Chaos in Electronic Circuits: Nonlinear Time Series Analysis
Energy Technology Data Exchange (ETDEWEB)
Wheat, Jr., Robert M. [Kennedy Western Univ., Cheyenne, WY (United States)
2003-07-01
Chaos in electronic circuits is a phenomenon that has been largely ignored by engineers, manufacturers, and researchers until the early 1990’s and the work of Chua, Matsumoto, and others. As the world becomes more dependent on electronic devices, the detrimental effects of non-normal operation of these devices becomes more significant. Developing a better understanding of the mechanisms involved in the chaotic behavior of electronic circuits is a logical step toward the prediction and prevention of any potentially catastrophic occurrence of this phenomenon. Also, a better understanding of chaotic behavior, in a general sense, could potentially lead to better accuracy in the prediction of natural events such as weather, volcanic activity, and earthquakes. As a first step in this improvement of understanding, and as part of the research being reported here, methods of computer modeling, identifying and analyzing, and producing chaotic behavior in simple electronic circuits have been developed. The computer models were developed using both the Alternative Transient Program (ATP) and Spice, the analysis techniques have been implemented using the C and C++ programming languages, and the chaotically behaving circuits developed using “off the shelf” electronic components.
International Nuclear Information System (INIS)
Bonnet, Nogl; Nuzillard, Danielle
2005-01-01
A complementary approach is proposed for analysing series of electron energy-loss spectra that can be recorded with the spectrum-line technique, across an interface for instance. This approach, called blind source separation (BSS) or independent component analysis (ICA), complements two existing methods: the spatial difference approach and multivariate statistical analysis. The principle of the technique is presented and illustrations are given through one simulated example and one real example
DEFF Research Database (Denmark)
Fischer, Paul; Hilbert, Astrid
2012-01-01
We introduce a platform which supplies an easy-to-handle, interactive, extendable, and fast analysis tool for time series analysis. In contrast to other software suits like Maple, Matlab, or R, which use a command-line-like interface and where the user has to memorize/look-up the appropriate...... commands, our application is select-and-click-driven. It allows to derive many different sequences of deviations for a given time series and to visualize them in different ways in order to judge their expressive power and to reuse the procedure found. For many transformations or model-ts, the user may...... choose between manual and automated parameter selection. The user can dene new transformations and add them to the system. The application contains efficient implementations of advanced and recent techniques for time series analysis including techniques related to extreme value analysis and filtering...
Perotte, Adler; Ranganath, Rajesh; Hirsch, Jamie S; Blei, David; Elhadad, Noémie
2015-07-01
As adoption of electronic health records continues to increase, there is an opportunity to incorporate clinical documentation as well as laboratory values and demographics into risk prediction modeling. The authors develop a risk prediction model for chronic kidney disease (CKD) progression from stage III to stage IV that includes longitudinal data and features drawn from clinical documentation. The study cohort consisted of 2908 primary-care clinic patients who had at least three visits prior to January 1, 2013 and developed CKD stage III during their documented history. Development and validation cohorts were randomly selected from this cohort and the study datasets included longitudinal inpatient and outpatient data from these populations. Time series analysis (Kalman filter) and survival analysis (Cox proportional hazards) were combined to produce a range of risk models. These models were evaluated using concordance, a discriminatory statistic. A risk model incorporating longitudinal data on clinical documentation and laboratory test results (concordance 0.849) predicts progression from state III CKD to stage IV CKD more accurately when compared to a similar model without laboratory test results (concordance 0.733, P<.001), a model that only considers the most recent laboratory test results (concordance 0.819, P < .031) and a model based on estimated glomerular filtration rate (concordance 0.779, P < .001). A risk prediction model that takes longitudinal laboratory test results and clinical documentation into consideration can predict CKD progression from stage III to stage IV more accurately than three models that do not take all of these variables into consideration. © The Author 2015. Published by Oxford University Press on behalf of the American Medical Informatics Association.
Dowding, Dawn W; Turley, Marianne; Garrido, Terhilda
2012-01-01
To evaluate the impact of electronic health record (EHR) implementation on nursing care processes and outcomes. Interrupted time series analysis, 2003-2009. A large US not-for-profit integrated health care organization. 29 hospitals in Northern and Southern California. An integrated EHR including computerized physician order entry, nursing documentation, risk assessment tools, and documentation tools. Percentage of patients with completed risk assessments for hospital acquired pressure ulcers (HAPUs) and falls (process measures) and rates of HAPU and falls (outcome measures). EHR implementation was significantly associated with an increase in documentation rates for HAPU risk (coefficient 2.21, 95% CI 0.67 to 3.75); the increase for fall risk was not statistically significant (0.36; -3.58 to 4.30). EHR implementation was associated with a 13% decrease in HAPU rates (coefficient -0.76, 95% CI -1.37 to -0.16) but no decrease in fall rates (-0.091; -0.29 to 0.11). Irrespective of EHR implementation, HAPU rates decreased significantly over time (-0.16; -0.20 to -0.13), while fall rates did not (0.0052; -0.01 to 0.02). Hospital region was a significant predictor of variation for both HAPU (0.72; 0.30 to 1.14) and fall rates (0.57; 0.41 to 0.72). The introduction of an integrated EHR was associated with a reduction in the number of HAPUs but not in patient fall rates. Other factors, such as changes over time and hospital region, were also associated with variation in outcomes. The findings suggest that EHR impact on nursing care processes and outcomes is dependent on a number of factors that should be further explored.
Woodward, Wayne A; Elliott, Alan C
2011-01-01
""There is scarcely a standard technique that the reader will find left out … this book is highly recommended for those requiring a ready introduction to applicable methods in time series and serves as a useful resource for pedagogical purposes.""-International Statistical Review (2014), 82""Current time series theory for practice is well summarized in this book.""-Emmanuel Parzen, Texas A&M University""What an extraordinary range of topics covered, all very insightfully. I like [the authors'] innovations very much, such as the AR factor table.""-David Findley, U.S. Census Bureau (retired)""…
Time Series Analysis and Forecasting by Example
Bisgaard, Soren
2011-01-01
An intuition-based approach enables you to master time series analysis with ease Time Series Analysis and Forecasting by Example provides the fundamental techniques in time series analysis using various examples. By introducing necessary theory through examples that showcase the discussed topics, the authors successfully help readers develop an intuitive understanding of seemingly complicated time series models and their implications. The book presents methodologies for time series analysis in a simplified, example-based approach. Using graphics, the authors discuss each presented example in
The analysis of time series: an introduction
National Research Council Canada - National Science Library
Chatfield, Christopher
1989-01-01
.... A variety of practical examples are given to support the theory. The book covers a wide range of time-series topics, including probability models for time series, Box-Jenkins forecasting, spectral analysis, linear systems and system identification...
Time series analysis time series analysis methods and applications
Rao, Tata Subba; Rao, C R
2012-01-01
The field of statistics not only affects all areas of scientific activity, but also many other matters such as public policy. It is branching rapidly into so many different subjects that a series of handbooks is the only way of comprehensively presenting the various aspects of statistical methodology, applications, and recent developments. The Handbook of Statistics is a series of self-contained reference books. Each volume is devoted to a particular topic in statistics, with Volume 30 dealing with time series. The series is addressed to the entire community of statisticians and scientists in various disciplines who use statistical methodology in their work. At the same time, special emphasis is placed on applications-oriented techniques, with the applied statistician in mind as the primary audience. Comprehensively presents the various aspects of statistical methodology Discusses a wide variety of diverse applications and recent developments Contributors are internationally renowened experts in their respect...
A Course in Time Series Analysis
Peña, Daniel; Tsay, Ruey S
2011-01-01
New statistical methods and future directions of research in time series A Course in Time Series Analysis demonstrates how to build time series models for univariate and multivariate time series data. It brings together material previously available only in the professional literature and presents a unified view of the most advanced procedures available for time series model building. The authors begin with basic concepts in univariate time series, providing an up-to-date presentation of ARIMA models, including the Kalman filter, outlier analysis, automatic methods for building ARIMA models, a
Directory of Open Access Journals (Sweden)
Shamindri M. Arachchige
2011-12-01
Full Text Available Mixed-metal supramolecular complexes have been designed that photochemically absorb solar light, undergo photoinitiated electron collection and reduce water to produce hydrogen fuel using low energy visible light. This manuscript describes these systems with an analysis of the photophysics of a series of six supramolecular complexes, [{(TL2Ru(dpp}2RhX2](PF65 with TL = bpy, phen or Ph2phen with X = Cl or Br. The process of light conversion to a fuel requires a system to perform a number of complicated steps including the absorption of light, the generation of charge separation on a molecular level, the reduction by one and then two electrons and the interaction with the water substrate to produce hydrogen. The manuscript explores the rate of intramolecular electron transfer, rate of quenching of the supramolecules by the DMA electron donor, rate of reduction of the complex by DMA from the 3MLCT excited state, as well as overall rate of reduction of the complex via visible light excitation. Probing a series of complexes in detail exploring the variation of rates of important reactions as a function of sub-unit modification provides insight into the role of each process in the overall efficiency of water reduction to produce hydrogen. The kinetic analysis shows that the complexes display different rates of excited state reactions that vary with TL and halide. The role of the MLCT excited state is elucidated by this kinetic study which shows that the 3MLCT state and not the 3MMCT is likely that key contributor to the photoreduction of these complexes. The kinetic analysis of the excited state dynamics and reactions of the complexes are important as this class of supramolecules behaves as photoinitiated electron collectors and photocatalysts for the reduction of water to hydrogen.
The foundations of modern time series analysis
Mills, Terence C
2011-01-01
This book develops the analysis of Time Series from its formal beginnings in the 1890s through to the publication of Box and Jenkins' watershed publication in 1970, showing how these methods laid the foundations for the modern techniques of Time Series analysis that are in use today.
Analysis of series resonant converter with series-parallel connection
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.
Analysis of Heavy-Tailed Time Series
DEFF Research Database (Denmark)
Xie, Xiaolei
This thesis is about analysis of heavy-tailed time series. We discuss tail properties of real-world equity return series and investigate the possibility that a single tail index is shared by all return series of actively traded equities in a market. Conditions for this hypothesis to be true...... are identified. We study the eigenvalues and eigenvectors of sample covariance and sample auto-covariance matrices of multivariate heavy-tailed time series, and particularly for time series with very high dimensions. Asymptotic approximations of the eigenvalues and eigenvectors of such matrices are found...... and expressed in terms of the parameters of the dependence structure, among others. Furthermore, we study an importance sampling method for estimating rare-event probabilities of multivariate heavy-tailed time series generated by matrix recursion. We show that the proposed algorithm is efficient in the sense...
Applied time series analysis and innovative computing
Ao, Sio-Iong
2010-01-01
This text is a systematic, state-of-the-art introduction to the use of innovative computing paradigms as an investigative tool for applications in time series analysis. It includes frontier case studies based on recent research.
Time Series Analysis Forecasting and Control
Box, George E P; Reinsel, Gregory C
2011-01-01
A modernized new edition of one of the most trusted books on time series analysis. Since publication of the first edition in 1970, Time Series Analysis has served as one of the most influential and prominent works on the subject. This new edition maintains its balanced presentation of the tools for modeling and analyzing time series and also introduces the latest developments that have occurred n the field over the past decade through applications from areas such as business, finance, and engineering. The Fourth Edition provides a clearly written exploration of the key methods for building, cl
Lacson, Ronilda; O'Connor, Stacy D; Sahni, V Anik; Roy, Christopher; Dalal, Anuj; Desai, Sonali; Khorasani, Ramin
2016-07-01
Optimal critical test result communication is a Joint Commission national patient safety goal and requires documentation of closed-loop communication among care providers in the medical record. Electronic alert notification systems can facilitate an auditable process for creating alerts for transmission and acknowledgement of critical test results. We evaluated the impact of a patient safety initiative with an alert notification system on reducing critical results lacking documented communication, and assessed potential overuse of the alerting system for communicating results. We implemented an alert notification system-Alert Notification of Critical Results (ANCR)-in January 2010. We reviewed radiology reports finalised in 2009-2014 which lacked documented communication between the radiologist and another care provider, and assessed the impact of ANCR on the proportion of such reports with critical findings, using trend analysis over 10 semiannual time periods. To evaluate potential overuse of ANCR, we assessed the proportion of reports with non-critical results among provider-communicated reports. The proportion of reports with critical results among reports without documented communication decreased significantly over 4 years (2009-2014) from 0.19 to 0.05 (pcommunicated reports with non-critical results remained unchanged over time before and after ANCR implementation (0.20 to 0.15, p=0.45, Cochran-Armitage trend test). A patient safety initiative with an alert notification system reduced the proportion of critical results among reports lacking documented communication between care providers. We observed no change in documented communication of non-critical results, suggesting the system did not promote overuse. Future studies are needed to evaluate whether such systems prevent subsequent patient harm. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/
Visibility Graph Based Time Series Analysis.
