerva

This series of illustrated booklets presents 13 Indian stories in a bilingual format of English and Assiniboine, an Indian tribal language. Written on the first grade level, the stories have the following titles: (1) "Orange Tree in Lodgepole"; (2) "Pretty Flower"; (3) Inktomi and the Rock"; (4) "Inktomi and the…

Revision of Primary Series Maps

USGS Publications Warehouse

,

2000-01-01

In 1992, the U.S. Geological Survey (USGS) completed a 50-year effort to provide primary series map coverage of the United States. Many of these maps now need to be updated to reflect the construction of new roads and highways and other changes that have taken place over time. The USGS has formulated a graphic revision plan to help keep the primary series maps current. Primary series maps include 1:20,000-scale quadrangles of Puerto Rico, 1:24,000- or 1:25,000-scale quadrangles of the conterminous United States, Hawaii, and U.S. Territories, and 1:63,360-scale quadrangles of Alaska. The revision of primary series maps from new collection sources is accomplished using a variety of processes. The raster revision process combines the scanned content of paper maps with raster updating technologies. The vector revision process involves the automated plotting of updated vector files. Traditional processes use analog stereoplotters and manual scribing instruments on specially coated map separates. The ability to select from or combine these processes increases the efficiency of the National Mapping Division map revision program.

75 FR 55699 - Series LLCs and Cell Companies

Federal Register 2010, 2011, 2012, 2013, 2014

2010-09-14

... Series LLCs and Cell Companies AGENCY: Internal Revenue Service (IRS), Treasury. ACTION: Notice of... Federal tax purposes of a series of a domestic series limited liability company (LLC), a cell of a domestic cell company, or a foreign series or cell that conducts an insurance business. The proposed...

Students' Conception of Infinite Series

ERIC Educational Resources Information Center

Martinez-Planell, Rafael; Gonzalez, Ana Carmen; DiCristina, Gladys; Acevedo, Vanessa

2012-01-01

This is a report of a study of students' understanding of infinite series. It has a three-fold purpose: to show that students may construct two essentially different notions of infinite series, to show that one of the constructions is particularly difficult for students, and to examine the way in which these two different constructions may be…

Homogenising time series: beliefs, dogmas and facts

NASA Astrophysics Data System (ADS)

Domonkos, P.

2011-06-01

In the recent decades various homogenisation methods have been developed, but the real effects of their application on time series are still not known sufficiently. The ongoing COST action HOME (COST ES0601) is devoted to reveal the real impacts of homogenisation methods more detailed and with higher confidence than earlier. As a part of the COST activity, a benchmark dataset was built whose characteristics approach well the characteristics of real networks of observed time series. This dataset offers much better opportunity than ever before to test the wide variety of homogenisation methods, and analyse the real effects of selected theoretical recommendations. Empirical results show that real observed time series usually include several inhomogeneities of different sizes. Small inhomogeneities often have similar statistical characteristics than natural changes caused by climatic variability, thus the pure application of the classic theory that change-points of observed time series can be found and corrected one-by-one is impossible. However, after homogenisation the linear trends, seasonal changes and long-term fluctuations of time series are usually much closer to the reality than in raw time series. Some problems around detecting multiple structures of inhomogeneities, as well as that of time series comparisons within homogenisation procedures are discussed briefly in the study.

Quantum Dilogarithms and Partition q-Series

NASA Astrophysics Data System (ADS)

Kato, Akishi; Terashima, Yuji

2015-08-01

In our previous work (Kato and Terashima, Commun Math Phys. arXiv:1403.6569, 2014), we introduced the partition q-series for mutation loop γ—a loop in exchange quiver. In this paper, we show that for a certain class of mutation sequences, called reddening sequences, the graded version of partition q-series essentially coincides with the ordered product of quantum dilogarithm associated with each mutation; the partition q-series provides a state-sum description of combinatorial Donaldson-Thomas invariants introduced by Keller.

Quantifying memory in complex physiological time-series.

PubMed

Shirazi, Amir H; Raoufy, Mohammad R; Ebadi, Haleh; De Rui, Michele; Schiff, Sami; Mazloom, Roham; Hajizadeh, Sohrab; Gharibzadeh, Shahriar; Dehpour, Ahmad R; Amodio, Piero; Jafari, G Reza; Montagnese, Sara; Mani, Ali R

2013-01-01

In a time-series, memory is a statistical feature that lasts for a period of time and distinguishes the time-series from a random, or memory-less, process. In the present study, the concept of "memory length" was used to define the time period, or scale over which rare events within a physiological time-series do not appear randomly. The method is based on inverse statistical analysis and provides empiric evidence that rare fluctuations in cardio-respiratory time-series are 'forgotten' quickly in healthy subjects while the memory for such events is significantly prolonged in pathological conditions such as asthma (respiratory time-series) and liver cirrhosis (heart-beat time-series). The memory length was significantly higher in patients with uncontrolled asthma compared to healthy volunteers. Likewise, it was significantly higher in patients with decompensated cirrhosis compared to those with compensated cirrhosis and healthy volunteers. We also observed that the cardio-respiratory system has simple low order dynamics and short memory around its average, and high order dynamics around rare fluctuations.

Quantifying Memory in Complex Physiological Time-Series

PubMed Central

Shirazi, Amir H.; Raoufy, Mohammad R.; Ebadi, Haleh; De Rui, Michele; Schiff, Sami; Mazloom, Roham; Hajizadeh, Sohrab; Gharibzadeh, Shahriar; Dehpour, Ahmad R.; Amodio, Piero; Jafari, G. Reza; Montagnese, Sara; Mani, Ali R.

2013-01-01

In a time-series, memory is a statistical feature that lasts for a period of time and distinguishes the time-series from a random, or memory-less, process. In the present study, the concept of “memory length” was used to define the time period, or scale over which rare events within a physiological time-series do not appear randomly. The method is based on inverse statistical analysis and provides empiric evidence that rare fluctuations in cardio-respiratory time-series are ‘forgotten’ quickly in healthy subjects while the memory for such events is significantly prolonged in pathological conditions such as asthma (respiratory time-series) and liver cirrhosis (heart-beat time-series). The memory length was significantly higher in patients with uncontrolled asthma compared to healthy volunteers. Likewise, it was significantly higher in patients with decompensated cirrhosis compared to those with compensated cirrhosis and healthy volunteers. We also observed that the cardio-respiratory system has simple low order dynamics and short memory around its average, and high order dynamics around rare fluctuations. PMID:24039811

Multivariate Time Series Decomposition into Oscillation Components.

PubMed

Matsuda, Takeru; Komaki, Fumiyasu

2017-08-01

Many time series are considered to be a superposition of several oscillation components. We have proposed a method for decomposing univariate time series into oscillation components and estimating their phases (Matsuda & Komaki, 2017 ). In this study, we extend that method to multivariate time series. We assume that several oscillators underlie the given multivariate time series and that each variable corresponds to a superposition of the projections of the oscillators. Thus, the oscillators superpose on each variable with amplitude and phase modulation. Based on this idea, we develop gaussian linear state-space models and use them to decompose the given multivariate time series. The model parameters are estimated from data using the empirical Bayes method, and the number of oscillators is determined using the Akaike information criterion. Therefore, the proposed method extracts underlying oscillators in a data-driven manner and enables investigation of phase dynamics in a given multivariate time series. Numerical results show the effectiveness of the proposed method. From monthly mean north-south sunspot number data, the proposed method reveals an interesting phase relationship.

Technology Utilization Conference Series, volume 1

NASA Technical Reports Server (NTRS)

1975-01-01

The design, development, and results of a series of technology utilization conferences are presented. The conference series represents the development of a viable and successful means of encouraging the transfer of technology to the minority business community.

75 FR 901 - Airworthiness Directives; Honeywell International Inc. ALF502 Series and LF507 Series Turbofan...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-01-07

.... ALF502 series and LF507 series turbofan engines with certain fuel manifold assemblies installed. That AD... of certain part number (P/N) fuel manifold assemblies for cracks, and replacement of cracked fuel manifolds with serviceable manifolds. This AD continues to require inspecting those fuel manifolds for...

The Harmonic Series Diverges Again and Again

ERIC Educational Resources Information Center

Kifowit, Steven J.; Stamps, Terra A.

2006-01-01

The harmonic series is one of the most celebrated infinite series of mathematics. A quick glance at a variety of modern calculus textbooks reveals that there are two very popular proofs of the divergence of the harmonic series. In this article, the authors survey these popular proofs along with many other proofs that are equally simple and…

Reprint Series: Computation of Pi. RS-7.

ERIC Educational Resources Information Center

Schaaf, William L., Ed.

This is one in a series of SMSG supplementary and enrichment pamphlets for high school students. This series makes available expository articles which appeared in a variety of mathematical periodicals. Topics covered include: (1) the latest about pi; (2) a series useful in the computation of pi; (3) an ENIAC determination of pi and e to more than…

A method for transferring NASTRAN data between dissimilar computers. [application to CDC 6000 series, IBM 360-370 series, and Univac 1100 series computers

NASA Technical Reports Server (NTRS)

Rogers, J. L., Jr.

1973-01-01

The NASTRAN computer program is capable of executing on three different types of computers: (1) the CDC 6000 series, (2) the IBM 360-370 series, and (3) the Univac 1100 series. A typical activity requiring transfer of data between dissimilar computers is the analysis of a large structure such as the space shuttle by substructuring. Models of portions of the vehicle which have been analyzed by subcontractors using their computers must be integrated into a model of the complete structure by the prime contractor on his computer. Presently the transfer of NASTRAN matrices or tables between two different types of computers is accomplished by punched cards or a magnetic tape containing card images. These methods of data transfer do not satisfy the requirements for intercomputer data transfer associated with a substructuring activity. To provide a more satisfactory transfer of data, two new programs, RDUSER and WRTUSER, were created.

Defining new dental phenotypes using 3-D image analysis to enhance discrimination and insights into biological processes

PubMed Central

Smith, Richard; Zaitoun, Halla; Coxon, Tom; Karmo, Mayada; Kaur, Gurpreet; Townsend, Grant; Harris, Edward F.; Brook, Alan

2009-01-01

analysis and a 3-D image analysis system. The mesio-distal (MD), labio-lingual (LL) and inciso-gingival (IG) dimensions were recorded using our 2-D system and the same projected variables were also recorded using a newly developed 3-D system for comparison. Values of Pearson's correlation coefficient between measurements obtained using the two techniques were significant at the 0.01 probability level for variables mesio-distal and incisal-gingival with labio-lingual significant at the 0.05 level for the upper left side only, confirming their comparability. For both 2-D and 3-D systems the intra- and inter-operator reliability was substantial or excellent for variables mesio-distal, labio-lingual, incisal-gingival actual and projected and actual surface area. The reliability was good for inter-operator reliability measurement of the labio-lingual dimension using 3-D. Conclusions We have developed a new 3-D laser scanning system that enables additional dental phenotypes to be defined. It has been validated against an established 2-D system and shown to provide measurements with excellent reliability, both within and between operators. This new approach provides exciting possibilities for exploring normal and abnormal variations in dental morphology and development applicable to research on genetic and environmental factors. PMID:18644585

Ocean time-series near Bermuda: Hydrostation S and the US JGOFS Bermuda Atlantic time-series study

NASA Technical Reports Server (NTRS)

Michaels, Anthony F.; Knap, Anthony H.

1992-01-01

Bermuda is the site of two ocean time-series programs. At Hydrostation S, the ongoing biweekly profiles of temperature, salinity and oxygen now span 37 years. This is one of the longest open-ocean time-series data sets and provides a view of decadal scale variability in ocean processes. In 1988, the U.S. JGOFS Bermuda Atlantic Time-series Study began a wide range of measurements at a frequency of 14-18 cruises each year to understand temporal variability in ocean biogeochemistry. On each cruise, the data range from chemical analyses of discrete water samples to data from electronic packages of hydrographic and optics sensors. In addition, a range of biological and geochemical rate measurements are conducted that integrate over time-periods of minutes to days. This sampling strategy yields a reasonable resolution of the major seasonal patterns and of decadal scale variability. The Sargasso Sea also has a variety of episodic production events on scales of days to weeks and these are only poorly resolved. In addition, there is a substantial amount of mesoscale variability in this region and some of the perceived temporal patterns are caused by the intersection of the biweekly sampling with the natural spatial variability. In the Bermuda time-series programs, we have added a series of additional cruises to begin to assess these other sources of variation and their impacts on the interpretation of the main time-series record. However, the adequate resolution of higher frequency temporal patterns will probably require the introduction of new sampling strategies and some emerging technologies such as biogeochemical moorings and autonomous underwater vehicles.

Finding Sums for an Infinite Class of Alternating Series

ERIC Educational Resources Information Center

Chen, Zhibo; Wei, Sheng; Xiao, Xuerong

2012-01-01

Calculus II students know that many alternating series are convergent by the Alternating Series Test. However, they know few alternating series (except geometric series and some trivial ones) for which they can find the sum. In this article, we present a method that enables the students to find sums for infinitely many alternating series in the…

Legends Lecture Series III

NASA Image and Video Library

2011-07-27

Marina Benigno (far right) at Stennis Space Center, welcomes former administrative assistants and secretaries to the third Legends Lecture Series session. Lecture participants spoke about their work experiences with Stennis directors and deputy directors. Panel participants included Janet Austill (l to r), Mary Lou Matthews, Helen Paul, Wanda Howard, Ann Westendorf and Mary Gene Dick. Austill, Howard and Westendorf all worked with center directors during their Stennis careers. Dick, Matthews and Paul served with deputy directors at Stennis. The Legends Lecture Series is part of a yearlong celebration of the 50th anniversary of Stennis Space Center.

Forbidden patterns in financial time series

NASA Astrophysics Data System (ADS)

Zanin, Massimiliano

2008-03-01

The existence of forbidden patterns, i.e., certain missing sequences in a given time series, is a recently proposed instrument of potential application in the study of time series. Forbidden patterns are related to the permutation entropy, which has the basic properties of classic chaos indicators, such as Lyapunov exponent or Kolmogorov entropy, thus allowing to separate deterministic (usually chaotic) from random series; however, it requires fewer values of the series to be calculated, and it is suitable for using with small datasets. In this paper, the appearance of forbidden patterns is studied in different economical indicators such as stock indices (Dow Jones Industrial Average and Nasdaq Composite), NYSE stocks (IBM and Boeing), and others (ten year Bond interest rate), to find evidence of deterministic behavior in their evolutions. Moreover, the rate of appearance of the forbidden patterns is calculated, and some considerations about the underlying dynamics are suggested.

Detecting chaos in irregularly sampled time series.

PubMed

Kulp, C W

2013-09-01

Recently, Wiebe and Virgin [Chaos 22, 013136 (2012)] developed an algorithm which detects chaos by analyzing a time series' power spectrum which is computed using the Discrete Fourier Transform (DFT). Their algorithm, like other time series characterization algorithms, requires that the time series be regularly sampled. Real-world data, however, are often irregularly sampled, thus, making the detection of chaotic behavior difficult or impossible with those methods. In this paper, a characterization algorithm is presented, which effectively detects chaos in irregularly sampled time series. The work presented here is a modification of Wiebe and Virgin's algorithm and uses the Lomb-Scargle Periodogram (LSP) to compute a series' power spectrum instead of the DFT. The DFT is not appropriate for irregularly sampled time series. However, the LSP is capable of computing the frequency content of irregularly sampled data. Furthermore, a new method of analyzing the power spectrum is developed, which can be useful for differentiating between chaotic and non-chaotic behavior. The new characterization algorithm is successfully applied to irregularly sampled data generated by a model as well as data consisting of observations of variable stars.

Case Series Investigations in Cognitive Neuropsychology

PubMed Central

Schwartz, Myrna F.; Dell, Gary S.

2011-01-01

Case series methodology involves the systematic assessment of a sample of related patients, with the goal of understanding how and why they differ from one another. This method has become increasingly important in cognitive neuropsychology, which has long been identified with single-subject research. We review case series studies dealing with impaired semantic memory, reading, and language production, and draw attention to the affinity of this methodology for testing theories that are expressed as computational models and for addressing questions about neuroanatomy. It is concluded that case series methods usefully complement single-subject techniques. PMID:21714756

Clustering Financial Time Series by Network Community Analysis

NASA Astrophysics Data System (ADS)

Piccardi, Carlo; Calatroni, Lisa; Bertoni, Fabio

In this paper, we describe a method for clustering financial time series which is based on community analysis, a recently developed approach for partitioning the nodes of a network (graph). A network with N nodes is associated to the set of N time series. The weight of the link (i, j), which quantifies the similarity between the two corresponding time series, is defined according to a metric based on symbolic time series analysis, which has recently proved effective in the context of financial time series. Then, searching for network communities allows one to identify groups of nodes (and then time series) with strong similarity. A quantitative assessment of the significance of the obtained partition is also provided. The method is applied to two distinct case-studies concerning the US and Italy Stock Exchange, respectively. In the US case, the stability of the partitions over time is also thoroughly investigated. The results favorably compare with those obtained with the standard tools typically used for clustering financial time series, such as the minimal spanning tree and the hierarchical tree.

Eisenstein series for infinite-dimensional U-duality groups

NASA Astrophysics Data System (ADS)

Fleig, Philipp; Kleinschmidt, Axel

2012-06-01

We consider Eisenstein series appearing as coefficients of curvature corrections in the low-energy expansion of type II string theory four-graviton scattering amplitudes. We define these Eisenstein series over all groups in the E n series of string duality groups, and in particular for the infinite-dimensional Kac-Moody groups E 9, E 10 and E 11. We show that, remarkably, the so-called constant term of Kac-Moody-Eisenstein series contains only a finite number of terms for particular choices of a parameter appearing in the definition of the series. This resonates with the idea that the constant term of the Eisenstein series encodes perturbative string corrections in BPS-protected sectors allowing only a finite number of corrections. We underpin our findings with an extensive discussion of physical degeneration limits in D < 3 space-time dimensions.

Cross-correlation of point series using a new method

NASA Technical Reports Server (NTRS)

Strothers, Richard B.

1994-01-01

Traditional methods of cross-correlation of two time series do not apply to point time series. Here, a new method, devised specifically for point series, utilizes a correlation measure that is based in the rms difference (or, alternatively, the median absolute difference) between nearest neightbors in overlapped segments of the two series. Error estimates for the observed locations of the points, as well as a systematic shift of one series with respect to the other to accommodate a constant, but unknown, lead or lag, are easily incorporated into the analysis using Monte Carlo techniques. A methodological restriction adopted here is that one series be treated as a template series against which the other, called the target series, is cross-correlated. To estimate a significance level for the correlation measure, the adopted alternative (null) hypothesis is that the target series arises from a homogeneous Poisson process. The new method is applied to cross-correlating the times of the greatest geomagnetic storms with the times of maximum in the undecennial solar activity cycle.

Entropic Analysis of Electromyography Time Series

NASA Astrophysics Data System (ADS)

Kaufman, Miron; Sung, Paul

2005-03-01

We are in the process of assessing the effectiveness of fractal and entropic measures for the diagnostic of low back pain from surface electromyography (EMG) time series. Surface electromyography (EMG) is used to assess patients with low back pain. In a typical EMG measurement, the voltage is measured every millisecond. We observed back muscle fatiguing during one minute, which results in a time series with 60,000 entries. We characterize the complexity of time series by computing the Shannon entropy time dependence. The analysis of the time series from different relevant muscles from healthy and low back pain (LBP) individuals provides evidence that the level of variability of back muscle activities is much larger for healthy individuals than for individuals with LBP. In general the time dependence of the entropy shows a crossover from a diffusive regime to a regime characterized by long time correlations (self organization) at about 0.01s.

Directionality volatility in electroencephalogram time series

NASA Astrophysics Data System (ADS)

Mansor, Mahayaudin M.; Green, David A.; Metcalfe, Andrew V.

2016-06-01

We compare time series of electroencephalograms (EEGs) from healthy volunteers with EEGs from subjects diagnosed with epilepsy. The EEG time series from the healthy group are recorded during awake state with their eyes open and eyes closed, and the records from subjects with epilepsy are taken from three different recording regions of pre-surgical diagnosis: hippocampal, epileptogenic and seizure zone. The comparisons for these 5 categories are in terms of deviations from linear time series models with constant variance Gaussian white noise error inputs. One feature investigated is directionality, and how this can be modelled by either non-linear threshold autoregressive models or non-Gaussian errors. A second feature is volatility, which is modelled by Generalized AutoRegressive Conditional Heteroskedasticity (GARCH) processes. Other features include the proportion of variability accounted for by time series models, and the skewness and the kurtosis of the residuals. The results suggest these comparisons may have diagnostic potential for epilepsy and provide early warning of seizures.

Time Series Model Identification by Estimating Information.

DTIC Science & Technology

1982-11-01

principle, Applications of Statistics, P. R. Krishnaiah , ed., North-Holland: Amsterdam, 27-41. Anderson, T. W. (1971). The Statistical Analysis of Time Series...E. (1969). Multiple Time Series Modeling, Multivariate Analysis II, edited by P. Krishnaiah , Academic Press: New York, 389-409. Parzen, E. (1981...Newton, H. J. (1980). Multiple Time Series Modeling, II Multivariate Analysis - V, edited by P. Krishnaiah , North Holland: Amsterdam, 181-197. Shibata, R

Lower GI Series

MedlinePlus

... may ask the person to change position several times to evenly coat the large intestine with the barium • if the health care provider has ordered a double-contrast lower GI series, the radiologist will inject air through the tube ...

An Energy-Based Similarity Measure for Time Series

NASA Astrophysics Data System (ADS)

Boudraa, Abdel-Ouahab; Cexus, Jean-Christophe; Groussat, Mathieu; Brunagel, Pierre

2007-12-01

A new similarity measure, called SimilB, for time series analysis, based on the cross-[InlineEquation not available: see fulltext.]-energy operator (2004), is introduced. [InlineEquation not available: see fulltext.] is a nonlinear measure which quantifies the interaction between two time series. Compared to Euclidean distance (ED) or the Pearson correlation coefficient (CC), SimilB includes the temporal information and relative changes of the time series using the first and second derivatives of the time series. SimilB is well suited for both nonstationary and stationary time series and particularly those presenting discontinuities. Some new properties of [InlineEquation not available: see fulltext.] are presented. Particularly, we show that [InlineEquation not available: see fulltext.] as similarity measure is robust to both scale and time shift. SimilB is illustrated with synthetic time series and an artificial dataset and compared to the CC and the ED measures.

Legends Lecture Series II

NASA Image and Video Library

2011-04-05

Current and former leaders discuss the growth of NASA's John C. Stennis Space Center during a Legends Lecture Series onsite on April 5. Stennis launched the Legends Lecture Series last November as part of a yearlong celebration of its 50th anniversary. The April 5 session focused on growth of Stennis into a unique federal city during the 1970s and the establishment of NASA's Earth Resources Laboratory at the site. Presenters at the April 5 event included (l to r): George Schloegel, mayor of Gulfport; Jack Rogers, former director of NASA Center Operations at Stennis; and Wayne Mooneyhan, former director of NASA's Earth Resources Laboratory at Stennis.

Fa Keih Reading Series. Book 1.

ERIC Educational Resources Information Center

Sung, Robert

This is the first of a reading series designed primarily for students who are interested in continuing to learn Chinese in a Chinese bilingual program at the secondary level. It follows "The Golden Mountain Reading Series" developed for students in the elementary grades. Each lesson contains the following elements: vocabulary,…

76 FR 65941 - Airworthiness Directives; Rolls-Royce plc RB211-524 Series, RB211-Trent 700 Series, and RB211...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-10-25

... Airworthiness Directives; Rolls-Royce plc RB211-524 Series, RB211-Trent 700 Series, and RB211-Trent 800 Series...-Royce plc (RR), asked us to consider changing the information for getting the service information to... plc, PO Box 31, Derby, DE24 8BJ, United Kingdom, phone: 011-44-1331-242424, fax: 011-44-1332- 249936...

Scale-dependent intrinsic entropies of complex time series.

PubMed

Yeh, Jia-Rong; Peng, Chung-Kang; Huang, Norden E

2016-04-13

Multi-scale entropy (MSE) was developed as a measure of complexity for complex time series, and it has been applied widely in recent years. The MSE algorithm is based on the assumption that biological systems possess the ability to adapt and function in an ever-changing environment, and these systems need to operate across multiple temporal and spatial scales, such that their complexity is also multi-scale and hierarchical. Here, we present a systematic approach to apply the empirical mode decomposition algorithm, which can detrend time series on various time scales, prior to analysing a signal's complexity by measuring the irregularity of its dynamics on multiple time scales. Simulated time series of fractal Gaussian noise and human heartbeat time series were used to study the performance of this new approach. We show that our method can successfully quantify the fractal properties of the simulated time series and can accurately distinguish modulations in human heartbeat time series in health and disease. © 2016 The Author(s).

Contemporary Children and Basal Reading Series.

ERIC Educational Resources Information Center

Klebacher, Kathryn F.

Contemporary children must deal with many family problems that children 20 years ago never had to face, including divorce, parental separation, death, working mothers, and economic status. To determine how well current basal reading series reflect the changing American family, the stories of four basal reading series for grades four, five, and six…

Extending nonlinear analysis to short ecological time series.

PubMed

Hsieh, Chih-hao; Anderson, Christian; Sugihara, George

2008-01-01

Nonlinearity is important and ubiquitous in ecology. Though detectable in principle, nonlinear behavior is often difficult to characterize, analyze, and incorporate mechanistically into models of ecosystem function. One obvious reason is that quantitative nonlinear analysis tools are data intensive (require long time series), and time series in ecology are generally short. Here we demonstrate a useful method that circumvents data limitation and reduces sampling error by combining ecologically similar multispecies time series into one long time series. With this technique, individual ecological time series containing as few as 20 data points can be mined for such important information as (1) significantly improved forecast ability, (2) the presence and location of nonlinearity, and (3) the effective dimensionality (the number of relevant variables) of an ecological system.

Parameters Design of Series Resonant Inverter Circuit

NASA Astrophysics Data System (ADS)

Qi, Xingkun; Peng, Yonglong; Li, Yabin

This paper analyzes the main circuit structure of series resonant inverter, and designs the components parameters of the main circuit.That provides a theoretical method for the design of series resonant inverter.

Efficient Algorithms for Segmentation of Item-Set Time Series

NASA Astrophysics Data System (ADS)

Chundi, Parvathi; Rosenkrantz, Daniel J.

We propose a special type of time series, which we call an item-set time series, to facilitate the temporal analysis of software version histories, email logs, stock market data, etc. In an item-set time series, each observed data value is a set of discrete items. We formalize the concept of an item-set time series and present efficient algorithms for segmenting a given item-set time series. Segmentation of a time series partitions the time series into a sequence of segments where each segment is constructed by combining consecutive time points of the time series. Each segment is associated with an item set that is computed from the item sets of the time points in that segment, using a function which we call a measure function. We then define a concept called the segment difference, which measures the difference between the item set of a segment and the item sets of the time points in that segment. The segment difference values are required to construct an optimal segmentation of the time series. We describe novel and efficient algorithms to compute segment difference values for each of the measure functions described in the paper. We outline a dynamic programming based scheme to construct an optimal segmentation of the given item-set time series. We use the item-set time series segmentation techniques to analyze the temporal content of three different data sets—Enron email, stock market data, and a synthetic data set. The experimental results show that an optimal segmentation of item-set time series data captures much more temporal content than a segmentation constructed based on the number of time points in each segment, without examining the item set data at the time points, and can be used to analyze different types of temporal data.

FATS: Feature Analysis for Time Series

NASA Astrophysics Data System (ADS)

Nun, Isadora; Protopapas, Pavlos; Sim, Brandon; Zhu, Ming; Dave, Rahul; Castro, Nicolas; Pichara, Karim

2017-11-01

FATS facilitates and standardizes feature extraction for time series data; it quickly and efficiently calculates a compilation of many existing light curve features. Users can characterize or analyze an astronomical photometric database, though this library is not necessarily restricted to the astronomical domain and can also be applied to any kind of time series data.

Forecasting Enrollments with Fuzzy Time Series.

ERIC Educational Resources Information Center

Song, Qiang; Chissom, Brad S.

The concept of fuzzy time series is introduced and used to forecast the enrollment of a university. Fuzzy time series, an aspect of fuzzy set theory, forecasts enrollment using a first-order time-invariant model. To evaluate the model, the conventional linear regression technique is applied and the predicted values obtained are compared to the…

4-H Science Inquiry Video Series

ERIC Educational Resources Information Center

Green, Jeremy W.; Black, Lynette; Willis, Patrick

2013-01-01

Studies support science inquiry as a positive method and approach for 4-H professionals and volunteers to use for teaching science-based practices to youth. The development of a science inquiry video series has yielded positive results as it relates to youth development education and science. The video series highlights how to conduct science-rich…

The Serious Series: Presenting Performing Arts in Succession.

ERIC Educational Resources Information Center

Miner, Stephen

1989-01-01

Four or five events together constitute a lively arts 'series'. Ways to make a college series a success are discussed, covering: goal setting, the talent, and promotion. The usual series range from four to six performances and allows a season ticket holder to experience varied selections of performing arts attraction. (MLW)

Phase walk analysis of leptokurtic time series.

PubMed

Schreiber, Korbinian; Modest, Heike I; Räth, Christoph

2018-06-01

The Fourier phase information play a key role for the quantified description of nonlinear data. We present a novel tool for time series analysis that identifies nonlinearities by sensitively detecting correlations among the Fourier phases. The method, being called phase walk analysis, is based on well established measures from random walk analysis, which are now applied to the unwrapped Fourier phases of time series. We provide an analytical description of its functionality and demonstrate its capabilities on systematically controlled leptokurtic noise. Hereby, we investigate the properties of leptokurtic time series and their influence on the Fourier phases of time series. The phase walk analysis is applied to measured and simulated intermittent time series, whose probability density distribution is approximated by power laws. We use the day-to-day returns of the Dow-Jones industrial average, a synthetic time series with tailored nonlinearities mimicing the power law behavior of the Dow-Jones and the acceleration of the wind at an Atlantic offshore site. Testing for nonlinearities by means of surrogates shows that the new method yields strong significances for nonlinear behavior. Due to the drastically decreased computing time as compared to embedding space methods, the number of surrogate realizations can be increased by orders of magnitude. Thereby, the probability distribution of the test statistics can very accurately be derived and parameterized, which allows for much more precise tests on nonlinearities.

Learning time series for intelligent monitoring

NASA Technical Reports Server (NTRS)

Manganaris, Stefanos; Fisher, Doug

1994-01-01

We address the problem of classifying time series according to their morphological features in the time domain. In a supervised machine-learning framework, we induce a classification procedure from a set of preclassified examples. For each class, we infer a model that captures its morphological features using Bayesian model induction and the minimum message length approach to assign priors. In the performance task, we classify a time series in one of the learned classes when there is enough evidence to support that decision. Time series with sufficiently novel features, belonging to classes not present in the training set, are recognized as such. We report results from experiments in a monitoring domain of interest to NASA.

Time Series Model Identification and Prediction Variance Horizon.

DTIC Science & Technology

1980-06-01

stationary time series Y(t). -6- In terms of p(v), the definition of the three time series memory types is: No Memory Short Memory Long Memory X IP (v)I 0 0...X lp(v)l < - I IP (v) = v=1 v=l v=l Within short memory time series there are three types whose classification in terms of correlation functions is...1974) "Some Recent Advances in Time Series Modeling", TEEE Transactions on Automatic ControZ, VoZ . AC-19, No. 6, December, 723-730. Parzen, E. (1976) "An

Sensor-Generated Time Series Events: A Definition Language

PubMed Central

Anguera, Aurea; Lara, Juan A.; Lizcano, David; Martínez, Maria Aurora; Pazos, Juan

2012-01-01

There are now a great many domains where information is recorded by sensors over a limited time period or on a permanent basis. This data flow leads to sequences of data known as time series. In many domains, like seismography or medicine, time series analysis focuses on particular regions of interest, known as events, whereas the remainder of the time series contains hardly any useful information. In these domains, there is a need for mechanisms to identify and locate such events. In this paper, we propose an events definition language that is general enough to be used to easily and naturally define events in time series recorded by sensors in any domain. The proposed language has been applied to the definition of time series events generated within the branch of medicine dealing with balance-related functions in human beings. A device, called posturograph, is used to study balance-related functions. The platform has four sensors that record the pressure intensity being exerted on the platform, generating four interrelated time series. As opposed to the existing ad hoc proposals, the results confirm that the proposed language is valid, that is generally applicable and accurate, for identifying the events contained in the time series.

Series and parallel arc-fault circuit interrupter tests.

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

Johnson, Jay Dean; Fresquez, Armando J.; Gudgel, Bob

2013-07-01

While the 2011 National Electrical Codeª (NEC) only requires series arc-fault protection, some arc-fault circuit interrupter (AFCI) manufacturers are designing products to detect and mitigate both series and parallel arc-faults. Sandia National Laboratories (SNL) has extensively investigated the electrical differences of series and parallel arc-faults and has offered possible classification and mitigation solutions. As part of this effort, Sandia National Laboratories has collaborated with MidNite Solar to create and test a 24-string combiner box with an AFCI which detects, differentiates, and de-energizes series and parallel arc-faults. In the case of the MidNite AFCI prototype, series arc-faults are mitigated by openingmore » the PV strings, whereas parallel arc-faults are mitigated by shorting the array. A range of different experimental series and parallel arc-fault tests with the MidNite combiner box were performed at the Distributed Energy Technologies Laboratory (DETL) at SNL in Albuquerque, NM. In all the tests, the prototype de-energized the arc-faults in the time period required by the arc-fault circuit interrupt testing standard, UL 1699B. The experimental tests confirm series and parallel arc-faults can be successfully mitigated with a combiner box-integrated solution.« less

Computing singularities of perturbation series

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

Kvaal, Simen; Jarlebring, Elias; Michiels, Wim

2011-03-15

Many properties of current ab initio approaches to the quantum many-body problem, both perturbational and otherwise, are related to the singularity structure of the Rayleigh-Schroedinger perturbation series. A numerical procedure is presented that in principle computes the complete set of singularities, including the dominant singularity which limits the radius of convergence. The method approximates the singularities as eigenvalues of a certain generalized eigenvalue equation which is solved using iterative techniques. It relies on computation of the action of the Hamiltonian matrix on a vector and does not rely on the terms in the perturbation series. The method can be usefulmore » for studying perturbation series of typical systems of moderate size, for fundamental development of resummation schemes, and for understanding the structure of singularities for typical systems. Some illustrative model problems are studied, including a helium-like model with {delta}-function interactions for which Moeller-Plesset perturbation theory is considered and the radius of convergence found.« less

Financial Time-series Analysis: a Brief Overview

NASA Astrophysics Data System (ADS)

Chakraborti, A.; Patriarca, M.; Santhanam, M. S.

Prices of commodities or assets produce what is called time-series. Different kinds of financial time-series have been recorded and studied for decades. Nowadays, all transactions on a financial market are recorded, leading to a huge amount of data available, either for free in the Internet or commercially. Financial time-series analysis is of great interest to practitioners as well as to theoreticians, for making inferences and predictions. Furthermore, the stochastic uncertainties inherent in financial time-series and the theory needed to deal with them make the subject especially interesting not only to economists, but also to statisticians and physicists [1]. While it would be a formidable task to make an exhaustive review on the topic, with this review we try to give a flavor of some of its aspects.

31 CFR 315.31 - Series H bonds.

Code of Federal Regulations, 2014 CFR

2014-07-01

.... Series H bonds are current income bonds issued at par (face amount). Interest on a Series H bond is paid... the Fiscal Service for recognition as voluntary guardian for the purpose of receiving and collecting...

Characterizing artifacts in RR stress test time series.

PubMed

Astudillo-Salinas, Fabian; Palacio-Baus, Kenneth; Solano-Quinde, Lizandro; Medina, Ruben; Wong, Sara

2016-08-01

Electrocardiographic stress test records have a lot of artifacts. In this paper we explore a simple method to characterize the amount of artifacts present in unprocessed RR stress test time series. Four time series classes were defined: Very good lead, Good lead, Low quality lead and Useless lead. 65 ECG, 8 lead, records of stress test series were analyzed. Firstly, RR-time series were annotated by two experts. The automatic methodology is based on dividing the RR-time series in non-overlapping windows. Each window is marked as noisy whenever it exceeds an established standard deviation threshold (SDT). Series are classified according to the percentage of windows that exceeds a given value, based upon the first manual annotation. Different SDT were explored. Results show that SDT close to 20% (as a percentage of the mean) provides the best results. The coincidence between annotators classification is 70.77% whereas, the coincidence between the second annotator and the automatic method providing the best matches is larger than 63%. Leads classified as Very good leads and Good leads could be combined to improve automatic heartbeat labeling.

31 CFR 315.31 - Series H bonds.

Code of Federal Regulations, 2013 CFR

2013-07-01

.... Series H bonds are current income bonds issued at par (face amount). Interest on a Series H bond is paid... the Public Debt for recognition as voluntary guardian for the purpose of receiving and collecting the...

31 CFR 315.31 - Series H bonds.

Code of Federal Regulations, 2012 CFR

2012-07-01

.... Series H bonds are current income bonds issued at par (face amount). Interest on a Series H bond is paid... the Public Debt for recognition as voluntary guardian for the purpose of receiving and collecting the...

31 CFR 315.31 - Series H bonds.

Code of Federal Regulations, 2011 CFR

2011-07-01

.... Series H bonds are current income bonds issued at par (face amount). Interest on a Series H bond is paid... the Public Debt for recognition as voluntary guardian for the purpose of receiving and collecting the...

Combined scanning transmission electron microscopy tilt- and focal series.

PubMed

Dahmen, Tim; Baudoin, Jean-Pierre; Lupini, Andrew R; Kübel, Christian; Slusallek, Philipp; de Jonge, Niels

2014-04-01

In this study, a combined tilt- and focal series is proposed as a new recording scheme for high-angle annular dark-field scanning transmission electron microscopy (STEM) tomography. Three-dimensional (3D) data were acquired by mechanically tilting the specimen, and recording a through-focal series at each tilt direction. The sample was a whole-mount macrophage cell with embedded gold nanoparticles. The tilt-focal algebraic reconstruction technique (TF-ART) is introduced as a new algorithm to reconstruct tomograms from such combined tilt- and focal series. The feasibility of TF-ART was demonstrated by 3D reconstruction of the experimental 3D data. The results were compared with a conventional STEM tilt series of a similar sample. The combined tilt- and focal series led to smaller "missing wedge" artifacts, and a higher axial resolution than obtained for the STEM tilt series, thus improving on one of the main issues of tilt series-based electron tomography.

Nonlinear parametric model for Granger causality of time series

NASA Astrophysics Data System (ADS)

Marinazzo, Daniele; Pellicoro, Mario; Stramaglia, Sebastiano

2006-06-01

The notion of Granger causality between two time series examines if the prediction of one series could be improved by incorporating information of the other. In particular, if the prediction error of the first time series is reduced by including measurements from the second time series, then the second time series is said to have a causal influence on the first one. We propose a radial basis function approach to nonlinear Granger causality. The proposed model is not constrained to be additive in variables from the two time series and can approximate any function of these variables, still being suitable to evaluate causality. Usefulness of this measure of causality is shown in two applications. In the first application, a physiological one, we consider time series of heart rate and blood pressure in congestive heart failure patients and patients affected by sepsis: we find that sepsis patients, unlike congestive heart failure patients, show symmetric causal relationships between the two time series. In the second application, we consider the feedback loop in a model of excitatory and inhibitory neurons: we find that in this system causality measures the combined influence of couplings and membrane time constants.

Properties of 91 Southern Soil Series

Treesearch

Basil D. Doss; W. M. Broadfoot

1956-01-01

From June 1954 to July 1955 the Vicksburg Infiltration Project collected and analyzed samples of 91 soil series in 7 southern states. The purpose was to supply the U. S. Army with information needed for specialized research on military trafficability, but the basic data on soil properties should be of interest to soil scientists generally. The 91 series may be...

A Power Series Expansion and Its Applications

ERIC Educational Resources Information Center

Chen, Hongwei

2006-01-01

Using the power series solution of a differential equation and the computation of a parametric integral, two elementary proofs are given for the power series expansion of (arcsin x)[squared], as well as some applications of this expansion.

The Biology and Space Exploration Video Series

NASA Technical Reports Server (NTRS)

William, Jacqueline M.; Murthy, Gita; Rapa, Steve; Hargens, Alan R.

1995-01-01

The Biology and Space Exploration video series illustrates NASA's commitment to increasing the public awareness and understanding of life sciences in space. The video series collection, which was initiated by Dr. Joan Vernikos at NASA headquarters and Dr. Alan Hargens at NASA Ames Research Center, will be distributed to universities and other institutions around the United States. The video series parallels the "Biology and Space Exploration" course taught by NASA Ames scientists at Stanford University, Palo Alto, California. In the past, students have shown considerable enthusiasm for this course and have gained a much better appreciation and understanding of space life sciences and exploration. However, due to the unique nature of the topics and the scarcity of available educational materials, most students in other universities around the country are unable to benefit from this educational experience. Therefore, with the assistance of Ames experts, we are producing a video series on selected aspects of life sciences in space to expose undergraduate students to the effects of gravity on living systems. Additionally, the video series collection contains space flight footage, graphics, charts, pictures, and interviews to make the materials interesting and intelligible to viewers.

Time series modeling in traffic safety research.

PubMed

Lavrenz, Steven M; Vlahogianni, Eleni I; Gkritza, Konstantina; Ke, Yue

2018-08-01

The use of statistical models for analyzing traffic safety (crash) data has been well-established. However, time series techniques have traditionally been underrepresented in the corresponding literature, due to challenges in data collection, along with a limited knowledge of proper methodology. In recent years, new types of high-resolution traffic safety data, especially in measuring driver behavior, have made time series modeling techniques an increasingly salient topic of study. Yet there remains a dearth of information to guide analysts in their use. This paper provides an overview of the state of the art in using time series models in traffic safety research, and discusses some of the fundamental techniques and considerations in classic time series modeling. It also presents ongoing and future opportunities for expanding the use of time series models, and explores newer modeling techniques, including computational intelligence models, which hold promise in effectively handling ever-larger data sets. The information contained herein is meant to guide safety researchers in understanding this broad area of transportation data analysis, and provide a framework for understanding safety trends that can influence policy-making. Copyright © 2017 Elsevier Ltd. All rights reserved.

Arithmetical functions and irrationality of Lambert series

NASA Astrophysics Data System (ADS)

Duverney, Daniel

2011-09-01

We use a method of Erdös in order to prove the linear independence over Q of the numbers 1, ∑ n = 1+∞1/qn2-1, ∑ n = 1+∞n/qn2-1 for every q∈Z, with |q|≥2. The main idea consists in considering the two above series as Lambert series. This allows to expand them as power series of 1/q. The Taylor coefficients of these expansions are arithmetical functions, whose properties allow to apply an elementary irrationality criterion, which yields the result.

Series approximation to probability densities

NASA Astrophysics Data System (ADS)

Cohen, L.

2018-04-01

One of the historical and fundamental uses of the Edgeworth and Gram-Charlier series is to "correct" a Gaussian density when it is determined that the probability density under consideration has moments that do not correspond to the Gaussian [5, 6]. There is a fundamental difficulty with these methods in that if the series are truncated, then the resulting approximate density is not manifestly positive. The aim of this paper is to attempt to expand a probability density so that if it is truncated it will still be manifestly positive.