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.
Visibility Graph Based Time Series Analysis.
Directory of Open Access Journals (Sweden)
Mutua Stephen
Full Text Available 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.
Energy Technology Data Exchange (ETDEWEB)
Dunzlaff, P. [North-West Univ., Potchefstroom (South Africa). Centre for Space Research; Kiel Univ. (Germany). Inst. fuer Experimentelle und Angewandte Physik; Heber, B. [Kiel Univ. (Germany). Inst. fuer Experimentelle und Angewandte Physik; Kopp, A. [Kiel Univ. (Germany). Inst. fuer Experimentelle und Angewandte Physik; North-West Univ., Potchefstroom (South Africa). Centre for Space Research; Potgieter, M.S. [North-West Univ., Potchefstroom (South Africa). Centre for Space Research
2013-11-01
The dynamics of the Jovian magnetosphere is dominated by the planet's fast rotation with a period of {proportional_to} 10 h.Within the magnetosphere, this periodicity can in particular be seen in the temporal variation of the spectral index of MeV electrons: every {proportional_to} 10 h the counting rates show a maximum (minimum), while the spectral index shows a minimum (maximum) known as the Jovian ''clock'' mechanism. In this study we re-analyse Ulysses and Pioneer 10/11 data and show that another periodic modulation in the MeV electrons can be identified, manifested by local maxima of the spectral index and local minima of the counting rates. For Ulysses, this modulation can be observed throughout the magnetosphere near the magnetic equator, suggesting an azimuthal asymmetric distribution of MeV electrons near the current sheet. This modulation is found to trail the ''clock'' mechanism by {proportional_to} 3.25 h. The Pioneer 10 data, however, only show occasional evidence of the presence of these local maxima while there is no evidence of this modulation in the Pioneer 11 data. A comparison of the times of observed minor peaks and Ulysses' distance from the current sheet using a simple rigid disc model as well as the model of Khurana and Schwarzl (2005) is performed.
International Nuclear Information System (INIS)
Dunzlaff, P.; Kiel Univ.; Heber, B.; Kopp, A.; North-West Univ., Potchefstroom; Potgieter, M.S.
2013-01-01
The dynamics of the Jovian magnetosphere is dominated by the planet's fast rotation with a period of ∝ 10 h.Within the magnetosphere, this periodicity can in particular be seen in the temporal variation of the spectral index of MeV electrons: every ∝ 10 h the counting rates show a maximum (minimum), while the spectral index shows a minimum (maximum) known as the Jovian ''clock'' mechanism. In this study we re-analyse Ulysses and Pioneer 10/11 data and show that another periodic modulation in the MeV electrons can be identified, manifested by local maxima of the spectral index and local minima of the counting rates. For Ulysses, this modulation can be observed throughout the magnetosphere near the magnetic equator, suggesting an azimuthal asymmetric distribution of MeV electrons near the current sheet. This modulation is found to trail the ''clock'' mechanism by ∝ 3.25 h. The Pioneer 10 data, however, only show occasional evidence of the presence of these local maxima while there is no evidence of this modulation in the Pioneer 11 data. A comparison of the times of observed minor peaks and Ulysses' distance from the current sheet using a simple rigid disc model as well as the model of Khurana and Schwarzl (2005) is performed.
Allan deviation analysis of financial return series
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.
Introduction to time series analysis and forecasting
Montgomery, Douglas C; Kulahci, Murat
2008-01-01
An accessible introduction to the most current thinking in and practicality of forecasting techniques in the context of time-oriented data. Analyzing time-oriented data and forecasting are among the most important problems that analysts face across many fields, ranging from finance and economics to production operations and the natural sciences. As a result, there is a widespread need for large groups of people in a variety of fields to understand the basic concepts of time series analysis and forecasting. Introduction to Time Series Analysis and Forecasting presents the time series analysis branch of applied statistics as the underlying methodology for developing practical forecasts, and it also bridges the gap between theory and practice by equipping readers with the tools needed to analyze time-oriented data and construct useful, short- to medium-term, statistically based forecasts.
Entropic Analysis of Electromyography Time Series
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.
Introduction to time series analysis and forecasting
Montgomery, Douglas C; Kulahci, Murat
2015-01-01
Praise for the First Edition ""…[t]he book is great for readers who need to apply the methods and models presented but have little background in mathematics and statistics."" -MAA Reviews Thoroughly updated throughout, Introduction to Time Series Analysis and Forecasting, Second Edition presents the underlying theories of time series analysis that are needed to analyze time-oriented data and construct real-world short- to medium-term statistical forecasts. Authored by highly-experienced academics and professionals in engineering statistics, the Second Edition features discussions on both
Nonlinear Time Series Analysis via Neural Networks
Volná, Eva; Janošek, Michal; Kocian, Václav; Kotyrba, Martin
This article deals with a time series analysis based on neural networks in order to make an effective forex market [Moore and Roche, J. Int. Econ. 58, 387-411 (2002)] pattern recognition. Our goal is to find and recognize important patterns which repeatedly appear in the market history to adapt our trading system behaviour based on them.
Lecture notes for Advanced Time Series Analysis
DEFF Research Database (Denmark)
Madsen, Henrik; Holst, Jan
1997-01-01
A first version of this notes was used at the lectures in Grenoble, and they are now extended and improved (together with Jan Holst), and used in Ph.D. courses on Advanced Time Series Analysis at IMM and at the Department of Mathematical Statistics, University of Lund, 1994, 1997, ...
Power electronics reliability analysis.
Energy Technology Data Exchange (ETDEWEB)
Smith, Mark A.; Atcitty, Stanley
2009-12-01
This report provides the DOE and industry with a general process for analyzing power electronics reliability. The analysis can help with understanding the main causes of failures, downtime, and cost and how to reduce them. One approach is to collect field maintenance data and use it directly to calculate reliability metrics related to each cause. Another approach is to model the functional structure of the equipment using a fault tree to derive system reliability from component reliability. Analysis of a fictitious device demonstrates the latter process. Optimization can use the resulting baseline model to decide how to improve reliability and/or lower costs. It is recommended that both electric utilities and equipment manufacturers make provisions to collect and share data in order to lay the groundwork for improving reliability into the future. Reliability analysis helps guide reliability improvements in hardware and software technology including condition monitoring and prognostics and health management.
A taylor series approach to survival analysis
International Nuclear Information System (INIS)
Brodsky, J.B.; Groer, P.G.
1984-09-01
A method of survival analysis using hazard functions is developed. The method uses the well known mathematical theory for Taylor Series. Hypothesis tests of the adequacy of many statistical models, including proportional hazards and linear and/or quadratic dose responses, are obtained. A partial analysis of leukemia mortality in the Life Span Study cohort is used as an example. Furthermore, a relatively robust estimation procedure for the proportional hazards model is proposed. (author)
Time series analysis of barometric pressure data
International Nuclear Information System (INIS)
La Rocca, Paola; Riggi, Francesco; Riggi, Daniele
2010-01-01
Time series of atmospheric pressure data, collected over a period of several years, were analysed to provide undergraduate students with educational examples of application of simple statistical methods of analysis. In addition to basic methods for the analysis of periodicities, a comparison of two forecast models, one based on autoregression algorithms, and the other making use of an artificial neural network, was made. Results show that the application of artificial neural networks may give slightly better results compared to traditional methods.
The Statistical Analysis of Time Series
Anderson, T W
2011-01-01
The Wiley Classics Library consists of selected books that have become recognized classics in their respective fields. With these new unabridged and inexpensive editions, Wiley hopes to extend the life of these important works by making them available to future generations of mathematicians and scientists. Currently available in the Series: T. W. Anderson Statistical Analysis of Time Series T. S. Arthanari & Yadolah Dodge Mathematical Programming in Statistics Emil Artin Geometric Algebra Norman T. J. Bailey The Elements of Stochastic Processes with Applications to the Natural Sciences George
Fourier analysis of time series an introduction
Bloomfield, Peter
2000-01-01
A new, revised edition of a yet unrivaled work on frequency domain analysis Long recognized for his unique focus on frequency domain methods for the analysis of time series data as well as for his applied, easy-to-understand approach, Peter Bloomfield brings his well-known 1976 work thoroughly up to date. With a minimum of mathematics and an engaging, highly rewarding style, Bloomfield provides in-depth discussions of harmonic regression, harmonic analysis, complex demodulation, and spectrum analysis. All methods are clearly illustrated using examples of specific data sets, while ample
Nonlinear time series analysis with R
Huffaker, Ray; Rosa, Rodolfo
2017-01-01
In the process of data analysis, the investigator is often facing highly-volatile and random-appearing observed data. A vast body of literature shows that the assumption of underlying stochastic processes was not necessarily representing the nature of the processes under investigation and, when other tools were used, deterministic features emerged. Non Linear Time Series Analysis (NLTS) allows researchers to test whether observed volatility conceals systematic non linear behavior, and to rigorously characterize governing dynamics. Behavioral patterns detected by non linear time series analysis, along with scientific principles and other expert information, guide the specification of mechanistic models that serve to explain real-world behavior rather than merely reproducing it. Often there is a misconception regarding the complexity of the level of mathematics needed to understand and utilize the tools of NLTS (for instance Chaos theory). However, mathematics used in NLTS is much simpler than many other subjec...
Time-Series Analysis: A Cautionary Tale
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.
Inverse Problem Approach for the Alignment of Electron Tomographic Series
International Nuclear Information System (INIS)
Tran, V.D.; Moreaud, M.; Thiebaut, E.; Denis, L.; Becker, J.M.
2014-01-01
In the refining industry, morphological measurements of particles have become an essential part in the characterization catalyst supports. Through these parameters, one can infer the specific physico-chemical properties of the studied materials. One of the main acquisition techniques is electron tomography (or nano-tomography). 3D volumes are reconstructed from sets of projections from different angles made by a Transmission Electron Microscope (TEM). This technique provides a real three-dimensional information at the nano-metric scale. A major issue in this method is the misalignment of the projections that contributes to the reconstruction. The current alignment techniques usually employ fiducial markers such as gold particles for a correct alignment of the images. When the use of markers is not possible, the correlation between adjacent projections is used to align them. However, this method sometimes fails. In this paper, we propose a new method based on the inverse problem approach where a certain criterion is minimized using a variant of the Nelder and Mead simplex algorithm. The proposed approach is composed of two steps. The first step consists of an initial alignment process, which relies on the minimization of a cost function based on robust statistics measuring the similarity of a projection to its previous projections in the series. It reduces strong shifts resulting from the acquisition between successive projections. In the second step, the pre-registered projections are used to initialize an iterative alignment-refinement process which alternates between (i) volume reconstructions and (ii) registrations of measured projections onto simulated projections computed from the volume reconstructed in (i). At the end of this process, we have a correct reconstruction of the volume, the projections being correctly aligned. Our method is tested on simulated data and shown to estimate accurately the translation, rotation and scale of arbitrary transforms. We
Electronic Circuit Analysis Language (ECAL)
Chenghang, C.
1983-03-01
The computer aided design technique is an important development in computer applications and it is an important component of computer science. The special language for electronic circuit analysis is the foundation of computer aided design or computer aided circuit analysis (abbreviated as CACD and CACA) of simulated circuits. Electronic circuit analysis language (ECAL) is a comparatively simple and easy to use circuit analysis special language which uses the FORTRAN language to carry out the explanatory executions. It is capable of conducting dc analysis, ac analysis, and transient analysis of a circuit. Futhermore, the results of the dc analysis can be used directly as the initial conditions for the ac and transient analyses.
Highly comparative time-series analysis: the empirical structure of time series and their methods.
Fulcher, Ben D; Little, Max A; Jones, Nick S
2013-06-06
The process of collecting and organizing sets of observations represents a common theme throughout the history of science. However, despite the ubiquity of scientists measuring, recording and analysing the dynamics of different processes, an extensive organization of scientific time-series data and analysis methods has never been performed. Addressing this, annotated collections of over 35 000 real-world and model-generated time series, and over 9000 time-series analysis algorithms are analysed in this work. We introduce reduced representations of both time series, in terms of their properties measured by diverse scientific methods, and of time-series analysis methods, in terms of their behaviour on empirical time series, and use them to organize these interdisciplinary resources. This new approach to comparing across diverse scientific data and methods allows us to organize time-series datasets automatically according to their properties, retrieve alternatives to particular analysis methods developed in other scientific disciplines and automate the selection of useful methods for time-series classification and regression tasks. The broad scientific utility of these tools is demonstrated on datasets of electroencephalograms, self-affine time series, heartbeat intervals, speech signals and others, in each case contributing novel analysis techniques to the existing literature. Highly comparative techniques that compare across an interdisciplinary literature can thus be used to guide more focused research in time-series analysis for applications across the scientific disciplines.
Time series analysis of temporal networks
Sikdar, Sandipan; Ganguly, Niloy; Mukherjee, Animesh
2016-01-01
A common but an important feature of all real-world networks is that they are temporal in nature, i.e., the network structure changes over time. Due to this dynamic nature, it becomes difficult to propose suitable growth models that can explain the various important characteristic properties of these networks. In fact, in many application oriented studies only knowing these properties is sufficient. For instance, if one wishes to launch a targeted attack on a network, this can be done even without the knowledge of the full network structure; rather an estimate of some of the properties is sufficient enough to launch the attack. We, in this paper show that even if the network structure at a future time point is not available one can still manage to estimate its properties. We propose a novel method to map a temporal network to a set of time series instances, analyze them and using a standard forecast model of time series, try to predict the properties of a temporal network at a later time instance. To our aim, we consider eight properties such as number of active nodes, average degree, clustering coefficient etc. and apply our prediction framework on them. We mainly focus on the temporal network of human face-to-face contacts and observe that it represents a stochastic process with memory that can be modeled as Auto-Regressive-Integrated-Moving-Average (ARIMA). We use cross validation techniques to find the percentage accuracy of our predictions. An important observation is that the frequency domain properties of the time series obtained from spectrogram analysis could be used to refine the prediction framework by identifying beforehand the cases where the error in prediction is likely to be high. This leads to an improvement of 7.96% (for error level ≤20%) in prediction accuracy on an average across all datasets. As an application we show how such prediction scheme can be used to launch targeted attacks on temporal networks. Contribution to the Topical Issue
Electronics via waveform analysis
Craig, Edwin C
1993-01-01
The author believes that a good basic understanding of electronics can be achieved by detailed visual analyses of the actual voltage waveforms present in selected circuits. The voltage waveforms included in this text were photographed using a 35-rrun camera in an attempt to make the book more attractive. This book is intended for the use of students with a variety of backgrounds. For this reason considerable material has been placed in the Appendix for those students who find it useful. The Appendix includes many basic electricity and electronic concepts as well as mathematical derivations that are not vital to the understanding of the circuit being discussed in the text at that time. Also some derivations might be so long that, if included in the text, it could affect the concentration of the student on the circuit being studied. The author has tried to make the book comprehensive enough so that a student could use it as a self-study course, providing one has access to adequate laboratory equipment.
Nonparametric factor analysis of time series
Rodríguez-Poo, Juan M.; Linton, Oliver Bruce
1998-01-01
We introduce a nonparametric smoothing procedure for nonparametric factor analaysis of multivariate time series. The asymptotic properties of the proposed procedures are derived. We present an application based on the residuals from the Fair macromodel.
DIY Solar Market Analysis Webinar Series: Solar Resource and Technical
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 Potential | State, Local, and Tribal Governments | NREL DIY Solar Market Analysis Webinar
Inverse Problem Approach for the Alignment of Electron Tomographic Series.
Tran , Viet Dung; Moreaud , Maxime; Thiébaut , Éric; Denis , L.; Becker , Jean-Marie
2014-01-01
In the refining industry, morphological measurements of particles have become an essential part in the characterization catalyst supports. Through these parameters, one can infer the specific physicochemical properties of the studied materials. One of the main acquisition techniques is electron tomography (or nanotomography). 3D volumes are reconstructed from sets of projections from different angles made by a Transmission Elect...
Horváth, Csilla; Kornelis, Marcel; Leeflang, Peter S.H.
2002-01-01
In this review, we give a comprehensive summary of time series techniques in marketing, and discuss a variety of time series analysis (TSA) techniques and models. We classify them in the sets (i) univariate TSA, (ii) multivariate TSA, and (iii) multiple TSA. We provide relevant marketing
Time series analysis in the social sciences the fundamentals
Shin, Youseop
2017-01-01
Times Series Analysis in the Social Sciences is a practical and highly readable introduction written exclusively for students and researchers whose mathematical background is limited to basic algebra. The book focuses on fundamental elements of time series analysis that social scientists need to understand so they can employ time series analysis for their research and practice. Through step-by-step explanations and using monthly violent crime rates as case studies, this book explains univariate time series from the preliminary visual analysis through the modeling of seasonality, trends, and re
Energy Technology Data Exchange (ETDEWEB)
Carey, John J.; Allen, Jeremy P. [School of Chemistry and CRANN, Trinity College Dublin, Dublin 2 (Ireland); Scanlon, David O. [University College London, Kathleen Lonsdale Materials Chemistry, 20 Gordon Street, London WC1H 0AJ (United Kingdom); Diamond Light Source Ltd., Diamond House, Harwell Science and Innovation Campus, Didcot, Oxfordshire OX11 0DE (United Kingdom); Watson, Graeme W., E-mail: watsong@tcd.ie [School of Chemistry and CRANN, Trinity College Dublin, Dublin 2 (Ireland)
2014-05-01
In this study, density functional theory is used to evaluate the electronic structure of the antimony chalcogenide series. Analysis of the electronic density of states and charge density shows that asymmetric density, or ‘lone pairs’, forms on the Sb{sup III} cations in the distorted oxide, sulphide and selenide materials. The asymmetric density progressively weakens down the series, due to the increase in energy of valence p states from O to Te, and is absent for Sb{sub 2}Te{sub 3}. The fundamental and optical band gaps were calculated and Sb{sub 2}O{sub 3}, Sb{sub 2}S{sub 3} and Sb{sub 2}Se{sub 3} have indirect band gaps, while Sb{sub 2}Te{sub 3} was calculated to have a direct band gap at Γ. The band gaps are also seen to reduce from Sb{sub 2}O{sub 3} to Sb{sub 2}Te{sub 3}. The optical band gap for Sb{sub 2}O{sub 3} makes it a candidate as a transparent conducting oxide, while Sb{sub 2}S{sub 3} and Sb{sub 2}Se{sub 3} have suitable band gaps for thin film solar cell absorbers. - Graphical abstract: A schematic illustrating the interaction between the Sb{sup III} cations and the chalcogenide anions and the change in their respective energy levels down the series. - Highlights: • The electronic structure of the antimony chalcogenide series is modelled using DFT. • Asymmetric density is present on distorted systems and absent on the symmetric telluride system. • Asymmetric density is formed from the mixing of Sb 5s and anion p states, where the anti-bonding combination is stabilised by the Sb 5p states. • The asymmetric density weakens down the series due to the increase in energy of chalcogenide p states. • The increase in energy of the anion p states reduces the fundamental and optical band gaps.
TIME SERIES ANALYSIS USING A UNIQUE MODEL OF TRANSFORMATION
Directory of Open Access Journals (Sweden)
Goran Klepac
2007-12-01
Full Text Available REFII1 model is an authorial mathematical model for time series data mining. The main purpose of that model is to automate time series analysis, through a unique transformation model of time series. An advantage of this approach of time series analysis is the linkage of different methods for time series analysis, linking traditional data mining tools in time series, and constructing new algorithms for analyzing time series. It is worth mentioning that REFII model is not a closed system, which means that we have a finite set of methods. At first, this is a model for transformation of values of time series, which prepares data used by different sets of methods based on the same model of transformation in a domain of problem space. REFII model gives a new approach in time series analysis based on a unique model of transformation, which is a base for all kind of time series analysis. The advantage of REFII model is its possible application in many different areas such as finance, medicine, voice recognition, face recognition and text mining.
Mathematical foundations of time series analysis a concise introduction
Beran, Jan
2017-01-01
This book provides a concise introduction to the mathematical foundations of time series analysis, with an emphasis on mathematical clarity. The text is reduced to the essential logical core, mostly using the symbolic language of mathematics, thus enabling readers to very quickly grasp the essential reasoning behind time series analysis. It appeals to anybody wanting to understand time series in a precise, mathematical manner. It is suitable for graduate courses in time series analysis but is equally useful as a reference work for students and researchers alike.
Time Series Analysis Using Geometric Template Matching.
Frank, Jordan; Mannor, Shie; Pineau, Joelle; Precup, Doina
2013-03-01
We present a novel framework for analyzing univariate time series data. At the heart of the approach is a versatile algorithm for measuring the similarity of two segments of time series called geometric template matching (GeTeM). First, we use GeTeM to compute a similarity measure for clustering and nearest-neighbor classification. Next, we present a semi-supervised learning algorithm that uses the similarity measure with hierarchical clustering in order to improve classification performance when unlabeled training data are available. Finally, we present a boosting framework called TDEBOOST, which uses an ensemble of GeTeM classifiers. TDEBOOST augments the traditional boosting approach with an additional step in which the features used as inputs to the classifier are adapted at each step to improve the training error. We empirically evaluate the proposed approaches on several datasets, such as accelerometer data collected from wearable sensors and ECG data.
Growth And Export Expansion In Mauritius - A Time Series Analysis ...
African Journals Online (AJOL)
Growth And Export Expansion In Mauritius - A Time Series Analysis. ... RV Sannassee, R Pearce ... Using Granger Causality tests, the short-run analysis results revealed that there is significant reciprocal causality between real export earnings ...
Stochastic time series analysis of hydrology data for water resources
Sathish, S.; Khadar Babu, S. K.
2017-11-01
The prediction to current publication of stochastic time series analysis in hydrology and seasonal stage. The different statistical tests for predicting the hydrology time series on Thomas-Fiering model. The hydrology time series of flood flow have accept a great deal of consideration worldwide. The concentration of stochastic process areas of time series analysis method are expanding with develop concerns about seasonal periods and global warming. The recent trend by the researchers for testing seasonal periods in the hydrologic flowseries using stochastic process on Thomas-Fiering model. The present article proposed to predict the seasonal periods in hydrology using Thomas-Fiering model.
Economic Analysis in Series-Distillation Desalination
Directory of Open Access Journals (Sweden)
Mirna Rahmah Lubis
2010-06-01
Full Text Available The ability to produce potable water economically is the primary purpose of seawater desalination research. Reverse osmosis (RO and multi-stage flash (MSF cost more than potable water produced from fresh water resources. Therefore, this research investigates a high-efficiency mechanical vapor-compression distillation system that employs an improved water flow arrangement. The incoming salt concentration was 0.15% salt for brackish water and 3.5% salt for seawater, whereas the outgoing salt concentration was 1.5% and 7%, respectively. Distillation was performed at 439 K and 722 kPa for both brackish water feed and seawater feed. Water costs of the various conditions were calculated for brackish water and seawater feeds using optimum conditions considered as 25 and 20 stages, respectively. For brackish water at a temperature difference of 0.96 K, the energy requirement is 2.0 kWh/m3. At this condition, the estimated water cost is $0.39/m3 achieved with 10,000,000 gal/day distillate, 30-year bond, 5% interest rate, and $0.05/kWh electricity. For seawater at a temperature difference of 0.44 K, the energy requirement is 3.97 kWh/m3 and the estimated water cost is $0.61/m3. Greater efficiency of the vapor compression system is achieved by connecting multiple evaporators in series, rather than the traditional parallel arrangement. The efficiency results from the gradual increase of salinity in each stage of the series arrangement in comparison to parallel. Calculations using various temperature differences between boiling brine and condensing steam show the series arrangement has the greatest improvement at lower temperature differences. Keywords: desalination, dropwise condensation, mechanical-vapor compression
Analysis of JET ELMy time series
International Nuclear Information System (INIS)
Zvejnieks, G.; Kuzovkov, V.N.
2005-01-01
Full text: Achievement of the planned operational regime in the next generation tokamaks (such as ITER) still faces principal problems. One of the main challenges is obtaining the control of edge localized modes (ELMs), which should lead to both long plasma pulse times and reasonable divertor life time. In order to control ELMs the hypothesis was proposed by Degeling [1] that ELMs exhibit features of chaotic dynamics and thus a standard chaos control methods might be applicable. However, our findings which are based on the nonlinear autoregressive (NAR) model contradict this hypothesis for JET ELMy time-series. In turn, it means that ELM behavior is of a relaxation or random type. These conclusions coincide with our previous results obtained for ASDEX Upgrade time series [2]. [1] A.W. Degeling, Y.R. Martin, P.E. Bak, J. B.Lister, and X. Llobet, Plasma Phys. Control. Fusion 43, 1671 (2001). [2] G. Zvejnieks, V.N. Kuzovkov, O. Dumbrajs, A.W. Degeling, W. Suttrop, H. Urano, and H. Zohm, Physics of Plasmas 11, 5658 (2004)
Tool Wear Monitoring Using Time Series Analysis
Song, Dong Yeul; Ohara, Yasuhiro; Tamaki, Haruo; Suga, Masanobu
A tool wear monitoring approach considering the nonlinear behavior of cutting mechanism caused by tool wear and/or localized chipping is proposed, and its effectiveness is verified through the cutting experiment and actual turning machining. Moreover, the variation in the surface roughness of the machined workpiece is also discussed using this approach. In this approach, the residual error between the actually measured vibration signal and the estimated signal obtained from the time series model corresponding to dynamic model of cutting is introduced as the feature of diagnosis. Consequently, it is found that the early tool wear state (i.e. flank wear under 40µm) can be monitored, and also the optimal tool exchange time and the tool wear state for actual turning machining can be judged by this change in the residual error. Moreover, the variation of surface roughness Pz in the range of 3 to 8µm can be estimated by the monitoring of the residual error.