Analysis of Nonstationary Time Series for Biological Rhythms Research.

PubMed

Leise, Tanya L

2017-06-01

This article is part of a Journal of Biological Rhythms series exploring analysis and statistics topics relevant to researchers in biological rhythms and sleep research. The goal is to provide an overview of the most common issues that arise in the analysis and interpretation of data in these fields. In this article on time series analysis for biological rhythms, we describe some methods for assessing the rhythmic properties of time series, including tests of whether a time series is indeed rhythmic. Because biological rhythms can exhibit significant fluctuations in their period, phase, and amplitude, their analysis may require methods appropriate for nonstationary time series, such as wavelet transforms, which can measure how these rhythmic parameters change over time. We illustrate these methods using simulated and real time series.

Time series smoother for effect detection.

PubMed

You, Cheng; Lin, Dennis K J; Young, S Stanley

2018-01-01

In environmental epidemiology, it is often encountered that multiple time series data with a long-term trend, including seasonality, cannot be fully adjusted by the observed covariates. The long-term trend is difficult to separate from abnormal short-term signals of interest. This paper addresses how to estimate the long-term trend in order to recover short-term signals. Our case study demonstrates that the current spline smoothing methods can result in significant positive and negative cross-correlations from the same dataset, depending on how the smoothing parameters are chosen. To circumvent this dilemma, three classes of time series smoothers are proposed to detrend time series data. These smoothers do not require fine tuning of parameters and can be applied to recover short-term signals. The properties of these smoothers are shown with both a case study using a factorial design and a simulation study using datasets generated from the original dataset. General guidelines are provided on how to discover short-term signals from time series with a long-term trend. The benefit of this research is that a problem is identified and characteristics of possible solutions are determined.

Time series smoother for effect detection

PubMed Central

Lin, Dennis K. J.; Young, S. Stanley

2018-01-01

In environmental epidemiology, it is often encountered that multiple time series data with a long-term trend, including seasonality, cannot be fully adjusted by the observed covariates. The long-term trend is difficult to separate from abnormal short-term signals of interest. This paper addresses how to estimate the long-term trend in order to recover short-term signals. Our case study demonstrates that the current spline smoothing methods can result in significant positive and negative cross-correlations from the same dataset, depending on how the smoothing parameters are chosen. To circumvent this dilemma, three classes of time series smoothers are proposed to detrend time series data. These smoothers do not require fine tuning of parameters and can be applied to recover short-term signals. The properties of these smoothers are shown with both a case study using a factorial design and a simulation study using datasets generated from the original dataset. General guidelines are provided on how to discover short-term signals from time series with a long-term trend. The benefit of this research is that a problem is identified and characteristics of possible solutions are determined. PMID:29684033

75 FR 54462 - Airworthiness Directives; Bombardier-Rotax GmbH 912 F Series and 912 S Series Reciprocating Engines

Federal Register 2010, 2011, 2012, 2013, 2014

2010-09-08

... Airworthiness Directives; Bombardier-Rotax GmbH 912 F Series and 912 S Series Reciprocating Engines AGENCY... result in exceeding of the fuel pressure and might cause engine malfunction and/or massive fuel leakage... engine malfunction or a massive fuel leak. These conditions could cause loss of control of the airplane...

Eisenstein Series and String Thresholds

NASA Astrophysics Data System (ADS)

Obers, N. A.; Pioline, B.

We investigate the relevance of Eisenstein series for representing certain G()-invariant string theory amplitudes which receive corrections from BPS states only. G() may stand for any of the mapping class, T-duality and U-duality groups Sl(d,(), SO(d,d,() or Ed+1(d+1)(() respectively. Using G()-invariant mass formulae, we construct invariant modular functions on the symmetric space K\\G() of non-compact type, with K the maximal compact subgroup of G(), that generalize the standard non-holomorphic Eisenstein series arising in harmonic analysis on the fundamental domain of the Poincaré upper half-plane. Comparing the asymptotics and eigenvalues of the Eisenstein series under second order differential operators with quantities arising in one- and g-loop string amplitudes, we obtain a manifestly T-duality invariant representation of the latter, conjecture their non-perturbative U-duality invariant extension, and analyze the resulting non-perturbative effects. This includes the R4 and R4H4g-4 couplings in toroidal compactifications of M-theory to any dimension D>= 4 and D>= 6 respectively.

Time series of the northeast Pacific

NASA Astrophysics Data System (ADS)

Peña, M. Angelica; Bograd, Steven J.

2007-10-01

In July 2006, the North Pacific Marine Science Organization (PICES) and Fisheries & Oceans Canada sponsored the symposium “Time Series of the Northeast Pacific: A symposium to mark the 50th anniversary of Line P”. The symposium, which celebrated 50 years of oceanography along Line P and at Ocean Station Papa (OSP), explored the scientific value of the Line P and other long oceanographic time series of the northeast Pacific (NEP). Overviews of the principal NEP time-series were presented, which facilitated regional comparisons and promoted interaction and exchange of information among investigators working in the NEP. More than 80 scientists from 8 countries attended the symposium. This introductory essay is a brief overview of the symposium and the 10 papers that were selected for this special issue of Progress in Oceanography.

AMTEC vapor-vapor series connected cells

NASA Technical Reports Server (NTRS)

Underwood, Mark L. (Inventor); Williams, Roger M. (Inventor); Ryan, Margaret A. (Inventor); Nakamura, Barbara J. (Inventor); Oconnor, Dennis E. (Inventor)

1995-01-01

An alkali metal thermoelectric converter (AMTEC) having a plurality of cells structurally connected in series to form a septum dividing a plenum into two chambers, and electrically connected in series, is provided with porous metal anodes and porous metal cathodes in the cells. The cells may be planar or annular, and in either case a metal alkali vapor at a high temperature is provided to the plenum through one chamber on one side of the wall and returned to a vapor boiler after condensation at a chamber on the other side of the wall in the plenum. If the cells are annular, a heating core may be placed along the axis of the stacked cells. This arrangement of series-connected cells allows efficient generation of power at high voltage and low current.

Teachers' Views of Mathematics Textbook Series in Flanders: Does it (Not) Matter Which Mathematics Textbook Series Schools Choose?

ERIC Educational Resources Information Center

Van Steenbrugge, H.; Valcke, M.; Desoete, A.

2013-01-01

The debate on the differential effects of mathematics textbook series is a recurrent topic in the research literature. Research results remain inconclusive, pointing to a lack of evidence to decide on the relevance of the selection by schools of a mathematics textbook series. Studies also point to difficulties in comparing textbooks. Recently, in…

Characterizing time series via complexity-entropy curves

NASA Astrophysics Data System (ADS)

Ribeiro, Haroldo V.; Jauregui, Max; Zunino, Luciano; Lenzi, Ervin K.

2017-06-01

The search for patterns in time series is a very common task when dealing with complex systems. This is usually accomplished by employing a complexity measure such as entropies and fractal dimensions. However, such measures usually only capture a single aspect of the system dynamics. Here, we propose a family of complexity measures for time series based on a generalization of the complexity-entropy causality plane. By replacing the Shannon entropy by a monoparametric entropy (Tsallis q entropy) and after considering the proper generalization of the statistical complexity (q complexity), we build up a parametric curve (the q -complexity-entropy curve) that is used for characterizing and classifying time series. Based on simple exact results and numerical simulations of stochastic processes, we show that these curves can distinguish among different long-range, short-range, and oscillating correlated behaviors. Also, we verify that simulated chaotic and stochastic time series can be distinguished based on whether these curves are open or closed. We further test this technique in experimental scenarios related to chaotic laser intensity, stock price, sunspot, and geomagnetic dynamics, confirming its usefulness. Finally, we prove that these curves enhance the automatic classification of time series with long-range correlations and interbeat intervals of healthy subjects and patients with heart disease.

A Normalized Sunspot-Area Series Starting in 1832: An Update

NASA Astrophysics Data System (ADS)

Carrasco, V. M. S.; Vaquero, J. M.; Gallego, M. C.; Sánchez-Bajo, F.

2016-11-01

A new normalized sunspot-area series has been reconstructed from the series obtained by the Royal Greenwich Observatory and other contemporary institutions for the period 1874 - 2008 and the area series compiled by De la Rue, Stewart, and Loewy from 1832 to 1868. Since the two sets of series do not overlap in time, we used the new version of sunspot index number (Version 2) published by Sunspot Index and Long-term Solar Observations (SILSO) as a link between them. We also present a spectral analysis of the normalized-area series in search of periodicities beyond the well-known solar cycle of 11 years and a study of the Waldmeier effect in the new version of sunspot number and the sunspot-area series presented in this study. We conclude that while this effect is significant in the new series of sunspot number, it has a weak relationship with the sunspot-area series.

Data imputation analysis for Cosmic Rays time series

NASA Astrophysics Data System (ADS)

Fernandes, R. C.; Lucio, P. S.; Fernandez, J. H.

2017-05-01

The occurrence of missing data concerning Galactic Cosmic Rays time series (GCR) is inevitable since loss of data is due to mechanical and human failure or technical problems and different periods of operation of GCR stations. The aim of this study was to perform multiple dataset imputation in order to depict the observational dataset. The study has used the monthly time series of GCR Climax (CLMX) and Roma (ROME) from 1960 to 2004 to simulate scenarios of 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80% and 90% of missing data compared to observed ROME series, with 50 replicates. Then, the CLMX station as a proxy for allocation of these scenarios was used. Three different methods for monthly dataset imputation were selected: AMÉLIA II - runs the bootstrap Expectation Maximization algorithm, MICE - runs an algorithm via Multivariate Imputation by Chained Equations and MTSDI - an Expectation Maximization algorithm-based method for imputation of missing values in multivariate normal time series. The synthetic time series compared with the observed ROME series has also been evaluated using several skill measures as such as RMSE, NRMSE, Agreement Index, R, R2, F-test and t-test. The results showed that for CLMX and ROME, the R2 and R statistics were equal to 0.98 and 0.96, respectively. It was observed that increases in the number of gaps generate loss of quality of the time series. Data imputation was more efficient with MTSDI method, with negligible errors and best skill coefficients. The results suggest a limit of about 60% of missing data for imputation, for monthly averages, no more than this. It is noteworthy that CLMX, ROME and KIEL stations present no missing data in the target period. This methodology allowed reconstructing 43 time series.

Developing consistent time series landsat data products

USDA-ARS?s Scientific Manuscript database

The Landsat series satellite has provided earth observation data record continuously since early 1970s. There are increasing demands on having a consistent time series of Landsat data products. In this presentation, I will summarize the work supported by the USGS Landsat Science Team project from 20...

Multifractal analysis of visibility graph-based Ito-related connectivity time series.

PubMed

Czechowski, Zbigniew; Lovallo, Michele; Telesca, Luciano

2016-02-01

In this study, we investigate multifractal properties of connectivity time series resulting from the visibility graph applied to normally distributed time series generated by the Ito equations with multiplicative power-law noise. We show that multifractality of the connectivity time series (i.e., the series of numbers of links outgoing any node) increases with the exponent of the power-law noise. The multifractality of the connectivity time series could be due to the width of connectivity degree distribution that can be related to the exit time of the associated Ito time series. Furthermore, the connectivity time series are characterized by persistence, although the original Ito time series are random; this is due to the procedure of visibility graph that, connecting the values of the time series, generates persistence but destroys most of the nonlinear correlations. Moreover, the visibility graph is sensitive for detecting wide "depressions" in input time series.

Complex network approach to fractional time series

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

Manshour, Pouya

In order to extract correlation information inherited in stochastic time series, the visibility graph algorithm has been recently proposed, by which a time series can be mapped onto a complex network. We demonstrate that the visibility algorithm is not an appropriate one to study the correlation aspects of a time series. We then employ the horizontal visibility algorithm, as a much simpler one, to map fractional processes onto complex networks. The degree distributions are shown to have parabolic exponential forms with Hurst dependent fitting parameter. Further, we take into account other topological properties such as maximum eigenvalue of the adjacencymore » matrix and the degree assortativity, and show that such topological quantities can also be used to predict the Hurst exponent, with an exception for anti-persistent fractional Gaussian noises. To solve this problem, we take into account the Spearman correlation coefficient between nodes' degrees and their corresponding data values in the original time series.« less

Advanced spectral methods for climatic time series

USGS Publications Warehouse

Ghil, M.; Allen, M.R.; Dettinger, M.D.; Ide, K.; Kondrashov, D.; Mann, M.E.; Robertson, A.W.; Saunders, A.; Tian, Y.; Varadi, F.; Yiou, P.

2002-01-01

The analysis of univariate or multivariate time series provides crucial information to describe, understand, and predict climatic variability. The discovery and implementation of a number of novel methods for extracting useful information from time series has recently revitalized this classical field of study. Considerable progress has also been made in interpreting the information so obtained in terms of dynamical systems theory. In this review we describe the connections between time series analysis and nonlinear dynamics, discuss signal- to-noise enhancement, and present some of the novel methods for spectral analysis. The various steps, as well as the advantages and disadvantages of these methods, are illustrated by their application to an important climatic time series, the Southern Oscillation Index. This index captures major features of interannual climate variability and is used extensively in its prediction. Regional and global sea surface temperature data sets are used to illustrate multivariate spectral methods. Open questions and further prospects conclude the review.

A novel weight determination method for time series data aggregation

NASA Astrophysics Data System (ADS)

Xu, Paiheng; Zhang, Rong; Deng, Yong

2017-09-01

Aggregation in time series is of great importance in time series smoothing, predicting and other time series analysis process, which makes it crucial to address the weights in times series correctly and reasonably. In this paper, a novel method to obtain the weights in time series is proposed, in which we adopt induced ordered weighted aggregation (IOWA) operator and visibility graph averaging (VGA) operator and linearly combine the weights separately generated by the two operator. The IOWA operator is introduced to the weight determination of time series, through which the time decay factor is taken into consideration. The VGA operator is able to generate weights with respect to the degree distribution in the visibility graph constructed from the corresponding time series, which reflects the relative importance of vertices in time series. The proposed method is applied to two practical datasets to illustrate its merits. The aggregation of Construction Cost Index (CCI) demonstrates the ability of proposed method to smooth time series, while the aggregation of The Taiwan Stock Exchange Capitalization Weighted Stock Index (TAIEX) illustrate how proposed method maintain the variation tendency of original data.

76 FR 77857 - Seasons Series Trust, et al.; Notice of Application

Federal Register 2010, 2011, 2012, 2013, 2014

2011-12-14

...] Seasons Series Trust, et al.; Notice of Application December 8, 2011. AGENCY: Securities and Exchange... 12d1-2 under the Act to invest in certain financial instruments. Applicants: Seasons Series Trust (``Seasons''), SunAmerica Series Trust (``Series Trust''), VALIC Company II (``VALIC II''), SunAmerica Series...

Higher-Order Hurst Signatures: Dynamical Information in Time Series

NASA Astrophysics Data System (ADS)

Ferenbaugh, Willis

2005-10-01

Understanding and comparing time series from different systems requires characteristic measures of the dynamics embedded in the series. The Hurst exponent is a second-order dynamical measure of a time series which grew up within the blossoming fractal world of Mandelbrot. This characteristic measure is directly related to the behavior of the autocorrelation, the power-spectrum, and other second-order things. And as with these other measures, the Hurst exponent captures and quantifies some but not all of the intrinsic nature of a series. The more elusive characteristics live in the phase spectrum and the higher-order spectra. This research is a continuing quest to (more) fully characterize the dynamical information in time series produced by plasma experiments or models. The goal is to supplement the series information which can be represented by a Hurst exponent, and we would like to develop supplemental techniques in analogy with Hurst's original R/S analysis. These techniques should be another way to plumb the higher-order dynamics.

Modeling Time Series Data for Supervised Learning

ERIC Educational Resources Information Center

Baydogan, Mustafa Gokce

2012-01-01

Temporal data are increasingly prevalent and important in analytics. Time series (TS) data are chronological sequences of observations and an important class of temporal data. Fields such as medicine, finance, learning science and multimedia naturally generate TS data. Each series provide a high-dimensional data vector that challenges the learning…

NASA's Applied Remote Sensing Training (ARSET) Webinar Series

Atmospheric Science Data Center

2016-07-12

NASA's Applied Remote Sensing Training (ARSET) Webinar Series Tuesday, July 12, 2016 ... you of a free training opportunity: Introduction to Remote Sensing for Air Quality Applications Webinar Series Beginning in ...

The Lesson Plan of the Month. Series 3. 10 Lesson Series.

ERIC Educational Resources Information Center

Phi Alpha Delta Fraternity International, Granada Hills, CA. Public Service Center.

Focusing on current topics germane to law-related education (LRE), this guide features ten LRE lessons. As part of a series of lesson plans compiled by Phi Alpha Delta, this collection presents a lesson plan on current issues for each month of the school year. Intended for high school and middle school with adaptations for elementary school, the…

Layered Ensemble Architecture for Time Series Forecasting.

PubMed

Rahman, Md Mustafizur; Islam, Md Monirul; Murase, Kazuyuki; Yao, Xin

2016-01-01

Time series forecasting (TSF) has been widely used in many application areas such as science, engineering, and finance. The phenomena generating time series are usually unknown and information available for forecasting is only limited to the past values of the series. It is, therefore, necessary to use an appropriate number of past values, termed lag, for forecasting. This paper proposes a layered ensemble architecture (LEA) for TSF problems. Our LEA consists of two layers, each of which uses an ensemble of multilayer perceptron (MLP) networks. While the first ensemble layer tries to find an appropriate lag, the second ensemble layer employs the obtained lag for forecasting. Unlike most previous work on TSF, the proposed architecture considers both accuracy and diversity of the individual networks in constructing an ensemble. LEA trains different networks in the ensemble by using different training sets with an aim of maintaining diversity among the networks. However, it uses the appropriate lag and combines the best trained networks to construct the ensemble. This indicates LEAs emphasis on accuracy of the networks. The proposed architecture has been tested extensively on time series data of neural network (NN)3 and NN5 competitions. It has also been tested on several standard benchmark time series data. In terms of forecasting accuracy, our experimental results have revealed clearly that LEA is better than other ensemble and nonensemble methods.

Energy-Based Wavelet De-Noising of Hydrologic Time Series

PubMed Central

Sang, Yan-Fang; Liu, Changming; Wang, Zhonggen; Wen, Jun; Shang, Lunyu

2014-01-01

De-noising is a substantial issue in hydrologic time series analysis, but it is a difficult task due to the defect of methods. In this paper an energy-based wavelet de-noising method was proposed. It is to remove noise by comparing energy distribution of series with the background energy distribution, which is established from Monte-Carlo test. Differing from wavelet threshold de-noising (WTD) method with the basis of wavelet coefficient thresholding, the proposed method is based on energy distribution of series. It can distinguish noise from deterministic components in series, and uncertainty of de-noising result can be quantitatively estimated using proper confidence interval, but WTD method cannot do this. Analysis of both synthetic and observed series verified the comparable power of the proposed method and WTD, but de-noising process by the former is more easily operable. The results also indicate the influences of three key factors (wavelet choice, decomposition level choice and noise content) on wavelet de-noising. Wavelet should be carefully chosen when using the proposed method. The suitable decomposition level for wavelet de-noising should correspond to series' deterministic sub-signal which has the smallest temporal scale. If too much noise is included in a series, accurate de-noising result cannot be obtained by the proposed method or WTD, but the series would show pure random but not autocorrelation characters, so de-noising is no longer needed. PMID:25360533

Transition Icons for Time-Series Visualization and Exploratory Analysis.

PubMed

Nickerson, Paul V; Baharloo, Raheleh; Wanigatunga, Amal A; Manini, Todd M; Tighe, Patrick J; Rashidi, Parisa

2018-03-01

The modern healthcare landscape has seen the rapid emergence of techniques and devices that temporally monitor and record physiological signals. The prevalence of time-series data within the healthcare field necessitates the development of methods that can analyze the data in order to draw meaningful conclusions. Time-series behavior is notoriously difficult to intuitively understand due to its intrinsic high-dimensionality, which is compounded in the case of analyzing groups of time series collected from different patients. Our framework, which we call transition icons, renders common patterns in a visual format useful for understanding the shared behavior within groups of time series. Transition icons are adept at detecting and displaying subtle differences and similarities, e.g., between measurements taken from patients receiving different treatment strategies or stratified by demographics. We introduce various methods that collectively allow for exploratory analysis of groups of time series, while being free of distribution assumptions and including simple heuristics for parameter determination. Our technique extracts discrete transition patterns from symbolic aggregate approXimation representations, and compiles transition frequencies into a bag of patterns constructed for each group. These transition frequencies are normalized and aligned in icon form to intuitively display the underlying patterns. We demonstrate the transition icon technique for two time-series datasets-postoperative pain scores, and hip-worn accelerometer activity counts. We believe transition icons can be an important tool for researchers approaching time-series data, as they give rich and intuitive information about collective time-series behaviors.

Remote Sensing Time Series Product Tool

NASA Technical Reports Server (NTRS)

Predos, Don; Ryan, Robert E.; Ross, Kenton W.

2006-01-01

The TSPT (Time Series Product Tool) software was custom-designed for NASA to rapidly create and display single-band and band-combination time series, such as NDVI (Normalized Difference Vegetation Index) images, for wide-area crop surveillance and for other time-critical applications. The TSPT, developed in MATLAB, allows users to create and display various MODIS (Moderate Resolution Imaging Spectroradiometer) or simulated VIIRS (Visible/Infrared Imager Radiometer Suite) products as single images, as time series plots at a selected location, or as temporally processed image videos. Manually creating these types of products is extremely labor intensive; however, the TSPT development tool makes the process simplified and efficient. MODIS is ideal for monitoring large crop areas because of its wide swath (2330 km), its relatively small ground sample distance (250 m), and its high temporal revisit time (twice daily). Furthermore, because MODIS imagery is acquired daily, rapid changes in vegetative health can potentially be detected. The new TSPT technology provides users with the ability to temporally process high-revisit-rate satellite imagery, such as that acquired from MODIS and from its successor, the VIIRS. The TSPT features the important capability of fusing data from both MODIS instruments onboard the Terra and Aqua satellites, which drastically improves cloud statistics. With the TSPT, MODIS metadata is used to find and optionally remove bad and suspect data. Noise removal and temporal processing techniques allow users to create low-noise time series plots and image videos and to select settings and thresholds that tailor particular output products. The TSPT GUI (graphical user interface) provides an interactive environment for crafting what-if scenarios by enabling a user to repeat product generation using different settings and thresholds. The TSPT Application Programming Interface provides more fine-tuned control of product generation, allowing experienced

Recurrent Neural Network Applications for Astronomical Time Series

NASA Astrophysics Data System (ADS)

Protopapas, Pavlos

2017-06-01

The benefits of good predictive models in astronomy lie in early event prediction systems and effective resource allocation. Current time series methods applicable to regular time series have not evolved to generalize for irregular time series. In this talk, I will describe two Recurrent Neural Network methods, Long Short-Term Memory (LSTM) and Echo State Networks (ESNs) for predicting irregular time series. Feature engineering along with a non-linear modeling proved to be an effective predictor. For noisy time series, the prediction is improved by training the network on error realizations using the error estimates from astronomical light curves. In addition to this, we propose a new neural network architecture to remove correlation from the residuals in order to improve prediction and compensate for the noisy data. Finally, I show how to set hyperparameters for a stable and performant solution correctly. In this work, we circumvent this obstacle by optimizing ESN hyperparameters using Bayesian optimization with Gaussian Process priors. This automates the tuning procedure, enabling users to employ the power of RNN without needing an in-depth understanding of the tuning procedure.

Inspiring Examples in Rearrangements of Infinite Series

ERIC Educational Resources Information Center

Ramasinghe, W.

2002-01-01

Simple examples are really encouraging in the understanding of rearrangements of infinite series, since many texts and teachers provide only existence theorems. In the absence of examples, an existence theorem is just a statement and lends little confidence to understanding. Iterated sums of double series seem to have a similar spirit of…

OA-7 Veggie Series 1 Processing

NASA Image and Video Library

2017-02-15

Charles Spern, project manager on the Engineering Services Contract (ESC), and Glenn Washington, ESC quality assurance specialist, perform final inspections of the Veggie Series 1 plant experiment inside a laboratory in the Space Station Processing Facility at NASA's Kennedy Space Center in Florida. The Series 1 experiment is being readied for flight aboard Orbital ATK's Cygnus module on its seventh (OA-7) Commercial Resupply Services mission to the International Space Station. The Veggie system is on the space station.

Algorithm for Compressing Time-Series Data

NASA Technical Reports Server (NTRS)

Hawkins, S. Edward, III; Darlington, Edward Hugo

2012-01-01

An algorithm based on Chebyshev polynomials effects lossy compression of time-series data or other one-dimensional data streams (e.g., spectral data) that are arranged in blocks for sequential transmission. The algorithm was developed for use in transmitting data from spacecraft scientific instruments to Earth stations. In spite of its lossy nature, the algorithm preserves the information needed for scientific analysis. The algorithm is computationally simple, yet compresses data streams by factors much greater than two. The algorithm is not restricted to spacecraft or scientific uses: it is applicable to time-series data in general. The algorithm can also be applied to general multidimensional data that have been converted to time-series data, a typical example being image data acquired by raster scanning. However, unlike most prior image-data-compression algorithms, this algorithm neither depends on nor exploits the two-dimensional spatial correlations that are generally present in images. In order to understand the essence of this compression algorithm, it is necessary to understand that the net effect of this algorithm and the associated decompression algorithm is to approximate the original stream of data as a sequence of finite series of Chebyshev polynomials. For the purpose of this algorithm, a block of data or interval of time for which a Chebyshev polynomial series is fitted to the original data is denoted a fitting interval. Chebyshev approximation has two properties that make it particularly effective for compressing serial data streams with minimal loss of scientific information: The errors associated with a Chebyshev approximation are nearly uniformly distributed over the fitting interval (this is known in the art as the "equal error property"); and the maximum deviations of the fitted Chebyshev polynomial from the original data have the smallest possible values (this is known in the art as the "min-max property").

Visualizing frequent patterns in large multivariate time series

NASA Astrophysics Data System (ADS)

Hao, M.; Marwah, M.; Janetzko, H.; Sharma, R.; Keim, D. A.; Dayal, U.; Patnaik, D.; Ramakrishnan, N.

2011-01-01

The detection of previously unknown, frequently occurring patterns in time series, often called motifs, has been recognized as an important task. However, it is difficult to discover and visualize these motifs as their numbers increase, especially in large multivariate time series. To find frequent motifs, we use several temporal data mining and event encoding techniques to cluster and convert a multivariate time series to a sequence of events. Then we quantify the efficiency of the discovered motifs by linking them with a performance metric. To visualize frequent patterns in a large time series with potentially hundreds of nested motifs on a single display, we introduce three novel visual analytics methods: (1) motif layout, using colored rectangles for visualizing the occurrences and hierarchical relationships of motifs in a multivariate time series, (2) motif distortion, for enlarging or shrinking motifs as appropriate for easy analysis and (3) motif merging, to combine a number of identical adjacent motif instances without cluttering the display. Analysts can interactively optimize the degree of distortion and merging to get the best possible view. A specific motif (e.g., the most efficient or least efficient motif) can be quickly detected from a large time series for further investigation. We have applied these methods to two real-world data sets: data center cooling and oil well production. The results provide important new insights into the recurring patterns.

Robust extrema features for time-series data analysis.

PubMed

Vemulapalli, Pramod K; Monga, Vishal; Brennan, Sean N

2013-06-01

The extraction of robust features for comparing and analyzing time series is a fundamentally important problem. Research efforts in this area encompass dimensionality reduction using popular signal analysis tools such as the discrete Fourier and wavelet transforms, various distance metrics, and the extraction of interest points from time series. Recently, extrema features for analysis of time-series data have assumed increasing significance because of their natural robustness under a variety of practical distortions, their economy of representation, and their computational benefits. Invariably, the process of encoding extrema features is preceded by filtering of the time series with an intuitively motivated filter (e.g., for smoothing), and subsequent thresholding to identify robust extrema. We define the properties of robustness, uniqueness, and cardinality as a means to identify the design choices available in each step of the feature generation process. Unlike existing methods, which utilize filters "inspired" from either domain knowledge or intuition, we explicitly optimize the filter based on training time series to optimize robustness of the extracted extrema features. We demonstrate further that the underlying filter optimization problem reduces to an eigenvalue problem and has a tractable solution. An encoding technique that enhances control over cardinality and uniqueness is also presented. Experimental results obtained for the problem of time series subsequence matching establish the merits of the proposed algorithm.

Convolution of Two Series

ERIC Educational Resources Information Center

Umar, A.; Yusau, B.; Ghandi, B. M.

2007-01-01

In this note, we introduce and discuss convolutions of two series. The idea is simple and can be introduced to higher secondary school classes, and has the potential of providing a good background for the well known convolution of function.

Tribal Science 2016 Webinar Series: ecoAmbassadors Program

EPA Pesticide Factsheets

The U.S. EPA Sustainable and Healthy Communities (SHC) Seminar Series presents the Tribal Science Webinar Series, co-hosted by the National Center for Environmental Research (NCER) and the Office of Science Policy.

Pearson correlation estimation for irregularly sampled time series

NASA Astrophysics Data System (ADS)

Rehfeld, K.; Marwan, N.; Heitzig, J.; Kurths, J.

2012-04-01

Many applications in the geosciences call for the joint and objective analysis of irregular time series. For automated processing, robust measures of linear and nonlinear association are needed. Up to now, the standard approach would have been to reconstruct the time series on a regular grid, using linear or spline interpolation. Interpolation, however, comes with systematic side-effects, as it increases the auto-correlation in the time series. We have searched for the best method to estimate Pearson correlation for irregular time series, i.e. the one with the lowest estimation bias and variance. We adapted a kernel-based approach, using Gaussian weights. Pearson correlation is calculated, in principle, as a mean over products of previously centralized observations. In the regularly sampled case, observations in both time series were observed at the same time and thus the allocation of measurement values into pairs of products is straightforward. In the irregularly sampled case, however, measurements were not necessarily observed at the same time. Now, the key idea of the kernel-based method is to calculate weighted means of products, with the weight depending on the time separation between the observations. If the lagged correlation function is desired, the weights depend on the absolute difference between observation time separation and the estimation lag. To assess the applicability of the approach we used extensive simulations to determine the extent of interpolation side-effects with increasing irregularity of time series. We compared different approaches, based on (linear) interpolation, the Lomb-Scargle Fourier Transform, the sinc kernel and the Gaussian kernel. We investigated the role of kernel bandwidth and signal-to-noise ratio in the simulations. We found that the Gaussian kernel approach offers significant advantages and low Root-Mean Square Errors for regular, slightly irregular and very irregular time series. We therefore conclude that it is a good

Basic Fishing. Aquatic Skills Series. Instructor Manual.

ERIC Educational Resources Information Center

Staton, Robert D., Jr.

Part of a series of self-contained instructional units to teach Missourians how to use outdoor resources wisely and skillfully, this module of the Aquatic Skills Series introduces the basics of sport fishing using spin-casting equipment. The instructor may modify the module to meet the individual needs of class members based on age, experience…

Series expansion of the modified Einstein Procedure

Treesearch

Seema Chandrakant Shah-Fairbank

2009-01-01

This study examines calculating total sediment discharge based on the Modified Einstein Procedure (MEP). A new procedure based on the Series Expansion of the Modified Einstein Procedure (SEMEP) has been developed. This procedure contains four main modifications to MEP. First, SEMEP solves the Einstein integrals quickly and accurately based on a series expansion. Next,...

Atomic Fuel, Understanding the Atom Series. Revised.

ERIC Educational Resources Information Center

Hogerton, John F.

This publication is part of the "Understanding the Atom" series. Complete sets of the series are available free to teachers, schools, and public librarians who can make them available for reference or use by groups. Among the topics discussed are: What Atomic Fuel Is; The Odyssey of Uranium; Production of Uranium; Fabrication of Reactor…

17 CFR 20.5 - Series S filings.

Code of Federal Regulations, 2012 CFR

2012-04-01

... 17 Commodity and Securities Exchanges 1 2012-04-01 2012-04-01 false Series S filings. 20.5 Section... FOR PHYSICAL COMMODITY SWAPS § 20.5 Series S filings. (a) 102S filing. (1) When a counterparty... 102S filing only once for each counterparty, even if such persons at various times have multiple...

Non-parametric characterization of long-term rainfall time series

NASA Astrophysics Data System (ADS)

Tiwari, Harinarayan; Pandey, Brij Kishor

2018-03-01

The statistical study of rainfall time series is one of the approaches for efficient hydrological system design. Identifying, and characterizing long-term rainfall time series could aid in improving hydrological systems forecasting. In the present study, eventual statistics was applied for the long-term (1851-2006) rainfall time series under seven meteorological regions of India. Linear trend analysis was carried out using Mann-Kendall test for the observed rainfall series. The observed trend using the above-mentioned approach has been ascertained using the innovative trend analysis method. Innovative trend analysis has been found to be a strong tool to detect the general trend of rainfall time series. Sequential Mann-Kendall test has also been carried out to examine nonlinear trends of the series. The partial sum of cumulative deviation test is also found to be suitable to detect the nonlinear trend. Innovative trend analysis, sequential Mann-Kendall test and partial cumulative deviation test have potential to detect the general as well as nonlinear trend for the rainfall time series. Annual rainfall analysis suggests that the maximum changes in mean rainfall is 11.53% for West Peninsular India, whereas the maximum fall in mean rainfall is 7.8% for the North Mountainous Indian region. The innovative trend analysis method is also capable of finding the number of change point available in the time series. Additionally, we have performed von Neumann ratio test and cumulative deviation test to estimate the departure from homogeneity. Singular spectrum analysis has been applied in this study to evaluate the order of departure from homogeneity in the rainfall time series. Monsoon season (JS) of North Mountainous India and West Peninsular India zones has higher departure from homogeneity and singular spectrum analysis shows the results to be in coherence with the same.

On the Prony series representation of stretched exponential relaxation

NASA Astrophysics Data System (ADS)

Mauro, John C.; Mauro, Yihong Z.

2018-09-01

Stretched exponential relaxation is a ubiquitous feature of homogeneous glasses. The stretched exponential decay function can be derived from the diffusion-trap model, which predicts certain critical values of the fractional stretching exponent, β. In practical implementations of glass relaxation models, it is computationally convenient to represent the stretched exponential function as a Prony series of simple exponentials. Here, we perform a comprehensive mathematical analysis of the Prony series approximation of the stretched exponential relaxation, including optimized coefficients for certain critical values of β. The fitting quality of the Prony series is analyzed as a function of the number of terms in the series. With a sufficient number of terms, the Prony series can accurately capture the time evolution of the stretched exponential function, including its "fat tail" at long times. However, it is unable to capture the divergence of the first-derivative of the stretched exponential function in the limit of zero time. We also present a frequency-domain analysis of the Prony series representation of the stretched exponential function and discuss its physical implications for the modeling of glass relaxation behavior.

Exploratory Causal Analysis in Bivariate Time Series Data

NASA Astrophysics Data System (ADS)

McCracken, James M.

Many scientific disciplines rely on observational data of systems for which it is difficult (or impossible) to implement controlled experiments and data analysis techniques are required for identifying causal information and relationships directly from observational data. This need has lead to the development of many different time series causality approaches and tools including transfer entropy, convergent cross-mapping (CCM), and Granger causality statistics. In this thesis, the existing time series causality method of CCM is extended by introducing a new method called pairwise asymmetric inference (PAI). It is found that CCM may provide counter-intuitive causal inferences for simple dynamics with strong intuitive notions of causality, and the CCM causal inference can be a function of physical parameters that are seemingly unrelated to the existence of a driving relationship in the system. For example, a CCM causal inference might alternate between ''voltage drives current'' and ''current drives voltage'' as the frequency of the voltage signal is changed in a series circuit with a single resistor and inductor. PAI is introduced to address both of these limitations. Many of the current approaches in the times series causality literature are not computationally straightforward to apply, do not follow directly from assumptions of probabilistic causality, depend on assumed models for the time series generating process, or rely on embedding procedures. A new approach, called causal leaning, is introduced in this work to avoid these issues. The leaning is found to provide causal inferences that agree with intuition for both simple systems and more complicated empirical examples, including space weather data sets. The leaning may provide a clearer interpretation of the results than those from existing time series causality tools. A practicing analyst can explore the literature to find many proposals for identifying drivers and causal connections in times series data

Molecular series-tunneling junctions.

PubMed

Liao, Kung-Ching; Hsu, Liang-Yan; Bowers, Carleen M; Rabitz, Herschel; Whitesides, George M

2015-05-13

Charge transport through junctions consisting of insulating molecular units is a quantum phenomenon that cannot be described adequately by classical circuit laws. This paper explores tunneling current densities in self-assembled monolayer (SAM)-based junctions with the structure Ag(TS)/O2C-R1-R2-H//Ga2O3/EGaIn, where Ag(TS) is template-stripped silver and EGaIn is the eutectic alloy of gallium and indium; R1 and R2 refer to two classes of insulating molecular units-(CH2)n and (C6H4)m-that are connected in series and have different tunneling decay constants in the Simmons equation. These junctions can be analyzed as a form of series-tunneling junctions based on the observation that permuting the order of R1 and R2 in the junction does not alter the overall rate of charge transport. By using the Ag/O2C interface, this system decouples the highest occupied molecular orbital (HOMO, which is localized on the carboxylate group) from strong interactions with the R1 and R2 units. The differences in rates of tunneling are thus determined by the electronic structure of the groups R1 and R2; these differences are not influenced by the order of R1 and R2 in the SAM. In an electrical potential model that rationalizes this observation, R1 and R2 contribute independently to the height of the barrier. This model explicitly assumes that contributions to rates of tunneling from the Ag(TS)/O2C and H//Ga2O3 interfaces are constant across the series examined. The current density of these series-tunneling junctions can be described by J(V) = J0(V) exp(-β1d1 - β2d2), where J(V) is the current density (A/cm(2)) at applied voltage V and βi and di are the parameters describing the attenuation of the tunneling current through a rectangular tunneling barrier, with width d and a height related to the attenuation factor β.

Series Expansion of Functions with He's Homotopy Perturbation Method

ERIC Educational Resources Information Center

Khattri, Sanjay Kumar

2012-01-01

Finding a series expansion, such as Taylor series, of functions is an important mathematical concept with many applications. Homotopy perturbation method (HPM) is a new, easy to use and effective tool for solving a variety of mathematical problems. In this study, we present how to apply HPM to obtain a series expansion of functions. Consequently,…

TechNovation Lecture Series

NASA Image and Video Library

2011-02-17

Karim R. Lakhani, assistant professor at Harvard Business School, kicked off the Office of the Chief Technologist TechNovation Lecture series with his talk "Accessing the Ideas Cloud" on Thursday, Feb. 17, 2011 at NASA Headquarters in Washington. Photo Credit: (NASA/Carla Cioffi)

CHEMICAL TIME-SERIES SAMPLING

EPA Science Inventory

The rationale for chemical time-series sampling has its roots in the same fundamental relationships as govern well hydraulics. Samples of ground water are collected as a function of increasing time of pumpage. The most efficient pattern of collection consists of logarithmically s...

Power Series Solution to the Pendulum Equation

ERIC Educational Resources Information Center

Benacka, Jan

2009-01-01

This note gives a power series solution to the pendulum equation that enables to investigate the system in an analytical way only, i.e. to avoid numeric methods. A method of determining the number of the terms for getting a required relative error is presented that uses bigger and lesser geometric series. The solution is suitable for modelling the…

Construct-a-Greenhouse. Science by Design Series.

ERIC Educational Resources Information Center

Lee, Felicia

This book is one of four books in the Science-by-Design Series created by TERC and funded by the National Science Foundation (NSF). This series presents directed instruction on how to successfully formulate and carry out product design. Students learn and apply concepts in science and technology to design and build a pair of insulated gloves, a…

Index to the Understanding the Atom Series.

ERIC Educational Resources Information Center

Atomic Energy Commission, Oak Ridge, TN. Div. of Technical Information.

This index was prepared for the set of 51 booklets in the "Understanding the Atom Series" published by the U. S. Atomic Energy Commission for high school students and their teachers. In addition to the index, a complete list of the series is provided in which the booklets are grouped into the categories of physics, chemistry, biology, nuclear…

Simplification of multiple Fourier series - An example of algorithmic approach

NASA Technical Reports Server (NTRS)

Ng, E. W.

1981-01-01

This paper describes one example of multiple Fourier series which originate from a problem of spectral analysis of time series data. The example is exercised here with an algorithmic approach which can be generalized for other series manipulation on a computer. The generalized approach is presently pursued towards applications to a variety of multiple series and towards a general purpose algorithm for computer algebra implementation.

Diagenetic trends of a tertiary low-rank coal series

NASA Astrophysics Data System (ADS)

Boudou, Jean-Paul; Durand, Bernard; Oudin, Jean-Louis

1984-10-01

The Mahakam delta (Kalimantan, Indonesia) coals represent all the evolution stages between freshly-deposited plant/peat material, lignites and bituminous coals. The geochemical techniques used to study this coal series included elemental analysis, extraction of humic compounds, infrared spectroscopy and 13C nuclear magnetic resonance of the total coal. The main mechanisms of early maturation in this series are loss of oxygenated compounds, aromatisation and condensation of the organic matter. These changes, which have already been suggested for other coal series and partially reported for sedimentary organic matter, were confirmed and described in more detail for the Mahakam coal series.

Non-linear forecasting in high-frequency financial time series

NASA Astrophysics Data System (ADS)

Strozzi, F.; Zaldívar, J. M.

2005-08-01

A new methodology based on state space reconstruction techniques has been developed for trading in financial markets. The methodology has been tested using 18 high-frequency foreign exchange time series. The results are in apparent contradiction with the efficient market hypothesis which states that no profitable information about future movements can be obtained by studying the past prices series. In our (off-line) analysis positive gain may be obtained in all those series. The trading methodology is quite general and may be adapted to other financial time series. Finally, the steps for its on-line application are discussed.

Pseudo-random bit generator based on lag time series

NASA Astrophysics Data System (ADS)

García-Martínez, M.; Campos-Cantón, E.

2014-12-01

In this paper, we present a pseudo-random bit generator (PRBG) based on two lag time series of the logistic map using positive and negative values in the bifurcation parameter. In order to hidden the map used to build the pseudo-random series we have used a delay in the generation of time series. These new series when they are mapped xn against xn+1 present a cloud of points unrelated to the logistic map. Finally, the pseudo-random sequences have been tested with the suite of NIST giving satisfactory results for use in stream ciphers.

Botany, Taxonomy and Cytology of Crocus sativus series

PubMed Central

Saxena, R. B.

2010-01-01

Saffron is produced from the dried styles of Crocus sativus L. (Iridaceae) which is unknown as wild plant, representing a sterile triploid. These belong to subgenus Crocus series Crocus sativus – series are closely related species; and are difficult to be separated taxonomically and have a complex cytology. Botany of C. sativus – series, taxonomy of their species and their infraspecific taxa are presented, and their distribution, ecology and phenology; full description and chromosome counts are provided with key to their identification. PMID:22131743

An Evaluation of FREESTYLE, A Television Series to Reduce Sex-Role Stereotypes. Research Report Series, Institute for Social Research.