Metagenomics meets time series analysis: unraveling microbial community dynamics
Faust, K.; Lahti, L.M.; Gonze, D.; Vos, de W.M.; Raes, J.
2015-01-01
The recent increase in the number of microbial time series studies offers new insights into the stability and dynamics of microbial communities, from the world's oceans to human microbiota. Dedicated time series analysis tools allow taking full advantage of these data. Such tools can reveal periodic
GET electronics samples data analysis
International Nuclear Information System (INIS)
Giovinazzo, J.; Goigoux, T.; Anvar, S.; Baron, P.; Blank, B.; Delagnes, E.; Grinyer, G.F.; Pancin, J.; Pedroza, J.L.; Pibernat, J.; Pollacco, E.; Rebii, A.
2016-01-01
The General Electronics for TPCs (GET) has been developed to equip a generation of time projection chamber detectors for nuclear physics, and may also be used for a wider range of detector types. The goal of this paper is to propose first analysis procedures to be applied on raw data samples from the GET system, in order to correct for systematic effects observed on test measurements. We also present a method to estimate the response function of the GET system channels. The response function is required in analysis where the input signal needs to be reconstructed, in terms of time distribution, from the registered output samples.
Topic Time Series Analysis of Microblogs
2014-10-01
may be distributed more globally. Tweets on a specific topic that cluster spatially, temporally or both might be of interest to analysts, marketers ...of $ and @, with the latter only in the case that it is the only character in the token (the @ symbol is significant in its usage by Instagram in...is generated by Instagram . Topic 80, Distance: 143.2101 Top words: 1. rawr 2. ˆ0ˆ 3. kill 4. jurassic 5. dinosaur Analysis: This topic is quite
Comparative analysis of the terms "electronic commerce" and "electronic business"
Kavaliauskienė, Virginija; Šarapovas, Tadas
2002-01-01
Establishing the terms that clearly and consistently describe growing and dynamic networked economy is a critical first step toward further analysis and evaluation of electronic commerce and electronic business processes. Electronic commerce is making an impact on the ways that purchasing activities are being conducted. Much of the early literature on this subject was very speculative. However, the growth of e-commerce has enabled more observations to be made of the use of electronic business...
Time Series Factor Analysis with an Application to Measuring Money
Gilbert, Paul D.; Meijer, Erik
2005-01-01
Time series factor analysis (TSFA) and its associated statistical theory is developed. Unlike dynamic factor analysis (DFA), TSFA obviates the need for explicitly modeling the process dynamics of the underlying phenomena. It also differs from standard factor analysis (FA) in important respects: the
Time averaging, ageing and delay analysis of financial time series
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.
Biostatistics series module 9: Survival analysis
Directory of Open Access Journals (Sweden)
Avijit Hazra
2017-01-01
Full Text Available Survival analysis is concerned with “time to event“ data. Conventionally, it dealt with cancer death as the event in question, but it can handle any event occurring over a time frame, and this need not be always adverse in nature. When the outcome of a study is the time to an event, it is often not possible to wait until the event in question has happened to all the subjects, for example, until all are dead. In addition, subjects may leave the study prematurely. Such situations lead to what is called censored observations as complete information is not available for these subjects. The data set is thus an assemblage of times to the event in question and times after which no more information on the individual is available. Survival analysis methods are the only techniques capable of handling censored observations without treating them as missing data. They also make no assumption regarding normal distribution of time to event data. Descriptive methods for exploring survival times in a sample include life table and Kaplan–Meier techniques as well as various kinds of distribution fitting as advanced modeling techniques. The Kaplan–Meier cumulative survival probability over time plot has become the signature plot for biomedical survival analysis. Several techniques are available for comparing the survival experience in two or more groups – the log-rank test is popularly used. This test can also be used to produce an odds ratio as an estimate of risk of the event in the test group; this is called hazard ratio (HR. Limitations of the traditional log-rank test have led to various modifications and enhancements. Finally, survival analysis offers different regression models for estimating the impact of multiple predictors on survival. Cox's proportional hazard model is the most general of the regression methods that allows the hazard function to be modeled on a set of explanatory variables without making restrictive assumptions concerning the
Time Series Analysis of Insar Data: Methods and Trends
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.
Stochastic Analysis : A Series of Lectures
Dozzi, Marco; Flandoli, Franco; Russo, Francesco
2015-01-01
This book presents in thirteen refereed survey articles an overview of modern activity in stochastic analysis, written by leading international experts. The topics addressed include stochastic fluid dynamics and regularization by noise of deterministic dynamical systems; stochastic partial differential equations driven by Gaussian or Lévy noise, including the relationship between parabolic equations and particle systems, and wave equations in a geometric framework; Malliavin calculus and applications to stochastic numerics; stochastic integration in Banach spaces; porous media-type equations; stochastic deformations of classical mechanics and Feynman integrals and stochastic differential equations with reflection. The articles are based on short courses given at the Centre Interfacultaire Bernoulli of the Ecole Polytechnique Fédérale de Lausanne, Switzerland, from January to June 2012. They offer a valuable resource not only for specialists, but also for other researchers and Ph.D. students in the fields o...
Transition Icons for Time-Series Visualization and Exploratory Analysis.
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.
Volatility Analysis of Bitcoin Price Time Series
Directory of Open Access Journals (Sweden)
Lukáš Pichl
2017-12-01
Full Text Available Bitcoin has the largest share in the total capitalization of cryptocurrency markets currently reaching above 70 billion USD. In this work we focus on the price of Bitcoin in terms of standard currencies and their volatility over the last five years. The average day-to-day return throughout this period is 0.328%, amounting in exponential growth from 6 USD to over 4,000 USD per 1 BTC at present. Multi-scale analysis is performed from the level of the tick data, through the 5 min, 1 hour and 1 day scales. Distribution of trading volumes (1 sec, 1 min, 1 hour and 1 day aggregated from the Kraken BTCEUR tick data is provided that shows the artifacts of algorithmic trading (selling transactions with volume peaks distributed at integer multiples of BTC unit. Arbitrage opportunities are studied using the EUR, USD and CNY currencies. Whereas the arbitrage spread for EUR-USD currency pair is found narrow at the order of a percent, at the 1 hour sampling period the arbitrage spread for USD-CNY (and similarly EUR-CNY is found to be more substantial, reaching as high as above 5 percent on rare occasions. The volatility of BTC exchange rates is modeled using the day-to-day distribution of logarithmic return, and the Realized Volatility, sum of the squared logarithmic returns on 5-minute basis. In this work we demonstrate that the Heterogeneous Autoregressive model for Realized Volatility Andersen et al. (2007 applies reasonably well to the BTCUSD dataset. Finally, a feed-forward neural network with 2 hidden layers using 10-day moving window sampling daily return predictors is applied to estimate the next-day logarithmic return. The results show that such an artificial neural network prediction is capable of approximate capture of the actual log return distribution; more sophisticated methods, such as recurrent neural networks and LSTM (Long Short Term Memory techniques from deep learning may be necessary for higher prediction accuracy.
Multivariate time series analysis with R and financial applications
Tsay, Ruey S
2013-01-01
Since the publication of his first book, Analysis of Financial Time Series, Ruey Tsay has become one of the most influential and prominent experts on the topic of time series. Different from the traditional and oftentimes complex approach to multivariate (MV) time series, this sequel book emphasizes structural specification, which results in simplified parsimonious VARMA modeling and, hence, eases comprehension. Through a fundamental balance between theory and applications, the book supplies readers with an accessible approach to financial econometric models and their applications to real-worl
Elements of nonlinear time series analysis and forecasting
De Gooijer, Jan G
2017-01-01
This book provides an overview of the current state-of-the-art of nonlinear time series analysis, richly illustrated with examples, pseudocode algorithms and real-world applications. Avoiding a “theorem-proof” format, it shows concrete applications on a variety of empirical time series. The book can be used in graduate courses in nonlinear time series and at the same time also includes interesting material for more advanced readers. Though it is largely self-contained, readers require an understanding of basic linear time series concepts, Markov chains and Monte Carlo simulation methods. The book covers time-domain and frequency-domain methods for the analysis of both univariate and multivariate (vector) time series. It makes a clear distinction between parametric models on the one hand, and semi- and nonparametric models/methods on the other. This offers the reader the option of concentrating exclusively on one of these nonlinear time series analysis methods. To make the book as user friendly as possible...
The Photoplethismographic Signal Processed with Nonlinear Time Series Analysis Tools
International Nuclear Information System (INIS)
Hernandez Caceres, Jose Luis; Hong, Rolando; Garcia Lanz, Abel; Garcia Dominguez, Luis; Cabannas, Karelia
2001-01-01
Finger photoplethismography (PPG) signals were submitted to nonlinear time series analysis. The applied analytical techniques were: (i) High degree polynomial fitting for baseline estimation; (ii) FFT analysis for estimating power spectra; (iii) fractal dimension estimation via the Higuchi's time-domain method, and (iv) kernel nonparametric estimation for reconstructing noise free-attractors and also for estimating signal's stochastic components
Nonlinear time series analysis of the human electrocardiogram
International Nuclear Information System (INIS)
Perc, Matjaz
2005-01-01
We analyse the human electrocardiogram with simple nonlinear time series analysis methods that are appropriate for graduate as well as undergraduate courses. In particular, attention is devoted to the notions of determinism and stationarity in physiological data. We emphasize that methods of nonlinear time series analysis can be successfully applied only if the studied data set originates from a deterministic stationary system. After positively establishing the presence of determinism and stationarity in the studied electrocardiogram, we calculate the maximal Lyapunov exponent, thus providing interesting insights into the dynamics of the human heart. Moreover, to facilitate interest and enable the integration of nonlinear time series analysis methods into the curriculum at an early stage of the educational process, we also provide user-friendly programs for each implemented method
Handbook of Time Series Analysis Recent Theoretical Developments and Applications
Schelter, Björn; Timmer, Jens
2006-01-01
This handbook provides an up-to-date survey of current research topics and applications of time series analysis methods written by leading experts in their fields. It covers recent developments in univariate as well as bivariate and multivariate time series analysis techniques ranging from physics' to life sciences' applications. Each chapter comprises both methodological aspects and applications to real world complex systems, such as the human brain or Earth's climate. Covering an exceptionally broad spectrum of topics, beginners, experts and practitioners who seek to understand the latest de
Dutta, Aniruddha; Yuan, Biao; Clukay, Christopher J.; Grabill, Christopher N.; Heinrich, Helge; Bhattacharya, Aniket; Kuebler, Stephen M.
2012-02-01
We report on the quantitative analysis of electrolessly deposited Au and Ag nanoparticles (NPs) on SU8 polymer with the help of High-Angle Annular Dark-Field Scanning Transmission Electron Microscopy (HAADF-STEM) in tilt series. Au NPs act as nucleating agents for the electroless deposition of silver. Au NPs were prepared by attachingAu^3+cations to amine functionalized SU8 polymeric surfaces and then reducing it with aqueous NaBH4. The nanoscale morphology of the deposited NPs on the surface of polymer has been studied from the dark field TEM cross sectional images. Ag NPs were deposited on the cross-linked polymeric surface from a silver citrate solution reduced by hydroquinone. HAADF-STEM enables us to determine the distances between the NPs and their exact locations at and near the surface. The particle distribution, sizes and densities provide us with the data necessary to control the parameters for the development of the electroless deposition technique for emerging nanoscale technologies.
Time series analysis and its applications with R examples
Shumway, Robert H
2017-01-01
The fourth edition of this popular graduate textbook, like its predecessors, presents a balanced and comprehensive treatment of both time and frequency domain methods with accompanying theory. Numerous examples using nontrivial data illustrate solutions to problems such as discovering natural and anthropogenic climate change, evaluating pain perception experiments using functional magnetic resonance imaging, and monitoring a nuclear test ban treaty. The book is designed as a textbook for graduate level students in the physical, biological, and social sciences and as a graduate level text in statistics. Some parts may also serve as an undergraduate introductory course. Theory and methodology are separated to allow presentations on different levels. In addition to coverage of classical methods of time series regression, ARIMA models, spectral analysis and state-space models, the text includes modern developments including categorical time series analysis, multivariate spectral methods, long memory series, nonli...
Multiresolution analysis of Bursa Malaysia KLCI time series
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.
Time Series Analysis of Wheat Futures Reward in China
Institute of Scientific and Technical Information of China (English)
无
2005-01-01
Different from the fact that the main researches are focused on single futures contract and lack of the comparison of different periods, this paper described the statistical characteristics of wheat futures reward time series of Zhengzhou Commodity Exchange in recent three years. Besides the basic statistic analysis, the paper used the GARCH and EGARCH model to describe the time series which had the ARCH effect and analyzed the persistence of volatility shocks and the leverage effect. The results showed that compared with that of normal one,wheat futures reward series were abnormality, leptokurtic and thick tail distribution. The study also found that two-part of the reward series had no autocorrelation. Among the six correlative series, three ones presented the ARCH effect. By using of the Auto-regressive Distributed Lag Model, GARCH model and EGARCH model, the paper demonstrates the persistence of volatility shocks and the leverage effect on the wheat futures reward time series. The results reveal that on the one hand, the statistical characteristics of the wheat futures reward are similar to the aboard mature futures market as a whole. But on the other hand, the results reflect some shortages such as the immatureness and the over-control by the government in the Chinese future market.
Time series analysis in chaotic diode resonator circuit
Energy Technology Data Exchange (ETDEWEB)
Hanias, M.P. [TEI of Chalkis, GR 34400, Evia, Chalkis (Greece)] e-mail: mhanias@teihal.gr; Giannaris, G. [TEI of Chalkis, GR 34400, Evia, Chalkis (Greece); Spyridakis, A. [TEI of Chalkis, GR 34400, Evia, Chalkis (Greece); Rigas, A. [TEI of Chalkis, GR 34400, Evia, Chalkis (Greece)
2006-01-01
A diode resonator chaotic circuit is presented. Multisim is used to simulate the circuit and show the presence of chaos. Time series analysis performed by the method proposed by Grasberger and Procaccia. The correlation and minimum embedding dimension {nu} and m {sub min}, respectively, were calculated. Also the corresponding Kolmogorov entropy was calculated.
Time series analysis in chaotic diode resonator circuit
International Nuclear Information System (INIS)
Hanias, M.P.; Giannaris, G.; Spyridakis, A.; Rigas, A.
2006-01-01
A diode resonator chaotic circuit is presented. Multisim is used to simulate the circuit and show the presence of chaos. Time series analysis performed by the method proposed by Grasberger and Procaccia. The correlation and minimum embedding dimension ν and m min , respectively, were calculated. Also the corresponding Kolmogorov entropy was calculated
Time series analysis of monthly pulpwood use in the Northeast
James T. Bones
1980-01-01
Time series analysis was used to develop a model that depicts pulpwood use in the Northeast. The model is useful in forecasting future pulpwood requirements (short term) or monitoring pulpwood-use activity in relation to past use patterns. The model predicted a downturn in use during 1980.
Multi-granular trend detection for time-series analysis
van Goethem, A.I.; Staals, F.; Löffler, M.; Dykes, J.; Speckmann, B.
2017-01-01
Time series (such as stock prices) and ensembles (such as model runs for weather forecasts) are two important types of one-dimensional time-varying data. Such data is readily available in large quantities but visual analysis of the raw data quickly becomes infeasible, even for moderately sized data
Time Series Analysis Based on Running Mann Whitney Z Statistics
A sensitive and objective time series analysis method based on the calculation of Mann Whitney U statistics is described. This method samples data rankings over moving time windows, converts those samples to Mann-Whitney U statistics, and then normalizes the U statistics to Z statistics using Monte-...
Time series analysis in astronomy: Limits and potentialities
DEFF Research Database (Denmark)
Vio, R.; Kristensen, N.R.; Madsen, Henrik
2005-01-01
In this paper we consider the problem of the limits concerning the physical information that can be extracted from the analysis of one or more time series ( light curves) typical of astrophysical objects. On the basis of theoretical considerations and numerical simulations, we show that with no a...
Time Series Analysis of 3D Coordinates Using Nonstochastic Observations
Velsink, H.
2016-01-01
Adjustment and testing of a combination of stochastic and nonstochastic observations is applied to the deformation analysis of a time series of 3D coordinates. Nonstochastic observations are constant values that are treated as if they were observations. They are used to formulate constraints on
Time Series Analysis of 3D Coordinates Using Nonstochastic Observations
Hiddo Velsink
2016-01-01
From the article: Abstract Adjustment and testing of a combination of stochastic and nonstochastic observations is applied to the deformation analysis of a time series of 3D coordinates. Nonstochastic observations are constant values that are treated as if they were observations. They are used to
Identification of human operator performance models utilizing time series analysis
Holden, F. M.; Shinners, S. M.
1973-01-01
The results of an effort performed by Sperry Systems Management Division for AMRL in applying time series analysis as a tool for modeling the human operator are presented. This technique is utilized for determining the variation of the human transfer function under various levels of stress. The human operator's model is determined based on actual input and output data from a tracking experiment.
Analysis and implementation of LLC-T series parallel resonant ...
African Journals Online (AJOL)
A prototype 300 W, 100 kHz converter is designed and built to experimentally demonstrate, dynamic and steady state performance for the LLC-T series parallel resonant converter. A comparative study is performed between experimental results and the simulation studies. The analysis shows that the output of converter is ...
Time series analysis methods and applications for flight data
Zhang, Jianye
2017-01-01
This book focuses on different facets of flight data analysis, including the basic goals, methods, and implementation techniques. As mass flight data possesses the typical characteristics of time series, the time series analysis methods and their application for flight data have been illustrated from several aspects, such as data filtering, data extension, feature optimization, similarity search, trend monitoring, fault diagnosis, and parameter prediction, etc. An intelligent information-processing platform for flight data has been established to assist in aircraft condition monitoring, training evaluation and scientific maintenance. The book will serve as a reference resource for people working in aviation management and maintenance, as well as researchers and engineers in the fields of data analysis and data mining.
Time series analysis of ozone data in Isfahan
Omidvari, M.; Hassanzadeh, S.; Hosseinibalam, F.
2008-07-01
Time series analysis used to investigate the stratospheric ozone formation and decomposition processes. Different time series methods are applied to detect the reason for extreme high ozone concentrations for each season. Data was convert into seasonal component and frequency domain, the latter has been evaluated by using the Fast Fourier Transform (FFT), spectral analysis. The power density spectrum estimated from the ozone data showed peaks at cycle duration of 22, 20, 36, 186, 365 and 40 days. According to seasonal component analysis most fluctuation was in 1999 and 2000, but the least fluctuation was in 2003. The best correlation between ozone and sun radiation was found in 2000. Other variables which are not available cause to this fluctuation in the 1999 and 2001. The trend of ozone is increasing in 1999 and is decreasing in other years.
ITS - The integrated TIGER series of coupled electron/photon Monte Carlo transport codes
International Nuclear Information System (INIS)
Halbleib, J.A.; Mehlhorn, T.A.
1985-01-01
The TIGER series of time-independent coupled electron/photon Monte Carlo transport codes is a group of multimaterial, multidimensional codes designed to provide a state-of-the-art description of the production and transport of the electron/photon cascade. The codes follow both electrons and photons from 1.0 GeV down to 1.0 keV, and the user has the option of combining the collisional transport with transport in macroscopic electric and magnetic fields of arbitrary spatial dependence. Source particles can be either electrons or photons. The most important output data are (a) charge and energy deposition profiles, (b) integral and differential escape coefficients for both electrons and photons, (c) differential electron and photon flux, and (d) pulse-height distributions for selected regions of the problem geometry. The base codes of the series differ from one another primarily in their dimensionality and geometric modeling. They include (a) a one-dimensional multilayer code, (b) a code that describes the transport in two-dimensional axisymmetric cylindrical material geometries with a fully three-dimensional description of particle trajectories, and (c) a general three-dimensional transport code which employs a combinatorial geometry scheme. These base codes were designed primarily for describing radiation transport for those situations in which the detailed atomic structure of the transport medium is not important. For some applications, it is desirable to have a more detailed model of the low energy transport. The system includes three additional codes that contain a more elaborate ionization/relaxation model than the base codes. Finally, the system includes two codes that combine the collisional transport of the multidimensional base codes with transport in macroscopic electric and magnetic fields of arbitrary spatial dependence
GENDER ANALYSIS OF ELECTRONIC INFORMATION
African Journals Online (AJOL)
use of internet Search engines such as google, yahoo and other free internet resources was found ... empirical studies are undertaken to examine the influence of gender ... H3: Perceived ease of use is positively related to the use of electronic.
Time series analysis of nuclear instrumentation in EBR-II
International Nuclear Information System (INIS)
Imel, G.R.
1996-01-01
Results of a time series analysis of the scaler count data from the 3 wide range nuclear detectors in the Experimental Breeder Reactor-II are presented. One of the channels was replaced, and it was desired to determine if there was any statistically significant change (ie, improvement) in the channel's response after the replacement. Data were collected from all 3 channels for 16-day periods before and after detector replacement. Time series analysis and statistical tests showed that there was no significant change after the detector replacement. Also, there were no statistically significant differences among the 3 channels, either before or after the replacement. Finally, it was determined that errors in the reactivity change inferred from subcritical count monitoring during fuel handling would be on the other of 20-30 cents for single count intervals
Mathematical methods in time series analysis and digital image processing
Kurths, J; Maass, P; Timmer, J
2008-01-01
The aim of this volume is to bring together research directions in theoretical signal and imaging processing developed rather independently in electrical engineering, theoretical physics, mathematics and the computer sciences. In particular, mathematically justified algorithms and methods, the mathematical analysis of these algorithms, and methods as well as the investigation of connections between methods from time series analysis and image processing are reviewed. An interdisciplinary comparison of these methods, drawing upon common sets of test problems from medicine and geophysical/enviromental sciences, is also addressed. This volume coherently summarizes work carried out in the field of theoretical signal and image processing. It focuses on non-linear and non-parametric models for time series as well as on adaptive methods in image processing.
Spectral Unmixing Analysis of Time Series Landsat 8 Images
Zhuo, R.; Xu, L.; Peng, J.; Chen, Y.
2018-05-01
Temporal analysis of Landsat 8 images opens up new opportunities in the unmixing procedure. Although spectral analysis of time series Landsat imagery has its own advantage, it has rarely been studied. Nevertheless, using the temporal information can provide improved unmixing performance when compared to independent image analyses. Moreover, different land cover types may demonstrate different temporal patterns, which can aid the discrimination of different natures. Therefore, this letter presents time series K-P-Means, a new solution to the problem of unmixing time series Landsat imagery. The proposed approach is to obtain the "purified" pixels in order to achieve optimal unmixing performance. The vertex component analysis (VCA) is used to extract endmembers for endmember initialization. First, nonnegative least square (NNLS) is used to estimate abundance maps by using the endmember. Then, the estimated endmember is the mean value of "purified" pixels, which is the residual of the mixed pixel after excluding the contribution of all nondominant endmembers. Assembling two main steps (abundance estimation and endmember update) into the iterative optimization framework generates the complete algorithm. Experiments using both simulated and real Landsat 8 images show that the proposed "joint unmixing" approach provides more accurate endmember and abundance estimation results compared with "separate unmixing" approach.
Notes on economic time series analysis system theoretic perspectives
Aoki, Masanao
1983-01-01
In seminars and graduate level courses I have had several opportunities to discuss modeling and analysis of time series with economists and economic graduate students during the past several years. These experiences made me aware of a gap between what economic graduate students are taught about vector-valued time series and what is available in recent system literature. Wishing to fill or narrow the gap that I suspect is more widely spread than my personal experiences indicate, I have written these notes to augment and reor ganize materials I have given in these courses and seminars. I have endeavored to present, in as much a self-contained way as practicable, a body of results and techniques in system theory that I judge to be relevant and useful to economists interested in using time series in their research. I have essentially acted as an intermediary and interpreter of system theoretic results and perspectives in time series by filtering out non-essential details, and presenting coherent accounts of wha...
Topological data analysis of financial time series: Landscapes of crashes
Gidea, Marian; Katz, Yuri
2018-02-01
We explore the evolution of daily returns of four major US stock market indices during the technology crash of 2000, and the financial crisis of 2007-2009. Our methodology is based on topological data analysis (TDA). We use persistence homology to detect and quantify topological patterns that appear in multidimensional time series. Using a sliding window, we extract time-dependent point cloud data sets, to which we associate a topological space. We detect transient loops that appear in this space, and we measure their persistence. This is encoded in real-valued functions referred to as a 'persistence landscapes'. We quantify the temporal changes in persistence landscapes via their Lp-norms. We test this procedure on multidimensional time series generated by various non-linear and non-equilibrium models. We find that, in the vicinity of financial meltdowns, the Lp-norms exhibit strong growth prior to the primary peak, which ascends during a crash. Remarkably, the average spectral density at low frequencies of the time series of Lp-norms of the persistence landscapes demonstrates a strong rising trend for 250 trading days prior to either dotcom crash on 03/10/2000, or to the Lehman bankruptcy on 09/15/2008. Our study suggests that TDA provides a new type of econometric analysis, which complements the standard statistical measures. The method can be used to detect early warning signals of imminent market crashes. We believe that this approach can be used beyond the analysis of financial time series presented here.