ERIC Educational Resources Information Center

Johnston, Jerome; And Others

This study is the main element of the summative evaluation of "Freestyle," a television series on sex-role stereotyping and career awareness. The series was developed for fourth to sixth graders viewing it at home or at school and contains 13 half-hour episodes. In seven test sites across the country, 268 teachers used…

The Soil Series in Soil Classifications of the United States

NASA Astrophysics Data System (ADS)

Indorante, Samuel; Beaudette, Dylan; Brevik, Eric C.

2014-05-01

Organized national soil survey began in the United States in 1899, with soil types as the units being mapped. The soil series concept was introduced into the U.S. soil survey in 1903 as a way to relate soils being mapped in one area to the soils of other areas. The original concept of a soil series was all soil types formed in the same parent materials that were of the same geologic age. However, within about 15 years soil series became the primary units being mapped in U.S. soil survey. Soil types became subdivisions of soil series, with the subdivisions based on changes in texture. As the soil series became the primary mapping unit the concept of what a soil series was also changed. Instead of being based on parent materials and geologic age, the soil series of the 1920s was based on the morphology and composition of the soil profile. Another major change in the concept of soil series occurred when U.S. Soil Taxonomy was released in 1975. Under Soil Taxonomy, the soil series subdivisions were based on the uses the soils might be put to, particularly their agricultural uses (Simonson, 1997). While the concept of the soil series has changed over the years, the term soil series has been the longest-lived term in U.S. soil classification. It has appeared in every official classification system used by the U.S. soil survey (Brevik and Hartemink, 2013). The first classification system was put together by Milton Whitney in 1909 and had soil series at its second lowest level, with soil type at the lowest level. The second classification system used by the U.S. soil survey was developed by C.F. Marbut, H.H. Bennett, J.E. Lapham, and M.H. Lapham in 1913. It had soil series at the second highest level, with soil classes and soil types at more detailed levels. This was followed by another system in 1938 developed by M. Baldwin, C.E. Kellogg, and J. Thorp. In this system soil series were again at the second lowest level with soil types at the lowest level. The soil type

Series Elastic Actuators for legged robots

NASA Astrophysics Data System (ADS)

Pratt, Jerry E.; Krupp, Benjamin T.

2004-09-01

Series Elastic Actuators provide many benefits in force control of robots in unconstrained environments. These benefits include high force fidelity, extremely low impedance, low friction, and good force control bandwidth. Series Elastic Actuators employ a novel mechanical design architecture which goes against the common machine design principal of "stiffer is better." A compliant element is placed between the gear train and driven load to intentionally reduce the stiffness of the actuator. A position sensor measures the deflection, and the force output is accurately calculated using Hooke"s Law (F=Kx). A control loop then servos the actuator to the desired output force. The resulting actuator has inherent shock tolerance, high force fidelity and extremely low impedance. These characteristics are desirable in many applications including legged robots, exoskeletons for human performance amplification, robotic arms, haptic interfaces, and adaptive suspensions. We describe several variations of Series Elastic Actuators that have been developed using both electric and hydraulic components.

Comparative study on the fauna composition of intertidal invertebrates between natural and artificial substrata in the northeastern coast of Jeju Island

NASA Astrophysics Data System (ADS)

Cha, Jae-Hoon; Kim, Kwang-Bae; Song, Ji-Na; Kim, In-Soo; Seo, Jeong-Bin; Kwoun, Chul-Hwi

2013-12-01

This study was carried out to learn about differences in the sessile macrobenthic fauna communities between the artificial and natural habitats. There were some differences in terms of species composition and dominant species and community structure between two habitat types. The dominant species include Pollicipes mitella and Granuilittorina exigua in natural rocky intertidal zones; Monodonta labio confusa, Ligia exotica, Tetraclita japonica in the artificial rocky intertidal zones. Among all the species, L. exotica and T. japonica occurred only in the artificial rocky intertidal zone. The results of cluster analysis and nMDS analysis showed a distinct difference in community structure between artificial and natural rocky intertidal zones. The fauna in the natural rocky intertidal zones were similar to each other and the fauna in the artificial rocky intertidal zones were divided depending on the slope of the substratum. In the case of a sloping tetrapod, M. labio confusa and P. mitella were dominant, but at the vertical artificial seawall, Cellana nigrolineata, L. exotica T. japonica were dominant. The analysis of the species presented in natural and artificial rocky intertidal areas showed the exclusive presence of 10 species on natural rocks and 12 species on artificial rocks. The species in the natural rocky intertidal area included mobile gastropods and cnidarians (i.e. rock anemones), and the species in the artificial rocky intertidal area mostly included non-mobile attached animals. The artificial novel structure seems to contribute to increasing the heterogeneity of habitats for marine invertebrate species and an increase the species diversity in rocky coastal areas.

GNSS Network time series analysis

NASA Astrophysics Data System (ADS)

Normand, M.; Balodis, J.; Janpaule, I.; Haritonova, D.

2012-12-01

Time series of GNSS station results of both the EUPOS®-Riga and LatPos networks have been developed at the Institute of Geodesy and Geoinformation (University of Latvia) using Bernese v.5.0 software. The base stations were selected among the EPN and IGS stations in surroundings of Latvia at the distances up to 700 km. The results of time series are analysed and coordinate velocity vectors have been determined. The background of the map of tectonic faults helps to interpret the GNSS station coordinate velocity vector behaviour in proper environment. The outlying situations recognized. The question still aroused on the nature of the some of outlying situations. The dependence from various influences has been tested.

Sequences, Series, and Mathematica.

ERIC Educational Resources Information Center

Mathews, John H.

1992-01-01

Describes how the computer algebra system Mathematica can be used to enhance the teaching of the topics of sequences and series. Examines its capabilities to find exact, approximate, and graphically generated approximate solutions to problems from these topics and to understand proofs about sequences. (MDH)

Extending "the Rubber Rope": Convergent Series, Divergent Series and the Integrating Factor

ERIC Educational Resources Information Center

McCartney, Mark

2013-01-01

A well-known mathematical puzzle regarding a worm crawling along an elastic rope is considered. The resulting generalizations provide examples for use in a teaching context including applications of series summation, the use of the integrating factor for the solution of differential equations, and the evaluation of definite integrals. A number of…

The Divergence of Balanced Harmonic-Like Series

ERIC Educational Resources Information Center

Lutzer, Carl V.; Marengo, James E.

2006-01-01

Consider the series [image omitted] where the value of each a[subscript n] is determined by the flip of a coin: heads on the "n"th toss will mean that a[subscript n] =1 and tails that a[subscript n] = -1. Assuming that the coin is "fair," what is the probability that this "harmonic-like" series converges? After a moment's thought, many people…

Case Series in Cognitive Neuropsychology: Promise, Perils and Proper Perspective

PubMed Central

Rapp, Brenda

2012-01-01

Schwartz & Dell (2010) advocated for a major role for case series investigations in cognitive neuropsychology. They defined the key features of this approach and presented a number of arguments and examples illustrating the benefits of case series studies and their contribution to computational cognitive neuropsychology. In the Special Issue on “Case Series in Cognitive Neuropsychology” there are six commentaries on Schwartz and Dell (2010) as well as a response to the six commentaries by Dell and Schwartz. In this paper, I provide a brief summary of the key points made in Schwartz and Dell (2010) and I review the promise and perils of case series design as revealed by the six commentaries. I conclude by placing the set of papers within a broader perspective, providing some clarification of the historical record on case series and single case approaches, raising some cautionary notes for case series studies and situating both case series and single case approaches within the larger context of theory development in the cognitive sciences. PMID:22746685

Multiscale structure of time series revealed by the monotony spectrum.

PubMed

Vamoş, Călin

2017-03-01

Observation of complex systems produces time series with specific dynamics at different time scales. The majority of the existing numerical methods for multiscale analysis first decompose the time series into several simpler components and the multiscale structure is given by the properties of their components. We present a numerical method which describes the multiscale structure of arbitrary time series without decomposing them. It is based on the monotony spectrum defined as the variation of the mean amplitude of the monotonic segments with respect to the mean local time scale during successive averagings of the time series, the local time scales being the durations of the monotonic segments. The maxima of the monotony spectrum indicate the time scales which dominate the variations of the time series. We show that the monotony spectrum can correctly analyze a diversity of artificial time series and can discriminate the existence of deterministic variations at large time scales from the random fluctuations. As an application we analyze the multifractal structure of some hydrological time series.

Uranium series dating of Allan Hills ice

NASA Technical Reports Server (NTRS)

Fireman, E. L.

1986-01-01

Uranium-238 decay series nuclides dissolved in Antarctic ice samples were measured in areas of both high and low concentrations of volcanic glass shards. Ice from the Allan Hills site (high shard content) had high Ra-226, Th-230 and U-234 activities but similarly low U-238 activities in comparison with Antarctic ice samples without shards. The Ra-226, Th-230 and U-234 excesses were found to be proportional to the shard content, while the U-238 decay series results were consistent with the assumption that alpha decay products recoiled into the ice from the shards. Through this method of uranium series dating, it was learned that the Allen Hills Cul de Sac ice is approximately 325,000 years old.

Long series of geomagnetic measurements - unique at satellite era

NASA Astrophysics Data System (ADS)

Mandea, Mioara; Balasis, Georgios

2017-04-01

We have long appreciated that magnetic measurements obtained at Earth's surface are of great value in characterizing geomagnetic field behavior and then probing the deep interior of our Planet. The existence of new magnetic satellite missions data offer a new detailed global understanding of the geomagnetic field. However, when our interest moves over long-time scales, the very long series of measurements play an important role. Here, we firstly provide an updated series of geomagnetic declination in Paris, shortly after a very special occasion: its value has reached zero after some 350 years of westerly values. We take this occasion to emphasize the importance of long series of continuous measurements, mainly when various techniques are used to detect the abrupt changes in geomagnetic field, the geomagnetic jerks. Many novel concepts originated in dynamical systems or information theory have been developed, partly motivated by specific research questions from the geosciences. This continuously extending toolbox of nonlinear time series analysis is a key to understand the complexity of geomagnetic field. Here, motivated by these efforts, a series of entropy analysis are applied to geomagnetic field time series aiming to detect dynamical complex changes associated with geomagnetic jerks.

Evaluation of Scaling Invariance Embedded in Short Time Series

PubMed Central

Pan, Xue; Hou, Lei; Stephen, Mutua; Yang, Huijie; Zhu, Chenping

2014-01-01

Scaling invariance of time series has been making great contributions in diverse research fields. But how to evaluate scaling exponent from a real-world series is still an open problem. Finite length of time series may induce unacceptable fluctuation and bias to statistical quantities and consequent invalidation of currently used standard methods. In this paper a new concept called correlation-dependent balanced estimation of diffusion entropy is developed to evaluate scale-invariance in very short time series with length . Calculations with specified Hurst exponent values of show that by using the standard central moving average de-trending procedure this method can evaluate the scaling exponents for short time series with ignorable bias () and sharp confidential interval (standard deviation ). Considering the stride series from ten volunteers along an approximate oval path of a specified length, we observe that though the averages and deviations of scaling exponents are close, their evolutionary behaviors display rich patterns. It has potential use in analyzing physiological signals, detecting early warning signals, and so on. As an emphasis, the our core contribution is that by means of the proposed method one can estimate precisely shannon entropy from limited records. PMID:25549356

78 FR 20701 - Munder Series Trust, et al.;

Federal Register 2010, 2011, 2012, 2013, 2014

2013-04-05

... designed to ensure that the Sub-Advisers comply with a Sub- Advised Series' investment objectives, policies...] Munder Series Trust, et al.; Notice of Application March 29, 2013. AGENCY: Securities and Exchange... would grant relief from certain disclosure requirements. [[Page 20702

Simulation of time series by distorted Gaussian processes

NASA Technical Reports Server (NTRS)

Greenhall, C. A.

1977-01-01

Distorted stationary Gaussian process can be used to provide computer-generated imitations of experimental time series. A method of analyzing a source time series and synthesizing an imitation is shown, and an example using X-band radiometer data is given.

Silverleaf: An Experimental Series in Support of Nightshade

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

Danielson, Jeremy; Bauer, Amy L.

2016-12-23

In this series, a prototype package was designed and fielded to address a major technical risk of Nightshade: A comprehensive suite of drives and diagnostics must fit within a small space. In addition, this series satisfies a milestone for the project.

Time series, periodograms, and significance

NASA Astrophysics Data System (ADS)

Hernandez, G.

1999-05-01

The geophysical literature shows a wide and conflicting usage of methods employed to extract meaningful information on coherent oscillations from measurements. This makes it difficult, if not impossible, to relate the findings reported by different authors. Therefore, we have undertaken a critical investigation of the tests and methodology used for determining the presence of statistically significant coherent oscillations in periodograms derived from time series. Statistical significance tests are only valid when performed on the independent frequencies present in a measurement. Both the number of possible independent frequencies in a periodogram and the significance tests are determined by the number of degrees of freedom, which is the number of true independent measurements, present in the time series, rather than the number of sample points in the measurement. The number of degrees of freedom is an intrinsic property of the data, and it must be determined from the serial coherence of the time series. As part of this investigation, a detailed study has been performed which clearly illustrates the deleterious effects that the apparently innocent and commonly used processes of filtering, de-trending, and tapering of data have on periodogram analysis and the consequent difficulties in the interpretation of the statistical significance thus derived. For the sake of clarity, a specific example of actual field measurements containing unevenly-spaced measurements, gaps, etc., as well as synthetic examples, have been used to illustrate the periodogram approach, and pitfalls, leading to the (statistical) significance tests for the presence of coherent oscillations. Among the insights of this investigation are: (1) the concept of a time series being (statistically) band limited by its own serial coherence and thus having a critical sampling rate which defines one of the necessary requirements for the proper statistical design of an experiment; (2) the design of a critical

On the Approximation of Generalized Lipschitz Function by Euler Means of Conjugate Series of Fourier Series

PubMed Central

Kushwaha, Jitendra Kumar

2013-01-01

Approximation theory is a very important field which has various applications in pure and applied mathematics. The present study deals with a new theorem on the approximation of functions of Lipschitz class by using Euler's mean of conjugate series of Fourier series. In this paper, the degree of approximation by using Euler's means of conjugate of functions belonging to Lip (ξ(t), p) class has been obtained. Lipα and Lip (α, p) classes are the particular cases of Lip (ξ(t), p) class. The main result of this paper generalizes some well-known results in this direction. PMID:24379744

Trend time-series modeling and forecasting with neural networks.

PubMed

Qi, Min; Zhang, G Peter

2008-05-01

Despite its great importance, there has been no general consensus on how to model the trends in time-series data. Compared to traditional approaches, neural networks (NNs) have shown some promise in time-series forecasting. This paper investigates how to best model trend time series using NNs. Four different strategies (raw data, raw data with time index, detrending, and differencing) are used to model various trend patterns (linear, nonlinear, deterministic, stochastic, and breaking trend). We find that with NNs differencing often gives meritorious results regardless of the underlying data generating processes (DGPs). This finding is also confirmed by the real gross national product (GNP) series.

Computation of solar perturbations with Poisson series

NASA Technical Reports Server (NTRS)

Broucke, R.

1974-01-01

Description of a project for computing first-order perturbations of natural or artificial satellites by integrating the equations of motion on a computer with automatic Poisson series expansions. A basic feature of the method of solution is that the classical variation-of-parameters formulation is used rather than rectangular coordinates. However, the variation-of-parameters formulation uses the three rectangular components of the disturbing force rather than the classical disturbing function, so that there is no problem in expanding the disturbing function in series. Another characteristic of the variation-of-parameters formulation employed is that six rather unusual variables are used in order to avoid singularities at the zero eccentricity and zero (or 90 deg) inclination. The integration process starts by assuming that all the orbit elements present on the right-hand sides of the equations of motion are constants. These right-hand sides are then simple Poisson series which can be obtained with the use of the Bessel expansions of the two-body problem in conjunction with certain interation methods. These Poisson series can then be integrated term by term, and a first-order solution is obtained.

The Basel Problem as a Rearrangement of Series

ERIC Educational Resources Information Center

Benko, David; Molokach, John

2013-01-01

We give an elementary solution to the famous Basel Problem, originally solved by Euler in 1735. We square the well-known series for arctan(1) due to Leibniz, and use a surprising relation among the re-arranged terms of this squared series.

New Educational Video Series From AGU

NASA Astrophysics Data System (ADS)

Adamec, Bethany Holm; Sollosi, Derek

2013-04-01

A new video series entitled Live Education Activity Resource Network (LEARN) With AGU was recently launched. This series of short Earth and space science-related videos is designed to give K-12 formal and informal educators the tools they need to try new hands-on activities with their students. Research indicates that hands-on learning and problem solving are important ways for students to learn, but educators do not always know where to begin or think that they need a lot of materials to do a hands-on activity (which often is not the case).

Time Series Decomposition into Oscillation Components and Phase Estimation.

PubMed

Matsuda, Takeru; Komaki, Fumiyasu

2017-02-01

Many time series are naturally considered as a superposition of several oscillation components. For example, electroencephalogram (EEG) time series include oscillation components such as alpha, beta, and gamma. We propose a method for decomposing time series into such oscillation components using state-space models. Based on the concept of random frequency modulation, gaussian linear state-space models for oscillation components are developed. In this model, the frequency of an oscillator fluctuates by noise. Time series decomposition is accomplished by this model like the Bayesian seasonal adjustment method. Since the model parameters are estimated from data by the empirical Bayes' method, the amplitudes and the frequencies of oscillation components are determined in a data-driven manner. Also, the appropriate number of oscillation components is determined with the Akaike information criterion (AIC). In this way, the proposed method provides a natural decomposition of the given time series into oscillation components. In neuroscience, the phase of neural time series plays an important role in neural information processing. The proposed method can be used to estimate the phase of each oscillation component and has several advantages over a conventional method based on the Hilbert transform. Thus, the proposed method enables an investigation of the phase dynamics of time series. Numerical results show that the proposed method succeeds in extracting intermittent oscillations like ripples and detecting the phase reset phenomena. We apply the proposed method to real data from various fields such as astronomy, ecology, tidology, and neuroscience.

Baseline series fragrance markers fail to predict contact allergy.

PubMed

Mann, Jack; McFadden, John P; White, Jonathan M L; White, Ian R; Banerjee, Piu

2014-05-01

Negative patch test results with fragrance allergy markers in the European baseline series do not always predict a negative reaction to individual fragrance substances. To determine the frequencies of positive test reactions to the 26 fragrance substances for which labelling is mandatory in the EU, and how effectively reactions to fragrance markers in the baseline series predict positive reactions to the fragrance substances that are labelled. The records of 1951 eczema patients, routinely tested with the labelled fragrance substances and with an extended European baseline series in 2011 and 2012, were retrospectively reviewed. Two hundred and eighty-one (14.4%) (71.2% females) reacted to one or more allergens from the labelled-fragrance substance series and/or a fragrance marker from the European baseline series. The allergens that were positive with the greatest frequencies were cinnamyl alcohol (48; 2.46%), Evernia furfuracea (44; 2.26%), and isoeugenol (40; 2.05%). Of the 203 patients who reacted to any of the 26 fragrances in the labelled-fragrance substance series, only 117 (57.6%) also reacted to a fragrance marker in the baseline series. One hundred and seven (52.7%) reacted to either fragrance mix I or fragrance mix II, 28 (13.8%) reacted to Myroxylon pereirae, and 13 (6.4%) reacted to hydroxyisohexyl 3-cyclohexene carboxaldehyde. These findings confirm that the standard fragrance markers fail to identify patients with contact allergies to the 26 fragrances. © 2014 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

The examination of headache activity using time-series research designs.

PubMed

Houle, Timothy T; Remble, Thomas A; Houle, Thomas A

2005-05-01

The majority of research conducted on headache has utilized cross-sectional designs which preclude the examination of dynamic factors and principally rely on group-level effects. The present article describes the application of an individual-oriented process model using time-series analytical techniques. The blending of a time-series approach with an interactive process model allows consideration of the relationships of intra-individual dynamic processes, while not precluding the researcher to examine inter-individual differences. The authors explore the nature of time-series data and present two necessary assumptions underlying the time-series approach. The concept of shock and its contribution to headache activity is also presented. The time-series approach is not without its problems and two such problems are specifically reported: autocorrelation and the distribution of daily observations. The article concludes with the presentation of several analytical techniques suited to examine the time-series interactive process model.

A perturbative approach for enhancing the performance of time series forecasting.

PubMed

de Mattos Neto, Paulo S G; Ferreira, Tiago A E; Lima, Aranildo R; Vasconcelos, Germano C; Cavalcanti, George D C

2017-04-01

This paper proposes a method to perform time series prediction based on perturbation theory. The approach is based on continuously adjusting an initial forecasting model to asymptotically approximate a desired time series model. First, a predictive model generates an initial forecasting for a time series. Second, a residual time series is calculated as the difference between the original time series and the initial forecasting. If that residual series is not white noise, then it can be used to improve the accuracy of the initial model and a new predictive model is adjusted using residual series. The whole process is repeated until convergence or the residual series becomes white noise. The output of the method is then given by summing up the outputs of all trained predictive models in a perturbative sense. To test the method, an experimental investigation was conducted on six real world time series. A comparison was made with six other methods experimented and ten other results found in the literature. Results show that not only the performance of the initial model is significantly improved but also the proposed method outperforms the other results previously published. Copyright © 2017 Elsevier Ltd. All rights reserved.

Three Important Taylor Series for Introductory Physics

DTIC Science & Technology

2009-09-01

series by the sum of its first few terms is useful throughout an introductory physics course . Example applications [1, 2] include estimating square...Lat. Am. J. Phys. Educ. Vol. 3, No. 3, Sept. 2009 535 http://www.journal.lapen.org.mx Three Important Taylor Series for Introductory Physics...one dimension, which instructively ties the mathematical development to physics concepts already presented in introductory courses . Keywords

Orthodontic bracket slot dimensions as measured from entire bracket series.

PubMed

Brown, Paul; Wagner, Warren; Choi, Hyden

2015-07-01

To measure the slot dimensions of an entire series of metal orthodontic brackets. Ten bracket series approximating five complete sets of brackets each were imaged and measured. Descriptive statistics were generated. Slot dimension varied significantly from series to series as well as within the series themselves. About one-third of the brackets would not accommodate a full-size wire, and 15% to 20% are 0.001 inches or larger than the nominal advertised size. The clinician is unlikely to have on hand complete sets (upper and lower 5-5) of ideal brackets and should both expect and be able to be accommodate tooth movement through wire bending in three planes of space to overcome any bracket deficiencies.

"Feeling" Series and Parallel Resistances.

ERIC Educational Resources Information Center

Morse, Robert A.

1993-01-01

Equipped with drinking straws and stirring straws, a teacher can help students understand how resistances in electric circuits combine in series and in parallel. Follow-up suggestions are provided. (ZWH)

Wavelet transform approach for fitting financial time series data

NASA Astrophysics Data System (ADS)

Ahmed, Amel Abdoullah; Ismail, Mohd Tahir

2015-10-01

This study investigates a newly developed technique; a combined wavelet filtering and VEC model, to study the dynamic relationship among financial time series. Wavelet filter has been used to annihilate noise data in daily data set of NASDAQ stock market of US, and three stock markets of Middle East and North Africa (MENA) region, namely, Egypt, Jordan, and Istanbul. The data covered is from 6/29/2001 to 5/5/2009. After that, the returns of generated series by wavelet filter and original series are analyzed by cointegration test and VEC model. The results show that the cointegration test affirms the existence of cointegration between the studied series, and there is a long-term relationship between the US, stock markets and MENA stock markets. A comparison between the proposed model and traditional model demonstrates that, the proposed model (DWT with VEC model) outperforms traditional model (VEC model) to fit the financial stock markets series well, and shows real information about these relationships among the stock markets.

Characterization of time series via Rényi complexity-entropy curves

NASA Astrophysics Data System (ADS)

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

2018-05-01

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

Extending the rubber rope: convergent series, divergent series and the integrating factor

NASA Astrophysics Data System (ADS)

McCartney, Mark

2013-06-01

A well-known mathematical puzzle regarding a worm crawling along an elastic rope is considered. The resulting generalizations provide examples for use in a teaching context including applications of series summation, the use of the integrating factor for the solution of differential equations, and the evaluation of definite integrals. A number of potential classroom exercises are given.

American Contact Dermatitis Society Core Allergen Series: 2017 Update.

PubMed

Schalock, Peter C; Dunnick, Cory A; Nedorost, Susan; Brod, Bruce; Warshaw, Erin; Mowad, Christen

The American Contact Dermatitis Society Core Allergen Series was introduced in 2012. After 4 years of use, changes in our recommended allergens are necessary. For the updated series, we have reordered the first 4 panels to approximately mirror the current TRUE Test and removed parthenolide, triclosan, glutaraldehyde, and jasmine. Polymyxin B, lavender, sodium benzoate, ethylhexylglycerin, and benzoic acid are new additions to the American Contact Dermatitis Society series.

Improvements to surrogate data methods for nonstationary time series.

PubMed

Lucio, J H; Valdés, R; Rodríguez, L R

2012-05-01

The method of surrogate data has been extensively applied to hypothesis testing of system linearity, when only one realization of the system, a time series, is known. Normally, surrogate data should preserve the linear stochastic structure and the amplitude distribution of the original series. Classical surrogate data methods (such as random permutation, amplitude adjusted Fourier transform, or iterative amplitude adjusted Fourier transform) are successful at preserving one or both of these features in stationary cases. However, they always produce stationary surrogates, hence existing nonstationarity could be interpreted as dynamic nonlinearity. Certain modifications have been proposed that additionally preserve some nonstationarity, at the expense of reproducing a great deal of nonlinearity. However, even those methods generally fail to preserve the trend (i.e., global nonstationarity in the mean) of the original series. This is the case of time series with unit roots in their autoregressive structure. Additionally, those methods, based on Fourier transform, either need first and last values in the original series to match, or they need to select a piece of the original series with matching ends. These conditions are often inapplicable and the resulting surrogates are adversely affected by the well-known artefact problem. In this study, we propose a simple technique that, applied within existing Fourier-transform-based methods, generates surrogate data that jointly preserve the aforementioned characteristics of the original series, including (even strong) trends. Moreover, our technique avoids the negative effects of end mismatch. Several artificial and real, stationary and nonstationary, linear and nonlinear time series are examined, in order to demonstrate the advantages of the methods. Corresponding surrogate data are produced with the classical and with the proposed methods, and the results are compared.

Wavelet analysis and scaling properties of time series

NASA Astrophysics Data System (ADS)

Manimaran, P.; Panigrahi, Prasanta K.; Parikh, Jitendra C.

2005-10-01

We propose a wavelet based method for the characterization of the scaling behavior of nonstationary time series. It makes use of the built-in ability of the wavelets for capturing the trends in a data set, in variable window sizes. Discrete wavelets from the Daubechies family are used to illustrate the efficacy of this procedure. After studying binomial multifractal time series with the present and earlier approaches of detrending for comparison, we analyze the time series of averaged spin density in the 2D Ising model at the critical temperature, along with several experimental data sets possessing multifractal behavior.

Effects of Hofmeister salt series on gluten network formation: Part I. Cation series.

PubMed

Tuhumury, H C D; Small, D M; Day, L

2016-12-01

Different cationic salts were used to investigate the effects of the Hofmeister salt series on gluten network formation. The effects of cationic salts on wheat flour dough mixing properties, the rheological and the chemical properties of the gluten extracted from the dough with different respective salts, were investigated. The specific influence of different cationic salts on the gluten structure formation during dough mixing, compared to the sodium ion, were determined. The effects of different cations on dough and gluten of different flours mostly followed the Hofmeister series (NH4(+), K(+), Na(+), Mg(2+) and Ca(2+)). The impacts of cations on gluten structure and dough rheology at levels tested were relatively small. Therefore, the replacement of sodium from a technological standpoint is possible, particularly by monovalent cations such as NH4(+), or K(+). However the levels of replacement need to take into account sensory attributes of the cationic salts. Copyright © 2016 Elsevier Ltd. All rights reserved.

Nonstationary time series prediction combined with slow feature analysis

NASA Astrophysics Data System (ADS)

Wang, G.; Chen, X.

2015-07-01

Almost all climate time series have some degree of nonstationarity due to external driving forces perturbing the observed system. Therefore, these external driving forces should be taken into account when constructing the climate dynamics. This paper presents a new technique of obtaining the driving forces of a time series from the slow feature analysis (SFA) approach, and then introduces them into a predictive model to predict nonstationary time series. The basic theory of the technique is to consider the driving forces as state variables and to incorporate them into the predictive model. Experiments using a modified logistic time series and winter ozone data in Arosa, Switzerland, were conducted to test the model. The results showed improved prediction skills.

Curriculum Challenge from the Religious Right: The "Impressions" Reading Series.

ERIC Educational Resources Information Center

Adler, Louise; Tellez, Kip

1992-01-01

Studies curriculum challenges by religious conservatives to the "Impressions" reading series in California. Many parents thought the series promoted satanism, witchcraft, and disrespect toward parents. Data from 22 school districts, 4 of which dropped the series, illustrate the complex nature of such challenges and highlight school…

Modeling Non-Gaussian Time Series with Nonparametric Bayesian Model.

PubMed

Xu, Zhiguang; MacEachern, Steven; Xu, Xinyi

2015-02-01

We present a class of Bayesian copula models whose major components are the marginal (limiting) distribution of a stationary time series and the internal dynamics of the series. We argue that these are the two features with which an analyst is typically most familiar, and hence that these are natural components with which to work. For the marginal distribution, we use a nonparametric Bayesian prior distribution along with a cdf-inverse cdf transformation to obtain large support. For the internal dynamics, we rely on the traditionally successful techniques of normal-theory time series. Coupling the two components gives us a family of (Gaussian) copula transformed autoregressive models. The models provide coherent adjustments of time scales and are compatible with many extensions, including changes in volatility of the series. We describe basic properties of the models, show their ability to recover non-Gaussian marginal distributions, and use a GARCH modification of the basic model to analyze stock index return series. The models are found to provide better fit and improved short-range and long-range predictions than Gaussian competitors. The models are extensible to a large variety of fields, including continuous time models, spatial models, models for multiple series, models driven by external covariate streams, and non-stationary models.

Segmentation of time series with long-range fractal correlations

PubMed Central

Bernaola-Galván, P.; Oliver, J.L.; Hackenberg, M.; Coronado, A.V.; Ivanov, P.Ch.; Carpena, P.

2012-01-01

Segmentation is a standard method of data analysis to identify change-points dividing a nonstationary time series into homogeneous segments. However, for long-range fractal correlated series, most of the segmentation techniques detect spurious change-points which are simply due to the heterogeneities induced by the correlations and not to real nonstationarities. To avoid this oversegmentation, we present a segmentation algorithm which takes as a reference for homogeneity, instead of a random i.i.d. series, a correlated series modeled by a fractional noise with the same degree of correlations as the series to be segmented. We apply our algorithm to artificial series with long-range correlations and show that it systematically detects only the change-points produced by real nonstationarities and not those created by the correlations of the signal. Further, we apply the method to the sequence of the long arm of human chromosome 21, which is known to have long-range fractal correlations. We obtain only three segments that clearly correspond to the three regions of different G + C composition revealed by means of a multi-scale wavelet plot. Similar results have been obtained when segmenting all human chromosome sequences, showing the existence of previously unknown huge compositional superstructures in the human genome. PMID:23645997

Segmentation of time series with long-range fractal correlations.

PubMed

Bernaola-Galván, P; Oliver, J L; Hackenberg, M; Coronado, A V; Ivanov, P Ch; Carpena, P

2012-06-01

Segmentation is a standard method of data analysis to identify change-points dividing a nonstationary time series into homogeneous segments. However, for long-range fractal correlated series, most of the segmentation techniques detect spurious change-points which are simply due to the heterogeneities induced by the correlations and not to real nonstationarities. To avoid this oversegmentation, we present a segmentation algorithm which takes as a reference for homogeneity, instead of a random i.i.d. series, a correlated series modeled by a fractional noise with the same degree of correlations as the series to be segmented. We apply our algorithm to artificial series with long-range correlations and show that it systematically detects only the change-points produced by real nonstationarities and not those created by the correlations of the signal. Further, we apply the method to the sequence of the long arm of human chromosome 21, which is known to have long-range fractal correlations. We obtain only three segments that clearly correspond to the three regions of different G + C composition revealed by means of a multi-scale wavelet plot. Similar results have been obtained when segmenting all human chromosome sequences, showing the existence of previously unknown huge compositional superstructures in the human genome.

Evaluation of scaling invariance embedded in short time series.

PubMed

Pan, Xue; Hou, Lei; Stephen, Mutua; Yang, Huijie; Zhu, Chenping

2014-01-01

Scaling invariance of time series has been making great contributions in diverse research fields. But how to evaluate scaling exponent from a real-world series is still an open problem. Finite length of time series may induce unacceptable fluctuation and bias to statistical quantities and consequent invalidation of currently used standard methods. In this paper a new concept called correlation-dependent balanced estimation of diffusion entropy is developed to evaluate scale-invariance in very short time series with length ~10(2). Calculations with specified Hurst exponent values of 0.2,0.3,...,0.9 show that by using the standard central moving average de-trending procedure this method can evaluate the scaling exponents for short time series with ignorable bias (≤0.03) and sharp confidential interval (standard deviation ≤0.05). Considering the stride series from ten volunteers along an approximate oval path of a specified length, we observe that though the averages and deviations of scaling exponents are close, their evolutionary behaviors display rich patterns. It has potential use in analyzing physiological signals, detecting early warning signals, and so on. As an emphasis, the our core contribution is that by means of the proposed method one can estimate precisely shannon entropy from limited records.

Time Series Analysis of Insar Data: Methods and Trends

NASA Technical Reports Server (NTRS)

Osmanoglu, Batuhan; Sunar, Filiz; Wdowinski, Shimon; Cano-Cabral, Enrique

2015-01-01

Time series analysis of InSAR data has emerged as an important tool for monitoring and measuring the displacement of the Earth's surface. Changes in the Earth's surface can result from a wide range of phenomena such as earthquakes, volcanoes, landslides, variations in ground water levels, and changes in wetland water levels. Time series analysis is applied to interferometric phase measurements, which wrap around when the observed motion is larger than one-half of the radar wavelength. Thus, the spatio-temporal ''unwrapping" of phase observations is necessary to obtain physically meaningful results. Several different algorithms have been developed for time series analysis of InSAR data to solve for this ambiguity. These algorithms may employ different models for time series analysis, but they all generate a first-order deformation rate, which can be compared to each other. However, there is no single algorithm that can provide optimal results in all cases. Since time series analyses of InSAR data are used in a variety of applications with different characteristics, each algorithm possesses inherently unique strengths and weaknesses. In this review article, following a brief overview of InSAR technology, we discuss several algorithms developed for time series analysis of InSAR data using an example set of results for measuring subsidence rates in Mexico City.

Time-series modeling of long-term weight self-monitoring data.

PubMed

Helander, Elina; Pavel, Misha; Jimison, Holly; Korhonen, Ilkka

2015-08-01

Long-term self-monitoring of weight is beneficial for weight maintenance, especially after weight loss. Connected weight scales accumulate time series information over long term and hence enable time series analysis of the data. The analysis can reveal individual patterns, provide more sensitive detection of significant weight trends, and enable more accurate and timely prediction of weight outcomes. However, long term self-weighing data has several challenges which complicate the analysis. Especially, irregular sampling, missing data, and existence of periodic (e.g. diurnal and weekly) patterns are common. In this study, we apply time series modeling approach on daily weight time series from two individuals and describe information that can be extracted from this kind of data. We study the properties of weight time series data, missing data and its link to individuals behavior, periodic patterns and weight series segmentation. Being able to understand behavior through weight data and give relevant feedback is desired to lead to positive intervention on health behaviors.

Transmission of linear regression patterns between time series: From relationship in time series to complex networks

NASA Astrophysics Data System (ADS)

Gao, Xiangyun; An, Haizhong; Fang, Wei; Huang, Xuan; Li, Huajiao; Zhong, Weiqiong; Ding, Yinghui

2014-07-01

The linear regression parameters between two time series can be different under different lengths of observation period. If we study the whole period by the sliding window of a short period, the change of the linear regression parameters is a process of dynamic transmission over time. We tackle fundamental research that presents a simple and efficient computational scheme: a linear regression patterns transmission algorithm, which transforms linear regression patterns into directed and weighted networks. The linear regression patterns (nodes) are defined by the combination of intervals of the linear regression parameters and the results of the significance testing under different sizes of the sliding window. The transmissions between adjacent patterns are defined as edges, and the weights of the edges are the frequency of the transmissions. The major patterns, the distance, and the medium in the process of the transmission can be captured. The statistical results of weighted out-degree and betweenness centrality are mapped on timelines, which shows the features of the distribution of the results. Many measurements in different areas that involve two related time series variables could take advantage of this algorithm to characterize the dynamic relationships between the time series from a new perspective.

Transmission of linear regression patterns between time series: from relationship in time series to complex networks.

PubMed

Gao, Xiangyun; An, Haizhong; Fang, Wei; Huang, Xuan; Li, Huajiao; Zhong, Weiqiong; Ding, Yinghui

2014-07-01

The linear regression parameters between two time series can be different under different lengths of observation period. If we study the whole period by the sliding window of a short period, the change of the linear regression parameters is a process of dynamic transmission over time. We tackle fundamental research that presents a simple and efficient computational scheme: a linear regression patterns transmission algorithm, which transforms linear regression patterns into directed and weighted networks. The linear regression patterns (nodes) are defined by the combination of intervals of the linear regression parameters and the results of the significance testing under different sizes of the sliding window. The transmissions between adjacent patterns are defined as edges, and the weights of the edges are the frequency of the transmissions. The major patterns, the distance, and the medium in the process of the transmission can be captured. The statistical results of weighted out-degree and betweenness centrality are mapped on timelines, which shows the features of the distribution of the results. Many measurements in different areas that involve two related time series variables could take advantage of this algorithm to characterize the dynamic relationships between the time series from a new perspective.

Diamond Anniversary Lecture Series.

ERIC Educational Resources Information Center

Adams, Dewey A.; And Others

This document contains the texts of four lectures that were presented as part of a series commemorating the 75th anniversary of Ohio State University's Department of Agricultural Education. The first lecture, "The Conceptualization Process and Vocational Education Management," (Dewey A. Adams) discusses a five-step management behavior approach for…

Deconvolution of mixing time series on a graph

PubMed Central

Blocker, Alexander W.; Airoldi, Edoardo M.

2013-01-01

In many applications we are interested in making inference on latent time series from indirect measurements, which are often low-dimensional projections resulting from mixing or aggregation. Positron emission tomography, super-resolution, and network traffic monitoring are some examples. Inference in such settings requires solving a sequence of ill-posed inverse problems, yt = Axt, where the projection mechanism provides information on A. We consider problems in which A specifies mixing on a graph of times series that are bursty and sparse. We develop a multilevel state-space model for mixing times series and an efficient approach to inference. A simple model is used to calibrate regularization parameters that lead to efficient inference in the multilevel state-space model. We apply this method to the problem of estimating point-to-point traffic flows on a network from aggregate measurements. Our solution outperforms existing methods for this problem, and our two-stage approach suggests an efficient inference strategy for multilevel models of multivariate time series. PMID:25309135

A window-based time series feature extraction method.

PubMed

Katircioglu-Öztürk, Deniz; Güvenir, H Altay; Ravens, Ursula; Baykal, Nazife

2017-10-01

This study proposes a robust similarity score-based time series feature extraction method that is termed as Window-based Time series Feature ExtraCtion (WTC). Specifically, WTC generates domain-interpretable results and involves significantly low computational complexity thereby rendering itself useful for densely sampled and populated time series datasets. In this study, WTC is applied to a proprietary action potential (AP) time series dataset on human cardiomyocytes and three precordial leads from a publicly available electrocardiogram (ECG) dataset. This is followed by comparing WTC in terms of predictive accuracy and computational complexity with shapelet transform and fast shapelet transform (which constitutes an accelerated variant of the shapelet transform). The results indicate that WTC achieves a slightly higher classification performance with significantly lower execution time when compared to its shapelet-based alternatives. With respect to its interpretable features, WTC has a potential to enable medical experts to explore definitive common trends in novel datasets. Copyright © 2017 Elsevier Ltd. All rights reserved.

RADON CONCENTRATION TIME SERIES MODELING AND APPLICATION DISCUSSION.

PubMed

Stránský, V; Thinová, L

2017-11-01

In the year 2010 a continual radon measurement was established at Mladeč Caves in the Czech Republic using a continual radon monitor RADIM3A. In order to model radon time series in the years 2010-15, the Box-Jenkins Methodology, often used in econometrics, was applied. Because of the behavior of radon concentrations (RCs), a seasonal integrated, autoregressive moving averages model with exogenous variables (SARIMAX) has been chosen to model the measured time series. This model uses the time series seasonality, previously acquired values and delayed atmospheric parameters, to forecast RC. The developed model for RC time series is called regARIMA(5,1,3). Model residuals could be retrospectively compared with seismic evidence of local or global earthquakes, which occurred during the RCs measurement. This technique enables us to asses if continuously measured RC could serve an earthquake precursor. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Professional Nursing Series by Videoconferencing.

ERIC Educational Resources Information Center

Weber, Jeanne Rodier; Lawlor, Andrew C.

1998-01-01

A university consortium developed a continuing-education series for rural Pennsylvania nurses using videoconferencing. The program was well received by participants and proven a viable method of delivery to isolated areas. (SK)

Institute of Educational Technology. Series List. Reports and Papers Produced in Series 1969-1991. A Companion to "The Institute Bibliography."

ERIC Educational Resources Information Center

Whitehead, Don J., Comp.

Compiled to make available details of reports which contain the record of work by the research groups of the Open University's Institute of Educational Technology, this list is divided into two sections: (1) Completed Series; and (2) Current Series. Within each section the lists are placed in alphabetical order by program and, where known, the…

Water Splitting with Series-Connected Polymer Solar Cells.

PubMed

Esiner, Serkan; van Eersel, Harm; van Pruissen, Gijs W P; Turbiez, Mathieu; Wienk, Martijn M; Janssen, René A J

2016-10-12

We investigate light-driven electrochemical water splitting with series-connected polymer solar cells using a combined experimental and modeling approach. The expected maximum solar-to-hydrogen conversion efficiency (η STH ) for light-driven water splitting is modeled for two, three, and four series-connected polymer solar cells. In the modeling, we assume an electrochemical water splitting potential of 1.50 V and a polymer solar cell for which the external quantum efficiency and fill factor are both 0.65. The minimum photon energy loss (E loss ), defined as the energy difference between the optical band gap (E g ) and the open-circuit voltage (V oc ), is set to 0.8 eV, which we consider a realistic value for polymer solar cells. Within these approximations, two series-connected single junction cells with E g = 1.73 eV or three series-connected cells with E g = 1.44 eV are both expected to give an η STH of 6.9%. For four series-connected cells, the maximum η STH is slightly less at 6.2% at an optimal E g = 1.33 eV. Water splitting was performed with series-connected polymer solar cells using polymers with different band gaps. PTPTIBDT-OD (E g = 1.89 eV), PTB7-Th (E g = 1.56 eV), and PDPP5T-2 (E g = 1.44 eV) were blended with [70]PCBM as absorber layer for two, three, and four series-connected configurations, respectively, and provide η STH values of 4.1, 6.1, and 4.9% when using a retroreflective foil on top of the cell to enhance light absorption. The reasons for deviations with experiments are analyzed and found to be due to differences in E g and E loss . Light-driven electrochemical water splitting was also modeled for multijunction polymer solar cells with vertically stacked photoactive layers. Under identical assumptions, an η STH of 10.0% is predicted for multijunction cells.