Cluster analysis of activity-time series in motor learning
DEFF Research Database (Denmark)
Balslev, Daniela; Nielsen, Finn Å; Futiger, Sally A
2002-01-01
Neuroimaging studies of learning focus on brain areas where the activity changes as a function of time. To circumvent the difficult problem of model selection, we used a data-driven analytic tool, cluster analysis, which extracts representative temporal and spatial patterns from the voxel......-time series. The optimal number of clusters was chosen using a cross-validated likelihood method, which highlights the clustering pattern that generalizes best over the subjects. Data were acquired with PET at different time points during practice of a visuomotor task. The results from cluster analysis show...
International Nuclear Information System (INIS)
Schüngel, E; Brandt, S; Schulze, J; Donkó, Z; Korolov, I; Derzsi, A
2015-01-01
The self-excitation of plasma series resonance (PSR) oscillations plays an important role in the electron heating dynamics in capacitively coupled radio-frequency (CCRF) plasmas. In a combined approach of PIC/MCC simulations and a theoretical model based on an equivalent circuit, we investigate the self-excitation of PSR oscillations and their effect on the electron heating in geometrically symmetric CCRF plasmas driven by multiple consecutive harmonics. The discharge symmetry is controlled via the electrical asymmetry effect (EAE), i.e. by varying the total number of harmonics and tuning the phase shifts between them. It is demonstrated that PSR oscillations will be self-excited under both symmetric and asymmetric conditions, if (i) the charge–voltage relation of the plasma sheaths deviates from a simple quadratic behavior and (ii) the inductance of the plasma bulk exhibits a temporal modulation. These two effects have been neglected up to now, but we show that they must be included in the model in order to properly describe the nonlinear series resonance circuit and reproduce the self-excitation of PSR oscillations, which are observed in the electron current density resulting from simulations of geometrically symmetric CCRF plasmas. Furthermore, the effect of PSR self-excitation on the discharge current and the plasma properties, such as the potential profile, is illustrated by applying Fourier analysis. High-frequency oscillations in the entire spectrum between the applied frequencies and the local electron plasma frequency are observed. As a consequence, the electron heating is strongly enhanced by the presence of PSR oscillations. A complex electron heating dynamics is found during the expansion phase of the sheath, which is fully collapsed, when the PSR is initially self-excited. The nonlinear electron resonance heating (NERH) associated with the PSR oscillations causes a spatial asymmetry in the electron heating. By discussing the resulting ionization
Data analysis for electronic experiments
International Nuclear Information System (INIS)
Grote, H.
1981-01-01
In this lecture I schell attempt to cover the principal off-line software aspects in electronic experiments. Of course, this is too ambitious an undertaking for two reasons: Firstly the field is vast, and some important aspect will certainly have escaped my attention. Secondly, the choice of methods, features, algorithms, and packages presented will be biased through my personal opinion and experience, although to some extent it is influenced as well by the opinion and experience of my colleagues, who, like myself, are working in this field at CERN. Therefore, beware. Whenever I shall claim something to be evident, a matter of experience -- a fact --it ain't necessarily so. On the other hand, it will not be entirely wrong, since our experience is based on something like 30 experiments in high-energy physics using electronic for other people, and although these people are of course misled, one has to admit their existence. (orig.)
Time Series Analysis, Modeling and Applications A Computational Intelligence Perspective
Chen, Shyi-Ming
2013-01-01
Temporal and spatiotemporal data form an inherent fabric of the society as we are faced with streams of data coming from numerous sensors, data feeds, recordings associated with numerous areas of application embracing physical and human-generated phenomena (environmental data, financial markets, Internet activities, etc.). A quest for a thorough analysis, interpretation, modeling and prediction of time series comes with an ongoing challenge for developing models that are both accurate and user-friendly (interpretable). The volume is aimed to exploit the conceptual and algorithmic framework of Computational Intelligence (CI) to form a cohesive and comprehensive environment for building models of time series. The contributions covered in the volume are fully reflective of the wealth of the CI technologies by bringing together ideas, algorithms, and numeric studies, which convincingly demonstrate their relevance, maturity and visible usefulness. It reflects upon the truly remarkable diversity of methodological a...
Recurrence Density Enhanced Complex Networks for Nonlinear Time Series Analysis
Costa, Diego G. De B.; Reis, Barbara M. Da F.; Zou, Yong; Quiles, Marcos G.; Macau, Elbert E. N.
We introduce a new method, which is entitled Recurrence Density Enhanced Complex Network (RDE-CN), to properly analyze nonlinear time series. Our method first transforms a recurrence plot into a figure of a reduced number of points yet preserving the main and fundamental recurrence properties of the original plot. This resulting figure is then reinterpreted as a complex network, which is further characterized by network statistical measures. We illustrate the computational power of RDE-CN approach by time series by both the logistic map and experimental fluid flows, which show that our method distinguishes different dynamics sufficiently well as the traditional recurrence analysis. Therefore, the proposed methodology characterizes the recurrence matrix adequately, while using a reduced set of points from the original recurrence plots.
A new series of two-dimensional silicon crystals with versatile electronic properties
Chae, Kisung; Kim, Duck Young; Son, Young-Woo
2018-04-01
Silicon (Si) is one of the most extensively studied materials owing to its significance to semiconductor science and technology. While efforts to find a new three-dimensional (3D) Si crystal with unusual properties have made some progress, its two-dimensional (2D) phases have not yet been explored as much. Here, based on a newly developed systematic ab initio materials searching strategy, we report a series of novel 2D Si crystals with unprecedented structural and electronic properties. The new structures exhibit perfectly planar outermost surface layers of a distorted hexagonal network with their thicknesses varying with the atomic arrangement inside. Dramatic changes in electronic properties ranging from semimetal to semiconducting with indirect energy gaps and even to one with direct energy gaps are realized by varying thickness as well as by surface oxidation. Our predicted 2D Si crystals with flat surfaces and tunable electronic properties will shed light on the development of silicon-based 2D electronics technology.
Hsu, Liang-Yan; Wu, Ning; Rabitz, Herschel
2016-11-30
We investigate electron transport through series and parallel intramolecular circuits in the framework of the multi-level Redfield theory. Based on the assumption of weak monomer-bath couplings, the simulations depict the length and temperature dependence in six types of intramolecular circuits. In the tunneling regime, we find that the intramolecular circuit rule is only valid in the weak monomer coupling limit. In the thermally activated hopping regime, for circuits based on two different molecular units M a and M b with distinct activation energies E act,a > E act,b , the activation energies of M a and M b in series are nearly the same as E act,a while those in parallel are nearly the same as E act,b . This study gives a comprehensive description of electron transport through intramolecular circuits from tunneling to thermally activated hopping. We hope that this work can motivate additional studies to design intramolecular circuits based on different types of building blocks, and to explore the corresponding circuit laws and the length and temperature dependence of conductance.
M series resonant x-ray lines of barium for near threshold electron excitation
International Nuclear Information System (INIS)
Morgon, D.V.
1992-01-01
An investigation of the M series resonant x-ray emission lines of barium for near threshold electron excitation was undertaken with a vacuum double crystal spectrometer equipped with potassium acid phthalate crystals. X-ray continuum isochromats were obtained for barium samples using the double crystal spectrometer as a monochrometer set to pass 532 eV photons. The rotatable anode allowed the samples to be observed by either the double crystal spectrometer or a soft x-ray appearance potential spectrometer, which was used for monitoring the surface of the varium sample for contamination, and to provide a cross-check for the double crystal spectrometer data. Barium M series characteristic x-ray spectra for 2.0 keV electron excitation were obtained for a variety of samples, and it was discovered that the fluorescent and resonant x-ray emission line energies remained virtually the same, regardless of the chemical condition of the sample. The continuum resonance effect was observed for near-threshold energy electron excitation, but it was significantly weaker than the same effect observed previously for lanthanum or cerium. The electron excitation energy and intensity of this effect were strongly dependent on the chemical condition of the barium sample. X-ray continuum isochromats were observed for pure and contaminated barium samples at a photon energy of 532 eV. For pure metallic barium, a peak associated with 4f electronic states was observed at an energy of about 10.2 eV above the Fermi level. When the sample was exposed to 1.5 x 10 4 Langmuir of air, the 4f structure became more sharply peaked, and shifted to an energy of about 12.0 eV above the Fermi level. A continuum isochromat of barium oxide was also observed. Chemical shifts in barium M IV and M V appearance potential spectra are therefore caused soley by shifts in the energy position of the empty 4f electronic states relative to the Fermi level
Time series analysis for psychological research: examining and forecasting change.
Jebb, Andrew T; Tay, Louis; Wang, Wei; Huang, Qiming
2015-01-01
Psychological research has increasingly recognized the importance of integrating temporal dynamics into its theories, and innovations in longitudinal designs and analyses have allowed such theories to be formalized and tested. However, psychological researchers may be relatively unequipped to analyze such data, given its many characteristics and the general complexities involved in longitudinal modeling. The current paper introduces time series analysis to psychological research, an analytic domain that has been essential for understanding and predicting the behavior of variables across many diverse fields. First, the characteristics of time series data are discussed. Second, different time series modeling techniques are surveyed that can address various topics of interest to psychological researchers, including describing the pattern of change in a variable, modeling seasonal effects, assessing the immediate and long-term impact of a salient event, and forecasting future values. To illustrate these methods, an illustrative example based on online job search behavior is used throughout the paper, and a software tutorial in R for these analyses is provided in the Supplementary Materials.
Time series analysis for psychological research: examining and forecasting change
Jebb, Andrew T.; Tay, Louis; Wang, Wei; Huang, Qiming
2015-01-01
Psychological research has increasingly recognized the importance of integrating temporal dynamics into its theories, and innovations in longitudinal designs and analyses have allowed such theories to be formalized and tested. However, psychological researchers may be relatively unequipped to analyze such data, given its many characteristics and the general complexities involved in longitudinal modeling. The current paper introduces time series analysis to psychological research, an analytic domain that has been essential for understanding and predicting the behavior of variables across many diverse fields. First, the characteristics of time series data are discussed. Second, different time series modeling techniques are surveyed that can address various topics of interest to psychological researchers, including describing the pattern of change in a variable, modeling seasonal effects, assessing the immediate and long-term impact of a salient event, and forecasting future values. To illustrate these methods, an illustrative example based on online job search behavior is used throughout the paper, and a software tutorial in R for these analyses is provided in the Supplementary Materials. PMID:26106341
Critical analysis of industrial electron accelerators
Energy Technology Data Exchange (ETDEWEB)
Korenev, S. E-mail: sergey_korenev@steris.com
2004-10-01
The critical analysis of electron linacs for industrial applications (degradation of PTFE, curing of composites, modification of materials, sterilization and others) is considered in this report. Main physical requirements for industrial electron accelerators consist in the variations of beam parameters, such as kinetic energy and beam power. Questions for regulation of these beam parameters are considered. The level of absorbed dose in the irradiated product and throughput determines the main parameters of electron accelerator. The type of ideal electron linac for industrial applications is discussed.
Critical analysis of industrial electron accelerators
Korenev, S.
2004-09-01
The critical analysis of electron linacs for industrial applications (degradation of PTFE, curing of composites, modification of materials, sterlization and others) is considered in this report. Main physical requirements for industrial electron accelerators consist in the variations of beam parameters, such as kinetic energy and beam power. Questions for regulation of these beam parameters are considered. The level of absorbed dose in the irradiated product and throughput determines the main parameters of electron accelerator. The type of ideal electron linac for industrial applications is discussed.
Critical analysis of industrial electron accelerators
International Nuclear Information System (INIS)
Korenev, S.
2004-01-01
The critical analysis of electron linacs for industrial applications (degradation of PTFE, curing of composites, modification of materials, sterilization and others) is considered in this report. Main physical requirements for industrial electron accelerators consist in the variations of beam parameters, such as kinetic energy and beam power. Questions for regulation of these beam parameters are considered. The level of absorbed dose in the irradiated product and throughput determines the main parameters of electron accelerator. The type of ideal electron linac for industrial applications is discussed
Chaotic time series analysis in economics: Balance and perspectives
International Nuclear Information System (INIS)
Faggini, Marisa
2014-01-01
The aim of the paper is not to review the large body of work concerning nonlinear time series analysis in economics, about which much has been written, but rather to focus on the new techniques developed to detect chaotic behaviours in economic data. More specifically, our attention will be devoted to reviewing some of these techniques and their application to economic and financial data in order to understand why chaos theory, after a period of growing interest, appears now not to be such an interesting and promising research area
Chaotic time series analysis in economics: Balance and perspectives
Energy Technology Data Exchange (ETDEWEB)
Faggini, Marisa, E-mail: mfaggini@unisa.it [Dipartimento di Scienze Economiche e Statistiche, Università di Salerno, Fisciano 84084 (Italy)
2014-12-15
The aim of the paper is not to review the large body of work concerning nonlinear time series analysis in economics, about which much has been written, but rather to focus on the new techniques developed to detect chaotic behaviours in economic data. More specifically, our attention will be devoted to reviewing some of these techniques and their application to economic and financial data in order to understand why chaos theory, after a period of growing interest, appears now not to be such an interesting and promising research area.
Computer Series, 98. Electronics for Scientists: A Computer-Intensive Approach.
Scheeline, Alexander; Mork, Brian J.
1988-01-01
Reports the design for a principles-before-details presentation of electronics for an instrumental analysis class. Uses computers for data collection and simulations. Requires one semester with two 2.5-hour periods and two lectures per week. Includes lab and lecture syllabi. (MVL)
Time series clustering analysis of health-promoting behavior
Yang, Chi-Ta; Hung, Yu-Shiang; Deng, Guang-Feng
2013-10-01
Health promotion must be emphasized to achieve the World Health Organization goal of health for all. Since the global population is aging rapidly, ComCare elder health-promoting service was developed by the Taiwan Institute for Information Industry in 2011. Based on the Pender health promotion model, ComCare service offers five categories of health-promoting functions to address the everyday needs of seniors: nutrition management, social support, exercise management, health responsibility, stress management. To assess the overall ComCare service and to improve understanding of the health-promoting behavior of elders, this study analyzed health-promoting behavioral data automatically collected by the ComCare monitoring system. In the 30638 session records collected for 249 elders from January, 2012 to March, 2013, behavior patterns were identified by fuzzy c-mean time series clustering algorithm combined with autocorrelation-based representation schemes. The analysis showed that time series data for elder health-promoting behavior can be classified into four different clusters. Each type reveals different health-promoting needs, frequencies, function numbers and behaviors. The data analysis result can assist policymakers, health-care providers, and experts in medicine, public health, nursing and psychology and has been provided to Taiwan National Health Insurance Administration to assess the elder health-promoting behavior.
Time series analysis of gold production in Malaysia
Muda, Nora; Hoon, Lee Yuen
2012-05-01
Gold is a soft, malleable, bright yellow metallic element and unaffected by air or most reagents. It is highly valued as an asset or investment commodity and is extensively used in jewellery, industrial application, dentistry and medical applications. In Malaysia, gold mining is limited in several areas such as Pahang, Kelantan, Terengganu, Johor and Sarawak. The main purpose of this case study is to obtain a suitable model for the production of gold in Malaysia. The model can also be used to predict the data of Malaysia's gold production in the future. Box-Jenkins time series method was used to perform time series analysis with the following steps: identification, estimation, diagnostic checking and forecasting. In addition, the accuracy of prediction is tested using mean absolute percentage error (MAPE). From the analysis, the ARIMA (3,1,1) model was found to be the best fitted model with MAPE equals to 3.704%, indicating the prediction is very accurate. Hence, this model can be used for forecasting. This study is expected to help the private and public sectors to understand the gold production scenario and later plan the gold mining activities in Malaysia.
Predicting the Market Potential Using Time Series Analysis
Directory of Open Access Journals (Sweden)
Halmet Bradosti
2015-12-01
Full Text Available The aim of this analysis is to forecast a mini-market sales volume for the period of twelve months starting August 2015 to August 2016. The study is based on the monthly sales in Iraqi Dinar for a private local mini-market for the month of April 2014 to July 2015. As revealed on the graph and of course if the stagnant economic condition continues, the trend of future sales is down-warding. Based on time series analysis, the business may continue to operate and generate small revenues until August 2016. However, due to low sales volume, low profit margin and operating expenses, the revenues may not be adequate enough to produce positive net income and the business may not be able to operate afterward. The principal question rose from this is the forecasting sales in the region will be difficult where the business cycle so dynamic and revolutionary due to systematic risks and unforeseeable future.
International Nuclear Information System (INIS)
Williams, Dennis K.; Ranson, William F.
2003-01-01
One of the paradigmatic classes of problems that frequently arise in piping stress analysis discipline is the effect of local stresses created by supports and restraints attachments. Over the past 20 years, concerns have been identified by both regulatory agencies in the nuclear power industry and others in the process and chemicals industries concerning the effect of various stiff clamping arrangements on the expected life of the pipe and its various piping components. In many of the commonly utilized geometries and arrangements of pipe clamps, the elasticity problem becomes the axisymmetric stress and deformation determination in a hollow cylinder (pipe) subjected to the appropriate boundary conditions and respective loads per se. One of the geometries that serve as a pipe anchor is comprised of two pipe clamps that are bolted tightly to the pipe and affixed to a modified shoe-type arrangement. The shoe is employed for the purpose of providing an immovable base that can be easily attached either by bolting or welding to a structural steel pipe rack. Over the past 50 years, the computational tools available to the piping analyst have changed dramatically and thereby have caused the implementation of solutions to the basic problems of elasticity to change likewise. The need to obtain closed form elasticity solutions, however, has always been a driving force in engineering. The employment of symbolic calculus that is currently available through numerous software packages makes closed form solutions very economical. This paper briefly traces the solutions over the past 50 years to a variety of axisymmetric stress problems involving hollow circular cylinders employing a Fourier series representation. In the present example, a properly chosen Fourier series represent the mathematical simulation of the imposed axial displacements on the outside diametrical surface. A general solution technique is introduced for the axisymmetric discontinuity stresses resulting from an
Comparison of correlation analysis techniques for irregularly sampled time series
Directory of Open Access Journals (Sweden)
K. Rehfeld
2011-06-01
Full Text Available Geoscientific measurements often provide time series with irregular time sampling, requiring either data reconstruction (interpolation or sophisticated methods to handle irregular sampling. We compare the linear interpolation technique and different approaches for analyzing the correlation functions and persistence of irregularly sampled time series, as Lomb-Scargle Fourier transformation and kernel-based methods. In a thorough benchmark test we investigate the performance of these techniques.
All methods have comparable root mean square errors (RMSEs for low skewness of the inter-observation time distribution. For high skewness, very irregular data, interpolation bias and RMSE increase strongly. We find a 40 % lower RMSE for the lag-1 autocorrelation function (ACF for the Gaussian kernel method vs. the linear interpolation scheme,in the analysis of highly irregular time series. For the cross correlation function (CCF the RMSE is then lower by 60 %. The application of the Lomb-Scargle technique gave results comparable to the kernel methods for the univariate, but poorer results in the bivariate case. Especially the high-frequency components of the signal, where classical methods show a strong bias in ACF and CCF magnitude, are preserved when using the kernel methods.
We illustrate the performances of interpolation vs. Gaussian kernel method by applying both to paleo-data from four locations, reflecting late Holocene Asian monsoon variability as derived from speleothem δ^{18}O measurements. Cross correlation results are similar for both methods, which we attribute to the long time scales of the common variability. The persistence time (memory is strongly overestimated when using the standard, interpolation-based, approach. Hence, the Gaussian kernel is a reliable and more robust estimator with significant advantages compared to other techniques and suitable for large scale application to paleo-data.
Remote-Sensing Time Series Analysis, a Vegetation Monitoring Tool
McKellip, Rodney; Prados, Donald; Ryan, Robert; Ross, Kenton; Spruce, Joseph; Gasser, Gerald; Greer, Randall
2008-01-01
The Time Series Product Tool (TSPT) is software, developed in MATLAB , which creates and displays high signal-to- noise Vegetation Indices imagery and other higher-level products derived from remotely sensed data. This tool enables automated, rapid, large-scale regional surveillance of crops, forests, and other vegetation. TSPT temporally processes high-revisit-rate satellite imagery produced by the Moderate Resolution Imaging Spectroradiometer (MODIS) and by other remote-sensing systems. Although MODIS imagery is acquired daily, cloudiness and other sources of noise can greatly reduce the effective temporal resolution. To improve cloud statistics, the TSPT combines MODIS data from multiple satellites (Aqua and Terra). The TSPT produces MODIS products as single time-frame and multitemporal change images, as time-series plots at a selected location, or as temporally processed image videos. Using the TSPT program, MODIS metadata is used to remove and/or correct bad and suspect data. Bad pixel removal, multiple satellite data fusion, and temporal processing techniques create high-quality plots and animated image video sequences that depict changes in vegetation greenness. This tool provides several temporal processing options not found in other comparable imaging software tools. Because the framework to generate and use other algorithms is established, small modifications to this tool will enable the use of a large range of remotely sensed data types. An effective remote-sensing crop monitoring system must be able to detect subtle changes in plant health in the earliest stages, before the effects of a disease outbreak or other adverse environmental conditions can become widespread and devastating. The integration of the time series analysis tool with ground-based information, soil types, crop types, meteorological data, and crop growth models in a Geographic Information System, could provide the foundation for a large-area crop-surveillance system that could identify
Inorganic chemical analysis of environmental materials—A lecture series
Crock, J.G.; Lamothe, P.J.
2011-01-01
At the request of the faculty of the Colorado School of Mines, Golden, Colorado, the authors prepared and presented a lecture series to the students of a graduate level advanced instrumental analysis class. The slides and text presented in this report are a compilation and condensation of this series of lectures. The purpose of this report is to present the slides and notes and to emphasize the thought processes that should be used by a scientist submitting samples for analyses in order to procure analytical data to answer a research question. First and foremost, the analytical data generated can be no better than the samples submitted. The questions to be answered must first be well defined and the appropriate samples collected from the population that will answer the question. The proper methods of analysis, including proper sample preparation and digestion techniques, must then be applied. Care must be taken to achieve the required limits of detection of the critical analytes to yield detectable analyte concentration (above "action" levels) for the majority of the study's samples and to address what portion of those analytes answer the research question-total or partial concentrations. To guarantee a robust analytical result that answers the research question(s), a well-defined quality assurance and quality control (QA/QC) plan must be employed. This QA/QC plan must include the collection and analysis of field and laboratory blanks, sample duplicates, and matrix-matched standard reference materials (SRMs). The proper SRMs may include in-house materials and/or a selection of widely available commercial materials. A discussion of the preparation and applicability of in-house reference materials is also presented. Only when all these analytical issues are sufficiently addressed can the research questions be answered with known certainty.
STUDIES IN ASTRONOMICAL TIME SERIES ANALYSIS. VI. BAYESIAN BLOCK REPRESENTATIONS
Energy Technology Data Exchange (ETDEWEB)
Scargle, Jeffrey D. [Space Science and Astrobiology Division, MS 245-3, NASA Ames Research Center, Moffett Field, CA 94035-1000 (United States); Norris, Jay P. [Physics Department, Boise State University, 2110 University Drive, Boise, ID 83725-1570 (United States); Jackson, Brad [The Center for Applied Mathematics and Computer Science, Department of Mathematics, San Jose State University, One Washington Square, MH 308, San Jose, CA 95192-0103 (United States); Chiang, James, E-mail: jeffrey.d.scargle@nasa.gov [W. W. Hansen Experimental Physics Laboratory, Kavli Institute for Particle Astrophysics and Cosmology, Department of Physics and SLAC National Accelerator Laboratory, Stanford University, Stanford, CA 94305 (United States)
2013-02-20
This paper addresses the problem of detecting and characterizing local variability in time series and other forms of sequential data. The goal is to identify and characterize statistically significant variations, at the same time suppressing the inevitable corrupting observational errors. We present a simple nonparametric modeling technique and an algorithm implementing it-an improved and generalized version of Bayesian Blocks-that finds the optimal segmentation of the data in the observation interval. The structure of the algorithm allows it to be used in either a real-time trigger mode, or a retrospective mode. Maximum likelihood or marginal posterior functions to measure model fitness are presented for events, binned counts, and measurements at arbitrary times with known error distributions. Problems addressed include those connected with data gaps, variable exposure, extension to piecewise linear and piecewise exponential representations, multivariate time series data, analysis of variance, data on the circle, other data modes, and dispersed data. Simulations provide evidence that the detection efficiency for weak signals is close to a theoretical asymptotic limit derived by Arias-Castro et al. In the spirit of Reproducible Research all of the code and data necessary to reproduce all of the figures in this paper are included as supplementary material.