76 FR 47617 - BofA Funds Series Trust, et al.;

Federal Register 2010, 2011, 2012, 2013, 2014

2011-08-05

... Funds Series Trust, et al.; Notice of Application August 1, 2011. AGENCY: Securities and Exchange... Funds Series Trust (``BAFST'' or ``Trust''), on behalf of its series (the ``Funds'', BofA Advisors, LLC... Incorporated (together with any successor, ``MLPF&S'') (Trust, Advisor and MLPF&S, the ``Applicants'').\\1\\ \\1...

Empirical method to measure stochasticity and multifractality in nonlinear time series

NASA Astrophysics Data System (ADS)

Lin, Chih-Hao; Chang, Chia-Seng; Li, Sai-Ping

2013-12-01

An empirical algorithm is used here to study the stochastic and multifractal nature of nonlinear time series. A parameter can be defined to quantitatively measure the deviation of the time series from a Wiener process so that the stochasticity of different time series can be compared. The local volatility of the time series under study can be constructed using this algorithm, and the multifractal structure of the time series can be analyzed by using this local volatility. As an example, we employ this method to analyze financial time series from different stock markets. The result shows that while developed markets evolve very much like an Ito process, the emergent markets are far from efficient. Differences about the multifractal structures and leverage effects between developed and emergent markets are discussed. The algorithm used here can be applied in a similar fashion to study time series of other complex systems.

Publications - USBM Publications Series | Alaska Division of Geological &

Science.gov Websites

Publications Geologic Materials Center General Information Inventory Monthly Report Hours and Location Policy content USBM Publications Series Descriptions Series List AR - Agency Report B - Bulletin CR - Contract Report FR - Field Report IC - Information Circular MLA - Mineral Land Assessment MRS - Mineral Resource

Time Series Econometrics for the 21st Century

ERIC Educational Resources Information Center

Hansen, Bruce E.

2017-01-01

The field of econometrics largely started with time series analysis because many early datasets were time-series macroeconomic data. As the field developed, more cross-sectional and longitudinal datasets were collected, which today dominate the majority of academic empirical research. In nonacademic (private sector, central bank, and governmental)…

DIY Solar Market Analysis Webinar Series: Solar Resource and Technical

Science.gov Websites

Series: Solar Resource and Technical Potential DIY Solar Market Analysis Webinar Series: Solar Resource and Technical Potential Wednesday, June 11, 2014 As part of a Do-It-Yourself Solar Market Analysis summer series, NREL's Solar Technical Assistance Team (STAT) presented a live webinar titled, "Solar

Transformation-cost time-series method for analyzing irregularly sampled data

NASA Astrophysics Data System (ADS)

Ozken, Ibrahim; Eroglu, Deniz; Stemler, Thomas; Marwan, Norbert; Bagci, G. Baris; Kurths, Jürgen

2015-06-01

Irregular sampling of data sets is one of the challenges often encountered in time-series analysis, since traditional methods cannot be applied and the frequently used interpolation approach can corrupt the data and bias the subsequence analysis. Here we present the TrAnsformation-Cost Time-Series (TACTS) method, which allows us to analyze irregularly sampled data sets without degenerating the quality of the data set. Instead of using interpolation we consider time-series segments and determine how close they are to each other by determining the cost needed to transform one segment into the following one. Using a limited set of operations—with associated costs—to transform the time series segments, we determine a new time series, that is our transformation-cost time series. This cost time series is regularly sampled and can be analyzed using standard methods. While our main interest is the analysis of paleoclimate data, we develop our method using numerical examples like the logistic map and the Rössler oscillator. The numerical data allows us to test the stability of our method against noise and for different irregular samplings. In addition we provide guidance on how to choose the associated costs based on the time series at hand. The usefulness of the TACTS method is demonstrated using speleothem data from the Secret Cave in Borneo that is a good proxy for paleoclimatic variability in the monsoon activity around the maritime continent.

Transformation-cost time-series method for analyzing irregularly sampled data.

PubMed

Ozken, Ibrahim; Eroglu, Deniz; Stemler, Thomas; Marwan, Norbert; Bagci, G Baris; Kurths, Jürgen

2015-06-01

Irregular sampling of data sets is one of the challenges often encountered in time-series analysis, since traditional methods cannot be applied and the frequently used interpolation approach can corrupt the data and bias the subsequence analysis. Here we present the TrAnsformation-Cost Time-Series (TACTS) method, which allows us to analyze irregularly sampled data sets without degenerating the quality of the data set. Instead of using interpolation we consider time-series segments and determine how close they are to each other by determining the cost needed to transform one segment into the following one. Using a limited set of operations-with associated costs-to transform the time series segments, we determine a new time series, that is our transformation-cost time series. This cost time series is regularly sampled and can be analyzed using standard methods. While our main interest is the analysis of paleoclimate data, we develop our method using numerical examples like the logistic map and the Rössler oscillator. The numerical data allows us to test the stability of our method against noise and for different irregular samplings. In addition we provide guidance on how to choose the associated costs based on the time series at hand. The usefulness of the TACTS method is demonstrated using speleothem data from the Secret Cave in Borneo that is a good proxy for paleoclimatic variability in the monsoon activity around the maritime continent.

Semi-autonomous remote sensing time series generation tool

NASA Astrophysics Data System (ADS)

Babu, Dinesh Kumar; Kaufmann, Christof; Schmidt, Marco; Dhams, Thorsten; Conrad, Christopher

2017-10-01

High spatial and temporal resolution data is vital for crop monitoring and phenology change detection. Due to the lack of satellite architecture and frequent cloud cover issues, availability of daily high spatial data is still far from reality. Remote sensing time series generation of high spatial and temporal data by data fusion seems to be a practical alternative. However, it is not an easy process, since it involves multiple steps and also requires multiple tools. In this paper, a framework of Geo Information System (GIS) based tool is presented for semi-autonomous time series generation. This tool will eliminate the difficulties by automating all the steps and enable the users to generate synthetic time series data with ease. Firstly, all the steps required for the time series generation process are identified and grouped into blocks based on their functionalities. Later two main frameworks are created, one to perform all the pre-processing steps on various satellite data and the other one to perform data fusion to generate time series. The two frameworks can be used individually to perform specific tasks or they could be combined to perform both the processes in one go. This tool can handle most of the known geo data formats currently available which makes it a generic tool for time series generation of various remote sensing satellite data. This tool is developed as a common platform with good interface which provides lot of functionalities to enable further development of more remote sensing applications. A detailed description on the capabilities and the advantages of the frameworks are given in this paper.

ACC Study Guide Series.

ERIC Educational Resources Information Center

Austin Community Coll., TX. Rio Grande Campus.

Ten one-page instructional guides designed to assist Austin Community College (ACC) students in using the library and in writing research papers are presented in this series. The titles of the guides are: (1) "The Media Collection (We have more than books in the LRC)"; (2) "Encyclopedias"; (3) "Finding Books"; (4)…

Discrimination. Opposing Viewpoints Series.

ERIC Educational Resources Information Center

Williams, Mary E., Ed.

Books in the Opposing Viewpoints series challenge readers to question their own opinions and assumptions. By reading carefully balanced views, readers confront new ideas on the topic of interest. The Civil Rights Act of 1964, which prohibited job discrimination based on age, race, religion, gender, or national origin, provided the groundwork for…

Non-rigid Earth rotation series

NASA Astrophysics Data System (ADS)

Pashkevich, V. V.

2008-04-01

The last years a lot of attempts to derive a high-precision theory of the non-rigid Earth rotation was carried out. For these purposes the different transfer functions are used. Usually these transfer func- tions are applied to the series representing the nutation in longitude and in obliquity of the rigid Earth rotation with respect to the ecliptic of date. The aim of this investigation is a construction of the new high- precision non-rigid Earth rotation series (SN9000), dynamically adequate to the DE404/LE404 ephemeris over 2000 years, which are expressed as a function of Euler angles ψ, θ and φ with respect to the fixed ecliptic plane and equinox J2000.0. The early stages of the previous investigation: 1. The high-precision numerical solution of the rigid Earth rotation have been constructed (V.V.Pashkevich, G.I.Eroshkin and A.Brzezinski, 2004), (V.V.Pashkevich and G.I.Eroshkin, Proceedings of Journees 2004). The initial con- ditions have been calculated from SMART97 (P.Bretagnon, G.Francou, P.Rocher, J.L.Simon,1998). The discrepancies between the numerical solution and the semi-analytical solution SMART97 were obtained in Euler angles over 2000 years with one-day spacing. 2. Investigation of the discrepancies is carried out by the least squares and by the spectral analysis algorithms (V.V.Pashkevich and G.I.Eroshkin, Proceedings of Journees 2005). The high-precision rigid Earth rotation series S9000 are determined (V.V.Pashkevich and G.I.Eroshkin, 2005 ). The next stage of this investigation: 3. The new high-precision non-rigid Earth rotation series (SN9000), which are expressed as a function of Euler angles, are constructed by using the method (P.Bretagnon, P.M.Mathews, J.-L.Simon: 1999) and the transfer function MHB2002 (Mathews, P. M., Herring, T. A., and Buffett B. A., 2002).

On the Behavior of Eisenstein Series Through Elliptic Degeneration

NASA Astrophysics Data System (ADS)

Garbin, D.; Pippich, A.-M. V.

2009-12-01

Let Γ be a Fuchsian group of the first kind acting on the hyperbolic upper half plane {mathbb{H}}, and let {M = Γbackslash mathbb{H}} be the associated finite volume hyperbolic Riemann surface. If γ is a primitive parabolic, hyperbolic, resp. elliptic element of Γ, there is an associated parabolic, hyperbolic, resp. elliptic Eisenstein series. In this article, we study the limiting behavior of these Eisenstein series on an elliptically degenerating family of finite volume hyperbolic Riemann surfaces. In particular, we prove the following result. The elliptic Eisenstein series associated to a degenerating elliptic element converges up to a factor to the parabolic Eisenstein series associated to the parabolic element which fixes the newly developed cusp on the limit surface.

Nonstationary time series prediction combined with slow feature analysis

NASA Astrophysics Data System (ADS)

Wang, G.; Chen, X.

2015-01-01

Almost all climate time series have some degree of nonstationarity due to external driving forces perturbations of the observed system. Therefore, these external driving forces should be taken into account when reconstructing the climate dynamics. This paper presents a new technique of combining the driving force of a time series obtained using the Slow Feature Analysis (SFA) approach, then introducing the driving force into a predictive model to predict non-stationary time series. In essence, the main idea of the technique is to consider the driving forces as state variables and incorporate them into the prediction model. To test the method, experiments using a modified logistic time series and winter ozone data in Arosa, Switzerland, were conducted. The results showed improved and effective prediction skill.

Small Systems Monthly Webinar Series

EPA Pesticide Factsheets

Schedule for EPA's Office of Research and Development and Office of Water's monthly webinar series: challenges and treatment solutions for small drinking water systems. One continuing education contact hour is offered for each webinar.

Trash-Free Waters Webinar Series

EPA Pesticide Factsheets

The Trash-Free Waters Webinar Series promotes increased knowledge and understanding of the sources, distribution and impacts of plastics and microplastics in the environment with featured presenters who are experienced researchers in this field.

Aroma characterization based on aromatic series analysis in table grapes

PubMed Central

Wu, Yusen; Duan, Shuyan; Zhao, Liping; Gao, Zhen; Luo, Meng; Song, Shiren; Xu, Wenping; Zhang, Caixi; Ma, Chao; Wang, Shiping

2016-01-01

Aroma is an important part of quality in table grape, but the key aroma compounds and the aroma series of table grapes remains unknown. In this paper, we identified 67 aroma compounds in 20 table grape cultivars; 20 in pulp and 23 in skin were active compounds. C6 compounds were the basic background volatiles, but the aroma contents of pulp juice and skin depended mainly on the levels of esters and terpenes, respectively. Most obviously, ‘Kyoho’ grapevine series showed high contents of esters in pulp, while Muscat/floral cultivars showed abundant monoterpenes in skin. For the aroma series, table grapes were characterized mainly by herbaceous, floral, balsamic, sweet and fruity series. The simple and visualizable aroma profiles were established using aroma fingerprints based on the aromatic series. Hierarchical cluster analysis (HCA) and principal component analysis (PCA) showed that the aroma profiles of pulp juice, skin and whole berries could be classified into 5, 3, and 5 groups, respectively. Combined with sensory evaluation, we could conclude that fatty and balsamic series were the preferred aromatic series, and the contents of their contributors (β-ionone and octanal) may be useful as indicators for the improvement of breeding and cultivation measures for table grapes. PMID:27487935

Heat recovery system series arrangements

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

Kauffman, Justin P.; Welch, Andrew M.; Dawson, Gregory R.

The present disclosure is directed to heat recovery systems that employ two or more organic Rankine cycle (ORC) units disposed in series. According to certain embodiments, each ORC unit includes an evaporator that heats an organic working fluid, a turbine generator set that expands the working fluid to generate electricity, a condenser that cools the working fluid, and a pump that returns the working fluid to the evaporator. The heating fluid is directed through each evaporator to heat the working fluid circulating within each ORC unit, and the cooling fluid is directed through each condenser to cool the working fluidmore » circulating within each ORC unit. The heating fluid and the cooling fluid flow through the ORC units in series in the same or opposite directions.« less

Adaptive time-variant models for fuzzy-time-series forecasting.

PubMed

Wong, Wai-Keung; Bai, Enjian; Chu, Alice Wai-Ching

2010-12-01

A fuzzy time series has been applied to the prediction of enrollment, temperature, stock indices, and other domains. Related studies mainly focus on three factors, namely, the partition of discourse, the content of forecasting rules, and the methods of defuzzification, all of which greatly influence the prediction accuracy of forecasting models. These studies use fixed analysis window sizes for forecasting. In this paper, an adaptive time-variant fuzzy-time-series forecasting model (ATVF) is proposed to improve forecasting accuracy. The proposed model automatically adapts the analysis window size of fuzzy time series based on the prediction accuracy in the training phase and uses heuristic rules to generate forecasting values in the testing phase. The performance of the ATVF model is tested using both simulated and actual time series including the enrollments at the University of Alabama, Tuscaloosa, and the Taiwan Stock Exchange Capitalization Weighted Stock Index (TAIEX). The experiment results show that the proposed ATVF model achieves a significant improvement in forecasting accuracy as compared to other fuzzy-time-series forecasting models.

Characterizing Time Series Data Diversity for Wind Forecasting: Preprint

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

Hodge, Brian S; Chartan, Erol Kevin; Feng, Cong

Wind forecasting plays an important role in integrating variable and uncertain wind power into the power grid. Various forecasting models have been developed to improve the forecasting accuracy. However, it is challenging to accurately compare the true forecasting performances from different methods and forecasters due to the lack of diversity in forecasting test datasets. This paper proposes a time series characteristic analysis approach to visualize and quantify wind time series diversity. The developed method first calculates six time series characteristic indices from various perspectives. Then the principal component analysis is performed to reduce the data dimension while preserving the importantmore » information. The diversity of the time series dataset is visualized by the geometric distribution of the newly constructed principal component space. The volume of the 3-dimensional (3D) convex polytope (or the length of 1D number axis, or the area of the 2D convex polygon) is used to quantify the time series data diversity. The method is tested with five datasets with various degrees of diversity.« less

Permutation entropy of finite-length white-noise time series.

PubMed

Little, Douglas J; Kane, Deb M

2016-08-01

Permutation entropy (PE) is commonly used to discriminate complex structure from white noise in a time series. While the PE of white noise is well understood in the long time-series limit, analysis in the general case is currently lacking. Here the expectation value and variance of white-noise PE are derived as functions of the number of ordinal pattern trials, N, and the embedding dimension, D. It is demonstrated that the probability distribution of the white-noise PE converges to a χ^{2} distribution with D!-1 degrees of freedom as N becomes large. It is further demonstrated that the PE variance for an arbitrary time series can be estimated as the variance of a related metric, the Kullback-Leibler entropy (KLE), allowing the qualitative N≫D! condition to be recast as a quantitative estimate of the N required to achieve a desired PE calculation precision. Application of this theory to statistical inference is demonstrated in the case of an experimentally obtained noise series, where the probability of obtaining the observed PE value was calculated assuming a white-noise time series. Standard statistical inference can be used to draw conclusions whether the white-noise null hypothesis can be accepted or rejected. This methodology can be applied to other null hypotheses, such as discriminating whether two time series are generated from different complex system states.

Clinical time series prediction: towards a hierarchical dynamical system framework

PubMed Central

Liu, Zitao; Hauskrecht, Milos

2014-01-01

Objective Developing machine learning and data mining algorithms for building temporal models of clinical time series is important for understanding of the patient condition, the dynamics of a disease, effect of various patient management interventions and clinical decision making. In this work, we propose and develop a novel hierarchical framework for modeling clinical time series data of varied length and with irregularly sampled observations. Materials and methods Our hierarchical dynamical system framework for modeling clinical time series combines advantages of the two temporal modeling approaches: the linear dynamical system and the Gaussian process. We model the irregularly sampled clinical time series by using multiple Gaussian process sequences in the lower level of our hierarchical framework and capture the transitions between Gaussian processes by utilizing the linear dynamical system. The experiments are conducted on the complete blood count (CBC) panel data of 1000 post-surgical cardiac patients during their hospitalization. Our framework is evaluated and compared to multiple baseline approaches in terms of the mean absolute prediction error and the absolute percentage error. Results We tested our framework by first learning the time series model from data for the patient in the training set, and then applying the model in order to predict future time series values on the patients in the test set. We show that our model outperforms multiple existing models in terms of its predictive accuracy. Our method achieved a 3.13% average prediction accuracy improvement on ten CBC lab time series when it was compared against the best performing baseline. A 5.25% average accuracy improvement was observed when only short-term predictions were considered. Conclusion A new hierarchical dynamical system framework that lets us model irregularly sampled time series data is a promising new direction for modeling clinical time series and for improving their predictive

Clinical time series prediction: Toward a hierarchical dynamical system framework.

PubMed

Liu, Zitao; Hauskrecht, Milos

2015-09-01

Developing machine learning and data mining algorithms for building temporal models of clinical time series is important for understanding of the patient condition, the dynamics of a disease, effect of various patient management interventions and clinical decision making. In this work, we propose and develop a novel hierarchical framework for modeling clinical time series data of varied length and with irregularly sampled observations. Our hierarchical dynamical system framework for modeling clinical time series combines advantages of the two temporal modeling approaches: the linear dynamical system and the Gaussian process. We model the irregularly sampled clinical time series by using multiple Gaussian process sequences in the lower level of our hierarchical framework and capture the transitions between Gaussian processes by utilizing the linear dynamical system. The experiments are conducted on the complete blood count (CBC) panel data of 1000 post-surgical cardiac patients during their hospitalization. Our framework is evaluated and compared to multiple baseline approaches in terms of the mean absolute prediction error and the absolute percentage error. We tested our framework by first learning the time series model from data for the patients in the training set, and then using it to predict future time series values for the patients in the test set. We show that our model outperforms multiple existing models in terms of its predictive accuracy. Our method achieved a 3.13% average prediction accuracy improvement on ten CBC lab time series when it was compared against the best performing baseline. A 5.25% average accuracy improvement was observed when only short-term predictions were considered. A new hierarchical dynamical system framework that lets us model irregularly sampled time series data is a promising new direction for modeling clinical time series and for improving their predictive performance. Copyright © 2014 Elsevier B.V. All rights reserved.

Filter-based multiscale entropy analysis of complex physiological time series.

PubMed

Xu, Yuesheng; Zhao, Liang

2013-08-01

Multiscale entropy (MSE) has been widely and successfully used in analyzing the complexity of physiological time series. We reinterpret the averaging process in MSE as filtering a time series by a filter of a piecewise constant type. From this viewpoint, we introduce filter-based multiscale entropy (FME), which filters a time series to generate multiple frequency components, and then we compute the blockwise entropy of the resulting components. By choosing filters adapted to the feature of a given time series, FME is able to better capture its multiscale information and to provide more flexibility for studying its complexity. Motivated by the heart rate turbulence theory, which suggests that the human heartbeat interval time series can be described in piecewise linear patterns, we propose piecewise linear filter multiscale entropy (PLFME) for the complexity analysis of the time series. Numerical results from PLFME are more robust to data of various lengths than those from MSE. The numerical performance of the adaptive piecewise constant filter multiscale entropy without prior information is comparable to that of PLFME, whose design takes prior information into account.

Equalizer system and method for series connected energy storing devices

DOEpatents

Rouillard, Jean; Comte, Christophe; Hagen, Ronald A.; Knudson, Orlin B.; Morin, Andre; Ross, Guy

1999-01-01

An apparatus and method for regulating the charge voltage of a number of electrochemical cells connected in series is disclosed. Equalization circuitry is provided to control the amount of charge current supplied to individual electrochemical cells included within the series string of electrochemical cells without interrupting the flow of charge current through the series string. The equalization circuitry balances the potential of each of the electrochemical cells to within a pre-determined voltage setpoint tolerance during charging, and, if necessary, prior to initiating charging. Equalization of cell potentials may be effected toward the end of a charge cycle or throughout the charge cycle. Overcharge protection is also provided for each of the electrochemical cells coupled to the series connection. During a discharge mode of operation in accordance with one embodiment, the equalization circuitry is substantially non-conductive with respect to the flow of discharge current from the series string of electrochemical cells. In accordance with another embodiment, equalization of the series string of cells is effected during a discharge cycle.

Multichannel biomedical time series clustering via hierarchical probabilistic latent semantic analysis.

PubMed

Wang, Jin; Sun, Xiangping; Nahavandi, Saeid; Kouzani, Abbas; Wu, Yuchuan; She, Mary

2014-11-01

Biomedical time series clustering that automatically groups a collection of time series according to their internal similarity is of importance for medical record management and inspection such as bio-signals archiving and retrieval. In this paper, a novel framework that automatically groups a set of unlabelled multichannel biomedical time series according to their internal structural similarity is proposed. Specifically, we treat a multichannel biomedical time series as a document and extract local segments from the time series as words. We extend a topic model, i.e., the Hierarchical probabilistic Latent Semantic Analysis (H-pLSA), which was originally developed for visual motion analysis to cluster a set of unlabelled multichannel time series. The H-pLSA models each channel of the multichannel time series using a local pLSA in the first layer. The topics learned in the local pLSA are then fed to a global pLSA in the second layer to discover the categories of multichannel time series. Experiments on a dataset extracted from multichannel Electrocardiography (ECG) signals demonstrate that the proposed method performs better than previous state-of-the-art approaches and is relatively robust to the variations of parameters including length of local segments and dictionary size. Although the experimental evaluation used the multichannel ECG signals in a biometric scenario, the proposed algorithm is a universal framework for multichannel biomedical time series clustering according to their structural similarity, which has many applications in biomedical time series management. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Southern Salish Sea Habitat Map Series data catalog

USGS Publications Warehouse

Cochrane, Guy R.

2015-01-01

This data catalog contains much of the data used to prepare the SIMs in the Southern Salish Sea Habitat Map Series. Other data that were used to prepare the maps were compiled from previously published sources (for example, sediment samples and seismic reflection profiles) and are not included in this data series.

Power: Constitutional Update. Bar/School Partnership Programs Series.

ERIC Educational Resources Information Center

American Bar Association, Chicago, IL. Special Committee on Youth Education for Citizenship.

The fourth in a special series of handbooks dealing with constitutional themes, this document looks at power in the context of the U.S. Constitution. "The Constitution's Prescription for Freedom" (L. Peach) examines the separation of powers provided for in the Constitution. "The Concept of Power" (C. Roach) is a series of…

Science, Philosophy & Religion. Working Papers Series Volume 1.

ERIC Educational Resources Information Center

Schenck, David, Ed.

Lehigh University Technology Studies Resource Center has coordinated and produced a series of publications that focus on expanding an understanding of the social context of technology in contemporary society. This volume is the first in a series of working papers that aim to stimulate new research, facilitate dissemination, encourage peer review,…

Good Work! Instructor's Guide. Revised. Employability Skills Series.

ERIC Educational Resources Information Center

Farrow, Douglas R.

This instructor's guide accompanies the student booklet/unit on good work habits/behaviors in the Employability Skills Series. (The student booklet is available separately as CE 031 161.) It first discusses the Employability Skills Series. A section on administering the unit details purpose of the unit and major concepts to be developed, lists…

Characterization of the LAWB99-series and ORLEC-series Glasses

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

Fox, K. M.; Edwards, T. B.; Riley, W. T.

In this report, the Savannah River National Laboratory provides chemical analysis results for a series of simulated low activity waste (LAW) glass compositions. These data will be used in the development of improved sulfur solubility models for LAW glass. A procedure developed at the Pacific Northwest National Laboratory for producing sulfur saturated melts (SSMs) was used to fabricate the glasses characterized in this report. This method includes triplicate melting steps with excess sodium sulfate, followed by grinding and washing to remove unincorporated sulfur salts. The wash solutions were also analyzed as part of this study.

Lower GI Series (Barium Enema)

MedlinePlus

... You may be asked to change position several times to evenly coat the large intestine with the barium. If you are having a double-contrast lower GI series, the radiologist will inject air through the tube ...

Time series momentum and contrarian effects in the Chinese stock market

NASA Astrophysics Data System (ADS)

Shi, Huai-Long; Zhou, Wei-Xing

2017-10-01

This paper concentrates on the time series momentum or contrarian effects in the Chinese stock market. We evaluate the performance of the time series momentum strategy applied to major stock indices in mainland China and explore the relation between the performance of time series momentum strategies and some firm-specific characteristics. Our findings indicate that there is a time series momentum effect in the short run and a contrarian effect in the long run in the Chinese stock market. The performances of the time series momentum and contrarian strategies are highly dependent on the look-back and holding periods and firm-specific characteristics.

A Unified Method of Finding Laplace Transforms, Fourier Transforms, and Fourier Series. [and] An Inversion Method for Laplace Transforms, Fourier Transforms, and Fourier Series. Integral Transforms and Series Expansions. Modules and Monographs in Undergraduate Mathematics and Its Applications Project. UMAP Units 324 and 325.

ERIC Educational Resources Information Center

Grimm, C. A.

This document contains two units that examine integral transforms and series expansions. In the first module, the user is expected to learn how to use the unified method presented to obtain Laplace transforms, Fourier transforms, complex Fourier series, real Fourier series, and half-range sine series for given piecewise continuous functions. In…

Measurements of spatial population synchrony: influence of time series transformations.

PubMed

Chevalier, Mathieu; Laffaille, Pascal; Ferdy, Jean-Baptiste; Grenouillet, Gaël

2015-09-01

Two mechanisms have been proposed to explain spatial population synchrony: dispersal among populations, and the spatial correlation of density-independent factors (the "Moran effect"). To identify which of these two mechanisms is driving spatial population synchrony, time series transformations (TSTs) of abundance data have been used to remove the signature of one mechanism, and highlight the effect of the other. However, several issues with TSTs remain, and to date no consensus has emerged about how population time series should be handled in synchrony studies. Here, by using 3131 time series involving 34 fish species found in French rivers, we computed several metrics commonly used in synchrony studies to determine whether a large-scale climatic factor (temperature) influenced fish population dynamics at the regional scale, and to test the effect of three commonly used TSTs (detrending, prewhitening and a combination of both) on these metrics. We also tested whether the influence of TSTs on time series and population synchrony levels was related to the features of the time series using both empirical and simulated time series. For several species, and regardless of the TST used, we evidenced a Moran effect on freshwater fish populations. However, these results were globally biased downward by TSTs which reduced our ability to detect significant signals. Depending on the species and the features of the time series, we found that TSTs could lead to contradictory results, regardless of the metric considered. Finally, we suggest guidelines on how population time series should be processed in synchrony studies.

Functional DNA: Teaching Infinite Series through Genetic Analogy

ERIC Educational Resources Information Center

Kowalski, R. Travis

2011-01-01

This article presents an extended analogy that connects infinite sequences and series to the science of genetics, by identifying power series as "DNA for a function." This analogy allows standard topics such as convergence tests or Taylor approximations to be recast in a "forensic" light as mathematical analogs of genetic concepts such as DNA…

Exploring Fourier Series and Gibbs Phenomenon Using Mathematica

ERIC Educational Resources Information Center

Ghosh, Jonaki B.

2011-01-01

This article describes a laboratory module on Fourier series and Gibbs phenomenon which was undertaken by 32 Year 12 students. It shows how the use of CAS played the role of an "amplifier" by making higher level mathematical concepts accessible to students of year 12. Using Mathematica students were able to visualise Fourier series of…

Reviving Graduate Seminar Series through Non-Technical Presentations

ERIC Educational Resources Information Center

Madihally, Sundararajan V.

2011-01-01

Most chemical engineering programs that offer M.S. and Ph.D. degrees have a common seminar series for all the graduate students. Many would agree that seminars lack student interest, leading to ineffectiveness. We questioned the possibility of adding value to the seminar series by incorporating non-technical topics that may be more important to…

Common Issues in World Regions: A Video Series.

ERIC Educational Resources Information Center

Becker, James

1992-01-01

Describes a video series that offers information on the impact of current world problems on family life. Explains that the programs illustrate the five geographic themes by comparing the experiences of young people in North America and Western Europe. Suggests that the series helps teenagers see how the same problems affect families in different…

Parent's Journal. [Videotape Series].

ERIC Educational Resources Information Center

1999

Parent's Journal is a set of 16 videotapes for parents of prenatal, infant, and toddler-age children, created by the Alaska Native Home Base Video Project of the Tlingit and Haida Head Start Program. This series offers culturally relevant solutions to the challenges of parenting, drawing on the life stories and experiences of capable mothers and…

Family Feathers. [Videotape Series].

ERIC Educational Resources Information Center

1999

Family Feathers is a set of 18 videotapes for parents of preschool children, created by the Alaska Native Home Base Video Project of the Tlingit and Haida Head Start Program. This series offers culturally relevant solutions to the challenges of parenting, drawing on practical advice from Tlingit and Haida parents, wisdom from elders, and some of…

Online Conditional Outlier Detection in Nonstationary Time Series.

PubMed

Liu, Siqi; Wright, Adam; Hauskrecht, Milos

2017-05-01

The objective of this work is to develop methods for detecting outliers in time series data. Such methods can become the key component of various monitoring and alerting systems, where an outlier may be equal to some adverse condition that needs human attention. However, real-world time series are often affected by various sources of variability present in the environment that may influence the quality of detection; they may (1) explain some of the changes in the signal that would otherwise lead to false positive detections, as well as, (2) reduce the sensitivity of the detection algorithm leading to increase in false negatives. To alleviate these problems, we propose a new two-layer outlier detection approach that first tries to model and account for the nonstationarity and periodic variation in the time series, and then tries to use other observable variables in the environment to explain any additional signal variation. Our experiments on several data sets in different domains show that our method provides more accurate modeling of the time series, and that it is able to significantly improve outlier detection performance.

Analysis and generation of groundwater concentration time series

NASA Astrophysics Data System (ADS)

Crăciun, Maria; Vamoş, Călin; Suciu, Nicolae

2018-01-01

Concentration time series are provided by simulated concentrations of a nonreactive solute transported in groundwater, integrated over the transverse direction of a two-dimensional computational domain and recorded at the plume center of mass. The analysis of a statistical ensemble of time series reveals subtle features that are not captured by the first two moments which characterize the approximate Gaussian distribution of the two-dimensional concentration fields. The concentration time series exhibit a complex preasymptotic behavior driven by a nonstationary trend and correlated fluctuations with time-variable amplitude. Time series with almost the same statistics are generated by successively adding to a time-dependent trend a sum of linear regression terms, accounting for correlations between fluctuations around the trend and their increments in time, and terms of an amplitude modulated autoregressive noise of order one with time-varying parameter. The algorithm generalizes mixing models used in probability density function approaches. The well-known interaction by exchange with the mean mixing model is a special case consisting of a linear regression with constant coefficients.

Teaching English as a Second Language: Perspectives and Practices. A Series of Six Texts. Speaking and Understanding: Second of a Series.

ERIC Educational Resources Information Center

New York State Education Dept., Albany.

This book is designed to assist those who work with non-English dominant students by providing resource information relevant to second language teaching and learning. The articles in the series encompass both theory and practical learning techniques in six general topics. The articles in the second text of the series, concerning speaking and…

National Clearinghouse for Drug Abuse Information Selected Reference Series, Series 4, No. 1.

ERIC Educational Resources Information Center

National Inst. on Drug Abuse (DHEW/PHS), Rockville, MD. National Clearinghouse for Drug Abuse Information.

This bibliography, which attempts to gather the significant research on the reproductive effects of the drugs of abuse, is one in a series prepared by the National Clearinghouse for Drug Abuse Information on subjects of topical interest. Selection of literature is based on its currency, its significance in the field, and its availability in local…

The relation between periods’ identification and noises in hydrologic series data

NASA Astrophysics Data System (ADS)

Sang, Yan-Fang; Wang, Dong; Wu, Ji-Chun; Zhu, Qing-Ping; Wang, Ling

2009-04-01

SummaryIdentification of dominant periods is a typical and important issue in hydrologic series data analysis, since it is the basis of building effective stochastic models, understanding complex hydrologic processes, etc. However it is still a difficult task due to the influence of many interrelated factors, such as noises in hydrologic series data. In this paper, firstly the great influence of noises on periods' identification has been analyzed. Then, based on two conventional methods of hydrologic series analysis: wavelet analysis (WA) and maximum entropy spectral analysis (MESA), a new method of periods' identification of hydrologic series data, main series spectral analysis (MSSA), has been put forward, whose main idea is to identify periods of the main series on the basis of reducing hydrologic noises. Various methods (include fast Fourier transform (FFT), MESA and MSSA) have been applied to both synthetic series and observed hydrologic series. Results show that conventional methods (FFT and MESA) are not as good as expected due to the great influence of noises. However, this influence is not so strong while using the new method MSSA. In addition, by using the new de-noising method proposed in this paper, which is suitable for both normal noises and skew noises, the results are more reasonable, since noises separated from hydrologic series data generally follow skew probability distributions. In conclusion, based on comprehensive analyses, it can be stated that the proposed method MSSA could improve periods' identification by effectively reducing the influence of hydrologic noises.

Analysis of Time-Series Quasi-Experiments. Final Report.

ERIC Educational Resources Information Center

Glass, Gene V.; Maguire, Thomas O.

The objective of this project was to investigate the adequacy of statistical models developed by G. E. P. Box and G. C. Tiao for the analysis of time-series quasi-experiments: (1) The basic model developed by Box and Tiao is applied to actual time-series experiment data from two separate experiments, one in psychology and one in educational…

A Computer Evolution in Teaching Undergraduate Time Series

ERIC Educational Resources Information Center

Hodgess, Erin M.

2004-01-01

In teaching undergraduate time series courses, we have used a mixture of various statistical packages. We have finally been able to teach all of the applied concepts within one statistical package; R. This article describes the process that we use to conduct a thorough analysis of a time series. An example with a data set is provided. We compare…

Data series embedding and scale invariant statistics.

PubMed

Michieli, I; Medved, B; Ristov, S

2010-06-01

Data sequences acquired from bio-systems such as human gait data, heart rate interbeat data, or DNA sequences exhibit complex dynamics that is frequently described by a long-memory or power-law decay of autocorrelation function. One way of characterizing that dynamics is through scale invariant statistics or "fractal-like" behavior. For quantifying scale invariant parameters of physiological signals several methods have been proposed. Among them the most common are detrended fluctuation analysis, sample mean variance analyses, power spectral density analysis, R/S analysis, and recently in the realm of the multifractal approach, wavelet analysis. In this paper it is demonstrated that embedding the time series data in the high-dimensional pseudo-phase space reveals scale invariant statistics in the simple fashion. The procedure is applied on different stride interval data sets from human gait measurements time series (Physio-Bank data library). Results show that introduced mapping adequately separates long-memory from random behavior. Smaller gait data sets were analyzed and scale-free trends for limited scale intervals were successfully detected. The method was verified on artificially produced time series with known scaling behavior and with the varying content of noise. The possibility for the method to falsely detect long-range dependence in the artificially generated short range dependence series was investigated. (c) 2009 Elsevier B.V. All rights reserved.

Generalized Riemann hypothesis and stochastic time series

NASA Astrophysics Data System (ADS)

Mussardo, Giuseppe; LeClair, André

2018-06-01

Using the Dirichlet theorem on the equidistribution of residue classes modulo q and the Lemke Oliver–Soundararajan conjecture on the distribution of pairs of residues on consecutive primes, we show that the domain of convergence of the infinite product of Dirichlet L-functions of non-principal characters can be extended from down to , without encountering any zeros before reaching this critical line. The possibility of doing so can be traced back to a universal diffusive random walk behavior of a series C N over the primes which underlies the convergence of the infinite product of the Dirichlet functions. The series C N presents several aspects in common with stochastic time series and its control requires to address a problem similar to the single Brownian trajectory problem in statistical mechanics. In the case of the Dirichlet functions of non principal characters, we show that this problem can be solved in terms of a self-averaging procedure based on an ensemble of block variables computed on extended intervals of primes. Those intervals, called inertial intervals, ensure the ergodicity and stationarity of the time series underlying the quantity C N . The infinity of primes also ensures the absence of rare events which would have been responsible for a different scaling behavior than the universal law of the random walks.

Seri Rama: converting a shadow play puppet to Street Fighter.

PubMed

Ghani, D B A

2012-01-01

Shadow puppet plays, a traditional Malaysian theater art, is slowly losing its appeal to adolescents, who prefer computer games. To help reverse this decline, the authors incorporated the traditional Seri Rama character into the Street Fighter video game. Using modeling, texturing, and animation, they developed a 3D Seri Rama prototype. Users can control Seri Rama with a PlayStation game controller.

31 CFR 315.30 - Series E bonds and savings notes.

Code of Federal Regulations, 2010 CFR

2010-07-01

...) FISCAL SERVICE, DEPARTMENT OF THE TREASURY BUREAU OF THE PUBLIC DEBT REGULATIONS GOVERNING U.S. SAVINGS BONDS, SERIES A, B, C, D, E, F, G, H, J, AND K, AND U.S. SAVINGS NOTES Interest § 315.30 Series E bonds... 31 Money and Finance: Treasury 2 2010-07-01 2010-07-01 false Series E bonds and savings notes. 315...

Design considerations for case series models with exposure onset measurement error.

PubMed

Mohammed, Sandra M; Dalrymple, Lorien S; Sentürk, Damla; Nguyen, Danh V

2013-02-28

The case series model allows for estimation of the relative incidence of events, such as cardiovascular events, within a pre-specified time window after an exposure, such as an infection. The method requires only cases (individuals with events) and controls for all fixed/time-invariant confounders. The measurement error case series model extends the original case series model to handle imperfect data, where the timing of an infection (exposure) is not known precisely. In this work, we propose a method for power/sample size determination for the measurement error case series model. Extensive simulation studies are used to assess the accuracy of the proposed sample size formulas. We also examine the magnitude of the relative loss of power due to exposure onset measurement error, compared with the ideal situation where the time of exposure is measured precisely. To facilitate the design of case series studies, we provide publicly available web-based tools for determining power/sample size for both the measurement error case series model as well as the standard case series model. Copyright © 2012 John Wiley & Sons, Ltd.

Dobson total ozone series of Oxford: Reevaluation and applications

NASA Astrophysics Data System (ADS)

Vogler, C.; BröNnimann, S.; Staehelin, J.; Griffin, R. E. M.

2007-10-01

We have reevaluated the original total ozone measurements made in Oxford between 1924 and 1957, with a view to extending backward in time the existing total ozone series from 1957 to 1975. The Oxford measurements are the oldest Dobson observations in the world. Their prime importance, when coupled with the series from Arosa (since 1926) and Tromsø (since 1935), is for increasing basic understanding of stratospheric ozone and dynamics, while in relation to studies of the recent ozone depletion they constitute a baseline of considerable (and unique) significance and value. However, the reevaluation was made difficult on account of changes to the instruments and wavelengths as the early data collection methods evolved, while unknowns due to the influence of aerosols and the possible presence of dioxides of sulphur and nitrogen created additional problems. Our reevaluation was based on statistical procedures (comparisons with meteorological upper air data and ozone series from Arosa) and also on corrections suggested by Dobson himself. The comparisons demonstrate that the data are internally consistent and of good quality. Nevertheless, as post-1957 data were not assessed in this study, the series cannot be recommended at present for trend analysis, though the series can be used for climatological studies. By supplementing the Oxford data with other existing series, we present a European total ozone climatology for 1924-1939, 1950-1965, and 1988-2000 and analyze the data with respect to variables measuring the strength and the temperature of the polar vortex.

Scientific Library to Hold Annual Winter Video Series | Poster

Cancer.gov

The Scientific Library is getting ready for its Annual Winter Video Series. Beginning on Monday, January 9 and concluding on Friday, February 17, the Winter Video Series will consist of two different PBS programs, each with three episodes.

Self-affinity in the dengue fever time series

NASA Astrophysics Data System (ADS)

Azevedo, S. M.; Saba, H.; Miranda, J. G. V.; Filho, A. S. Nascimento; Moret, M. A.

2016-06-01

Dengue is a complex public health problem that is common in tropical and subtropical regions. This disease has risen substantially in the last three decades, and the physical symptoms depict the self-affine behavior of the occurrences of reported dengue cases in Bahia, Brazil. This study uses detrended fluctuation analysis (DFA) to verify the scale behavior in a time series of dengue cases and to evaluate the long-range correlations that are characterized by the power law α exponent for different cities in Bahia, Brazil. The scaling exponent (α) presents different long-range correlations, i.e. uncorrelated, anti-persistent, persistent and diffusive behaviors. The long-range correlations highlight the complex behavior of the time series of this disease. The findings show that there are two distinct types of scale behavior. In the first behavior, the time series presents a persistent α exponent for a one-month period. For large periods, the time series signal approaches subdiffusive behavior. The hypothesis of the long-range correlations in the time series of the occurrences of reported dengue cases was validated. The observed self-affinity is useful as a forecasting tool for future periods through extrapolation of the α exponent behavior. This complex system has a higher predictability in a relatively short time (approximately one month), and it suggests a new tool in epidemiological control strategies. However, predictions for large periods using DFA are hidden by the subdiffusive behavior.

Testing for nonlinearity in non-stationary physiological time series.

PubMed

Guarín, Diego; Delgado, Edilson; Orozco, Álvaro

2011-01-01

Testing for nonlinearity is one of the most important preprocessing steps in nonlinear time series analysis. Typically, this is done by means of the linear surrogate data methods. But it is a known fact that the validity of the results heavily depends on the stationarity of the time series. Since most physiological signals are non-stationary, it is easy to falsely detect nonlinearity using the linear surrogate data methods. In this document, we propose a methodology to extend the procedure for generating constrained surrogate time series in order to assess nonlinearity in non-stationary data. The method is based on the band-phase-randomized surrogates, which consists (contrary to the linear surrogate data methods) in randomizing only a portion of the Fourier phases in the high frequency domain. Analysis of simulated time series showed that in comparison to the linear surrogate data method, our method is able to discriminate between linear stationarity, linear non-stationary and nonlinear time series. Applying our methodology to heart rate variability (HRV) records of five healthy patients, we encountered that nonlinear correlations are present in this non-stationary physiological signals.

A univariate model of river water nitrate time series

NASA Astrophysics Data System (ADS)

Worrall, F.; Burt, T. P.

1999-01-01

Four time series were taken from three catchments in the North and South of England. The sites chosen included two in predominantly agricultural catchments, one at the tidal limit and one downstream of a sewage treatment works. A time series model was constructed for each of these series as a means of decomposing the elements controlling river water nitrate concentrations and to assess whether this approach could provide a simple management tool for protecting water abstractions. Autoregressive (AR) modelling of the detrended and deseasoned time series showed a "memory effect". This memory effect expressed itself as an increase in the winter-summer difference in nitrate levels that was dependent upon the nitrate concentration 12 or 6 months previously. Autoregressive moving average (ARMA) modelling showed that one of the series contained seasonal, non-stationary elements that appeared as an increasing trend in the winter-summer difference. The ARMA model was used to predict nitrate levels and predictions were tested against data held back from the model construction process - predictions gave average percentage errors of less than 10%. Empirical modelling can therefore provide a simple, efficient method for constructing management models for downstream water abstraction.

Rayleigh Scattering in Spectral Series with L-term Interference

NASA Astrophysics Data System (ADS)

Casini, R.; Manso Sainz, R.; del Pino Alemán, T.

2017-12-01

We derive a formalism to describe the scattering of polarized radiation over the full spectral range encompassed by atomic transitions belonging to the same spectral series (e.g., the H I Lyman and Balmer series, the UV multiplets of Fe I and Fe II). This allows us to study the role of radiation-induced coherence among the upper terms of the spectral series, and its contribution to Rayleigh scattering and the polarization of the solar continuum. We rely on previous theoretical results for the emissivity of a three-term atom of the Λ-type, taking into account partially coherent scattering, and generalize its expression in order to describe a “multiple Λ” atomic system underlying the formation of a spectral series. Our study shows that important polarization effects must be expected because of the combined action of partial frequency redistribution and radiation-induced coherence among the terms of the series. In particular, our model predicts the correct asymptotic limit of 100% polarization in the far wings of a complete (i.e., {{Δ }}L=0,+/- 1) group of transitions, which must be expected on the basis of the principle of spectroscopic stability.

Analyses of Inhomogeneities in Radiosonde Temperature and Humidity Time Series.

NASA Astrophysics Data System (ADS)

Zhai, Panmao; Eskridge, Robert E.

1996-04-01

Twice daily radiosonde data from selected stations in the United States (period 1948 to 1990) and China (period 1958 to 1990) were sorted into time series. These stations have one sounding taken in darkness and the other in sunlight. The analysis shows that the 0000 and 1200 UTC time series are highly correlated. Therefore, the Easterling and Peterson technique was tested on the 0000 and 1200 time series to detect inhomogeneities and to estimate the size of the biases. Discontinuities were detected using the difference series created from the 0000 and 1200 UTC time series. To establish that the detected bias was significant, a t test was performed to confirm that the change occurs in the daytime series but not in the nighttime series.Both U.S. and Chinese radiosonde temperature and humidity data include inhomogeneities caused by changes in radiosonde sensors and observation times. The U.S. humidity data have inhomogeneities that were caused by instrument changes and the censoring of data. The practice of reporting relative humidity as 19% when it is lower than 20% or the temperature is below 40°C is called censoring. This combination of procedural and instrument changes makes the detection of biases and adjustment of the data very difficult. In the Chinese temperatures, them are inhomogeneities related to a change in the radiation correction procedure.Test results demonstrate that a modified Easterling and Peterson method is suitable for use in detecting and adjusting time series radiosonde data.Accurate stations histories are very desirable. Stations histories can confirm that detected inhomogeneities are related to instrument or procedural changes. Adjustments can then he made to the data with some confidence.

Scaling properties of Polish rain series

NASA Astrophysics Data System (ADS)

Licznar, P.

2009-04-01

Scaling properties as well as multifractal nature of precipitation time series have not been studied for local Polish conditions until recently due to lack of long series of high-resolution data. The first Polish study of precipitation time series scaling phenomena was made on the base of pluviograph data from the Wroclaw University of Environmental and Life Sciences meteorological station located at the south-western part of the country. The 38 annual rainfall records from years 1962-2004 were converted into digital format and transformed into a standard format of 5-minute time series. The scaling properties and multifractal character of this material were studied by means of several different techniques: power spectral density analysis, functional box-counting, probability distribution/multiple scaling and trace moment methods. The result proved the general scaling character of time series at the range of time scales ranging form 5 minutes up to at least 24 hours. At the same time some characteristic breaks at scaling behavior were recognized. It is believed that the breaks were artificial and arising from the pluviograph rain gauge measuring precision limitations. Especially strong limitations at the precision of low-intensity precipitations recording by pluviograph rain gauge were found to be the main reason for artificial break at energy spectra, as was reported by other authors before. The analysis of co-dimension and moments scaling functions showed the signs of the first-order multifractal phase transition. Such behavior is typical for dressed multifractal processes that are observed by spatial or temporal averaging on scales larger than the inner-scale of those processes. The fractal dimension of rainfall process support derived from codimension and moments scaling functions geometry analysis was found to be 0.45. The same fractal dimension estimated by means of the functional box-counting method was equal to 0.58. At the final part of the study

Monograph on the use of the multivariate Gram Charlier series Type A

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

Hatayodom, T.; Heydt, G.

1978-01-01

The Gram-Charlier series in an infinite series expansion for a probability density function (pdf) in which terms of the series are Hermite polynomials. There are several Gram-Charlier series - the best known is Type A. The Gram-Charlier series, Type A (GCA) exists for both univariate and multivariate random variables. This monograph introduces the multivariate GCA and illustrates its use through several examples. A brief bibliography and discussion of Hermite polynomials is also included. 9 figures, 2 tables.

Nonlinear time-series-based adaptive control applications

NASA Technical Reports Server (NTRS)

Mohler, R. R.; Rajkumar, V.; Zakrzewski, R. R.

1991-01-01

A control design methodology based on a nonlinear time-series reference model is presented. It is indicated by highly nonlinear simulations that such designs successfully stabilize troublesome aircraft maneuvers undergoing large changes in angle of attack as well as large electric power transients due to line faults. In both applications, the nonlinear controller was significantly better than the corresponding linear adaptive controller. For the electric power network, a flexible AC transmission system with series capacitor power feedback control is studied. A bilinear autoregressive moving average reference model is identified from system data, and the feedback control is manipulated according to a desired reference state. The control is optimized according to a predictive one-step quadratic performance index. A similar algorithm is derived for control of rapid changes in aircraft angle of attack over a normally unstable flight regime. In the latter case, however, a generalization of a bilinear time-series model reference includes quadratic and cubic terms in angle of attack.

Time series regression studies in environmental epidemiology.

PubMed

Bhaskaran, Krishnan; Gasparrini, Antonio; Hajat, Shakoor; Smeeth, Liam; Armstrong, Ben

2013-08-01

Time series regression studies have been widely used in environmental epidemiology, notably in investigating the short-term associations between exposures such as air pollution, weather variables or pollen, and health outcomes such as mortality, myocardial infarction or disease-specific hospital admissions. Typically, for both exposure and outcome, data are available at regular time intervals (e.g. daily pollution levels and daily mortality counts) and the aim is to explore short-term associations between them. In this article, we describe the general features of time series data, and we outline the analysis process, beginning with descriptive analysis, then focusing on issues in time series regression that differ from other regression methods: modelling short-term fluctuations in the presence of seasonal and long-term patterns, dealing with time varying confounding factors and modelling delayed ('lagged') associations between exposure and outcome. We finish with advice on model checking and sensitivity analysis, and some common extensions to the basic model.

Stochastic nature of series of waiting times.

PubMed

Anvari, Mehrnaz; Aghamohammadi, Cina; Dashti-Naserabadi, H; Salehi, E; Behjat, E; Qorbani, M; Nezhad, M Khazaei; Zirak, M; Hadjihosseini, Ali; Peinke, Joachim; Tabar, M Reza Rahimi

2013-06-01

Although fluctuations in the waiting time series have been studied for a long time, some important issues such as its long-range memory and its stochastic features in the presence of nonstationarity have so far remained unstudied. Here we find that the "waiting times" series for a given increment level have long-range correlations with Hurst exponents belonging to the interval 1/2series has a short-range correlation, and then we study its stochastic nature using the Markovian method and determine the corresponding Kramers-Moyal coefficients. As an example, we analyze the velocity fluctuations in high Reynolds number turbulence and determine the level dependence of Markov time scales, as well as the drift and diffusion coefficients. We show that the waiting time distributions exhibit power law tails, and we were able to model the distribution with a continuous time random walk.

Stochastic nature of series of waiting times

NASA Astrophysics Data System (ADS)

Anvari, Mehrnaz; Aghamohammadi, Cina; Dashti-Naserabadi, H.; Salehi, E.; Behjat, E.; Qorbani, M.; Khazaei Nezhad, M.; Zirak, M.; Hadjihosseini, Ali; Peinke, Joachim; Tabar, M. Reza Rahimi

2013-06-01

Although fluctuations in the waiting time series have been studied for a long time, some important issues such as its long-range memory and its stochastic features in the presence of nonstationarity have so far remained unstudied. Here we find that the “waiting times” series for a given increment level have long-range correlations with Hurst exponents belonging to the interval 1/2series has a short-range correlation, and then we study its stochastic nature using the Markovian method and determine the corresponding Kramers-Moyal coefficients. As an example, we analyze the velocity fluctuations in high Reynolds number turbulence and determine the level dependence of Markov time scales, as well as the drift and diffusion coefficients. We show that the waiting time distributions exhibit power law tails, and we were able to model the distribution with a continuous time random walk.

Neonatal line width in deciduous incisors from Neolithic, mediaeval and modern skeletal samples from north-central Poland.

PubMed

Kurek, Marta; Żądzińska, Elżbieta; Sitek, Aneta; Borowska-Strugińska, Beata; Rosset, Iwona; Lorkiewicz, Wiesław

2016-01-01

The neonatal line is usually the first accentuated incremental line visible on the enamel. The prenatal environment significantly contributes to the width of the neonatal line, influencing the pace of reaching post-delivery homeostasis by the newborn's organism. Studies of the enamel of the earliest developing deciduous teeth can provide an insight into the prenatal development and the perinatal conditions of children of past human populations, thus being an additional source contributing to consideration of the influence of prenatal and perinatal factors modifying growth processes. The aim of this study was to examine whether the neonatal line, reflecting the conditions of the prenatal and perinatal environment, differed between the Neolithic, the mediaeval and the modern populations from the Kujawy region in north-central Poland. The material consisted of longitudinally ground sections of 57 human deciduous incisors obtained from children aged 1.0-7.5 years representing three archaeological series from Brześć Kujawski site. All teeth were sectioned in the labio-linqual plane using a diamond blade (Buechler IsoMet 1000). Final specimens were observed with the microscope Delta Optical Evolution 300 at 10× and 40× magnifications. For each tooth, linear measurements of the neonatal line width were performed on its labial surface at the three levels from the cemento-enamel junction. No significant difference was found in the mean neonatal line width depending on the tooth type and archaeological site, although the thickest neonatal line characterised children from the Neolithic series. In all analysed series, the neonatal line width was diversified depending on the child's age at death. The value of Spearman's rank correlation coefficient calculated for the correlation between the child's age at death and the neonatal line width was statistically significant. A clear increase in the width of the neonatal line was thus observed along with a decrease in the child

Robots as Imagined in the Television Series Humans.

PubMed

Wicclair, Mark R

2018-07-01

Humans is a science fiction television series set in what appears to be present-day London. What makes it science fiction is that in London and worldwide, there are robots that look like humans and can mimic human behavior. The series raises several important ethical and philosophical questions about artificial intelligence and robotics, which should be of interest to bioethicists.

Neural network versus classical time series forecasting models

NASA Astrophysics Data System (ADS)

Nor, Maria Elena; Safuan, Hamizah Mohd; Shab, Noorzehan Fazahiyah Md; Asrul, Mohd; Abdullah, Affendi; Mohamad, Nurul Asmaa Izzati; Lee, Muhammad Hisyam

2017-05-01

Artificial neural network (ANN) has advantage in time series forecasting as it has potential to solve complex forecasting problems. This is because ANN is data driven approach which able to be trained to map past values of a time series. In this study the forecast performance between neural network and classical time series forecasting method namely seasonal autoregressive integrated moving average models was being compared by utilizing gold price data. Moreover, the effect of different data preprocessing on the forecast performance of neural network being examined. The forecast accuracy was evaluated using mean absolute deviation, root mean square error and mean absolute percentage error. It was found that ANN produced the most accurate forecast when Box-Cox transformation was used as data preprocessing.

Implicit Wiener series analysis of epileptic seizure recordings.

PubMed

Barbero, Alvaro; Franz, Matthias; van Drongelen, Wim; Dorronsoro, José R; Schölkopf, Bernhard; Grosse-Wentrup, Moritz

2009-01-01

Implicit Wiener series are a powerful tool to build Volterra representations of time series with any degree of non-linearity. A natural question is then whether higher order representations yield more useful models. In this work we shall study this question for ECoG data channel relationships in epileptic seizure recordings, considering whether quadratic representations yield more accurate classifiers than linear ones. To do so we first show how to derive statistical information on the Volterra coefficient distribution and how to construct seizure classification patterns over that information. As our results illustrate, a quadratic model seems to provide no advantages over a linear one. Nevertheless, we shall also show that the interpretability of the implicit Wiener series provides insights into the inter-channel relationships of the recordings.

Delay differential analysis of time series.

PubMed

Lainscsek, Claudia; Sejnowski, Terrence J

2015-03-01

Nonlinear dynamical system analysis based on embedding theory has been used for modeling and prediction, but it also has applications to signal detection and classification of time series. An embedding creates a multidimensional geometrical object from a single time series. Traditionally either delay or derivative embeddings have been used. The delay embedding is composed of delayed versions of the signal, and the derivative embedding is composed of successive derivatives of the signal. The delay embedding has been extended to nonuniform embeddings to take multiple timescales into account. Both embeddings provide information on the underlying dynamical system without having direct access to all the system variables. Delay differential analysis is based on functional embeddings, a combination of the derivative embedding with nonuniform delay embeddings. Small delay differential equation (DDE) models that best represent relevant dynamic features of time series data are selected from a pool of candidate models for detection or classification. We show that the properties of DDEs support spectral analysis in the time domain where nonlinear correlation functions are used to detect frequencies, frequency and phase couplings, and bispectra. These can be efficiently computed with short time windows and are robust to noise. For frequency analysis, this framework is a multivariate extension of discrete Fourier transform (DFT), and for higher-order spectra, it is a linear and multivariate alternative to multidimensional fast Fourier transform of multidimensional correlations. This method can be applied to short or sparse time series and can be extended to cross-trial and cross-channel spectra if multiple short data segments of the same experiment are available. Together, this time-domain toolbox provides higher temporal resolution, increased frequency and phase coupling information, and it allows an easy and straightforward implementation of higher-order spectra across time

FALSE DETERMINATIONS OF CHAOS IN SHORT NOISY TIME SERIES. (R828745)

EPA Science Inventory

A method (NEMG) proposed in 1992 for diagnosing chaos in noisy time series with 50 or fewer observations entails fitting the time series with an empirical function which predicts an observation in the series from previous observations, and then estimating the rate of divergenc...

Power Laws, Scale Invariance and the Generalized Frobenius Series:

NASA Astrophysics Data System (ADS)

Visser, Matt; Yunes, Nicolas

We present a self-contained formalism for calculating the background solution, the linearized solutions and a class of generalized Frobenius-like solutions to a system of scale-invariant differential equations. We first cast the scale-invariant model into its equidimensional and autonomous forms, find its fixed points, and then obtain power-law background solutions. After linearizing about these fixed points, we find a second linearized solution, which provides a distinct collection of power laws characterizing the deviations from the fixed point. We prove that generically there will be a region surrounding the fixed point in which the complete general solution can be represented as a generalized Frobenius-like power series with exponents that are integer multiples of the exponents arising in the linearized problem. While discussions of the linearized system are common, and one can often find a discussion of power-series with integer exponents, power series with irrational (indeed complex) exponents are much rarer in the extant literature. The Frobenius-like series we encounter can be viewed as a variant of the rarely-discussed Liapunov expansion theorem (not to be confused with the more commonly encountered Liapunov functions and Liapunov exponents). As specific examples we apply these ideas to Newtonian and relativistic isothermal stars and construct two separate power series with the overlapping radius of convergence. The second of these power series solutions represents an expansion around "spatial infinity," and in realistic models it is this second power series that gives information about the stellar core, and the damped oscillations in core mass and core radius as the central pressure goes to infinity. The power-series solutions we obtain extend classical results; as exemplified for instance by the work of Lane, Emden, and Chandrasekhar in the Newtonian case, and that of Harrison, Thorne, Wakano, and Wheeler in the relativistic case. We also indicate how to

Signatures of ecological processes in microbial community time series.

PubMed

Faust, Karoline; Bauchinger, Franziska; Laroche, Béatrice; de Buyl, Sophie; Lahti, Leo; Washburne, Alex D; Gonze, Didier; Widder, Stefanie

2018-06-28

Growth rates, interactions between community members, stochasticity, and immigration are important drivers of microbial community dynamics. In sequencing data analysis, such as network construction and community model parameterization, we make implicit assumptions about the nature of these drivers and thereby restrict model outcome. Despite apparent risk of methodological bias, the validity of the assumptions is rarely tested, as comprehensive procedures are lacking. Here, we propose a classification scheme to determine the processes that gave rise to the observed time series and to enable better model selection. We implemented a three-step classification scheme in R that first determines whether dependence between successive time steps (temporal structure) is present in the time series and then assesses with a recently developed neutrality test whether interactions between species are required for the dynamics. If the first and second tests confirm the presence of temporal structure and interactions, then parameters for interaction models are estimated. To quantify the importance of temporal structure, we compute the noise-type profile of the community, which ranges from black in case of strong dependency to white in the absence of any dependency. We applied this scheme to simulated time series generated with the Dirichlet-multinomial (DM) distribution, Hubbell's neutral model, the generalized Lotka-Volterra model and its discrete variant (the Ricker model), and a self-organized instability model, as well as to human stool microbiota time series. The noise-type profiles for all but DM data clearly indicated distinctive structures. The neutrality test correctly classified all but DM and neutral time series as non-neutral. The procedure reliably identified time series for which interaction inference was suitable. Both tests were required, as we demonstrated that all structured time series, including those generated with the neutral model, achieved a moderate to high

A Comparative Analysis of Vocabulary Load of Three Provincially Adopted Primary Arithmetic Series.

ERIC Educational Resources Information Center

Horodezky, Betty; Weinstein, Pauline Smith

1981-01-01

Results indicated considerable difference in total number of running words among series; an increase in different words for grades two-three in each series; repetition of most words in each series between one and nine times; and no high degree of word overlap between series or grades in any given series. (Author/CM)

Evolution of the Sunspot Number and Solar Wind B Time Series

NASA Astrophysics Data System (ADS)

Cliver, Edward W.; Herbst, Konstantin

2018-03-01

The past two decades have witnessed significant changes in our knowledge of long-term solar and solar wind activity. The sunspot number time series (1700-present) developed by Rudolf Wolf during the second half of the 19th century was revised and extended by the group sunspot number series (1610-1995) of Hoyt and Schatten during the 1990s. The group sunspot number is significantly lower than the Wolf series before ˜1885. An effort from 2011-2015 to understand and remove differences between these two series via a series of workshops had the unintended consequence of prompting several alternative constructions of the sunspot number. Thus it has been necessary to expand and extend the sunspot number reconciliation process. On the solar wind side, after a decade of controversy, an ISSI International Team used geomagnetic and sunspot data to obtain a high-confidence time series of the solar wind magnetic field strength (B) from 1750-present that can be compared with two independent long-term (> ˜600 year) series of annual B-values based on cosmogenic nuclides. In this paper, we trace the twists and turns leading to our current understanding of long-term solar and solar wind activity.

Drunk driving detection based on classification of multivariate time series.

PubMed

Li, Zhenlong; Jin, Xue; Zhao, Xiaohua

2015-09-01

This paper addresses the problem of detecting drunk driving based on classification of multivariate time series. First, driving performance measures were collected from a test in a driving simulator located in the Traffic Research Center, Beijing University of Technology. Lateral position and steering angle were used to detect drunk driving. Second, multivariate time series analysis was performed to extract the features. A piecewise linear representation was used to represent multivariate time series. A bottom-up algorithm was then employed to separate multivariate time series. The slope and time interval of each segment were extracted as the features for classification. Third, a support vector machine classifier was used to classify driver's state into two classes (normal or drunk) according to the extracted features. The proposed approach achieved an accuracy of 80.0%. Drunk driving detection based on the analysis of multivariate time series is feasible and effective. The approach has implications for drunk driving detection. Copyright © 2015 Elsevier Ltd and National Safety Council. All rights reserved.

False-nearest-neighbors algorithm and noise-corrupted time series

NASA Astrophysics Data System (ADS)

Rhodes, Carl; Morari, Manfred

1997-05-01

The false-nearest-neighbors (FNN) algorithm was originally developed to determine the embedding dimension for autonomous time series. For noise-free computer-generated time series, the algorithm does a good job in predicting the embedding dimension. However, the problem of predicting the embedding dimension when the time-series data are corrupted by noise was not fully examined in the original studies of the FNN algorithm. Here it is shown that with large data sets, even small amounts of noise can lead to incorrect prediction of the embedding dimension. Surprisingly, as the length of the time series analyzed by FNN grows larger, the cause of incorrect prediction becomes more pronounced. An analysis of the effect of noise on the FNN algorithm and a solution for dealing with the effects of noise are given here. Some results on the theoretically correct choice of the FNN threshold are also presented.

Mars Sample Handling Protocol Workshop Series

NASA Technical Reports Server (NTRS)

Race, Margaret S. (Editor); Nealson, Kenneth H.; Rummel, John D. (Editor); Acevedo, Sara E. (Editor); Devincenzi, Donald L. (Technical Monitor)

2001-01-01

This report provides a record of the proceedings and recommendations of Workshop 3 of the Series, which was held in San Diego, California, March 19-21, 2001. Materials such as the Workshop agenda and participant lists as well as complete citations of all references and a glossary of terms and acronyms appear in the Appendices. Workshop 3 builds on the deliberations and findings of the earlier workshops in the Series, which have been reported separately. During Workshop 3, five individual sub-groups were formed to discuss the following topics: (1) Unifying Properties of Life, (2) Morphological organization and chemical properties, (3) Geochemical and geophysical properties, (4) Chemical Method and (5) Cell Biology Methods.

miniSEED: The Backbone Data Format for Seismological Time Series

NASA Astrophysics Data System (ADS)

Ahern, T. K.; Benson, R. B.; Trabant, C. M.

2017-12-01

In 1987, the International Federation of Digital Seismograph Networks (FDSN), adopted the Standard for the Exchange of Earthquake Data (SEED) format to be used for data archiving and exchange of seismological time series data. Since that time, the format has evolved to accommodate new capabilities and features. For example, a notable change in 1992 allowed the format, which includes both the comprehensive metadata and the time series samples, to be used in two additional forms: a container for metadata only called "dataless SEED", and 2) a stand-alone structure for time series called "miniSEED". While specifically designed for seismological data and related metadata, this format has proven to be a useful format for a wide variety of geophysical time series data. Many FDSN data centers now store temperature, pressure, infrasound, tilt and other time series measurements in this internationally used format. Since April 2016, members of the FDSN have been in discussions to design a next generation miniSEED format to accommodate current and future needs, to further generalize the format, and to address a number of historical problems or limitations. We believe the correct approach is to simplify the header, allow for arbitrary header additions, expand the current identifiers, and allow for anticipated future identifiers which are currently unknown. We also believe the primary goal of the format is for efficient archiving, selection and exchange of time series data. By focusing on these goals we avoid trying to generalize the format too broadly into specialized areas such as efficient, low-latency delivery, or including unbounded non-time series data. Our presentation will provide an overview of this format and highlight its most valuable characteristics for time series data from any geophysical domain or beyond.

Satellite Emission Range Inferred Earth Survey (SERIES) project

NASA Technical Reports Server (NTRS)

Buennagel, L. A.; Macdoran, P. F.; Neilan, R. E.; Spitzmesser, D. J.; Young, L. E.

1984-01-01

The Global Positioning System (GPS) was developed by the Department of Defense primarily for navigation use by the United States Armed Forces. The system will consist of a constellation of 18 operational Navigation Satellite Timing and Ranging (NAVSTAR) satellites by the late 1980's. During the last four years, the Satellite Emission Range Inferred Earth Surveying (SERIES) team at the Jet Propulsion Laboratory (JPL) has developed a novel receiver which is the heart of the SERIES geodetic system designed to use signals broadcast from the GPS. This receiver does not require knowledge of the exact code sequence being transmitted. In addition, when two SERIES receivers are used differentially to determine a baseline, few cm accuracies can be obtained. The initial engineering test phase has been completed for the SERIES Project. Baseline lengths, ranging from 150 meters to 171 kilometers, have been measured with 0.3 cm to 7 cm accuracies. This technology, which is sponsored by the NASA Geodynamics Program, has been developed at JPL to meet the challenge for high precision, cost-effective geodesy, and to complement the mobile Very Long Baseline Interferometry (VLBI) system for Earth surveying.

Online Conditional Outlier Detection in Nonstationary Time Series

PubMed Central

Liu, Siqi; Wright, Adam; Hauskrecht, Milos

2017-01-01

The objective of this work is to develop methods for detecting outliers in time series data. Such methods can become the key component of various monitoring and alerting systems, where an outlier may be equal to some adverse condition that needs human attention. However, real-world time series are often affected by various sources of variability present in the environment that may influence the quality of detection; they may (1) explain some of the changes in the signal that would otherwise lead to false positive detections, as well as, (2) reduce the sensitivity of the detection algorithm leading to increase in false negatives. To alleviate these problems, we propose a new two-layer outlier detection approach that first tries to model and account for the nonstationarity and periodic variation in the time series, and then tries to use other observable variables in the environment to explain any additional signal variation. Our experiments on several data sets in different domains show that our method provides more accurate modeling of the time series, and that it is able to significantly improve outlier detection performance. PMID:29644345

Quantifying Selection with Pool-Seq Time Series Data.

PubMed

Taus, Thomas; Futschik, Andreas; Schlötterer, Christian

2017-11-01

Allele frequency time series data constitute a powerful resource for unraveling mechanisms of adaptation, because the temporal dimension captures important information about evolutionary forces. In particular, Evolve and Resequence (E&R), the whole-genome sequencing of replicated experimentally evolving populations, is becoming increasingly popular. Based on computer simulations several studies proposed experimental parameters to optimize the identification of the selection targets. No such recommendations are available for the underlying parameters selection strength and dominance. Here, we introduce a highly accurate method to estimate selection parameters from replicated time series data, which is fast enough to be applied on a genome scale. Using this new method, we evaluate how experimental parameters can be optimized to obtain the most reliable estimates for selection parameters. We show that the effective population size (Ne) and the number of replicates have the largest impact. Because the number of time points and sequencing coverage had only a minor effect, we suggest that time series analysis is feasible without major increase in sequencing costs. We anticipate that time series analysis will become routine in E&R studies. © The Author 2017. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

Series Bosch System Development

NASA Technical Reports Server (NTRS)

Abney, Morgan B.; Evans, Christopher; Mansell, Matt; Swickrath, Michael

2012-01-01

State-of-the-art (SOA) carbon dioxide (CO2) reduction technology for the International Space Station produces methane as a byproduct. This methane is subsequently vented overboard. The associated loss of hydrogen ultimately reduces the mass of oxygen that can be recovered from CO2 in a closed-loop life support system. As an alternative to SOA CO2 reduction technology, NASA is exploring a Series-Bosch system capable of reducing CO2 with hydrogen to form water and solid carbon. This results in 100% theoretical recovery of oxygen from metabolic CO2. In the past, Bosch-based technology did not trade favorably against SOA technology due to a high power demand, low reaction efficiencies, concerns with carbon containment, and large resupply requirements necessary to replace expended catalyst cartridges. An alternative approach to Bosch technology, labeled "Series-Bosch," employs a new system design with optimized multi-stage reactors and a membrane-based separation and recycle capability. Multi-physics modeling of the first stage reactor, along with chemical process modeling of the integrated system, has resulted in a design with potential to trade significantly better than previous Bosch technology. The modeling process and resulting system architecture selection are discussed.

Uranium series, volcanic rocks

USGS Publications Warehouse

Vazquez, Jorge A.

2014-01-01

Application of U-series dating to volcanic rocks provides unique and valuable information about the absolute timing of crystallization and differentiation of magmas prior to eruption. The 238U–230Th and 230Th-226Ra methods are the most commonly employed for dating the crystallization of mafic to silicic magmas that erupt at volcanoes. Dates derived from the U–Th and Ra–Th methods reflect crystallization because diffusion of these elements at magmatic temperatures is sluggish (Cherniak 2010) and diffusive re-equilibration is insignificant over the timescales (less than or equal to 10^5 years) typically associated with pre-eruptive storage of nearly all magma compositions (Cooper and Reid 2008). Other dating methods based on elements that diffuse rapidly at magmatic temperatures, such as the 40Ar/39Ar and (U–Th)/He methods, yield dates for the cooling of magma at the time of eruption. Disequilibrium of some short-lived daughters of the uranium series such as 210Po may be fractionated by saturation of a volatile phase and can be employed to date magmatic gas loss that is synchronous with volcanic eruption (e.g., Rubin et al. 1994).

Fuzzy time-series based on Fibonacci sequence for stock price forecasting

NASA Astrophysics Data System (ADS)

Chen, Tai-Liang; Cheng, Ching-Hsue; Jong Teoh, Hia

2007-07-01

Time-series models have been utilized to make reasonably accurate predictions in the areas of stock price movements, academic enrollments, weather, etc. For promoting the forecasting performance of fuzzy time-series models, this paper proposes a new model, which incorporates the concept of the Fibonacci sequence, the framework of Song and Chissom's model and the weighted method of Yu's model. This paper employs a 5-year period TSMC (Taiwan Semiconductor Manufacturing Company) stock price data and a 13-year period of TAIEX (Taiwan Stock Exchange Capitalization Weighted Stock Index) stock index data as experimental datasets. By comparing our forecasting performances with Chen's (Forecasting enrollments based on fuzzy time-series. Fuzzy Sets Syst. 81 (1996) 311-319), Yu's (Weighted fuzzy time-series models for TAIEX forecasting. Physica A 349 (2004) 609-624) and Huarng's (The application of neural networks to forecast fuzzy time series. Physica A 336 (2006) 481-491) models, we conclude that the proposed model surpasses in accuracy these conventional fuzzy time-series models.

A more general system for Poisson series manipulation.

NASA Technical Reports Server (NTRS)

Cherniack, J. R.

1973-01-01

The design of a working Poisson series processor system is described that is more general than those currently in use. This system is the result of a series of compromises among efficiency, generality, ease of programing, and ease of use. The most general form of coefficients that can be multiplied efficiently is pointed out, and the place of general-purpose algebraic systems in celestial mechanics is discussed.

Characterizing time series: when Granger causality triggers complex networks

NASA Astrophysics Data System (ADS)

Ge, Tian; Cui, Yindong; Lin, Wei; Kurths, Jürgen; Liu, Chong

2012-08-01

In this paper, we propose a new approach to characterize time series with noise perturbations in both the time and frequency domains by combining Granger causality and complex networks. We construct directed and weighted complex networks from time series and use representative network measures to describe their physical and topological properties. Through analyzing the typical dynamical behaviors of some physical models and the MIT-BIHMassachusetts Institute of Technology-Beth Israel Hospital. human electrocardiogram data sets, we show that the proposed approach is able to capture and characterize various dynamics and has much potential for analyzing real-world time series of rather short length.

Time series analysis of InSAR data: Methods and trends

NASA Astrophysics Data System (ADS)

Osmanoğlu, Batuhan; Sunar, Filiz; Wdowinski, Shimon; Cabral-Cano, Enrique

2016-05-01

Time series analysis of InSAR data has emerged as an important tool for monitoring and measuring the displacement of the Earth's surface. Changes in the Earth's surface can result from a wide range of phenomena such as earthquakes, volcanoes, landslides, variations in ground water levels, and changes in wetland water levels. Time series analysis is applied to interferometric phase measurements, which wrap around when the observed motion is larger than one-half of the radar wavelength. Thus, the spatio-temporal ;unwrapping; of phase observations is necessary to obtain physically meaningful results. Several different algorithms have been developed for time series analysis of InSAR data to solve for this ambiguity. These algorithms may employ different models for time series analysis, but they all generate a first-order deformation rate, which can be compared to each other. However, there is no single algorithm that can provide optimal results in all cases. Since time series analyses of InSAR data are used in a variety of applications with different characteristics, each algorithm possesses inherently unique strengths and weaknesses. In this review article, following a brief overview of InSAR technology, we discuss several algorithms developed for time series analysis of InSAR data using an example set of results for measuring subsidence rates in Mexico City.

Rotation in the Dynamic Factor Modeling of Multivariate Stationary Time Series.

ERIC Educational Resources Information Center

Molenaar, Peter C. M.; Nesselroade, John R.

2001-01-01

Proposes a special rotation procedure for the exploratory dynamic factor model for stationary multivariate time series. The rotation procedure applies separately to each univariate component series of a q-variate latent factor series and transforms such a component, initially represented as white noise, into a univariate moving-average.…

Quebec. Reference Series No. 30.

ERIC Educational Resources Information Center

Department of External Affairs, Ottawa (Ontario).

This booklet, one of a series featuring the Canadian provinces, presents a brief overview of Quebec and is suitable for teacher reference or student reading. Separate sections discuss geography, climate, population, history, political history, recent politics, agriculture, forestry, mining, manufacturing and industry, hydroelectric power,…

Interpretation of a compositional time series

NASA Astrophysics Data System (ADS)

Tolosana-Delgado, R.; van den Boogaart, K. G.

2012-04-01

Common methods for multivariate time series analysis use linear operations, from the definition of a time-lagged covariance/correlation to the prediction of new outcomes. However, when the time series response is a composition (a vector of positive components showing the relative importance of a set of parts in a total, like percentages and proportions), then linear operations are afflicted of several problems. For instance, it has been long recognised that (auto/cross-)correlations between raw percentages are spurious, more dependent on which other components are being considered than on any natural link between the components of interest. Also, a long-term forecast of a composition in models with a linear trend will ultimately predict negative components. In general terms, compositional data should not be treated in a raw scale, but after a log-ratio transformation (Aitchison, 1986: The statistical analysis of compositional data. Chapman and Hill). This is so because the information conveyed by a compositional data is relative, as stated in their definition. The principle of working in coordinates allows to apply any sort of multivariate analysis to a log-ratio transformed composition, as long as this transformation is invertible. This principle is of full application to time series analysis. We will discuss how results (both auto/cross-correlation functions and predictions) can be back-transformed, viewed and interpreted in a meaningful way. One view is to use the exhaustive set of all possible pairwise log-ratios, which allows to express the results into D(D - 1)/2 separate, interpretable sets of one-dimensional models showing the behaviour of each possible pairwise log-ratios. Another view is the interpretation of estimated coefficients or correlations back-transformed in terms of compositions. These two views are compatible and complementary. These issues are illustrated with time series of seasonal precipitation patterns at different rain gauges of the USA

Identification of flood-rich and flood-poor periods in flood series

NASA Astrophysics Data System (ADS)

Mediero, Luis; Santillán, David; Garrote, Luis

2015-04-01

Recently, a general concern about non-stationarity of flood series has arisen, as changes in catchment response can be driven by several factors, such as climatic and land-use changes. Several studies to detect trends in flood series at either national or trans-national scales have been conducted. Trends are usually detected by the Mann-Kendall test. However, the results of this test depend on the starting and ending year of the series, which can lead to different results in terms of the period considered. The results can be conditioned to flood-poor and flood-rich periods located at the beginning or end of the series. A methodology to identify statistically significant flood-rich and flood-poor periods is developed, based on the comparison between the expected sampling variability of floods when stationarity is assumed and the observed variability of floods in a given series. The methodology is applied to a set of long series of annual maximum floods, peaks over threshold and counts of annual occurrences in peaks over threshold series observed in Spain in the period 1942-2009. Mediero et al. (2014) found a general decreasing trend in flood series in some parts of Spain that could be caused by a flood-rich period observed in 1950-1970, placed at the beginning of the flood series. The results of this study support the findings of Mediero et al. (2014), as a flood-rich period in 1950-1970 was identified in most of the selected sites. References: Mediero, L., Santillán, D., Garrote, L., Granados, A. Detection and attribution of trends in magnitude, frequency and timing of floods in Spain, Journal of Hydrology, 517, 1072-1088, 2014.

31 CFR 363.52 - What amount of book-entry Series EE and Series I savings bonds may I purchase in one year?

Code of Federal Regulations, 2010 CFR

2010-07-01

... for Series I savings bonds. (b) Computation of amount for gifts. Bonds purchased or transferred as gifts will be included in the computation of the purchase limitation for the account of the recipient... and Series I savings bonds may I purchase in one year? 363.52 Section 363.52 Money and Finance...

Providing web-based tools for time series access and analysis

NASA Astrophysics Data System (ADS)

Eberle, Jonas; Hüttich, Christian; Schmullius, Christiane

2014-05-01

Time series information is widely used in environmental change analyses and is also an essential information for stakeholders and governmental agencies. However, a challenging issue is the processing of raw data and the execution of time series analysis. In most cases, data has to be found, downloaded, processed and even converted in the correct data format prior to executing time series analysis tools. Data has to be prepared to use it in different existing software packages. Several packages like TIMESAT (Jönnson & Eklundh, 2004) for phenological studies, BFAST (Verbesselt et al., 2010) for breakpoint detection, and GreenBrown (Forkel et al., 2013) for trend calculations are provided as open-source software and can be executed from the command line. This is needed if data pre-processing and time series analysis is being automated. To bring both parts, automated data access and data analysis, together, a web-based system was developed to provide access to satellite based time series data and access to above mentioned analysis tools. Users of the web portal are able to specify a point or a polygon and an available dataset (e.g., Vegetation Indices and Land Surface Temperature datasets from NASA MODIS). The data is then being processed and provided as a time series CSV file. Afterwards the user can select an analysis tool that is being executed on the server. The final data (CSV, plot images, GeoTIFFs) is visualized in the web portal and can be downloaded for further usage. As a first use case, we built up a complimentary web-based system with NASA MODIS products for Germany and parts of Siberia based on the Earth Observation Monitor (www.earth-observation-monitor.net). The aim of this work is to make time series analysis with existing tools as easy as possible that users can focus on the interpretation of the results. References: Jönnson, P. and L. Eklundh (2004). TIMESAT - a program for analysing time-series of satellite sensor data. Computers and Geosciences 30

On a General Class of Trigonometric Functions and Fourier Series

ERIC Educational Resources Information Center

Pavao, H. Germano; Capelas de Oliveira, E.

2008-01-01

We discuss a general class of trigonometric functions whose corresponding Fourier series can be used to calculate several interesting numerical series. Particular cases are presented. (Contains 4 notes.)

Local normalization: Uncovering correlations in non-stationary financial time series

NASA Astrophysics Data System (ADS)

Schäfer, Rudi; Guhr, Thomas

2010-09-01

The measurement of correlations between financial time series is of vital importance for risk management. In this paper we address an estimation error that stems from the non-stationarity of the time series. We put forward a method to rid the time series of local trends and variable volatility, while preserving cross-correlations. We test this method in a Monte Carlo simulation, and apply it to empirical data for the S&P 500 stocks.

TechEdSat Nano-Satellite Series Fact Sheet

NASA Technical Reports Server (NTRS)

Murbach, Marcus; Martinez, Andres; Guarneros Luna, Ali

2014-01-01

TechEdSat-3p is the second generation in the TechEdSat-X series. The TechEdSat Series uses the CubeSat standards established by the California Polytechnic State University Cal Poly), San Luis Obispo. With typical blocks being constructed from 1-unit (1U 10x10x10 cm) increments, the TechEdSat-3p has a 3U volume with a 30 cm length. The project uniquely pairs advanced university students with NASA researchers in a rapid design-to-flight experience lasting 1-2 semesters.The TechEdSat Nano-Satellite Series provides a rapid platform for testing technologies for future NASA Earth and planetary missions, as well as providing students with an early exposure to flight hardware development and management.

Using SAR satellite data time series for regional glacier mapping

NASA Astrophysics Data System (ADS)

Winsvold, Solveig H.; Kääb, Andreas; Nuth, Christopher; Andreassen, Liss M.; van Pelt, Ward J. J.; Schellenberger, Thomas

2018-03-01

With dense SAR satellite data time series it is possible to map surface and subsurface glacier properties that vary in time. On Sentinel-1A and RADARSAT-2 backscatter time series images over mainland Norway and Svalbard, we outline how to map glaciers using descriptive methods. We present five application scenarios. The first shows potential for tracking transient snow lines with SAR backscatter time series and correlates with both optical satellite images (Sentinel-2A and Landsat 8) and equilibrium line altitudes derived from in situ surface mass balance data. In the second application scenario, time series representation of glacier facies corresponding to SAR glacier zones shows potential for a more accurate delineation of the zones and how they change in time. The third application scenario investigates the firn evolution using dense SAR backscatter time series together with a coupled energy balance and multilayer firn model. We find strong correlation between backscatter signals with both the modeled firn air content and modeled wetness in the firn. In the fourth application scenario, we highlight how winter rain events can be detected in SAR time series, revealing important information about the area extent of internal accumulation. In the last application scenario, averaged summer SAR images were found to have potential in assisting the process of mapping glaciers outlines, especially in the presence of seasonal snow. Altogether we present examples of how to map glaciers and to further understand glaciological processes using the existing and future massive amount of multi-sensor time series data.

Using Time-Series Regression to Predict Academic Library Circulations.

ERIC Educational Resources Information Center

Brooks, Terrence A.

1984-01-01

Four methods were used to forecast monthly circulation totals in 15 midwestern academic libraries: dummy time-series regression, lagged time-series regression, simple average (straight-line forecasting), monthly average (naive forecasting). In tests of forecasting accuracy, dummy regression method and monthly mean method exhibited smallest average…

Fundamentals of Construction. Introduction to Construction Series. Instructor Edition.

ERIC Educational Resources Information Center

Oklahoma State Dept. of Vocational and Technical Education, Stillwater. Curriculum and Instructional Materials Center.

This competency-based curriculum guide begins the Introduction to Construction series. The series is designed with the flexible training requirements of open shop contractors, preapprenticeship programs, multicraft high school programs, technology education programs, and cooperative education programs in mind. This guide contains 3 sections and 15…

Introduction to Carpentry. Introduction to Construction Series. Instructor Edition.

ERIC Educational Resources Information Center

Oklahoma State Dept. of Vocational and Technical Education, Stillwater. Curriculum and Instructional Materials Center.

This competency-based curriculum guide on the specialty area of carpentry is part of the Introduction to Construction series. The series is designed with the flexible training requirements of open shop contractors, preapprenticeship programs, multicraft high school programs, technology education programs, and cooperative education programs in…

Introduction to Bricklaying. Introduction to Construction Series. Instructor Edition.

ERIC Educational Resources Information Center

Oklahoma State Dept. of Vocational and Technical Education, Stillwater. Curriculum and Instructional Materials Center.

This competency-based curriculum guide on the specialty area of bricklaying is part of the Introduction to Construction series. The series is designed with the flexible training requirements of open shop contractors, preapprenticeship programs, multicraft high school programs, technology education programs, and cooperative education programs in…

Cold War: Talking with the Producers of the New Documentary Series.

ERIC Educational Resources Information Center

Social Education, 1998

1998-01-01

Highlights the Cable News Network's (CNN) documentary series "The Cold War." Interviews executive producer Jeremy Issacs and producer Martin Smith about the series and its usefulness for educators. Includes a broadcast schedule for the 24 episodes. Notes that the series is endorsed by the National Council for the Social Studies. (DSK)

Relating the large-scale structure of time series and visibility networks.

PubMed

Rodríguez, Miguel A

2017-06-01

The structure of time series is usually characterized by means of correlations. A new proposal based on visibility networks has been considered recently. Visibility networks are complex networks mapped from surfaces or time series using visibility properties. The structures of time series and visibility networks are closely related, as shown by means of fractional time series in recent works. In these works, a simple relationship between the Hurst exponent H of fractional time series and the exponent of the distribution of edges γ of the corresponding visibility network, which exhibits a power law, is shown. To check and generalize these results, in this paper we delve into this idea of connected structures by defining both structures more properly. In addition to the exponents used before, H and γ, which take into account local properties, we consider two more exponents that, as we will show, characterize global properties. These are the exponent α for time series, which gives the scaling of the variance with the size as var∼T^{2α}, and the exponent κ of their corresponding network, which gives the scaling of the averaged maximum of the number of edges, 〈k_{M}〉∼N^{κ}. With this representation, a more precise connection between the structures of general time series and their associated visibility network is achieved. Similarities and differences are more clearly established, and new scaling forms of complex networks appear in agreement with their respective classes of time series.

31 CFR 359.6 - When may I redeem my Series I bond?

Code of Federal Regulations, 2013 CFR

2013-07-01

... thereafter. You may redeem your Series I savings bond issued on February 1, 2003, or thereafter, at any time... 31 Money and Finance:Treasury 2 2013-07-01 2013-07-01 false When may I redeem my Series I bond... BONDS, SERIES I General Information § 359.6 When may I redeem my Series I bond? (a) Bonds issued on...

31 CFR 359.6 - When may I redeem my Series I bond?

Code of Federal Regulations, 2014 CFR

2014-07-01

... thereafter. You may redeem your Series I savings bond issued on February 1, 2003, or thereafter, at any time... 31 Money and Finance: Treasury 2 2014-07-01 2014-07-01 false When may I redeem my Series I bond... BONDS, SERIES I General Information § 359.6 When may I redeem my Series I bond? (a) Bonds issued on...

31 CFR 359.6 - When may I redeem my Series I bond?

Code of Federal Regulations, 2012 CFR

2012-07-01

... thereafter. You may redeem your Series I savings bond issued on February 1, 2003, or thereafter, at any time... 31 Money and Finance:Treasury 2 2012-07-01 2012-07-01 false When may I redeem my Series I bond... BONDS, SERIES I General Information § 359.6 When may I redeem my Series I bond? (a) Bonds issued on...

31 CFR 359.6 - When may I redeem my Series I bond?

Code of Federal Regulations, 2010 CFR

2010-07-01

... thereafter. You may redeem your Series I savings bond issued on February 1, 2003, or thereafter, at any time... 31 Money and Finance: Treasury 2 2010-07-01 2010-07-01 false When may I redeem my Series I bond... BONDS, SERIES I General Information § 359.6 When may I redeem my Series I bond? (a) Bonds issued on...

31 CFR 359.6 - When may I redeem my Series I bond?

Code of Federal Regulations, 2011 CFR

2011-07-01

... thereafter. You may redeem your Series I savings bond issued on February 1, 2003, or thereafter, at any time... 31 Money and Finance:Treasury 2 2011-07-01 2011-07-01 false When may I redeem my Series I bond... BONDS, SERIES I General Information § 359.6 When may I redeem my Series I bond? (a) Bonds issued on...

Evaluation of age-related changes with cross-sectional CT imaging of teeth

NASA Astrophysics Data System (ADS)

Fukui, Tatsumasa; Kita, Kanade; Kamemoto, Hiromasa; Nishiyama, Wataru; Yoshida, Hiroyasu; Iida, Yukihiro; Katsumata, Akitoshi; Muramatsu, Chisako; Fujita, Hiroshi

2017-03-01

Tooth pulp atrophy occurs with increasing age. An age estimation procedure using dental cone beam computed tomography (CBCT) imaging was developed. Clinical dental CBCT images of 60 patients (aged from 20 to 80 years) were evaluated. The ratio of the cross-sectional area of the pulp cavity to the cross-sectional area of the tooth (pulp cavity ratio) was calculated. The pulp cavity ratio in the labio-lingual plane of the mandibular anterior teeth and the mesio-distal plane of the maxillary anterior teeth was strongly correlated with the patients' age. The pulp cavity ratio of anterior teeth may be a useful parameter for estimating age.

Alberta. Reference Series No. 26.

ERIC Educational Resources Information Center

Department of External Affairs, Ottawa (Ontario).

This booklet, one of a series featuring the Canadian provinces, presents a brief overview of Alberta and is suitable for teacher reference or student reading. Separate sections discuss the history and population, the provincial government, the economy, transportation, communications, mineral resources, agriculture, manufacturing, forest products,…

Manitoba. Reference Series No. 28.

ERIC Educational Resources Information Center

Department of External Affairs, Ottawa (Ontario).

This booklet, one of a series featuring the Canadian provinces, presents a brief overview of Manitoba and is suitable for teacher reference or student reading. Separate sections discuss agriculture, mining, energy, transportation and communication, fishing, forestry, fur trapping, health and social services, education, and political life. Specific…

Ontario. Reference Series No. 29.

ERIC Educational Resources Information Center

Department of External Affairs, Ottawa (Ontario).

This booklet, one of a series featuring the Canadian provinces, presents a brief overview of Ontario and is suitable for teacher reference or student reading. Separate sections discuss geography, climate, history, agriculture, forestry, fishing, mining, manufacturing, transportation, energy, arts and culture, sports and recreation, and people and…

A proposal to create an extension to the European baseline series.

PubMed

Wilkinson, Mark; Gallo, Rosella; Goossens, An; Johansen, Jeanne D; Rustemeyer, Thomas; Sánchez-Pérez, Javier; Schuttelaar, Marie L; Uter, Wolfgang

2018-02-01

The current European baseline series consists of 30 allergens, and was last updated in 2015. To use data from the European Surveillance System on Contact Allergies (ESSCA) to propose an extension to the European baseline series in response to changes in environmental exposures. Data from departmental and national extensions to the baseline series, together with some temporary additions from departments contributing to the ESSCA, were collated during 2013-2014. In total, 31689 patients were patch tested in 46 European departments. Many departments and national groups already consider the current European baseline series to be a suboptimal screen, and use their own extensions to it. The haptens tested are heterogeneous, although there are some consistent themes. Potential haptens to include in an extension to the European baseline series comprise sodium metabisulfite, formaldehyde-releasing preservatives, additional markers of fragrance allergy, propolis, Compositae mix, and 2-hydroxyethyl methacrylate. In combination with other published work from the ESSCA, changes to the current European baseline series are proposed for discussion. As well as addition of the allergens listed above, it is suggested that primin and clioquinol should be deleted from the series, owing to reduced environmental exposure. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

DIY Solar Market Analysis Webinar Series: Top Solar Tools | State, Local,

Science.gov Websites

and Tribal Governments | NREL DIY Solar Market Analysis Webinar Series: Top Solar Tools DIY Solar Market Analysis Webinar Series: Top Solar Tools Wednesday, May 14, 2014 As part of a Do-It -Yourself Solar Market Analysis summer series, NREL's Solar Technical Assistance Team (STAT) presented a

Sub- and Quasi-Centurial Cycles in Solar and Geomagnetic Activity Data Series

NASA Astrophysics Data System (ADS)

Komitov, B.; Sello, S.; Duchlev, P.; Dechev, M.; Penev, K.; Koleva, K.

2016-07-01

The subject of this paper is the existence and stability of solar cycles with durations in the range of 20-250 years. Five types of data series are used: 1) the Zurich series (1749-2009 AD), the mean annual International sunspot number Ri, 2) the Group sunspot number series Rh (1610-1995 AD), 3) the simulated extended sunspot number from Extended time series of Solar Activity Indices (ESAI) (1090-2002 AD), 4) the simulated extended geomagnetic aa-index from ESAI (1099-2002 AD), 5) the Meudon filament series (1919-1991 AD). Two principally independent methods of time series analysis are used: the T-R periodogram analysis (both in standard and ``scanning window'' regimes) and the wavelet-analysis. The obtained results are very similar. A strong cycle with a mean duration of 55-60 years is found to exist in all series. On the other hand, a strong and stable quasi 110-120 years and ˜200-year cycles are obtained in all of these series except in the Ri one. The high importance of the long term solar activity dynamics for the aims of solar dynamo modeling and predictions is especially noted.

Scalable Prediction of Energy Consumption using Incremental Time Series Clustering

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

Simmhan, Yogesh; Noor, Muhammad Usman

2013-10-09

Time series datasets are a canonical form of high velocity Big Data, and often generated by pervasive sensors, such as found in smart infrastructure. Performing predictive analytics on time series data can be computationally complex, and requires approximation techniques. In this paper, we motivate this problem using a real application from the smart grid domain. We propose an incremental clustering technique, along with a novel affinity score for determining cluster similarity, which help reduce the prediction error for cumulative time series within a cluster. We evaluate this technique, along with optimizations, using real datasets from smart meters, totaling ~700,000 datamore » points, and show the efficacy of our techniques in improving the prediction error of time series data within polynomial time.« less

Symplectic geometry spectrum regression for prediction of noisy time series

NASA Astrophysics Data System (ADS)

Xie, Hong-Bo; Dokos, Socrates; Sivakumar, Bellie; Mengersen, Kerrie

2016-05-01

We present the symplectic geometry spectrum regression (SGSR) technique as well as a regularized method based on SGSR for prediction of nonlinear time series. The main tool of analysis is the symplectic geometry spectrum analysis, which decomposes a time series into the sum of a small number of independent and interpretable components. The key to successful regularization is to damp higher order symplectic geometry spectrum components. The effectiveness of SGSR and its superiority over local approximation using ordinary least squares are demonstrated through prediction of two noisy synthetic chaotic time series (Lorenz and Rössler series), and then tested for prediction of three real-world data sets (Mississippi River flow data and electromyographic and mechanomyographic signal recorded from human body).

CauseMap: fast inference of causality from complex time series.

PubMed

Maher, M Cyrus; Hernandez, Ryan D

2015-01-01

Background. Establishing health-related causal relationships is a central pursuit in biomedical research. Yet, the interdependent non-linearity of biological systems renders causal dynamics laborious and at times impractical to disentangle. This pursuit is further impeded by the dearth of time series that are sufficiently long to observe and understand recurrent patterns of flux. However, as data generation costs plummet and technologies like wearable devices democratize data collection, we anticipate a coming surge in the availability of biomedically-relevant time series data. Given the life-saving potential of these burgeoning resources, it is critical to invest in the development of open source software tools that are capable of drawing meaningful insight from vast amounts of time series data. Results. Here we present CauseMap, the first open source implementation of convergent cross mapping (CCM), a method for establishing causality from long time series data (≳25 observations). Compared to existing time series methods, CCM has the advantage of being model-free and robust to unmeasured confounding that could otherwise induce spurious associations. CCM builds on Takens' Theorem, a well-established result from dynamical systems theory that requires only mild assumptions. This theorem allows us to reconstruct high dimensional system dynamics using a time series of only a single variable. These reconstructions can be thought of as shadows of the true causal system. If reconstructed shadows can predict points from opposing time series, we can infer that the corresponding variables are providing views of the same causal system, and so are causally related. Unlike traditional metrics, this test can establish the directionality of causation, even in the presence of feedback loops. Furthermore, since CCM can extract causal relationships from times series of, e.g., a single individual, it may be a valuable tool to personalized medicine. We implement CCM in Julia, a

GNSS Network Time Series Analysis

NASA Astrophysics Data System (ADS)

Balodis, J.; Janpaule, I.; Haritonova, D.; Normand, M.; Silabriedis, G.; Zarinjsh, A.; Zvirgzds, J.

2012-04-01

Time series of GNSS station results of both the EUPOS®-RIGA and LATPOS networks has been developed at the Institute of Geodesy and Geoinformation (University of Latvia) using Bernese v.5.0 software. The base stations were selected among the EPN and IGS stations in surroundings of Latvia. In various day solutions the base station selection has been miscellaneous. Most frequently 5 - 8 base stations were selected from a set of stations {BOR1, JOEN, JOZE, MDVJ, METS, POLV, PULK, RIGA, TORA, VAAS, VISO, VLNS}. The rejection of "bad base stations" was performed by Bernese software depending on the quality of proper station data in proper day. This caused a reason of miscellaneous base station selection in various days. The results of time series are analysed. The question aroused on the nature of some outlying situations. The seasonal effect of the behaviour of the network has been identified when distance and elevation changes between stations has been analysed. The dependence from various influences has been recognised.

Computerized series solution of relativistic equations of motion.

NASA Technical Reports Server (NTRS)

Broucke, R.

1971-01-01

A method of solution of the equations of planetary motion is described. It consists of the use of numerical general perturbations in orbital elements and in rectangular coordinates. The solution is expanded in Fourier series in the mean anomaly with the aid of harmonic analysis and computerized series manipulation techniques. A detailed application to the relativistic motion of the planet Mercury is described both for Schwarzschild and isotropic coordinates.

Fast Algorithms for Mining Co-evolving Time Series

DTIC Science & Technology

2011-09-01

Keogh et al., 2001, 2004] and (b) forecasting, like an autoregressive integrated moving average model ( ARIMA ) and related meth- ods [Box et al., 1994...computing hardware? We develop models to mine time series with missing values, to extract compact representation from time sequences, to segment the...sequences, and to do forecasting. For large scale data, we propose algorithms for learning time series models , in particular, including Linear Dynamical

Introduction to Drywall. Introduction to Construction Series. Instructor Edition.

ERIC Educational Resources Information Center

Oklahoma State Dept. of Vocational and Technical Education, Stillwater. Curriculum and Instructional Materials Center.

This competency-based curriculum guide on the specialty area of drywall is part of the Introduction to Construction series. The series is designed with the flexible training requirements of open shop contractors, preapprenticeship programs, multicraft high school programs, technology education programs, and cooperative education programs in mind.…

Reprint Series: Prime Numbers and Perfect Numbers. RS-2.

ERIC Educational Resources Information Center

Schaaf, William L., Ed.

This is one in a series of SMSG supplementary and enrichment pamphlets for high school students. This series makes available expository articles which appeared in a variety of mathematical periodicals. Topics covered include: (1) the prime numbers; (2) mathematical sieves; (3) the factorgram; and (4) perfect numbers. (MP)

Introduction to Plumbing. Introduction to Construction Series. Instructor Edition.

ERIC Educational Resources Information Center

Oklahoma State Dept. of Vocational and Technical Education, Stillwater. Curriculum and Instructional Materials Center.

This competency-based curriculum guide on the specialty area of plumbing is part of the Introduction to Construction series. The series is designed with the flexible training requirements of open shop contractors, preapprenticeship programs, multicraft high school programs, technology education programs, and cooperative education programs in mind.…

Space Object Classification Using Fused Features of Time Series Data

NASA Astrophysics Data System (ADS)

Jia, B.; Pham, K. D.; Blasch, E.; Shen, D.; Wang, Z.; Chen, G.

In this paper, a fused feature vector consisting of raw time series and texture feature information is proposed for space object classification. The time series data includes historical orbit trajectories and asteroid light curves. The texture feature is derived from recurrence plots using Gabor filters for both unsupervised learning and supervised learning algorithms. The simulation results show that the classification algorithms using the fused feature vector achieve better performance than those using raw time series or texture features only.

Spectral analysis for GNSS coordinate time series using chirp Fourier transform

NASA Astrophysics Data System (ADS)

Feng, Shengtao; Bo, Wanju; Ma, Qingzun; Wang, Zifan

2017-12-01

Spectral analysis for global navigation satellite system (GNSS) coordinate time series provides a principal tool to understand the intrinsic mechanism that affects tectonic movements. Spectral analysis methods such as the fast Fourier transform, Lomb-Scargle spectrum, evolutionary power spectrum, wavelet power spectrum, etc. are used to find periodic characteristics in time series. Among spectral analysis methods, the chirp Fourier transform (CFT) with less stringent requirements is tested with synthetic and actual GNSS coordinate time series, which proves the accuracy and efficiency of the method. With the length of series only limited to even numbers, CFT provides a convenient tool for windowed spectral analysis. The results of ideal synthetic data prove CFT accurate and efficient, while the results of actual data show that CFT is usable to derive periodic information from GNSS coordinate time series.

Nonstationary frequency analysis for the trivariate flood series of the Weihe River

NASA Astrophysics Data System (ADS)

Jiang, Cong; Xiong, Lihua

2016-04-01

Some intensive human activities such as water-soil conservation can significantly alter the natural hydrological processes of rivers. In this study, the effect of the water-soil conservation on the trivariate flood series from the Weihe River located in the Northwest China is investigated. The annual maxima daily discharge, annual maxima 3-day flood volume and annual maxima 5-day flood volume are chosen as the study data and used to compose the trivariate flood series. The nonstationarities in both the individual univariate flood series and the corresponding antecedent precipitation series generating the flood events are examined by the Mann-Kendall trend test. It is found that all individual univariate flood series present significant decreasing trend, while the antecedent precipitation series can be treated as stationary. It indicates that the increase of the water-soil conservation land area has altered the rainfall-runoff relationship of the Weihe basin, and induced the nonstationarities in the three individual univariate flood series. The time-varying moments model based on the Pearson type III distribution is applied to capture the nonstationarities in the flood frequency distribution with the water-soil conservation land area introduced as the explanatory variable of the flood distribution parameters. Based on the analysis for each individual univariate flood series, the dependence structure among the three univariate flood series are investigated by the time-varying copula model also with the water-soil conservation land area as the explanatory variable of copula parameters. The results indicate that the dependence among the trivariate flood series is enhanced by the increase of water-soil conservation land area.

A Combined Length-of-Day Series Spanning 1832-1997

NASA Technical Reports Server (NTRS)

Gross, Richard S.

1999-01-01

The Earth's rotation is not constant but exhibits minute changes on all observable time scales ranging from subdaily to secular. This rich spectrum of observed Earth rotation changes reflects the rich variety of astronomical and geophysical phenomena that are causing the Earth's rotation to change, including, but not limited to, ocean and solid body tides, atmospheric wind and pressure changes, oceanic current and sea level height changes, post-glacial rebound, and torques acting at the core-mantle boundary. In particular, the decadal-scale variations of the Earth's rotation are thought to be largely caused by interactions between the Earth's outer core and mantle. Comparing the inferred Earth rotation variations caused by the various core-mantle interactions to observed variations requires Earth rotation observations spanning decades, if not centuries. During the past century many different techniques have been used to observe the Earth's rotation. By combining the individual Earth rotation series determined by each of these techniques, a series of the Earth's rotation can be obtained that is based upon independent measurements spanning the greatest possible time interval. In this study, independent observations of the Earth's rotation are combined to generate a length-of-day series spanning 1832-1997. The observations combined include lunar occultation measurements spanning 1832-1955, optical astrometric measurements spanning 1956-1982, lunar laser ranging measurements spanning 1970-1997, and very long baseline interferometric measurements spanning 1978-1998. These series are combined using a Kalman filter developed at JPL for just this purpose. The resulting combined length-of-day series will be presented and compared with other available length-of-day series of similar duration.

Magnitude and sign of long-range correlated time series: Decomposition and surrogate signal generation.

PubMed

Gómez-Extremera, Manuel; Carpena, Pedro; Ivanov, Plamen Ch; Bernaola-Galván, Pedro A

2016-04-01

We systematically study the scaling properties of the magnitude and sign of the fluctuations in correlated time series, which is a simple and useful approach to distinguish between systems with different dynamical properties but the same linear correlations. First, we decompose artificial long-range power-law linearly correlated time series into magnitude and sign series derived from the consecutive increments in the original series, and we study their correlation properties. We find analytical expressions for the correlation exponent of the sign series as a function of the exponent of the original series. Such expressions are necessary for modeling surrogate time series with desired scaling properties. Next, we study linear and nonlinear correlation properties of series composed as products of independent magnitude and sign series. These surrogate series can be considered as a zero-order approximation to the analysis of the coupling of magnitude and sign in real data, a problem still open in many fields. We find analytical results for the scaling behavior of the composed series as a function of the correlation exponents of the magnitude and sign series used in the composition, and we determine the ranges of magnitude and sign correlation exponents leading to either single scaling or to crossover behaviors. Finally, we obtain how the linear and nonlinear properties of the composed series depend on the correlation exponents of their magnitude and sign series. Based on this information we propose a method to generate surrogate series with controlled correlation exponent and multifractal spectrum.

Time-Series Analysis: A Cautionary Tale

NASA Technical Reports Server (NTRS)

Damadeo, Robert

2015-01-01

Time-series analysis has often been a useful tool in atmospheric science for deriving long-term trends in various atmospherically important parameters (e.g., temperature or the concentration of trace gas species). In particular, time-series analysis has been repeatedly applied to satellite datasets in order to derive the long-term trends in stratospheric ozone, which is a critical atmospheric constituent. However, many of the potential pitfalls relating to the non-uniform sampling of the datasets were often ignored and the results presented by the scientific community have been unknowingly biased. A newly developed and more robust application of this technique is applied to the Stratospheric Aerosol and Gas Experiment (SAGE) II version 7.0 ozone dataset and the previous biases and newly derived trends are presented.

Self-organising mixture autoregressive model for non-stationary time series modelling.

PubMed

Ni, He; Yin, Hujun

2008-12-01

Modelling non-stationary time series has been a difficult task for both parametric and nonparametric methods. One promising solution is to combine the flexibility of nonparametric models with the simplicity of parametric models. In this paper, the self-organising mixture autoregressive (SOMAR) network is adopted as a such mixture model. It breaks time series into underlying segments and at the same time fits local linear regressive models to the clusters of segments. In such a way, a global non-stationary time series is represented by a dynamic set of local linear regressive models. Neural gas is used for a more flexible structure of the mixture model. Furthermore, a new similarity measure has been introduced in the self-organising network to better quantify the similarity of time series segments. The network can be used naturally in modelling and forecasting non-stationary time series. Experiments on artificial, benchmark time series (e.g. Mackey-Glass) and real-world data (e.g. numbers of sunspots and Forex rates) are presented and the results show that the proposed SOMAR network is effective and superior to other similar approaches.

The Correlated Lecture Laboratory Series in Diagnostic Radiological Physics.

ERIC Educational Resources Information Center

Lamel, David A.; And Others

This series in diagnostic radiological physics has been designed to provide the physics background requisite for the proper conduct of medical diagnostic x-ray examinations. The basic goal of the series is to bridge physics theory and radiological practice, achieved by combining pertinent lecture material with laboratory exercises that illustrate…

The First Steps Series. [Videotapes].

ERIC Educational Resources Information Center

1998

This videotape series offers emotional support and self-confidence to parents reaching out for knowledge about how young children, grow, develop, and learn. The video "Common Concerns of Parents of Young" (30 minutes) features parents expressing some universal concerns regarding their young children. Child psychologists and pediatricians offer…

Newfoundland. Reference Series No. 34.

ERIC Educational Resources Information Center

Department of External Affairs, Ottawa (Ontario).

This booklet, one of a series featuring the Canadian provinces, presents a brief overview of Newfoundland and is suitable for teacher reference or student reading. Separate sections discuss geography and climate, history, economy, population and settlement, arts and culture, leisure and recreation, and heritage. Specific topics include the…

Saskatchewan. Reference Series No. 27.

ERIC Educational Resources Information Center

Department of External Affairs, Ottawa (Ontario).

This booklet, one of a series featuring the Canadian provinces, presents a brief overview of Saskatchewan and is suitable for teacher reference or student reading. Separate sections discuss history, economy, oil, uranium, potash, coal, minerals and metals, agriculture, forestry, tourism and recreation, arts and culture, and people. Specific topics…

Inference of scale-free networks from gene expression time series.

PubMed

Daisuke, Tominaga; Horton, Paul

2006-04-01

Quantitative time-series observation of gene expression is becoming possible, for example by cell array technology. However, there are no practical methods with which to infer network structures using only observed time-series data. As most computational models of biological networks for continuous time-series data have a high degree of freedom, it is almost impossible to infer the correct structures. On the other hand, it has been reported that some kinds of biological networks, such as gene networks and metabolic pathways, may have scale-free properties. We hypothesize that the architecture of inferred biological network models can be restricted to scale-free networks. We developed an inference algorithm for biological networks using only time-series data by introducing such a restriction. We adopt the S-system as the network model, and a distributed genetic algorithm to optimize models to fit its simulated results to observed time series data. We have tested our algorithm on a case study (simulated data). We compared optimization under no restriction, which allows for a fully connected network, and under the restriction that the total number of links must equal that expected from a scale free network. The restriction reduced both false positive and false negative estimation of the links and also the differences between model simulation and the given time-series data.

Oral lichen planus in childhood: a case series.

PubMed

Cascone, Marco; Celentano, Antonio; Adamo, Daniela; Leuci, Stefania; Ruoppo, Elvira; Mignogna, Michele D

2017-06-01

Although the exact incidence of pediatric oral lichen planus (OLP) is unknown, the oral mucosa seems to be less commonly involved, and the clinical presentation is often atypical. The aim of the study is to present a case series of OLP in childhood. From our database, we retrospectively selected and analyzed the clinical data of OLP patients under the age of 18 where the diagnosis had been confirmed by histopathological analysis. The case series from our database shows eight patients, four males and four females. The mean (±SD) age at the time of diagnosis of the disease was 13.5 (±2.73) years, ranging in age from 9 to 17. Clinically, a reticular pattern was present in six patients (75%), and the tongue was the most commonly involved oral site (six cases, 75%). We also report the first case of OLP in a 9-year-old girl affected by autoimmune polyendocrinopathy-candidiasis-ectodermal dystrophy. We report the largest case series of pediatric OLP published in literature thus far. Differences in the disease between adults and pediatric patients have been detected, but further investigation and a larger case series are needed to establish any detailed differences in clinical outcomes. © 2017 The International Society of Dermatology.

Common families across test series—how many do we need?

Treesearch

G.R. Johnson

2004-01-01

In order to compare families that are planted on different sites, many forest tree breeding programs include common families in their different series of trials. Computer simulation was used to examine how many common families were needed in each series of progeny trials in order to reliably compare families across series. Average gain and its associated variation...

The utility of patch tests using larger screening series of allergens.

PubMed

Larkin, A; Rietschel, R L

1998-09-01

The number of patch test allergens available within the United States for routine commercial purchase is limited. Allergens chosen for inclusion in routine screening series or patch test trays vary, and the degree of information obtained from any series may or may not serve a patient's needs. Knowledge of how well the allergens chosen for inclusion in the two commercially available sources perform compared with a more expansive panel of tests can help physicians select the more appropriate tests. From 1994 to mid-1997, 554 patients were tested with allergens recommended by the North American Contact Dermatitis Group (NACDG). This included all allergens currently available from both current domestic sources, although not in the identical form used by the Thin-layer Rapid Use Epicutaneous Test (TRUE) test (Glaxo Dermatology, Research Triangle Park, NC). Another 185 patients were tested with supplemental series of allergens. The larger the series of allergens used, the more positive tests were found and the more relevant tests as well. Hermal patch test allergens identified about 55% of the information found by the NACDG series; the TRUE test allergens (but not in the TRUE test system) identified 65%. Of the 103 reactions to supplemental allergens not found by the NACDG series, 59 were relevant. Larger series of allergens can enhance accurate diagnosis of allergic contact dermatitis. No single arbitrary series of allergens can adequately survey the contemporary environment of individual patients. Selection of allergens for testing requires consideration of the patient's history and access to appropriate environmental contactants.

High Speed Solution of Spacecraft Trajectory Problems Using Taylor Series Integration

NASA Technical Reports Server (NTRS)

Scott, James R.; Martini, Michael C.

2008-01-01

Taylor series integration is implemented in a spacecraft trajectory analysis code-the Spacecraft N-body Analysis Program (SNAP) - and compared with the code s existing eighth-order Runge-Kutta Fehlberg time integration scheme. Nine trajectory problems, including near Earth, lunar, Mars and Europa missions, are analyzed. Head-to-head comparison at five different error tolerances shows that, on average, Taylor series is faster than Runge-Kutta Fehlberg by a factor of 15.8. Results further show that Taylor series has superior convergence properties. Taylor series integration proves that it can provide rapid, highly accurate solutions to spacecraft trajectory problems.

High voltage series connected tandem junction solar battery

DOEpatents

Hanak, Joseph J.

1982-01-01

A high voltage series connected tandem junction solar battery which comprises a plurality of strips of tandem junction solar cells of hydrogenated amorphous silicon having one optical path and electrically interconnected by a tunnel junction. The layers of hydrogenated amorphous silicon, arranged in a tandem configuration, can have the same bandgap or differing bandgaps. The tandem junction strip solar cells are series connected to produce a solar battery of any desired voltage.

Ruptures of vulnerability: Linda Stein's Knight Series.

PubMed

Bible, Ann Vollmann

2010-01-01

Drawing on the work of Monique Wittig, this article understands Linda Stein's Knight Series as a lacunary writing communicating both her challenges to come to representation and her creative registration of subjectivity. The argument is grounded in an exploration of the rich interplay of power and vulnerability across the series as against the discourse of escapist fashion. Specifically, Stein's critical contradictions of inside and outside, conflated temporality, disjunctions between decoration and abstraction, and fluidity of sex and gender are examined. The discussion is elaborated through consideration of the work of Julia Kristeva, Elizabeth Grosz, and Hayao Miyazaki.

The Prediction of Teacher Turnover Employing Time Series Analysis.

ERIC Educational Resources Information Center

Costa, Crist H.

The purpose of this study was to combine knowledge of teacher demographic data with time-series forecasting methods to predict teacher turnover. Moving averages and exponential smoothing were used to forecast discrete time series. The study used data collected from the 22 largest school districts in Iowa, designated as FACT schools. Predictions…

Learning and Celebrating: The Glamour of Design Lecture Series

ERIC Educational Resources Information Center

Popov, Lubomir

2013-01-01

The purpose of this paper is to highlight the celebratory aspect of the Design Lecture Series, a tradition in architecture schools and interior design programs, its meaning for all constituent parties, and its contributions to creating professional identity and community. The Design Lecture Series is a public event popular in design programs,…

A study of stationarity in time series by using wavelet transform

NASA Astrophysics Data System (ADS)

Dghais, Amel Abdoullah Ahmed; Ismail, Mohd Tahir

2014-07-01

In this work the core objective is to apply discrete wavelet transform (DWT) functions namely Haar, Daubechies, Symmlet, Coiflet and discrete approximation of the meyer wavelets in non-stationary financial time series data from US stock market (DJIA30). The data consists of 2048 daily data of closing index starting from December 17, 2004 until October 23, 2012. From the unit root test the results show that the data is non stationary in the level. In order to study the stationarity of a time series, the autocorrelation function (ACF) is used. Results indicate that, Haar function is the lowest function to obtain noisy series as compared to Daubechies, Symmlet, Coiflet and discrete approximation of the meyer wavelets. In addition, the original data after decomposition by DWT is less noisy series than decomposition by DWT for return time series.

The Value of Interrupted Time-Series Experiments for Community Intervention Research

PubMed Central

Biglan, Anthony; Ary, Dennis; Wagenaar, Alexander C.

2015-01-01

Greater use of interrupted time-series experiments is advocated for community intervention research. Time-series designs enable the development of knowledge about the effects of community interventions and policies in circumstances in which randomized controlled trials are too expensive, premature, or simply impractical. The multiple baseline time-series design typically involves two or more communities that are repeatedly assessed, with the intervention introduced into one community at a time. It is particularly well suited to initial evaluations of community interventions and the refinement of those interventions. This paper describes the main features of multiple baseline designs and related repeated-measures time-series experiments, discusses the threats to internal validity in multiple baseline designs, and outlines techniques for statistical analyses of time-series data. Examples are given of the use of multiple baseline designs in evaluating community interventions and policy changes. PMID:11507793

Efficient Generation and Use of Power Series for Broad Application.

NASA Astrophysics Data System (ADS)

Rudmin, Joseph; Sochacki, James

2017-01-01

A brief history and overview of the Parker-Sockacki Method of Power Series generation is presented. This method generates power series to order n in time n2 for any system of differential equations that has a power series solution. The method is simple enough that novices to differential equations can easily learn it and immediately apply it. Maximal absolute error estimates allow one to determine the number of terms needed to reach desired accuracy. Ratios of coefficients in a solution with global convergence differ signficantly from that for a solution with only local convergence. Divergence of the series prevents one from overlooking poles. The method can always be cast in polynomial form, which allows separation of variables in almost all physical systems, facilitating exploration of hidden symmetries, and is implicitly symplectic.

Multiscale Poincaré plots for visualizing the structure of heartbeat time series.

PubMed

Henriques, Teresa S; Mariani, Sara; Burykin, Anton; Rodrigues, Filipa; Silva, Tiago F; Goldberger, Ary L

2016-02-09

Poincaré delay maps are widely used in the analysis of cardiac interbeat interval (RR) dynamics. To facilitate visualization of the structure of these time series, we introduce multiscale Poincaré (MSP) plots. Starting with the original RR time series, the method employs a coarse-graining procedure to create a family of time series, each of which represents the system's dynamics in a different time scale. Next, the Poincaré plots are constructed for the original and the coarse-grained time series. Finally, as an optional adjunct, color can be added to each point to represent its normalized frequency. We illustrate the MSP method on simulated Gaussian white and 1/f noise time series. The MSP plots of 1/f noise time series reveal relative conservation of the phase space area over multiple time scales, while those of white noise show a marked reduction in area. We also show how MSP plots can be used to illustrate the loss of complexity when heartbeat time series from healthy subjects are compared with those from patients with chronic (congestive) heart failure syndrome or with atrial fibrillation. This generalized multiscale approach to Poincaré plots may be useful in visualizing other types of time series.

Spectroscopy, Understanding the Atom Series.

ERIC Educational Resources Information Center

Hellman, Hal

This booklet is one of the "Understanding the Atom" Series. The science of spectroscopy is presented by a number of topics dealing with (1) the uses of spectroscopy, (2) its origin and background, (3) the basic optical systems of spectroscopes, spectrometers, and spectrophotometers, (4) the characteristics of wave motion, (5) the…

Introduction to the Special Series.

ERIC Educational Resources Information Center

Peterson, Lizette

1986-01-01

Presents a special series of seven articles dealing with biopsychosocial oncology, the role of psychology in cancer treatment. Includes an introduction by Lizette Peterson and articles by Thomas Burish and Michael Carey, Susan Jay et al., Shelley Taylor et al., David Cella and Susan Tross, Gerald Koocher, and Leonard Derogatis. (KS)

Building Alliances Series: Workforce Development

ERIC Educational Resources Information Center

Brady, Cecilia

2009-01-01

Public-private partnerships done right are a powerful tool for development, providing enduring solutions to some of the greatest challenges. To help familiarize readers with the art of alliance building, the Global Development Alliance (GDA) office has created a series of practical guides that highlight proven practices in partnerships,…

Electromechanical Devices. Energy Technology Series.

ERIC Educational Resources Information Center

Center for Occupational Research and Development, Inc., Waco, TX.

This course in electromechanical devices is one of 16 courses in the Energy Technology Series developed for an Energy Conservation-and-Use Technology curriculum. Intended for use in two-year postsecondary institutions to prepare technicians for employment, the courses are also useful in industry for updating employees in company-sponsored training…

Task Analysis Inventories. Series II.

ERIC Educational Resources Information Center

Wesson, Carl E.

This second in a series of task analysis inventories contains checklists of work performed in twenty-two occupations. Each inventory is a comprehensive list of work activities, responsibilities, educational courses, machines, tools, equipment, and work aids used and the products produced or services rendered in a designated occupational area. The…

Microcomputer Hardware. Energy Technology Series.

ERIC Educational Resources Information Center

Technical Education Research Centre-Southwest, Waco, TX.

This course in microcomputer hardware is one of 16 courses in the Energy Technology Series developed for an Energy Conservation-and-Use Technology curriculum. Intended for use in two-year postsecondary technical institutions to prepare technicians for employment, the courses are also useful in industry for updating employees in company-sponsored…

Teen Addiction. Current Controversies Series.

ERIC Educational Resources Information Center

Winters, Paul A., Ed.

The Current Controversies series explores social, political, and economic controversies that dominate the national and international scenes today from a variety of perspectives. Recent surveys have shown that, after years of decline, drug use among teenagers has increased during the 1990s, and that alcohol and tobacco use have remained…

Teen Series' Reception: Television, Adolescence and Culture of Feelings.

ERIC Educational Resources Information Center

Pasquier, Dominique

1996-01-01

Noting the popularity of television teen series among young viewers in France, this study examined how the programs are used as a way of defining gender identity for children and adolescents. Results indicated construction of meanings of characters and plots varied by age, gender, and social background of viewers. Relationship to series relied on…

Design and Implementation of a Professional Development Course Series.

PubMed

Welch, Beth; Spooner, Joshua J; Tanzer, Kim; Dintzner, Matthew R

2017-12-01

Objective. To design and implement a longitudinal course series focused on professional development and professional identity formation in pharmacy students at Western New England University. Methods. A four-year, theme-based course series was designed to sequentially and longitudinally impart the values, attributes, and characteristics of a professional pharmacist. Requirements of the course include: goal planning and reflective assignments, submission of "Best Works," attendance at professional meetings, completion of service hours, annual completion of a Pharmacy Professionalism Instrument, attendance at Dean's Seminar, participation in roundtable discussions, and maintenance of an electronic portfolio. Though the Professional Development course series carries no credit, these courses are progression requirements and students are assessed on a pass/fail basis. Results. Course pass rates in the 2015-2016 academic year for all four classes were 99% to 100%, suggesting the majority of students take professional development seriously and are achieving the intended outcomes of the courses. Conclusion. A professional development course series was designed and implemented in the new Doctor of Pharmacy program at Western New England University to enhance the professional identity formation of students.

High voltage power supply with modular series resonant inverters

DOEpatents

Dreifuerst, Gary R.; Merritt, Bernard T.

1995-01-01

A relatively small and compact high voltage, high current power supply for a laser utilizes a plurality of modules containing series resonant half bridge inverters. A pair of reverse conducting thyristors are incorporated in each series resonant inverter module such that the series resonant inverter modules are sequentially activated in phases 360.degree./n apart, where n=number of modules for n>2. Selective activation of the modules allows precise output control reducing ripple and improving efficiency. Each series resonant half bridge inverter module includes a transformer which has a cooling manifold for actively circulating a coolant such as water, to cool the transformer core as well as selected circuit elements. Conductors connecting and forming various circuit components comprise hollow, electrically conductive tubes such as copper. Coolant circulates through the tubes to remove heat. The conductive tubes act as electrically conductive lines for connecting various components of the power supply. Where it is desired to make electrical isolation breaks, tubes comprised of insulating material such as nylon are used to provide insulation and continue the fluid circuit.

High voltage power supply with modular series resonant inverters

DOEpatents

Dreifuerst, G.R.; Merritt, B.T.

1995-07-18

A relatively small and compact high voltage, high current power supply for a laser utilizes a plurality of modules containing series resonant half bridge inverters. A pair of reverse conducting thyristors are incorporated in each series resonant inverter module such that the series resonant inverter modules are sequentially activated in phases 360{degree}/n apart, where n=number of modules for n>2. Selective activation of the modules allows precise output control reducing ripple and improving efficiency. Each series resonant half bridge inverter module includes a transformer which has a cooling manifold for actively circulating a coolant such as water, to cool the transformer core as well as selected circuit elements. Conductors connecting and forming various circuit components comprise hollow, electrically conductive tubes such as copper. Coolant circulates through the tubes to remove heat. The conductive tubes act as electrically conductive lines for connecting various components of the power supply. Where it is desired to make electrical isolation breaks, tubes comprised of insulating material such as nylon are used to provide insulation and continue the fluid circuit. 11 figs.

Mars Sample Handling Protocol Workshop Series: Workshop 4

NASA Technical Reports Server (NTRS)

Race Margaret S. (Editor); DeVincenzi, Donald L. (Editor); Rummel, John D. (Editor); Acevedo, Sara E. (Editor)

2001-01-01

In preparation for missions to Mars that will involve the return of samples to Earth, it will be necessary to prepare for the receiving, handling, testing, distributing, and archiving of martian materials here on Earth. Previous groups and committees have studied selected aspects of sample return activities, but specific detailed protocols for the handling and testing of returned samples must still be developed. To further refine the requirements for sample hazard testing and to develop the criteria for subsequent release of sample materials from quarantine, the NASA Planetary Protection Officer convened a series of workshops in 2000-2001. The overall objective of the Workshop Series was to produce a Draft Protocol by which returned martian sample materials can be assessed for biological hazards and examined for evidence of life (extant or extinct) while safeguarding the purity of the samples from possible terrestrial contamination. This report also provides a record of the proceedings of Workshop 4, the final Workshop of the Series, which was held in Arlington, Virginia, June 5-7, 2001. During Workshop 4, the sub-groups were provided with a draft of the protocol compiled in May 2001 from the work done at prior Workshops in the Series. Then eight sub-groups were formed to discuss the following assigned topics: Review and Assess the Draft Protocol for Physical/Chemical Testing Review and Assess the Draft Protocol for Life Detection Testing Review and Assess the Draft Protocol for Biohazard Testing Environmental and Health/Monitoring and Safety Issues Requirements of the Draft Protocol for Facilities and Equipment Contingency Planning for Different Outcomes of the Draft Protocol Personnel Management Considerations in Implementation of the Draft Protocol Draft Protocol Implementation Process and Update Concepts This report provides the first complete presentation of the Draft Protocol for Mars Sample Handling to meet planetary protection needs. This Draft Protocol

Modelling road accidents: An approach using structural time series

NASA Astrophysics Data System (ADS)

Junus, Noor Wahida Md; Ismail, Mohd Tahir

2014-09-01

In this paper, the trend of road accidents in Malaysia for the years 2001 until 2012 was modelled using a structural time series approach. The structural time series model was identified using a stepwise method, and the residuals for each model were tested. The best-fitted model was chosen based on the smallest Akaike Information Criterion (AIC) and prediction error variance. In order to check the quality of the model, a data validation procedure was performed by predicting the monthly number of road accidents for the year 2012. Results indicate that the best specification of the structural time series model to represent road accidents is the local level with a seasonal model.

Rapid Calculation of Spacecraft Trajectories Using Efficient Taylor Series Integration

NASA Technical Reports Server (NTRS)

Scott, James R.; Martini, Michael C.

2011-01-01

A variable-order, variable-step Taylor series integration algorithm was implemented in NASA Glenn's SNAP (Spacecraft N-body Analysis Program) code. SNAP is a high-fidelity trajectory propagation program that can propagate the trajectory of a spacecraft about virtually any body in the solar system. The Taylor series algorithm's very high order accuracy and excellent stability properties lead to large reductions in computer time relative to the code's existing 8th order Runge-Kutta scheme. Head-to-head comparison on near-Earth, lunar, Mars, and Europa missions showed that Taylor series integration is 15.8 times faster than Runge- Kutta on average, and is more accurate. These speedups were obtained for calculations involving central body, other body, thrust, and drag forces. Similar speedups have been obtained for calculations that include J2 spherical harmonic for central body gravitation. The algorithm includes a step size selection method that directly calculates the step size and never requires a repeat step. High-order Taylor series integration algorithms have been shown to provide major reductions in computer time over conventional integration methods in numerous scientific applications. The objective here was to directly implement Taylor series integration in an existing trajectory analysis code and demonstrate that large reductions in computer time (order of magnitude) could be achieved while simultaneously maintaining high accuracy. This software greatly accelerates the calculation of spacecraft trajectories. At each time level, the spacecraft position, velocity, and mass are expanded in a high-order Taylor series whose coefficients are obtained through efficient differentiation arithmetic. This makes it possible to take very large time steps at minimal cost, resulting in large savings in computer time. The Taylor series algorithm is implemented primarily through three subroutines: (1) a driver routine that automatically introduces auxiliary variables and

Successful use of right unilateral ECT for catatonia: a case series.

PubMed

Cristancho, Pilar; Jewkes, Delaina; Mon, Thetsu; Conway, Charles

2014-03-01

Catatonia is a neuropsychiatric syndrome involving motor signs in association with disorders of mood, behavior, or thought. Bitemporal electrode placement electroconvulsive therapy (ECT) is a proven effective treatment for catatonia, and this mode of ECT delivery is the preferred method of treatment in this condition. Studies in major depressive disorder have demonstrated that suprathreshold, nondominant (right) hemisphere, unilateral electrode placement ECT has fewer adverse effects, especially cognitive adverse effects, than bitemporal ECT. This case series describes the use of right unilateral (RUL) ECT in 5 patients with catatonia. Before ECT, all 5 patients in this series initially failed therapy with benzodiazepines and psychotropic medications. Each catatonic patient received a series of 8 to 12 RUL ECT in an every-other-day series. After ECT, 4 of the 5 patients had a full recovery from catatonia. One patient achieved only partial response to RUL ECT, and no additional benefit was obtained with bitemporal ECT. All patients in this case series tolerated RUL ECT without major adverse effects. This case series illustrates successful use of RUL ECT in patients with catatonia and adds to the early literature demonstrating its effective use in treating this complex condition.

Further developments of series-connected superconducting tunnel junction to radiation detection

NASA Astrophysics Data System (ADS)

Kurakado, Masahiko; Ohsawa, Daisuke; Katano, Rintaro; Ito, Shin; Isozumi, Yasuhito

1997-10-01

One of the promising radiation detection devices for various practical applications is the series-connected superconducting tunnel junction (STJ) detector. In this article, interesting topics of the detectors are described since our previous work: e.g., more than two order higher detection efficiency compared with single STJ detectors, high count rate detection, and position resolution. Detectors were cooled to 0.35-0.4 K by means of a convenient 3He cryostat. The 5.9 and 6.5 keV x rays from 55Fe are separated by a detector specially designed for x-ray detection. The possible count rate of the series-junction detector estimated from the shaping-time constant applied in the measurements is high, e.g., over 104 counts per second. A series-junction detector equipped with a position sensing mechanism has shown a position resolution of about 35 μm in a sensing area with a radius of 1.1 mm. The position resolution of series junctions improves the energy resolution. A new type series-connected STJ detector is also proposed, i.e., the dispersed multitrap series-junction detector, for further improvement of detection efficiency and energy resolution.

COMPARISON OF PARALLEL AND SERIES HYBRID POWERTRAINS FOR TRANSIT BUS APPLICATION

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

Gao, Zhiming; Daw, C Stuart; Smith, David E

2016-01-01

The fuel economy and emissions of both conventional and hybrid buses equipped with emissions aftertreatment were evaluated via computational simulation for six representative city bus drive cycles. Both series and parallel configurations for the hybrid case were studied. The simulation results indicate that series hybrid buses have the greatest overall advantage in fuel economy. The series and parallel hybrid buses were predicted to produce similar CO and HC tailpipe emissions but were also predicted to have reduced NOx tailpipe emissions compared to the conventional bus in higher speed cycles. For the New York bus cycle (NYBC), which has the lowestmore » average speed among the cycles evaluated, the series bus tailpipe emissions were somewhat higher than they were for the conventional bus, while the parallel hybrid bus had significantly lower tailpipe emissions. All three bus powertrains were found to require periodic active DPF regeneration to maintain PM control. Plug-in operation of series hybrid buses appears to offer significant fuel economy benefits and is easily employed due to the relatively large battery capacity that is typical of the series hybrid configuration.« less

Energy Audits. Energy Technology Series.

ERIC Educational Resources Information Center

Center for Occupational Research and Development, Inc., Waco, TX.

This course in energy audits is one of 16 courses in the Energy Technology Series developed for an Energy Conservation-and-Use Technology curriculum. Intended for use in two-year postsecondary technical institutions to prepare technicians for employment, the courses are also useful in industry for updating employees in company-sponsored training…

Teenage Pregnancy. Opposing Viewpoints Series.

ERIC Educational Resources Information Center

Thompson, Stephen P.

Books in the Opposing Viewpoints series challenge readers to question their own opinions and assumptions. By reading carefully balanced views, readers confront new ideas on the topic of interest. Although some experts believe that the problem of teenage pregnancy has been overstated, other recent studies have led many people to believe that…

Lasers, Understanding the Atom Series.

ERIC Educational Resources Information Center

Hellman, Hal

This booklet is one of the booklets in the "Understanding the Atom Series" published by the U. S. Atomic Energy Commission for high school science teachers and their students. Basic information for understanding the laser is provided including discussion of the electromagnetic spectrum, radio waves, light and the atom, coherent light, controlled…

Detection of "noisy" chaos in a time series

NASA Technical Reports Server (NTRS)

Chon, K. H.; Kanters, J. K.; Cohen, R. J.; Holstein-Rathlou, N. H.

1997-01-01

Time series from biological system often displays fluctuations in the measured variables. Much effort has been directed at determining whether this variability reflects deterministic chaos, or whether it is merely "noise". The output from most biological systems is probably the result of both the internal dynamics of the systems, and the input to the system from the surroundings. This implies that the system should be viewed as a mixed system with both stochastic and deterministic components. We present a method that appears to be useful in deciding whether determinism is present in a time series, and if this determinism has chaotic attributes. The method relies on fitting a nonlinear autoregressive model to the time series followed by an estimation of the characteristic exponents of the model over the observed probability distribution of states for the system. The method is tested by computer simulations, and applied to heart rate variability data.

Duality between QCD perturbative series and power corrections

NASA Astrophysics Data System (ADS)

Narison, S.; Zakharov, V. I.

2009-08-01

We elaborate on the relation between perturbative and power-like corrections to short-distance sensitive QCD observables. We confront theoretical expectations with explicit perturbative calculations existing in literature. As is expected, the quadratic correction is dual to a long perturbative series and one should use one of them but not both. However, this might be true only for very long perturbative series, with number of terms needed in most cases exceeding the number of terms available. What has not been foreseen, the quartic corrections might also be dual to the perturbative series. If confirmed, this would imply a crucial modification of the dogma. We confront this quadratic correction against existing phenomenology (QCD (spectral) sum rules scales, determinations of light quark masses and of αs from τ-decay). We find no contradiction and (to some extent) better agreement with the data and with recent lattice calculations.

A data mining framework for time series estimation.

PubMed

Hu, Xiao; Xu, Peng; Wu, Shaozhi; Asgari, Shadnaz; Bergsneider, Marvin

2010-04-01

Time series estimation techniques are usually employed in biomedical research to derive variables less accessible from a set of related and more accessible variables. These techniques are traditionally built from systems modeling approaches including simulation, blind decovolution, and state estimation. In this work, we define target time series (TTS) and its related time series (RTS) as the output and input of a time series estimation process, respectively. We then propose a novel data mining framework for time series estimation when TTS and RTS represent different sets of observed variables from the same dynamic system. This is made possible by mining a database of instances of TTS, its simultaneously recorded RTS, and the input/output dynamic models between them. The key mining strategy is to formulate a mapping function for each TTS-RTS pair in the database that translates a feature vector extracted from RTS to the dissimilarity between true TTS and its estimate from the dynamic model associated with the same TTS-RTS pair. At run time, a feature vector is extracted from an inquiry RTS and supplied to the mapping function associated with each TTS-RTS pair to calculate a dissimilarity measure. An optimal TTS-RTS pair is then selected by analyzing these dissimilarity measures. The associated input/output model of the selected TTS-RTS pair is then used to simulate the TTS given the inquiry RTS as an input. An exemplary implementation was built to address a biomedical problem of noninvasive intracranial pressure assessment. The performance of the proposed method was superior to that of a simple training-free approach of finding the optimal TTS-RTS pair by a conventional similarity-based search on RTS features. 2009 Elsevier Inc. All rights reserved.

A multidisciplinary database for geophysical time series management

NASA Astrophysics Data System (ADS)

Montalto, P.; Aliotta, M.; Cassisi, C.; Prestifilippo, M.; Cannata, A.

2013-12-01

The variables collected by a sensor network constitute a heterogeneous data source that needs to be properly organized in order to be used in research and geophysical monitoring. With the time series term we refer to a set of observations of a given phenomenon acquired sequentially in time. When the time intervals are equally spaced one speaks of period or sampling frequency. Our work describes in detail a possible methodology for storage and management of time series using a specific data structure. We designed a framework, hereinafter called TSDSystem (Time Series Database System), in order to acquire time series from different data sources and standardize them within a relational database. The operation of standardization provides the ability to perform operations, such as query and visualization, of many measures synchronizing them using a common time scale. The proposed architecture follows a multiple layer paradigm (Loaders layer, Database layer and Business Logic layer). Each layer is specialized in performing particular operations for the reorganization and archiving of data from different sources such as ASCII, Excel, ODBC (Open DataBase Connectivity), file accessible from the Internet (web pages, XML). In particular, the loader layer performs a security check of the working status of each running software through an heartbeat system, in order to automate the discovery of acquisition issues and other warning conditions. Although our system has to manage huge amounts of data, performance is guaranteed by using a smart partitioning table strategy, that keeps balanced the percentage of data stored in each database table. TSDSystem also contains modules for the visualization of acquired data, that provide the possibility to query different time series on a specified time range, or follow the realtime signal acquisition, according to a data access policy from the users.

Noise analysis of GPS time series in Taiwan

NASA Astrophysics Data System (ADS)

Lee, You-Chia; Chang, Wu-Lung

2017-04-01

Global positioning system (GPS) usually used for researches of plate tectonics and crustal deformation. In most studies, GPS time series considered only time-independent noises (white noise), but time-dependent noises (flicker noise, random walk noise) which were found by nearly twenty years are also important to the precision of data. The rate uncertainties of stations will be underestimated if the GPS time series are assumed only time-independent noise. Therefore studying the noise properties of GPS time series is necessary in order to realize the precision and reliability of velocity estimates. The lengths of our GPS time series are from over 500 stations around Taiwan with time spans longer than 2.5 years up to 20 years. The GPS stations include different monument types such as deep drill braced, roof, metal tripod, and concrete pier, and the most common type in Taiwan is the metal tripod. We investigated the noise properties of continuous GPS time series by using the spectral index and amplitude of the power law noise. During the process we first remove the data outliers, and then estimate linear trend, size of offsets, and seasonal signals, and finally the amplitudes of the power-law and white noise are estimated simultaneously. Our preliminary results show that the noise amplitudes of the north component are smaller than that of the other two components, and the largest amplitudes are in the vertical. We also find that the amplitudes of white noise and power-law noises are positively correlated in three components. Comparisons of noise amplitudes of different monument types in Taiwan reveal that the deep drill braced monuments have smaller data uncertainties and therefore are more stable than other monuments.

Making History Come Alive. Parents and Children Together Series.

ERIC Educational Resources Information Center

ERIC Clearinghouse on Reading, English, and Communication, Bloomington, IN.

This book, one of a series, shows how to help children develop a sense of personal, local, and national history. The message of the series urges parents and children to spend time together, talk about stories, and learn together. The first part of each book presents stories appropriate for varying grade levels, both younger children and those in…

Reprint Series: Nature and History of Pi. RS-6.

ERIC Educational Resources Information Center

Schaaf, William L., Ed.

This is one in a series of SMSG supplementary and enrichment pamphlets for high school students. This series makes available expository articles which appeared in a variety of mathematical periodicals. Topics covered include: (1) the history of the number pi; (2) what's new about pi; (3) the number pi; (4) pi and probability; and (5) from the…

Success with Test-Taking. Parents and Children Together Series.

ERIC Educational Resources Information Center

ERIC Clearinghouse on Reading, English, and Communication, Bloomington, IN.

This book, one of a series, shares ideas on how parents can help children cope with and learn from tests. The message of the series urges parents and children to spend time together, talk about stories, and learn together. The first part of each book presents stories appropriate for varying grade levels, both younger children and those in grades…

Encouraging Good Homework Habits. Parents and Children Together Series.

ERIC Educational Resources Information Center

ERIC Clearinghouse on Reading, English, and Communication, Bloomington, IN.

This book, one of a series, focuses on help with homework. The message of the series urges parents and children to spend time together, talk about stories, and learn together. The first part of each book presents stories appropriate for varying grade levels, both younger children and those in grades three and four, and each book presents stories…

Stress and School Performance. Parents and Children Together Series.

ERIC Educational Resources Information Center

ERIC Clearinghouse on Reading, English, and Communication, Bloomington, IN.

This book, one of a series, focuses on how stress affects children's learning. The message of the series urges parents and children to spend time together, talk about stories, and learn together. The first part of each book presents stories appropriate for varying grade levels, both younger children and those in grades three and four, and each…

Bean Sprouts: A Television Series about Chinese-American Children.

ERIC Educational Resources Information Center

Chinese for Affirmative Action, San Francisco, CA. Chinese Media Committee.

This teaching guide accompanies a series of five half-hour television programs for children 7 through 12 years of age that depict Chinese American children in a variety of situations that foster a sense of group and individual identity. The emphasis of the series is on affective learning. The following issues are dealt with: (1) the ramifications…

Working with the School. Parents and Children Together Series.

ERIC Educational Resources Information Center

ERIC Clearinghouse on Reading, English, and Communication, Bloomington, IN.

This book, one of a series, discusses how parents can help children by working with the school. The message of this series of books urges parents and children to spend time together, talk about stories, and learn together. The first part of each book presents stories appropriate for varying grade levels, both younger children and those in grades…

Recurrent Neural Networks for Multivariate Time Series with Missing Values.

PubMed

Che, Zhengping; Purushotham, Sanjay; Cho, Kyunghyun; Sontag, David; Liu, Yan

2018-04-17

Multivariate time series data in practical applications, such as health care, geoscience, and biology, are characterized by a variety of missing values. In time series prediction and other related tasks, it has been noted that missing values and their missing patterns are often correlated with the target labels, a.k.a., informative missingness. There is very limited work on exploiting the missing patterns for effective imputation and improving prediction performance. In this paper, we develop novel deep learning models, namely GRU-D, as one of the early attempts. GRU-D is based on Gated Recurrent Unit (GRU), a state-of-the-art recurrent neural network. It takes two representations of missing patterns, i.e., masking and time interval, and effectively incorporates them into a deep model architecture so that it not only captures the long-term temporal dependencies in time series, but also utilizes the missing patterns to achieve better prediction results. Experiments of time series classification tasks on real-world clinical datasets (MIMIC-III, PhysioNet) and synthetic datasets demonstrate that our models achieve state-of-the-art performance and provide useful insights for better understanding and utilization of missing values in time series analysis.

Detection of Undocumented Changepoints Using Multiple Test Statistics and Composite Reference Series.

NASA Astrophysics Data System (ADS)

Menne, Matthew J.; Williams, Claude N., Jr.

2005-10-01

An evaluation of three hypothesis test statistics that are commonly used in the detection of undocumented changepoints is described. The goal of the evaluation was to determine whether the use of multiple tests could improve undocumented, artificial changepoint detection skill in climate series. The use of successive hypothesis testing is compared to optimal approaches, both of which are designed for situations in which multiple undocumented changepoints may be present. In addition, the importance of the form of the composite climate reference series is evaluated, particularly with regard to the impact of undocumented changepoints in the various component series that are used to calculate the composite.In a comparison of single test changepoint detection skill, the composite reference series formulation is shown to be less important than the choice of the hypothesis test statistic, provided that the composite is calculated from the serially complete and homogeneous component series. However, each of the evaluated composite series is not equally susceptible to the presence of changepoints in its components, which may be erroneously attributed to the target series. Moreover, a reference formulation that is based on the averaging of the first-difference component series is susceptible to random walks when the composition of the component series changes through time (e.g., values are missing), and its use is, therefore, not recommended. When more than one test is required to reject the null hypothesis of no changepoint, the number of detected changepoints is reduced proportionately less than the number of false alarms in a wide variety of Monte Carlo simulations. Consequently, a consensus of hypothesis tests appears to improve undocumented changepoint detection skill, especially when reference series homogeneity is violated. A consensus of successive hypothesis tests using a semihierarchic splitting algorithm also compares favorably to optimal solutions, even when

Predictive capabilities of series solutions for laminar free convection boundary layer heat transfer

NASA Technical Reports Server (NTRS)

Lin, F. N.; Chao, B. T.

1978-01-01

Various types of series solutions for predicting laminar, free-convection boundary-layer heat transfer over both isothermal and nonisothermal boundaries are reviewed. The methods include finite difference, Merk series, Blasius series, and Goertler series. Comparative results are presented for heat transfer over an isothermal, horizontal, elliptical cylinder in both slender and blunt configurations.

Time averaging, ageing and delay analysis of financial time series

NASA Astrophysics Data System (ADS)

Cherstvy, Andrey G.; Vinod, Deepak; Aghion, Erez; Chechkin, Aleksei V.; Metzler, Ralf

2017-06-01

We introduce three strategies for the analysis of financial time series based on time averaged observables. These comprise the time averaged mean squared displacement (MSD) as well as the ageing and delay time methods for varying fractions of the financial time series. We explore these concepts via statistical analysis of historic time series for several Dow Jones Industrial indices for the period from the 1960s to 2015. Remarkably, we discover a simple universal law for the delay time averaged MSD. The observed features of the financial time series dynamics agree well with our analytical results for the time averaged measurables for geometric Brownian motion, underlying the famed Black-Scholes-Merton model. The concepts we promote here are shown to be useful for financial data analysis and enable one to unveil new universal features of stock market dynamics.

Non-invasive breast biopsy method using GD-DTPA contrast enhanced MRI series and F-18-FDG PET/CT dynamic image series

NASA Astrophysics Data System (ADS)

Magri, Alphonso William

This study was undertaken to develop a nonsurgical breast biopsy from Gd-DTPA Contrast Enhanced Magnetic Resonance (CE-MR) images and F-18-FDG PET/CT dynamic image series. A five-step process was developed to accomplish this. (1) Dynamic PET series were nonrigidly registered to the initial frame using a finite element method (FEM) based registration that requires fiducial skin markers to sample the displacement field between image frames. A commercial FEM package (ANSYS) was used for meshing and FEM calculations. Dynamic PET image series registrations were evaluated using similarity measurements SAVD and NCC. (2) Dynamic CE-MR series were nonrigidly registered to the initial frame using two registration methods: a multi-resolution free-form deformation (FFD) registration driven by normalized mutual information, and a FEM-based registration method. Dynamic CE-MR image series registrations were evaluated using similarity measurements, localization measurements, and qualitative comparison of motion artifacts. FFD registration was found to be superior to FEM-based registration. (3) Nonlinear curve fitting was performed for each voxel of the PET/CT volume of activity versus time, based on a realistic two-compartmental Patlak model. Three parameters for this model were fitted; two of them describe the activity levels in the blood and in the cellular compartment, while the third characterizes the washout rate of F-18-FDG from the cellular compartment. (4) Nonlinear curve fitting was performed for each voxel of the MR volume of signal intensity versus time, based on a realistic two-compartment Brix model. Three parameters for this model were fitted: rate of Gd exiting the compartment, representing the extracellular space of a lesion; rate of Gd exiting a blood compartment; and a parameter that characterizes the strength of signal intensities. Curve fitting used for PET/CT and MR series was accomplished by application of the Levenburg-Marquardt nonlinear regression

Documentation of a spreadsheet for time-series analysis and drawdown estimation

USGS Publications Warehouse

Halford, Keith J.

2006-01-01

Drawdowns during aquifer tests can be obscured by barometric pressure changes, earth tides, regional pumping, and recharge events in the water-level record. These stresses can create water-level fluctuations that should be removed from observed water levels prior to estimating drawdowns. Simple models have been developed for estimating unpumped water levels during aquifer tests that are referred to as synthetic water levels. These models sum multiple time series such as barometric pressure, tidal potential, and background water levels to simulate non-pumping water levels. The amplitude and phase of each time series are adjusted so that synthetic water levels match measured water levels during periods unaffected by an aquifer test. Differences between synthetic and measured water levels are minimized with a sum-of-squares objective function. Root-mean-square errors during fitting and prediction periods were compared multiple times at four geographically diverse sites. Prediction error equaled fitting error when fitting periods were greater than or equal to four times prediction periods. The proposed drawdown estimation approach has been implemented in a spreadsheet application. Measured time series are independent so that collection frequencies can differ and sampling times can be asynchronous. Time series can be viewed selectively and magnified easily. Fitting and prediction periods can be defined graphically or entered directly. Synthetic water levels for each observation well are created with earth tides, measured time series, moving averages of time series, and differences between measured and moving averages of time series. Selected series and fitting parameters for synthetic water levels are stored and drawdowns are estimated for prediction periods. Drawdowns can be viewed independently and adjusted visually if an anomaly skews initial drawdowns away from 0. The number of observations in a drawdown time series can be reduced by averaging across user

InSAR Deformation Time Series Processed On-Demand in the Cloud

NASA Astrophysics Data System (ADS)

Horn, W. B.; Weeden, R.; Dimarchi, H.; Arko, S. A.; Hogenson, K.

2017-12-01

During this past year, ASF has developed a cloud-based on-demand processing system known as HyP3 (http://hyp3.asf.alaska.edu/), the Hybrid Pluggable Processing Pipeline, for Synthetic Aperture Radar (SAR) data. The system makes it easy for a user who doesn't have the time or inclination to install and use complex SAR processing software to leverage SAR data in their research or operations. One such processing algorithm is generation of a deformation time series product, which is a series of images representing ground displacements over time, which can be computed using a time series of interferometric SAR (InSAR) products. The set of software tools necessary to generate this useful product are difficult to install, configure, and use. Moreover, for a long time series with many images, the processing of just the interferograms can take days. Principally built by three undergraduate students at the ASF DAAC, the deformation time series processing relies the new Amazon Batch service, which enables processing of jobs with complex interconnected dependencies in a straightforward and efficient manner. In the case of generating a deformation time series product from a stack of single-look complex SAR images, the system uses Batch to serialize the up-front processing, interferogram generation, optional tropospheric correction, and deformation time series generation. The most time consuming portion is the interferogram generation, because even for a fairly small stack of images many interferograms need to be processed. By using AWS Batch, the interferograms are all generated in parallel; the entire process completes in hours rather than days. Additionally, the individual interferograms are saved in Amazon's cloud storage, so that when new data is acquired in the stack, an updated time series product can be generated with minimal addiitonal processing. This presentation will focus on the development techniques and enabling technologies that were used in developing the time

Aggregated Indexing of Biomedical Time Series Data

PubMed Central

Woodbridge, Jonathan; Mortazavi, Bobak; Sarrafzadeh, Majid; Bui, Alex A.T.

2016-01-01

Remote and wearable medical sensing has the potential to create very large and high dimensional datasets. Medical time series databases must be able to efficiently store, index, and mine these datasets to enable medical professionals to effectively analyze data collected from their patients. Conventional high dimensional indexing methods are a two stage process. First, a superset of the true matches is efficiently extracted from the database. Second, supersets are pruned by comparing each of their objects to the query object and rejecting any objects falling outside a predetermined radius. This pruning stage heavily dominates the computational complexity of most conventional search algorithms. Therefore, indexing algorithms can be significantly improved by reducing the amount of pruning. This paper presents an online algorithm to aggregate biomedical times series data to significantly reduce the search space (index size) without compromising the quality of search results. This algorithm is built on the observation that biomedical time series signals are composed of cyclical and often similar patterns. This algorithm takes in a stream of segments and groups them to highly concentrated collections. Locality Sensitive Hashing (LSH) is used to reduce the overall complexity of the algorithm, allowing it to run online. The output of this aggregation is used to populate an index. The proposed algorithm yields logarithmic growth of the index (with respect to the total number of objects) while keeping sensitivity and specificity simultaneously above 98%. Both memory and runtime complexities of time series search are improved when using aggregated indexes. In addition, data mining tasks, such as clustering, exhibit runtimes that are orders of magnitudes faster when run on aggregated indexes. PMID:27617298

31 CFR 351.6 - When may I redeem my Series EE savings bond?

Code of Federal Regulations, 2014 CFR

2014-07-01

... before January 1, 2003. You may redeem your Series EE savings bond at any time beginning six months after... 31 Money and Finance: Treasury 2 2014-07-01 2014-07-01 false When may I redeem my Series EE... SAVINGS BONDS, SERIES EE Maturities, Redemption Values, and Investment Yields of Series EE Savings Bonds...

31 CFR 351.6 - When may I redeem my Series EE savings bond?

Code of Federal Regulations, 2012 CFR

2012-07-01

... before January 1, 2003. You may redeem your Series EE savings bond at any time beginning six months after... 31 Money and Finance:Treasury 2 2012-07-01 2012-07-01 false When may I redeem my Series EE savings... SAVINGS BONDS, SERIES EE Maturities, Redemption Values, and Investment Yields of Series EE Savings Bonds...

31 CFR 351.6 - When may I redeem my Series EE savings bond?

Code of Federal Regulations, 2010 CFR

2010-07-01

... before January 1, 2003. You may redeem your Series EE savings bond at any time beginning six months after... 31 Money and Finance: Treasury 2 2010-07-01 2010-07-01 false When may I redeem my Series EE... SAVINGS BONDS, SERIES EE Maturities, Redemption Values, and Investment Yields of Series EE Savings Bonds...

31 CFR 351.6 - When may I redeem my Series EE savings bond?

Code of Federal Regulations, 2013 CFR

2013-07-01

... before January 1, 2003. You may redeem your Series EE savings bond at any time beginning six months after... 31 Money and Finance:Treasury 2 2013-07-01 2013-07-01 false When may I redeem my Series EE savings... SAVINGS BONDS, SERIES EE Maturities, Redemption Values, and Investment Yields of Series EE Savings Bonds...

31 CFR 351.6 - When may I redeem my Series EE savings bond?

Code of Federal Regulations, 2011 CFR

2011-07-01

... before January 1, 2003. You may redeem your Series EE savings bond at any time beginning six months after... 31 Money and Finance:Treasury 2 2011-07-01 2011-07-01 false When may I redeem my Series EE savings... SAVINGS BONDS, SERIES EE Maturities, Redemption Values, and Investment Yields of Series EE Savings Bonds...

Interracial America. Opposing Viewpoints Series.

ERIC Educational Resources Information Center

Szumski, Bonnie, Ed.

Books in the Opposing Viewpoints Series present debates about current issues that can be used to teach critical reading and thinking skills. The varied opinions in each book examine different aspects of a single issue. The topics covered in this volume explore the racial and ethnic tensions that concern many Americans today. The racial divide…

Education Issues. GAO Transition Series.

ERIC Educational Resources Information Center

Comptroller General of the U.S., Washington, DC.

This summary report is one of a series addressing major policy, management, or program issues facing Congress and the administration. The issues identified in this report indicate the need to: reduce the cost and preserve the integrity of higher education student loan and grant programs; enhance the federal role in monitoring lenders, agencies,…

Summation of power series in particle physics

NASA Astrophysics Data System (ADS)

Fischer, Jan

1999-04-01

The large-order behaviour of power series used in quantum theory (perturbation series and the operator-product expansion) is discussed and relevant summation methods are reviewed. It is emphasised that, in most physically interesting situations, the mere knowledge of the expansion coefficients is not sufficient for a unique determination of the function expanded, and the necessity of some additional, extra-perturbative, input is pointed out. Several possible nonperturbative inputs are suggested. Applications to various problems of quantum chromodynamics are considered. This lecture was presented on the special Memorial Day dedicated to Professor Ryszard R˛czka at this Workshop. The last section is devoted to my personal recollections of this remarkable personality.

Option pricing from wavelet-filtered financial series

NASA Astrophysics Data System (ADS)

de Almeida, V. T. X.; Moriconi, L.

2012-10-01

We perform wavelet decomposition of high frequency financial time series into large and small time scale components. Taking the FTSE100 index as a case study, and working with the Haar basis, it turns out that the small scale component defined by most (≃99.6%) of the wavelet coefficients can be neglected for the purpose of option premium evaluation. The relevance of the hugely compressed information provided by low-pass wavelet-filtering is related to the fact that the non-gaussian statistical structure of the original financial time series is essentially preserved for expiration times which are larger than just one trading day.

Superfund Redevelopment Initiative Quarterly Webinar Series

EPA Pesticide Factsheets

Superfund Redevelopment Initiative hosts a series of quarterly webinars on redevelopment of Superfund sites across the country that discuss the different types of reuse that are possible and share how particular sites have become reuse success stories.

78 FR 69888 - ETFis Series Trust I, et al.; Notice of Application

Federal Register 2010, 2011, 2012, 2013, 2014

2013-11-21

...] ETFis Series Trust I, et al.; Notice of Application November 15, 2013. AGENCY: Securities and Exchange... Units; and (e) certain registered management investment companies and unit investment trusts outside of the same group of investment companies as the series to acquire Shares. APPLICANTS: ETFis Series Trust...

Approximate Entropies for Stochastic Time Series and EKG Time Series of Patients with Epilepsy and Pseudoseizures

NASA Astrophysics Data System (ADS)

Vyhnalek, Brian; Zurcher, Ulrich; O'Dwyer, Rebecca; Kaufman, Miron

2009-10-01

A wide range of heart rate irregularities have been reported in small studies of patients with temporal lobe epilepsy [TLE]. We hypothesize that patients with TLE display cardiac dysautonomia in either a subclinical or clinical manner. In a small study, we have retrospectively identified (2003-8) two groups of patients from the epilepsy monitoring unit [EMU] at the Cleveland Clinic. No patients were diagnosed with cardiovascular morbidities. The control group consisted of patients with confirmed pseudoseizures and the experimental group had confirmed right temporal lobe epilepsy through a seizure free outcome after temporal lobectomy. We quantified the heart rate variability using the approximate entropy [ApEn]. We found similar values of the ApEn in all three states of consciousness (awake, sleep, and proceeding seizure onset). In the TLE group, there is some evidence for greater variability in the awake than in either the sleep or proceeding seizure onset. Here we present results for mathematically-generated time series: the heart rate fluctuations ξ follow the γ statistics i.e., p(ξ)=γ-1(k) ξ^k exp(-ξ). This probability function has well-known properties and its Shannon entropy can be expressed in terms of the γ-function. The parameter k allows us to generate a family of heart rate time series with different statistics. The ApEn calculated for the generated time series for different values of k mimic the properties found for the TLE and pseudoseizure group. Our results suggest that the ApEn is an effective tool to probe differences in statistics of heart rate fluctuations.

Time series patterns and language support in DBMS

NASA Astrophysics Data System (ADS)

Telnarova, Zdenka

2017-07-01

This contribution is focused on pattern type Time Series as a rich in semantics representation of data. Some example of implementation of this pattern type in traditional Data Base Management Systems is briefly presented. There are many approaches how to manipulate with patterns and query patterns. Crucial issue can be seen in systematic approach to pattern management and specific pattern query language which takes into consideration semantics of patterns. Query language SQL-TS for manipulating with patterns is shown on Time Series data.

Using forbidden ordinal patterns to detect determinism in irregularly sampled time series.

PubMed

Kulp, C W; Chobot, J M; Niskala, B J; Needhammer, C J

2016-02-01

It is known that when symbolizing a time series into ordinal patterns using the Bandt-Pompe (BP) methodology, there will be ordinal patterns called forbidden patterns that do not occur in a deterministic series. The existence of forbidden patterns can be used to identify deterministic dynamics. In this paper, the ability to use forbidden patterns to detect determinism in irregularly sampled time series is tested on data generated from a continuous model system. The study is done in three parts. First, the effects of sampling time on the number of forbidden patterns are studied on regularly sampled time series. The next two parts focus on two types of irregular-sampling, missing data and timing jitter. It is shown that forbidden patterns can be used to detect determinism in irregularly sampled time series for low degrees of sampling irregularity (as defined in the paper). In addition, comments are made about the appropriateness of using the BP methodology to symbolize irregularly sampled time series.

OceanSITES: Sustained Ocean Time Series Observations in the Global Ocean.

NASA Astrophysics Data System (ADS)

Weller, R. A.; Gallage, C.; Send, U.; Lampitt, R. S.; Lukas, R.

2016-02-01

Time series observations at critical or representative locations are an essential element of a global ocean observing system that is unique and complements other approaches to sustained observing. OceanSITES is an international group of oceanographers associated with such time series sites. OceanSITES exists to promote the continuation and extension of ocean time series sites around the globe. It also exists to plan and oversee the global array of sites in order to address the needs of research, climate change detection, operational applications, and policy makers. OceanSITES is a voluntary group that sits as an Action Group of the JCOMM-OPS Data Buoy Cooperation Panel, where JCOMM-OPS is the operational ocean observing oversight group of the Joint Commission on Oceanography and Marine Meteorology of the International Oceanographic Commission and the World Meteorological Organization. The way forward includes working to complete the global array, moving toward multidisciplinary instrumentation on a subset of the sites, and increasing utilization of the time series data, which are freely available from two Global Data Assembly Centers, one at the National Data Buoy Center and one at Coriolis at IFREMER. One recnet OceanSITES initiative and several results from OceanSITES time series sites are presented. The recent initiative was the assembly of a pool of temperature/conductivity recorders fro provision to OceanSITES sites in order to provide deep ocean temperature and salinity time series. Examples from specific sites include: a 15-year record of surface meteorology and air-sea fluxes from off northern Chile that shows evidence of long-term trends in surface forcing; change in upper ocean salinity and stratification in association with regional change in the hydrological cycle can be seen at the Hawaii time series site; results from monitoring Atlantic meridional transport; and results from a European multidisciplinary time series site.

UAS in the NAS Flight Test Series 3 Overview

NASA Technical Reports Server (NTRS)

Murphy, James R.

2015-01-01

The UAS Integration in the NAS Project is conducting a series of flight tests to acheive the following objectives: 1.) Validate results previously collected during project simulations with live data 2.) Evaluate TCAS IISS interoperability 3.) Test fully integrated system in a relevant live test environment 4.) Inform final DAA and C2 MOPS 5.) Reduce risk for Flight Test Series 4.

Writing for professional publication. Part 12: summary of the series.

PubMed

Fowler, John

The previous articles in this series have explored the practical issues of writing for professional publication. In this final article, John Fowler, an experienced nursing lecturer and author, summarises the series and presents an overview of the practicalities of writing for publication.

Operation of the J-series thruster using inert gas

NASA Technical Reports Server (NTRS)

Rawlin, V. K.

1982-01-01

Electron bombardment ion thrusters using inert gases are candidates for large space systems. The J-Series 30 cm diameter thruster, designed for operation up to 3 k-W with mercury, is at a state of technology readiness. The characteristics of operation with xenon, krypton, and argon propellants in a J-Series thruster with that obtained with mercury are compared. The performance of the discharge chamber, ion optics, and neutralizer and the overall efficiency as functions of input power and specific impulse and thruster lifetime were evaluated. As expected, the discharge chamber performance with inert gases decreased with decreasing atomic mass. Aspects of the J-Series thruster design which would require modification to provide operation at high power with insert gases were identified.

Adsorbate-induced lattice deformation in IRMOF-74 series

DOE PAGES

Jawahery, Sudi; Simon, Cory M.; Braun, Efrem; ...

2017-01-09

Here, IRMOF-74 analogues are among the most widely studied metal-organic frameworks (MOFs) for adsorption applications because of their one-dimensional channels and high metal density. Most studies involving the IRMOF-74 series assume that the crystal lattice is rigid. This assumption guides the interpretation of experimental data, as changes in the crystal symmetry have so far been ignored as a possibility in the literature. Here, we report a deformation pattern, induced by the adsorption of argon, for IRMOF-74-V. This work has two main implications. First, we use molecular simulations to demonstrate that the IRMOF-74 series undergoes a deformation that is similar tomore » the mechanism behind breathing MOFs, but is unique because the deformation pattern extends beyond a single unit cell of the original structure. Second, we provide an alternative interpretation of experimental small-angle X-ray scattering profiles of these systems, which changes how we view the fundamentals of adsorption in this MOF series.« less

Time series, correlation matrices and random matrix models

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

Vinayak; Seligman, Thomas H.

2014-01-08

In this set of five lectures the authors have presented techniques to analyze open classical and quantum systems using correlation matrices. For diverse reasons we shall see that random matrices play an important role to describe a null hypothesis or a minimum information hypothesis for the description of a quantum system or subsystem. In the former case various forms of correlation matrices of time series associated with the classical observables of some system. The fact that such series are necessarily finite, inevitably introduces noise and this finite time influence lead to a random or stochastic component in these time series.more » By consequence random correlation matrices have a random component, and corresponding ensembles are used. In the latter we use random matrices to describe high temperature environment or uncontrolled perturbations, ensembles of differing chaotic systems etc. The common theme of the lectures is thus the importance of random matrix theory in a wide range of fields in and around physics.« less

Multiresolution analysis of Bursa Malaysia KLCI time series

NASA Astrophysics Data System (ADS)

Ismail, Mohd Tahir; Dghais, Amel Abdoullah Ahmed

2017-05-01

In general, a time series is simply a sequence of numbers collected at regular intervals over a period. Financial time series data processing is concerned with the theory and practice of processing asset price over time, such as currency, commodity data, and stock market data. The primary aim of this study is to understand the fundamental characteristics of selected financial time series by using the time as well as the frequency domain analysis. After that prediction can be executed for the desired system for in sample forecasting. In this study, multiresolution analysis which the assist of discrete wavelet transforms (DWT) and maximal overlap discrete wavelet transform (MODWT) will be used to pinpoint special characteristics of Bursa Malaysia KLCI (Kuala Lumpur Composite Index) daily closing prices and return values. In addition, further case study discussions include the modeling of Bursa Malaysia KLCI using linear ARIMA with wavelets to address how multiresolution approach improves fitting and forecasting results.

On nonstationarity and antipersistency in global temperature series

NASA Astrophysics Data System (ADS)

KäRner, O.

2002-10-01

Statistical analysis is carried out for satellite-based global daily tropospheric and stratospheric temperature anomaly and solar irradiance data sets. Behavior of the series appears to be nonstationary with stationary daily increments. Estimating long-range dependence between the increments reveals a remarkable difference between the two temperature series. Global average tropospheric temperature anomaly behaves similarly to the solar irradiance anomaly. Their daily increments show antipersistency for scales longer than 2 months. The property points at a cumulative negative feedback in the Earth climate system governing the tropospheric variability during the last 22 years. The result emphasizes a dominating role of the solar irradiance variability in variations of the tropospheric temperature and gives no support to the theory of anthropogenic climate change. The global average stratospheric temperature anomaly proceeds like a 1-dim random walk at least up to 11 years, allowing good presentation by means of the autoregressive integrated moving average (ARIMA) models for monthly series.

Adsorbate-induced lattice deformation in IRMOF-74 series

PubMed Central

Jawahery, Sudi; Simon, Cory M.; Braun, Efrem; Witman, Matthew; Tiana, Davide; Vlaisavljevich, Bess; Smit, Berend

2017-01-01

IRMOF-74 analogues are among the most widely studied metal-organic frameworks (MOFs) for adsorption applications because of their one-dimensional channels and high metal density. Most studies involving the IRMOF-74 series assume that the crystal lattice is rigid. This assumption guides the interpretation of experimental data, as changes in the crystal symmetry have so far been ignored as a possibility in the literature. Here, we report a deformation pattern, induced by the adsorption of argon, for IRMOF-74-V. This work has two main implications. First, we use molecular simulations to demonstrate that the IRMOF-74 series undergoes a deformation that is similar to the mechanism behind breathing MOFs, but is unique because the deformation pattern extends beyond a single unit cell of the original structure. Second, we provide an alternative interpretation of experimental small-angle X-ray scattering profiles of these systems, which changes how we view the fundamentals of adsorption in this MOF series. PMID:28067222

Adsorbate-induced lattice deformation in IRMOF-74 series

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

Jawahery, Sudi; Simon, Cory M.; Braun, Efrem

Here, IRMOF-74 analogues are among the most widely studied metal-organic frameworks (MOFs) for adsorption applications because of their one-dimensional channels and high metal density. Most studies involving the IRMOF-74 series assume that the crystal lattice is rigid. This assumption guides the interpretation of experimental data, as changes in the crystal symmetry have so far been ignored as a possibility in the literature. Here, we report a deformation pattern, induced by the adsorption of argon, for IRMOF-74-V. This work has two main implications. First, we use molecular simulations to demonstrate that the IRMOF-74 series undergoes a deformation that is similar tomore » the mechanism behind breathing MOFs, but is unique because the deformation pattern extends beyond a single unit cell of the original structure. Second, we provide an alternative interpretation of experimental small-angle X-ray scattering profiles of these systems, which changes how we view the fundamentals of adsorption in this MOF series.« less

Using missing ordinal patterns to detect nonlinearity in time series data.

PubMed

Kulp, Christopher W; Zunino, Luciano; Osborne, Thomas; Zawadzki, Brianna

2017-08-01

The number of missing ordinal patterns (NMP) is the number of ordinal patterns that do not appear in a series after it has been symbolized using the Bandt and Pompe methodology. In this paper, the NMP is demonstrated as a test for nonlinearity using a surrogate framework in order to see if the NMP for a series is statistically different from the NMP of iterative amplitude adjusted Fourier transform (IAAFT) surrogates. It is found that the NMP works well as a test statistic for nonlinearity, even in the cases of very short time series. Both model and experimental time series are used to demonstrate the efficacy of the NMP as a test for nonlinearity.

Kinetic Titration Series with Biolayer Interferometry

PubMed Central

Frenzel, Daniel; Willbold, Dieter

2014-01-01

Biolayer interferometry is a method to analyze protein interactions in real-time. In this study, we illustrate the usefulness to quantitatively analyze high affinity protein ligand interactions employing a kinetic titration series for characterizing the interactions between two pairs of interaction patterns, in particular immunoglobulin G and protein G B1 as well as scFv IC16 and amyloid beta (1–42). Kinetic titration series are commonly used in surface plasmon resonance and involve sequential injections of analyte over a desired concentration range on a single ligand coated sensor chip without waiting for complete dissociation between the injections. We show that applying this method to biolayer interferometry is straightforward and i) circumvents problems in data evaluation caused by unavoidable sensor differences, ii) saves resources and iii) increases throughput if screening a multitude of different analyte/ligand combinations. PMID:25229647

Kinetic titration series with biolayer interferometry.

PubMed

Frenzel, Daniel; Willbold, Dieter

2014-01-01

Biolayer interferometry is a method to analyze protein interactions in real-time. In this study, we illustrate the usefulness to quantitatively analyze high affinity protein ligand interactions employing a kinetic titration series for characterizing the interactions between two pairs of interaction patterns, in particular immunoglobulin G and protein G B1 as well as scFv IC16 and amyloid beta (1-42). Kinetic titration series are commonly used in surface plasmon resonance and involve sequential injections of analyte over a desired concentration range on a single ligand coated sensor chip without waiting for complete dissociation between the injections. We show that applying this method to biolayer interferometry is straightforward and i) circumvents problems in data evaluation caused by unavoidable sensor differences, ii) saves resources and iii) increases throughput if screening a multitude of different analyte/ligand combinations.

Leadership. Research in Management Series.

ERIC Educational Resources Information Center

Neider, Linda L. Ed.; Schriesheim, Chester A., Ed.

This volume in the Research in Management series is devoted to the field of leadership--a look at where it has been and where it seems to be going. A "Foreword" (Linda L. Neider, Chester A. Schriesheim) is followed by seven chapters highlighting creative, new looks at leadership and adept analyses of leadership theories that have already…

Series Connected Buck-Boost Regulator

NASA Technical Reports Server (NTRS)

Birchenough, Arthur G. (Inventor)

2006-01-01

A Series Connected Buck-Boost Regulator (SCBBR) that switches only a fraction of the input power, resulting in relatively high efficiencies. The SCBBR has multiple operating modes including a buck, a boost, and a current limiting mode, so that an output voltage of the SCBBR ranges from below the source voltage to above the source voltage.

JWST NIRCam Time Series Observations

NASA Technical Reports Server (NTRS)

Greene, Tom; Schlawin, E.

2017-01-01

We explain how to make time-series observations with the Near-Infrared camera (NIRCam) science instrument of the James Webb Space Telescope. Both photometric and spectroscopic observations are described. We present the basic capabilities and performance of NIRCam and show examples of how to set its observing parameters using the Space Telescope Science Institute's Astronomer's Proposal Tool (APT).

Farming. Canada at Work Series.

ERIC Educational Resources Information Center

Love, Ann; Drake, Jane

This book is part of the Canada At Work series that introduces children to the people, machines, work and environmental concerns involved in bringing to market the products from important Canadian natural resources. This volume features a year-round look at two kinds of agriculture in Canada. On the vegetable farm, children find out about spring…

SeaWiFS Postlaunch Technical Report Series Cumulative Index

NASA Technical Reports Server (NTRS)

Hooker, Stanford B. (Editor); Firestone, Elaine R. (Editor)

2001-01-01

The Sea-viewing Wide Field-of-view Sensor (SeaWiFS) is the follow-on ocean color instrument to the Coastal Zone Color Scanner (CZCS), which ceased operations in 1986, after an eight-year mission. SeaWiFS was launched on 1 August 1997, onboard the OrbView-2 satellite, built by Orbital Sciences Corporation (OSC). The SeaWiFS Project at the National Aeronautics and Space Administration (NASA) Goddard Space Flight Center (GSFC), undertook the responsibility of documenting all aspects of this mission, which is critical to the ocean color and marine science communities. The start of this documentation was titled the SeaWiFS Technical Report Series, which ended after 43 volumes were published. A follow-on series was started, titled the SeaWiFS Postlaunch Technical Report Series. This particular volume of the so-called "Postlaunch Series" serves as a reference, or guidebook, to the previous 11 volumes and consists of 5 sections including an errata, an addendum, an index to key words and phrases, a list of acronyms used, and a list of all references cited. The editors will publish a cumulative index of this type after every five volumes.

Use of Time-Series, ARIMA Designs to Assess Program Efficacy.

ERIC Educational Resources Information Center

Braden, Jeffery P.; And Others

1990-01-01

Illustrates use of time-series designs for determining efficacy of interventions with fictitious data describing drug-abuse prevention program. Discusses problems and procedures associated with time-series data analysis using Auto Regressive Integrated Moving Averages (ARIMA) models. Example illustrates application of ARIMA analysis for…

hctsa: A Computational Framework for Automated Time-Series Phenotyping Using Massive Feature Extraction.

PubMed

Fulcher, Ben D; Jones, Nick S

2017-11-22

Phenotype measurements frequently take the form of time series, but we currently lack a systematic method for relating these complex data streams to scientifically meaningful outcomes, such as relating the movement dynamics of organisms to their genotype or measurements of brain dynamics of a patient to their disease diagnosis. Previous work addressed this problem by comparing implementations of thousands of diverse scientific time-series analysis methods in an approach termed highly comparative time-series analysis. Here, we introduce hctsa, a software tool for applying this methodological approach to data. hctsa includes an architecture for computing over 7,700 time-series features and a suite of analysis and visualization algorithms to automatically select useful and interpretable time-series features for a given application. Using exemplar applications to high-throughput phenotyping experiments, we show how hctsa allows researchers to leverage decades of time-series research to quantify and understand informative structure in time-series data. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

USL/DBMS NASA/RECON working paper series. Standards

NASA Technical Reports Server (NTRS)

Dominick, Wayne D. (Editor); Chum, Frank Y.

1984-01-01

The USL/DBMS NASA/RECON Working Paper Series contains a collection of reports representing results of activities being conducted by the Computer Science Department of the University of Southwestern Louisiana pursuant to the specifications of NASA Contract number NASw-3846. The work on this portion of the contract is being performed jointly by the University of Southwestern Louisiana and Southern University. This report contains the full set of standards for the development, formatting, reviewing, and issuance of entries within the USL/DBMS NASA/RECON Working Paper Series.

Multivariate stochastic analysis for Monthly hydrological time series at Cuyahoga River Basin

NASA Astrophysics Data System (ADS)

zhang, L.

2011-12-01

Copula has become a very powerful statistic and stochastic methodology in case of the multivariate analysis in Environmental and Water resources Engineering. In recent years, the popular one-parameter Archimedean copulas, e.g. Gumbel-Houggard copula, Cook-Johnson copula, Frank copula, the meta-elliptical copula, e.g. Gaussian Copula, Student-T copula, etc. have been applied in multivariate hydrological analyses, e.g. multivariate rainfall (rainfall intensity, duration and depth), flood (peak discharge, duration and volume), and drought analyses (drought length, mean and minimum SPI values, and drought mean areal extent). Copula has also been applied in the flood frequency analysis at the confluences of river systems by taking into account the dependence among upstream gauge stations rather than by using the hydrological routing technique. In most of the studies above, the annual time series have been considered as stationary signal which the time series have been assumed as independent identically distributed (i.i.d.) random variables. But in reality, hydrological time series, especially the daily and monthly hydrological time series, cannot be considered as i.i.d. random variables due to the periodicity existed in the data structure. Also, the stationary assumption is also under question due to the Climate Change and Land Use and Land Cover (LULC) change in the fast years. To this end, it is necessary to revaluate the classic approach for the study of hydrological time series by relaxing the stationary assumption by the use of nonstationary approach. Also as to the study of the dependence structure for the hydrological time series, the assumption of same type of univariate distribution also needs to be relaxed by adopting the copula theory. In this paper, the univariate monthly hydrological time series will be studied through the nonstationary time series analysis approach. The dependence structure of the multivariate monthly hydrological time series will be

A hybrid-domain approach for modeling climate data time series

NASA Astrophysics Data System (ADS)

Wen, Qiuzi H.; Wang, Xiaolan L.; Wong, Augustine

2011-09-01

In order to model climate data time series that often contain periodic variations, trends, and sudden changes in mean (mean shifts, mostly artificial), this study proposes a hybrid-domain (HD) algorithm, which incorporates a time domain test and a newly developed frequency domain test through an iterative procedure that is analogue to the well known backfitting algorithm. A two-phase competition procedure is developed to address the confounding issue between modeling periodic variations and mean shifts. A variety of distinctive features of climate data time series, including trends, periodic variations, mean shifts, and a dependent noise structure, can be modeled in tandem using the HD algorithm. This is particularly important for homogenization of climate data from a low density observing network in which reference series are not available to help preserve climatic trends and long-term periodic variations, preventing them from being mistaken as artificial shifts. The HD algorithm is also powerful in estimating trend and periodicity in a homogeneous data time series (i.e., in the absence of any mean shift). The performance of the HD algorithm (in terms of false alarm rate and hit rate in detecting shifts/cycles, and estimation accuracy) is assessed via a simulation study. Its power is further illustrated through its application to a few climate data time series.

PRESEE: An MDL/MML Algorithm to Time-Series Stream Segmenting

PubMed Central

Jiang, Yexi; Tang, Mingjie; Yuan, Changan; Tang, Changjie

2013-01-01

Time-series stream is one of the most common data types in data mining field. It is prevalent in fields such as stock market, ecology, and medical care. Segmentation is a key step to accelerate the processing speed of time-series stream mining. Previous algorithms for segmenting mainly focused on the issue of ameliorating precision instead of paying much attention to the efficiency. Moreover, the performance of these algorithms depends heavily on parameters, which are hard for the users to set. In this paper, we propose PRESEE (parameter-free, real-time, and scalable time-series stream segmenting algorithm), which greatly improves the efficiency of time-series stream segmenting. PRESEE is based on both MDL (minimum description length) and MML (minimum message length) methods, which could segment the data automatically. To evaluate the performance of PRESEE, we conduct several experiments on time-series streams of different types and compare it with the state-of-art algorithm. The empirical results show that PRESEE is very efficient for real-time stream datasets by improving segmenting speed nearly ten times. The novelty of this algorithm is further demonstrated by the application of PRESEE in segmenting real-time stream datasets from ChinaFLUX sensor networks data stream. PMID:23956693

Refined composite multiscale weighted-permutation entropy of financial time series

NASA Astrophysics Data System (ADS)

Zhang, Yongping; Shang, Pengjian

2018-04-01

For quantifying the complexity of nonlinear systems, multiscale weighted-permutation entropy (MWPE) has recently been proposed. MWPE has incorporated amplitude information and been applied to account for the multiple inherent dynamics of time series. However, MWPE may be unreliable, because its estimated values show large fluctuation for slight variation of the data locations, and a significant distinction only for the different length of time series. Therefore, we propose the refined composite multiscale weighted-permutation entropy (RCMWPE). By comparing the RCMWPE results with other methods' results on both synthetic data and financial time series, RCMWPE method shows not only the advantages inherited from MWPE but also lower sensitivity to the data locations, more stable and much less dependent on the length of time series. Moreover, we present and discuss the results of RCMWPE method on the daily price return series from Asian and European stock markets. There are significant differences between Asian markets and European markets, and the entropy values of Hang Seng Index (HSI) are close to but higher than those of European markets. The reliability of the proposed RCMWPE method has been supported by simulations on generated and real data. It could be applied to a variety of fields to quantify the complexity of the systems over multiple scales more accurately.

PRESEE: an MDL/MML algorithm to time-series stream segmenting.

PubMed

Xu, Kaikuo; Jiang, Yexi; Tang, Mingjie; Yuan, Changan; Tang, Changjie

2013-01-01

Time-series stream is one of the most common data types in data mining field. It is prevalent in fields such as stock market, ecology, and medical care. Segmentation is a key step to accelerate the processing speed of time-series stream mining. Previous algorithms for segmenting mainly focused on the issue of ameliorating precision instead of paying much attention to the efficiency. Moreover, the performance of these algorithms depends heavily on parameters, which are hard for the users to set. In this paper, we propose PRESEE (parameter-free, real-time, and scalable time-series stream segmenting algorithm), which greatly improves the efficiency of time-series stream segmenting. PRESEE is based on both MDL (minimum description length) and MML (minimum message length) methods, which could segment the data automatically. To evaluate the performance of PRESEE, we conduct several experiments on time-series streams of different types and compare it with the state-of-art algorithm. The empirical results show that PRESEE is very efficient for real-time stream datasets by improving segmenting speed nearly ten times. The novelty of this algorithm is further demonstrated by the application of PRESEE in segmenting real-time stream datasets from ChinaFLUX sensor networks data stream.

Stochastic modeling of hourly rainfall times series in Campania (Italy)

NASA Astrophysics Data System (ADS)

Giorgio, M.; Greco, R.

2009-04-01

Occurrence of flowslides and floods in small catchments is uneasy to predict, since it is affected by a number of variables, such as mechanical and hydraulic soil properties, slope morphology, vegetation coverage, rainfall spatial and temporal variability. Consequently, landslide risk assessment procedures and early warning systems still rely on simple empirical models based on correlation between recorded rainfall data and observed landslides and/or river discharges. Effectiveness of such systems could be improved by reliable quantitative rainfall prediction, which can allow gaining larger lead-times. Analysis of on-site recorded rainfall height time series represents the most effective approach for a reliable prediction of local temporal evolution of rainfall. Hydrological time series analysis is a widely studied field in hydrology, often carried out by means of autoregressive models, such as AR, ARMA, ARX, ARMAX (e.g. Salas [1992]). Such models gave the best results when applied to the analysis of autocorrelated hydrological time series, like river flow or level time series. Conversely, they are not able to model the behaviour of intermittent time series, like point rainfall height series usually are, especially when recorded with short sampling time intervals. More useful for this issue are the so-called DRIP (Disaggregated Rectangular Intensity Pulse) and NSRP (Neymann-Scott Rectangular Pulse) model [Heneker et al., 2001; Cowpertwait et al., 2002], usually adopted to generate synthetic point rainfall series. In this paper, the DRIP model approach is adopted, in which the sequence of rain storms and dry intervals constituting the structure of rainfall time series is modeled as an alternating renewal process. Final aim of the study is to provide a useful tool to implement an early warning system for hydrogeological risk management. Model calibration has been carried out with hourly rainfall hieght data provided by the rain gauges of Campania Region civil

On the type series of Scinax perpusillus (Lutz & Lutz, 1939) (Anura: Hylidae).

PubMed

Colaço, Gustavo; Silva, Helio Ricardo Da

2016-08-19

The literature regarding the type series of Scinax perpusillus (Lutz & Lutz, 1939) presents two distinct numbers for the holotype. In 1973, thirty-four years after the description, Bertha Lutz associated numbers to the type series. This numbering has been followed by subsequent reviewers of Scinax ever since, with exception of Peixoto (1987) who assigned another number to the holotype. Our reevaluation of the literature and examination of the type series allowed us to access that, in both cases, the numbers were incorrectly assigned to the specimens and determine the proper museum numbers for this series.

Technology Utilization Conference Series, volume 2

NASA Technical Reports Server (NTRS)

1975-01-01

Proceedings of a series of technology utilization conferences are presented. Commercial applications of space technology, machine tool and metal fabrication, energy and pollution, and mechanical design are among the topics discussed. Emphasis is placed on technology transfer and the minority businessman.

Child restraint workshop series. Volume 1

DOT National Transportation Integrated Search

1979-09-01

This final report describes the planning and implementing details of the Child Restraint Workshop series. A child restraint workshop was conducted in each of the : ten NHTSA regions. The purpose of the workshops was to improve the effectiveness of gr...

Equal Plate Charges on Series Capacitors?

ERIC Educational Resources Information Center

Illman, B. L.; Carlson, G. T.

1994-01-01

Provides a line of reasoning in support of the contention that the equal charge proposition is at best an approximation. Shows how the assumption of equal plate charge on capacitors in series contradicts the conservative nature of the electric field. (ZWH)

Historical Perspectives and Future Needs in the Development of the Soil Series Concept

NASA Astrophysics Data System (ADS)

Beaudette, Dylan E.; Brevik, Eric C.; Indorante, Samuel J.

2016-04-01

The soil series concept is an ever-evolving understanding of soil profile observations, their connection to the landscape, and functional limits on the range in characteristics that affect management. Historically, the soil series has played a pivotal role in the development of soil-landscape theory, modern soil survey methods, and concise delivery of soils information to the end-user-- in other words, soil series is the palette from which soil survey reports are crafted. Over the last 20 years the soil series has received considerable criticism as a means of soil information organization (soil survey development) and delivery (end-user application of soil survey data), with increasing pressure (internal and external) to retire the soil series. We propose that a modern re-examination of soil series information could help address several of the long-standing critiques of soil survey: consistency across survey vintage and political divisions and more robust estimates of soil properties and associated uncertainty. A new library of soil series data would include classic narratives describing morphology and management, quantitative descriptions of soil properties and their ranges, graphical depiction of the relationships between associated soil series, block diagrams illustrating soil-landscape models, maps of series distribution, and a probabilistic representation of a "typical" soil profile. These data would be derived from re-correlation of existing morphologic and characterization data informed by modern statistical methods and regional expertise.

Developing an Undergraduate Public Health Introductory Core Course Series.

PubMed

Nelson-Hurwitz, Denise C; Tagorda, Michelle; Kehl, Lisa; Buchthal, Opal V; Braun, Kathryn L

2018-01-01

The number of undergraduate public health education programs is increasing, but few publications provide examples of introductory public health courses that provide foundational knowledge and meet 2016 Council on Education in Public Health (CEPH) accreditation standards. This article presents the development and testing of a three-course, introductory series in public health at the University of Hawai'i at Mānoa (UHM). Development was informed by best pedagogical practices in education, web review of existing programs, literature review, key informant interviews, and accreditation standards. Student mastery of required concepts, domains, and competencies is assessed through testing and class assignments. Data from course evaluations, students' exit questionnaires at graduation, and faculty feedback were used to continuously evolve and adapt the curriculum. The three-course series-including Introduction to Public Health, Public Health Issues in Hawai'i, and Introduction to Global Health-was designed to provide incoming undergraduate public health students with a foundation in local, national, and global public health concepts and domains, while improving their skills in public health communication and information literacy. Data from class assignments, examinations, and later coursework suggest students are mastering the course materials and gaining required competencies. Data from course evaluation and exit questionnaires suggest that the students appreciate the series' approach and the challenge to apply course concepts locally and globally in subsequent courses. This foundational public health series provides a model for an introductory course series that can be implemented with existing resources by most programs, meets the new CEPH requirements, is well-received by students, and prepares students well for upper-division public health courses.

Time Series Modelling of Syphilis Incidence in China from 2005 to 2012.

PubMed

Zhang, Xingyu; Zhang, Tao; Pei, Jiao; Liu, Yuanyuan; Li, Xiaosong; Medrano-Gracia, Pau

2016-01-01

The infection rate of syphilis in China has increased dramatically in recent decades, becoming a serious public health concern. Early prediction of syphilis is therefore of great importance for heath planning and management. In this paper, we analyzed surveillance time series data for primary, secondary, tertiary, congenital and latent syphilis in mainland China from 2005 to 2012. Seasonality and long-term trend were explored with decomposition methods. Autoregressive integrated moving average (ARIMA) was used to fit a univariate time series model of syphilis incidence. A separate multi-variable time series for each syphilis type was also tested using an autoregressive integrated moving average model with exogenous variables (ARIMAX). The syphilis incidence rates have increased three-fold from 2005 to 2012. All syphilis time series showed strong seasonality and increasing long-term trend. Both ARIMA and ARIMAX models fitted and estimated syphilis incidence well. All univariate time series showed highest goodness-of-fit results with the ARIMA(0,0,1)×(0,1,1) model. Time series analysis was an effective tool for modelling the historical and future incidence of syphilis in China. The ARIMAX model showed superior performance than the ARIMA model for the modelling of syphilis incidence. Time series correlations existed between the models for primary, secondary, tertiary, congenital and latent syphilis.

31 CFR 351.49 - How are definitive Series EE savings bonds delivered?

Code of Federal Regulations, 2010 CFR

2010-07-01

... 31 Money and Finance: Treasury 2 2010-07-01 2010-07-01 false How are definitive Series EE savings bonds delivered? 351.49 Section 351.49 Money and Finance: Treasury Regulations Relating to Money and... UNITED STATES SAVINGS BONDS, SERIES EE Definitive Series EE Savings Bonds § 351.49 How are definitive...

31 CFR 359.37 - How are definitive Series I savings bonds delivered?

Code of Federal Regulations, 2010 CFR

2010-07-01

... 31 Money and Finance: Treasury 2 2010-07-01 2010-07-01 false How are definitive Series I savings bonds delivered? 359.37 Section 359.37 Money and Finance: Treasury Regulations Relating to Money and... UNITED STATES SAVINGS BONDS, SERIES I Definitive Series I Savings Bonds § 359.37 How are definitive...

Improving GNSS time series for volcano monitoring: application to Canary Islands (Spain)

NASA Astrophysics Data System (ADS)

García-Cañada, Laura; Sevilla, Miguel J.; Pereda de Pablo, Jorge; Domínguez Cerdeña, Itahiza

2017-04-01

The number of permanent GNSS stations has increased significantly in recent years for different geodetic applications such as volcano monitoring, which require a high precision. Recently we have started to have coordinates time series long enough so that we can apply different analysis and filters that allow us to improve the GNSS coordinates results. Following this idea we have processed data from GNSS permanent stations used by the Spanish Instituto Geográfico Nacional (IGN) for volcano monitoring in Canary Islands to obtained time series by double difference processing method with Bernese v5.0 for the period 2007-2014. We have identified the characteristics of these time series and obtained models to estimate velocities with greater accuracy and more realistic uncertainties. In order to improve the results we have used two kinds of filters to improve the time series. The first, a spatial filter, has been computed using the series of residuals of all stations in the Canary Islands without an anomalous behaviour after removing a linear trend. This allows us to apply this filter to all sets of coordinates of the permanent stations reducing their dispersion. The second filter takes account of the temporal correlation in the coordinate time series for each station individually. A research about the evolution of the velocity depending on the series length has been carried out and it has demonstrated the need for using time series of at least four years. Therefore, in those stations with more than four years of data, we calculated the velocity and the characteristic parameters in order to have time series of residuals. This methodology has been applied to the GNSS data network in El Hierro (Canary Islands) during the 2011-2012 eruption and the subsequent magmatic intrusions (2012-2014). The results show that in the new series it is easier to detect anomalous behaviours in the coordinates, so they are most useful to detect crustal deformations in volcano monitoring.

Introduction to Concrete Masonry. Introduction to Construction Series. Instructor Edition.

ERIC Educational Resources Information Center

Oklahoma State Dept. of Vocational and Technical Education, Stillwater. Curriculum and Instructional Materials Center.

This competency-based curriculum guide on the specialty area of concrete masonry is part of the Introduction to Construction series. The series is designed with the flexible training requirements of open shop contractors, preapprenticeship programs, multicraft high school programs, technology education programs, and cooperative education programs…

Introduction to Sheet Metal. Introduction to Construction Series. Instructor Edition.

ERIC Educational Resources Information Center

Oklahoma State Dept. of Vocational and Technical Education, Stillwater. Curriculum and Instructional Materials Center.

This competency-based curriculum guide on the specialty area of sheet metal is part of the Introduction to Construction series. The series is designed with the flexible training requirements of open shop contractors, preapprenticeship programs, multicraft high school programs, technology education programs, and cooperative education programs in…

Loop series for discrete statistical models on graphs

NASA Astrophysics Data System (ADS)

Chertkov, Michael; Chernyak, Vladimir Y.

2006-06-01

In this paper we present the derivation details, logic, and motivation for the three loop calculus introduced in Chertkov and Chernyak (2006 Phys. Rev. E 73 065102(R)). Generating functions for each of the three interrelated discrete statistical models are expressed in terms of a finite series. The first term in the series corresponds to the Bethe-Peierls belief-propagation (BP) contribution; the other terms are labelled by loops on the factor graph. All loop contributions are simple rational functions of spin correlation functions calculated within the BP approach. We discuss two alternative derivations of the loop series. One approach implements a set of local auxiliary integrations over continuous fields with the BP contribution corresponding to an integrand saddle-point value. The integrals are replaced by sums in the complementary approach, briefly explained in Chertkov and Chernyak (2006 Phys. Rev. E 73 065102(R)). Local gauge symmetry transformations that clarify an important invariant feature of the BP solution are revealed in both approaches. The individual terms change under the gauge transformation while the partition function remains invariant. The requirement for all individual terms to be nonzero only for closed loops in the factor graph (as opposed to paths with loose ends) is equivalent to fixing the first term in the series to be exactly equal to the BP contribution. Further applications of the loop calculus to problems in statistical physics, computer and information sciences are discussed.

Case Series.

PubMed

Vetrayan, Jayachandran; Othman, Suhana; Victor Paulraj, Smily Jesu Priya

2017-01-01

To assess the effectiveness and feasibility of behavioral sleep intervention for medicated children with ADHD. Six medicated children (five boys, one girl; aged 6-12 years) with ADHD participated in a 4-week sleep intervention program. The main behavioral strategies used were Faded Bedtime With Response Cost (FBRC) and positive reinforcement. Within a case-series design, objective measure (Sleep Disturbance Scale for Children [SDSC]) and subjective measure (sleep diaries) were used to record changes in children's sleep. For all six children, significant decrease was found in the severity of children's sleep problems (based on SDSC data). Bedtime resistance and mean sleep onset latency were reduced following the 4-week intervention program according to sleep diaries data. Gains were generally maintained at the follow-up. Parents perceived the intervention as being helpful. Based on the initial data, this intervention shows promise as an effective and feasible treatment.

Visual analytics techniques for large multi-attribute time series data

NASA Astrophysics Data System (ADS)

Hao, Ming C.; Dayal, Umeshwar; Keim, Daniel A.

2008-01-01

Time series data commonly occur when variables are monitored over time. Many real-world applications involve the comparison of long time series across multiple variables (multi-attributes). Often business people want to compare this year's monthly sales with last year's sales to make decisions. Data warehouse administrators (DBAs) want to know their daily data loading job performance. DBAs need to detect the outliers early enough to act upon them. In this paper, two new visual analytic techniques are introduced: The color cell-based Visual Time Series Line Charts and Maps highlight significant changes over time in a long time series data and the new Visual Content Query facilitates finding the contents and histories of interesting patterns and anomalies, which leads to root cause identification. We have applied both methods to two real-world applications to mine enterprise data warehouse and customer credit card fraud data to illustrate the wide applicability and usefulness of these techniques.

A Method for Comparing Multivariate Time Series with Different Dimensions

PubMed Central

Tapinos, Avraam; Mendes, Pedro

2013-01-01

In many situations it is desirable to compare dynamical systems based on their behavior. Similarity of behavior often implies similarity of internal mechanisms or dependency on common extrinsic factors. While there are widely used methods for comparing univariate time series, most dynamical systems are characterized by multivariate time series. Yet, comparison of multivariate time series has been limited to cases where they share a common dimensionality. A semi-metric is a distance function that has the properties of non-negativity, symmetry and reflexivity, but not sub-additivity. Here we develop a semi-metric – SMETS – that can be used for comparing groups of time series that may have different dimensions. To demonstrate its utility, the method is applied to dynamic models of biochemical networks and to portfolios of shares. The former is an example of a case where the dependencies between system variables are known, while in the latter the system is treated (and behaves) as a black box. PMID:23393554

Classification of time-series images using deep convolutional neural networks

NASA Astrophysics Data System (ADS)

Hatami, Nima; Gavet, Yann; Debayle, Johan

2018-04-01

Convolutional Neural Networks (CNN) has achieved a great success in image recognition task by automatically learning a hierarchical feature representation from raw data. While the majority of Time-Series Classification (TSC) literature is focused on 1D signals, this paper uses Recurrence Plots (RP) to transform time-series into 2D texture images and then take advantage of the deep CNN classifier. Image representation of time-series introduces different feature types that are not available for 1D signals, and therefore TSC can be treated as texture image recognition task. CNN model also allows learning different levels of representations together with a classifier, jointly and automatically. Therefore, using RP and CNN in a unified framework is expected to boost the recognition rate of TSC. Experimental results on the UCR time-series classification archive demonstrate competitive accuracy of the proposed approach, compared not only to the existing deep architectures, but also to the state-of-the art TSC algorithms.

A simple and fast representation space for classifying complex time series

NASA Astrophysics Data System (ADS)

Zunino, Luciano; Olivares, Felipe; Bariviera, Aurelio F.; Rosso, Osvaldo A.

2017-03-01

In the context of time series analysis considerable effort has been directed towards the implementation of efficient discriminating statistical quantifiers. Very recently, a simple and fast representation space has been introduced, namely the number of turning points versus the Abbe value. It is able to separate time series from stationary and non-stationary processes with long-range dependences. In this work we show that this bidimensional approach is useful for distinguishing complex time series: different sets of financial and physiological data are efficiently discriminated. Additionally, a multiscale generalization that takes into account the multiple time scales often involved in complex systems has been also proposed. This multiscale analysis is essential to reach a higher discriminative power between physiological time series in health and disease.

Fourier series expansion for nonlinear Hamiltonian oscillators.

PubMed

Méndez, Vicenç; Sans, Cristina; Campos, Daniel; Llopis, Isaac

2010-06-01

The problem of nonlinear Hamiltonian oscillators is one of the classical questions in physics. When an analytic solution is not possible, one can resort to obtaining a numerical solution or using perturbation theory around the linear problem. We apply the Fourier series expansion to find approximate solutions to the oscillator position as a function of time as well as the period-amplitude relationship. We compare our results with other recent approaches such as variational methods or heuristic approximations, in particular the Ren-He's method. Based on its application to the Duffing oscillator, the nonlinear pendulum and the eardrum equation, it is shown that the Fourier series expansion method is the most accurate.

31 CFR 359.4 - In what form are Series I savings bonds issued?

Code of Federal Regulations, 2010 CFR

2010-07-01

... (Continued) FISCAL SERVICE, DEPARTMENT OF THE TREASURY BUREAU OF THE PUBLIC DEBT OFFERING OF UNITED STATES SAVINGS BONDS, SERIES I General Information § 359.4 In what form are Series I savings bonds issued? Series...

Series: Practical guidance to qualitative research. Part 1: Introduction.

PubMed

Moser, Albine; Korstjens, Irene

2017-12-01

In the course of our supervisory work over the years, we have noticed that qualitative research tends to evoke a lot of questions and worries, so-called Frequently Asked Questions. This journal series of four articles intends to provide novice researchers with practical guidance for conducting high-quality qualitative research in primary care. By 'novice' we mean Master's students and junior researchers, as well as experienced quantitative researchers who are engaging in qualitative research for the first time. This series addresses their questions and provides researchers, readers, reviewers and editors with references to criteria and tools for judging the quality of papers reporting on qualitative research. This first article describes the key features of qualitative research, provides publications for further learning and reading, and gives an outline of the series.

Characteristics of the transmission of autoregressive sub-patterns in financial time series

NASA Astrophysics Data System (ADS)

Gao, Xiangyun; An, Haizhong; Fang, Wei; Huang, Xuan; Li, Huajiao; Zhong, Weiqiong

2014-09-01

There are many types of autoregressive patterns in financial time series, and they form a transmission process. Here, we define autoregressive patterns quantitatively through an econometrical regression model. We present a computational algorithm that sets the autoregressive patterns as nodes and transmissions between patterns as edges, and then converts the transmission process of autoregressive patterns in a time series into a network. We utilised daily Shanghai (securities) composite index time series to study the transmission characteristics of autoregressive patterns. We found statistically significant evidence that the financial market is not random and that there are similar characteristics between parts and whole time series. A few types of autoregressive sub-patterns and transmission patterns drive the oscillations of the financial market. A clustering effect on fluctuations appears in the transmission process, and certain non-major autoregressive sub-patterns have high media capabilities in the financial time series. Different stock indexes exhibit similar characteristics in the transmission of fluctuation information. This work not only proposes a distinctive perspective for analysing financial time series but also provides important information for investors.

Characteristics of the transmission of autoregressive sub-patterns in financial time series

PubMed Central

Gao, Xiangyun; An, Haizhong; Fang, Wei; Huang, Xuan; Li, Huajiao; Zhong, Weiqiong

2014-01-01

There are many types of autoregressive patterns in financial time series, and they form a transmission process. Here, we define autoregressive patterns quantitatively through an econometrical regression model. We present a computational algorithm that sets the autoregressive patterns as nodes and transmissions between patterns as edges, and then converts the transmission process of autoregressive patterns in a time series into a network. We utilised daily Shanghai (securities) composite index time series to study the transmission characteristics of autoregressive patterns. We found statistically significant evidence that the financial market is not random and that there are similar characteristics between parts and whole time series. A few types of autoregressive sub-patterns and transmission patterns drive the oscillations of the financial market. A clustering effect on fluctuations appears in the transmission process, and certain non-major autoregressive sub-patterns have high media capabilities in the financial time series. Different stock indexes exhibit similar characteristics in the transmission of fluctuation information. This work not only proposes a distinctive perspective for analysing financial time series but also provides important information for investors. PMID:25189200

Motors and Bulbs in Series

ERIC Educational Resources Information Center

Whitaker, Robert J.

2009-01-01

One of Paul Hewitt's "Figuring Physics" that appeared in this journal dealt with the heating of a motor. This phenomenon can be demonstrated with a miniature motor and a bulb as part of a series of activities with "batteries and bulbs." Students examine the effect on the brightness of a single bulb when a second, identical bulb is placed in series…

Printing Series. Duty Task List.

ERIC Educational Resources Information Center

Oklahoma State Dept. of Vocational and Technical Education, Stillwater. Curriculum and Instructional Materials Center.

This document contains the occupational duty/task lists for 10 occupations in the printing series. Each occupation is divided into a number of duties. A separate page for each duty in the occupation lists the tasks in that duty along with its code number and columns to indicate whether that particular duty has been taught and to provide space for…

Welding Series. Duty Task List.

ERIC Educational Resources Information Center

Oklahoma State Dept. of Vocational and Technical Education, Stillwater. Curriculum and Instructional Materials Center.

This document contains the occupational duty/task lists for six occupations in the welding series. Each occupation is divided into a number of duties. A separate page for each duty in the occupation lists the tasks in that duty along with its code number and columns to indicate whether that particular duty has been taught and to provide space for…

Off-diagonal series expansion for quantum partition functions

NASA Astrophysics Data System (ADS)

Hen, Itay

2018-05-01

We derive an integral-free thermodynamic perturbation series expansion for quantum partition functions which enables an analytical term-by-term calculation of the series. The expansion is carried out around the partition function of the classical component of the Hamiltonian with the expansion parameter being the strength of the off-diagonal, or quantum, portion. To demonstrate the usefulness of the technique we analytically compute to third order the partition functions of the 1D Ising model with longitudinal and transverse fields, and the quantum 1D Heisenberg model.

A new algorithm for automatic Outlier Detection in GPS Time Series

NASA Astrophysics Data System (ADS)

Cannavo', Flavio; Mattia, Mario; Rossi, Massimo; Palano, Mimmo; Bruno, Valentina

2010-05-01

Nowadays continuous GPS time series are considered a crucial product of GPS permanent networks, useful in many geo-science fields, such as active tectonics, seismology, crustal deformation and volcano monitoring (Altamimi et al. 2002, Elósegui et al. 2006, Aloisi et al. 2009). Although the GPS data elaboration software has increased in reliability, the time series are still affected by different kind of noise, from the intrinsic noise (e.g. thropospheric delay) to the un-modeled noise (e.g. cycle slips, satellite faults, parameters changing). Typically GPS Time Series present characteristic noise that is a linear combination of white noise and correlated colored noise, and this characteristic is fractal in the sense that is evident for every considered time scale or sampling rate. The un-modeled noise sources result in spikes, outliers and steps. These kind of errors can appreciably influence the estimation of velocities of the monitored sites. The outlier detection in generic time series is a widely treated problem in literature (Wei, 2005), while is not fully developed for the specific kind of GPS series. We propose a robust automatic procedure for cleaning the GPS time series from the outliers and, especially for long daily series, steps due to strong seismic or volcanic events or merely instrumentation changing such as antenna and receiver upgrades. The procedure is basically divided in two steps: a first step for the colored noise reduction and a second step for outlier detection through adaptive series segmentation. Both algorithms present novel ideas and are nearly unsupervised. In particular, we propose an algorithm to estimate an autoregressive model for colored noise in GPS time series in order to subtract the effect of non Gaussian noise on the series. This step is useful for the subsequent step (i.e. adaptive segmentation) which requires the hypothesis of Gaussian noise. The proposed algorithms are tested in a benchmark case study and the results

SeaWiFS Technical Report Series. Volume 43; SeaWiFS Prelaunch Technical Report Series Final Cumulative Index

NASA Technical Reports Server (NTRS)

Firestone, Elaine R. (Editor); Hooker, Stanford B.

1998-01-01

The Sea-viewing Wide Field-of-view Sensor (SeaWiFS) is the follow-on ocean color instrument to the Coastal Zone Color Scanner (CZCS), which ceased operations in 1986, after an eight-year mission. SeaWiFS was launched on 1 August 1997, on the SeaStar satellite, built by Orbital Sciences Corporation (OSC). The SeaWiFS Project at the National Aeronautics and Space Administration (NASA) Goddard Space Flight Center (GSFC), undertook the responsibility of documenting all aspects of this mission, which is critical to the ocean color and marine science communities. This documentation, entitled the SeaWiFS Technical Report Series, is in the form of NASA Technical Memorandum Number 104566 and 1998-104566. All reports published are volumes within the series. This particular volume, which is the last of the so-called Prelaunch Series serves as a reference, or guidebook, to the previous 42 volumes and consists of 6 sections including: an addenda, an errata, an index to key words and phrases, lists of acronyms and symbols used, and a list of all references cited. The editors have published a cumulative index of this type after every five volumes. Each index covers the reference topics published in all previous editions, that is, each new index includes all of the information contained in the preceding indexes with the exception of any addenda.

User Manual for the Data-Series Interface of the Gr Application Software

USGS Publications Warehouse

Donovan, John M.

2009-01-01

This manual describes the data-series interface for the Gr Application software. Basic tasks such as plotting, editing, manipulating, and printing data series are presented. The properties of the various types of data objects and graphical objects used within the application, and the relationships between them also are presented. Descriptions of compatible data-series file formats are provided.

Generalizing Integrals Involving X [superscript X] and Series Involving N [superscript N

ERIC Educational Resources Information Center

Osler, Thomas J.; Tsay, Jeffrey

2005-01-01

In this paper, the authors evaluate the series and integrals presented by P. Glaister. The authors show that this function has the Maclauren series expansion. The authors derive the series from the integral in two ways. The first derivation uses the technique employed by Glaister. The second derivation uses a change in variable in the integral.

Evaluation of recent GRACE monthly solution series with an ice sheet perspective

NASA Astrophysics Data System (ADS)

Horwath, Martin; Groh, Andreas

2016-04-01

GRACE monthly global gravity field solutions have undergone a remarkable evolution, leading to the latest (Release 5) series by CSR, GFZ, and JPL, to new series by other processing centers, such as ITSG and AIUB, as well as to efforts to derive combined solutions, particularly by the EGSIEM (European Gravity Service for Improved Emergency Management) project. For applications, such as GRACE inferences on ice sheet mass balance, the obvious question is on what GRACE solution series to base the assessment. Here we evaluate different GRACE solution series (including the ones listed above) in a unified framework. We concentrate on solutions expanded up to degree 90 or higher, since this is most appropriate for polar applications. We empirically assess the error levels in the spectral as well as in the spatial domain based on the month-to-month scatter in the high spherical harmonic degrees. We include empirical assessment of error correlations. We then apply all series to infer Antarctic and Greenland mass change time series and compare the results in terms of apparent signal content and noise level. We find that the ITSG solutions show lowest noise level in the high degrees (above 60). A preliminary combined solution from the EGSIEM project shows lowest noise in the degrees below 60. This virtue maps into the derived ice mass time series, where the EGSIEM-based results show the lowest noise in most cases. Meanwhile, there is no indication that any of the considered series systematically dampens actual geophysical signals.

Complexity quantification of cardiac variability time series using improved sample entropy (I-SampEn).

PubMed

Marwaha, Puneeta; Sunkaria, Ramesh Kumar

2016-09-01

The sample entropy (SampEn) has been widely used to quantify the complexity of RR-interval time series. It is a fact that higher complexity, and hence, entropy is associated with the RR-interval time series of healthy subjects. But, SampEn suffers from the disadvantage that it assigns higher entropy to the randomized surrogate time series as well as to certain pathological time series, which is a misleading observation. This wrong estimation of the complexity of a time series may be due to the fact that the existing SampEn technique updates the threshold value as a function of long-term standard deviation (SD) of a time series. However, time series of certain pathologies exhibits substantial variability in beat-to-beat fluctuations. So the SD of the first order difference (short term SD) of the time series should be considered while updating threshold value, to account for period-to-period variations inherited in a time series. In the present work, improved sample entropy (I-SampEn), a new methodology has been proposed in which threshold value is updated by considering the period-to-period variations of a time series. The I-SampEn technique results in assigning higher entropy value to age-matched healthy subjects than patients suffering atrial fibrillation (AF) and diabetes mellitus (DM). Our results are in agreement with the theory of reduction in complexity of RR-interval time series in patients suffering from chronic cardiovascular and non-cardiovascular diseases.

Visibility graph analysis on quarterly macroeconomic series of China based on complex network theory

NASA Astrophysics Data System (ADS)

Wang, Na; Li, Dong; Wang, Qiwen

2012-12-01

The visibility graph approach and complex network theory provide a new insight into time series analysis. The inheritance of the visibility graph from the original time series was further explored in the paper. We found that degree distributions of visibility graphs extracted from Pseudo Brownian Motion series obtained by the Frequency Domain algorithm exhibit exponential behaviors, in which the exponential exponent is a binomial function of the Hurst index inherited in the time series. Our simulations presented that the quantitative relations between the Hurst indexes and the exponents of degree distribution function are different for different series and the visibility graph inherits some important features of the original time series. Further, we convert some quarterly macroeconomic series including the growth rates of value-added of three industry series and the growth rates of Gross Domestic Product series of China to graphs by the visibility algorithm and explore the topological properties of graphs associated from the four macroeconomic series, namely, the degree distribution and correlations, the clustering coefficient, the average path length, and community structure. Based on complex network analysis we find degree distributions of associated networks from the growth rates of value-added of three industry series are almost exponential and the degree distributions of associated networks from the growth rates of GDP series are scale free. We also discussed the assortativity and disassortativity of the four associated networks as they are related to the evolutionary process of the original macroeconomic series. All the constructed networks have “small-world” features. The community structures of associated networks suggest dynamic changes of the original macroeconomic series. We also detected the relationship among government policy changes, community structures of associated networks and macroeconomic dynamics. We find great influences of government

A novel water quality data analysis framework based on time-series data mining.

PubMed