Time series analysis of brain regional volume by MR image
International Nuclear Information System (INIS)
Tanaka, Mika; Tarusawa, Ayaka; Nihei, Mitsuyo; Fukami, Tadanori; Yuasa, Tetsuya; Wu, Jin; Ishiwata, Kiichi; Ishii, Kenji
2010-01-01
The present study proposed a methodology of time series analysis of volumes of frontal, parietal, temporal and occipital lobes and cerebellum because such volumetric reports along the process of individual's aging have been scarcely presented. Subjects analyzed were brain images of 2 healthy males and 18 females of av. age of 69.0 y, of which T1-weighted 3D SPGR (spoiled gradient recalled in the steady state) acquisitions with a GE SIGNA EXCITE HD 1.5T machine were conducted for 4 times in the time series of 42-50 months. The image size was 256 x 256 x (86-124) voxels with digitization level 16 bits. As the template for the regions, the standard gray matter atlas (icbn452 a tlas p robability g ray) and its labeled one (icbn.Labels), provided by UCLA Laboratory of Neuro Imaging, were used for individual's standardization. Segmentation, normalization and coregistration were performed with the MR imaging software SPM8 (Statistic Parametric Mapping 8). Volumes of regions were calculated as their voxel ratio to the whole brain voxel in percent. It was found that the regional volumes decreased with aging in all above lobes examined and cerebellum in average percent per year of -0.11, -0.07, -0.04, -0.02, and -0.03, respectively. The procedure for calculation of the regional volumes, which has been manually operated hitherto, can be automatically conducted for the individual brain using the standard atlases above. (T.T.)
Studies in Astronomical Time Series Analysis. VI. Bayesian Block Representations
Scargle, Jeffrey D.; Norris, Jay P.; Jackson, Brad; Chiang, James
2013-01-01
This paper addresses the problem of detecting and characterizing local variability in time series and other forms of sequential data. The goal is to identify and characterize statistically significant variations, at the same time suppressing the inevitable corrupting observational errors. We present a simple nonparametric modeling technique and an algorithm implementing it-an improved and generalized version of Bayesian Blocks [Scargle 1998]-that finds the optimal segmentation of the data in the observation interval. The structure of the algorithm allows it to be used in either a real-time trigger mode, or a retrospective mode. Maximum likelihood or marginal posterior functions to measure model fitness are presented for events, binned counts, and measurements at arbitrary times with known error distributions. Problems addressed include those connected with data gaps, variable exposure, extension to piece- wise linear and piecewise exponential representations, multivariate time series data, analysis of variance, data on the circle, other data modes, and dispersed data. Simulations provide evidence that the detection efficiency for weak signals is close to a theoretical asymptotic limit derived by [Arias-Castro, Donoho and Huo 2003]. In the spirit of Reproducible Research [Donoho et al. (2008)] all of the code and data necessary to reproduce all of the figures in this paper are included as auxiliary material.
STUDIES IN ASTRONOMICAL TIME SERIES ANALYSIS. VI. BAYESIAN BLOCK REPRESENTATIONS
International Nuclear Information System (INIS)
Scargle, Jeffrey D.; Norris, Jay P.; Jackson, Brad; Chiang, James
2013-01-01
This paper addresses the problem of detecting and characterizing local variability in time series and other forms of sequential data. The goal is to identify and characterize statistically significant variations, at the same time suppressing the inevitable corrupting observational errors. We present a simple nonparametric modeling technique and an algorithm implementing it—an improved and generalized version of Bayesian Blocks—that finds the optimal segmentation of the data in the observation interval. The structure of the algorithm allows it to be used in either a real-time trigger mode, or a retrospective mode. Maximum likelihood or marginal posterior functions to measure model fitness are presented for events, binned counts, and measurements at arbitrary times with known error distributions. Problems addressed include those connected with data gaps, variable exposure, extension to piecewise linear and piecewise exponential representations, multivariate time series data, analysis of variance, data on the circle, other data modes, and dispersed data. Simulations provide evidence that the detection efficiency for weak signals is close to a theoretical asymptotic limit derived by Arias-Castro et al. In the spirit of Reproducible Research all of the code and data necessary to reproduce all of the figures in this paper are included as supplementary material.
International Nuclear Information System (INIS)
Munoz-Diosdado, A
2005-01-01
We analyzed databases with gait time series of adults and persons with Parkinson, Huntington and amyotrophic lateral sclerosis (ALS) diseases. We obtained the staircase graphs of accumulated events that can be bounded by a straight line whose slope can be used to distinguish between gait time series from healthy and ill persons. The global Hurst exponent of these series do not show tendencies, we intend that this is because some gait time series have monofractal behavior and others have multifractal behavior so they cannot be characterized with a single Hurst exponent. We calculated the multifractal spectra, obtained the spectra width and found that the spectra of the healthy young persons are almost monofractal. The spectra of ill persons are wider than the spectra of healthy persons. In opposition to the interbeat time series where the pathology implies loss of multifractality, in the gait time series the multifractal behavior emerges with the pathology. Data were collected from healthy and ill subjects as they walked in a roughly circular path and they have sensors in both feet, so we have one time series for the left foot and other for the right foot. First, we analyzed these time series separately, and then we compared both results, with direct comparison and with a cross correlation analysis. We tried to find differences in both time series that can be used as indicators of equilibrium problems
Energy Technology Data Exchange (ETDEWEB)
Munoz-Diosdado, A [Department of Mathematics, Unidad Profesional Interdisciplinaria de Biotecnologia, Instituto Politecnico Nacional, Av. Acueducto s/n, 07340, Mexico City (Mexico)
2005-01-01
We analyzed databases with gait time series of adults and persons with Parkinson, Huntington and amyotrophic lateral sclerosis (ALS) diseases. We obtained the staircase graphs of accumulated events that can be bounded by a straight line whose slope can be used to distinguish between gait time series from healthy and ill persons. The global Hurst exponent of these series do not show tendencies, we intend that this is because some gait time series have monofractal behavior and others have multifractal behavior so they cannot be characterized with a single Hurst exponent. We calculated the multifractal spectra, obtained the spectra width and found that the spectra of the healthy young persons are almost monofractal. The spectra of ill persons are wider than the spectra of healthy persons. In opposition to the interbeat time series where the pathology implies loss of multifractality, in the gait time series the multifractal behavior emerges with the pathology. Data were collected from healthy and ill subjects as they walked in a roughly circular path and they have sensors in both feet, so we have one time series for the left foot and other for the right foot. First, we analyzed these time series separately, and then we compared both results, with direct comparison and with a cross correlation analysis. We tried to find differences in both time series that can be used as indicators of equilibrium problems.
Discontinuous conduction mode analysis of phase-modulated series ...
Indian Academy of Sciences (India)
modulated dc–dc series resonant converter (SRC) operating in discontinuous conduction mode (DCM). The conventional fundamental harmonic approximation technique is extended for a non-ideal series resonant tank to clarify the limitations of ...
Centrality measures in temporal networks with time series analysis
Huang, Qiangjuan; Zhao, Chengli; Zhang, Xue; Wang, Xiaojie; Yi, Dongyun
2017-05-01
The study of identifying important nodes in networks has a wide application in different fields. However, the current researches are mostly based on static or aggregated networks. Recently, the increasing attention to networks with time-varying structure promotes the study of node centrality in temporal networks. In this paper, we define a supra-evolution matrix to depict the temporal network structure. With using of the time series analysis, the relationships between different time layers can be learned automatically. Based on the special form of the supra-evolution matrix, the eigenvector centrality calculating problem is turned into the calculation of eigenvectors of several low-dimensional matrices through iteration, which effectively reduces the computational complexity. Experiments are carried out on two real-world temporal networks, Enron email communication network and DBLP co-authorship network, the results of which show that our method is more efficient at discovering the important nodes than the common aggregating method.
Adult Craniopharyngioma: Case Series, Systematic Review, and Meta-Analysis.
Dandurand, Charlotte; Sepehry, Amir Ali; Asadi Lari, Mohammad Hossein; Akagami, Ryojo; Gooderham, Peter
2017-12-18
The optimal therapeutic approach for adult craniopharyngioma remains controversial. Some advocate for gross total resection (GTR), while others advocate for subtotal resection followed by adjuvant radiotherapy (STR + XRT). To conduct a systematic review and meta-analysis assessing the rate of recurrence in the follow-up of 3 yr in adult craniopharyngioma stratified by extent of resection and presence of adjuvant radiotherapy. MEDLINE (1946-July 1, 2016) and EMBASE (1980-June 30, 2016) were systematically reviewed. From1975 to 2013, 33 patients were treated with initial surgical resection for adult onset craniopharyngioma at our center and were reviewed for inclusion in this study. Data from 22 patients were available for inclusion as a case series in the systematic review. Eligible studies (n = 21) were identified from the literature in addition to a case series of our institutional experience. Three groups were available for analysis: GTR, STR + XRT, and STR. The rates of recurrence were 17%, 27%, and 45%, respectively. The risk of developing recurrence was significant for GTR vs STR (odds ratio [OR]: 0.24, 95% confidence interval [CI]: 0.15-0.38) and STR + XRT vs STR (OR: 0.20, 95% CI: 0.10-0.41). Risk of recurrence after GTR vs STR + XRT did not reach significance (OR: 0.63, 95% CI: 0.33-1.24, P = .18). This is the first and largest systematic review focusing on the rate of recurrence in adult craniopharyngioma. Although the rates of recurrence are favoring GTR, difference in risk of recurrence did not reach significance. This study provides guidance to clinicians and directions for future research with the need to stratify outcomes per treatment modalities. Copyright © 2017 by the Congress of Neurological Surgeons
Assessing Spontaneous Combustion Instability with Nonlinear Time Series Analysis
Eberhart, C. J.; Casiano, M. J.
2015-01-01
Considerable interest lies in the ability to characterize the onset of spontaneous instabilities within liquid propellant rocket engine (LPRE) combustion devices. Linear techniques, such as fast Fourier transforms, various correlation parameters, and critical damping parameters, have been used at great length for over fifty years. Recently, nonlinear time series methods have been applied to deduce information pertaining to instability incipiency hidden in seemingly stochastic combustion noise. A technique commonly used in biological sciences known as the Multifractal Detrended Fluctuation Analysis has been extended to the combustion dynamics field, and is introduced here as a data analysis approach complementary to linear ones. Advancing, a modified technique is leveraged to extract artifacts of impending combustion instability that present themselves a priori growth to limit cycle amplitudes. Analysis is demonstrated on data from J-2X gas generator testing during which a distinct spontaneous instability was observed. Comparisons are made to previous work wherein the data were characterized using linear approaches. Verification of the technique is performed by examining idealized signals and comparing two separate, independently developed tools.
Interrupted time-series analysis: studying trends in neurosurgery.
Wong, Ricky H; Smieliauskas, Fabrice; Pan, I-Wen; Lam, Sandi K
2015-12-01
OBJECT Neurosurgery studies traditionally have evaluated the effects of interventions on health care outcomes by studying overall changes in measured outcomes over time. Yet, this type of linear analysis is limited due to lack of consideration of the trend's effects both pre- and postintervention and the potential for confounding influences. The aim of this study was to illustrate interrupted time-series analysis (ITSA) as applied to an example in the neurosurgical literature and highlight ITSA's potential for future applications. METHODS The methods used in previous neurosurgical studies were analyzed and then compared with the methodology of ITSA. RESULTS The ITSA method was identified in the neurosurgical literature as an important technique for isolating the effect of an intervention (such as a policy change or a quality and safety initiative) on a health outcome independent of other factors driving trends in the outcome. The authors determined that ITSA allows for analysis of the intervention's immediate impact on outcome level and on subsequent trends and enables a more careful measure of the causal effects of interventions on health care outcomes. CONCLUSIONS ITSA represents a significant improvement over traditional observational study designs in quantifying the impact of an intervention. ITSA is a useful statistical procedure to understand, consider, and implement as the field of neurosurgery evolves in sophistication in big-data analytics, economics, and health services research.
Modeling activity patterns of wildlife using time-series analysis.
Zhang, Jindong; Hull, Vanessa; Ouyang, Zhiyun; He, Liang; Connor, Thomas; Yang, Hongbo; Huang, Jinyan; Zhou, Shiqiang; Zhang, Zejun; Zhou, Caiquan; Zhang, Hemin; Liu, Jianguo
2017-04-01
The study of wildlife activity patterns is an effective approach to understanding fundamental ecological and evolutionary processes. However, traditional statistical approaches used to conduct quantitative analysis have thus far had limited success in revealing underlying mechanisms driving activity patterns. Here, we combine wavelet analysis, a type of frequency-based time-series analysis, with high-resolution activity data from accelerometers embedded in GPS collars to explore the effects of internal states (e.g., pregnancy) and external factors (e.g., seasonal dynamics of resources and weather) on activity patterns of the endangered giant panda ( Ailuropoda melanoleuca ). Giant pandas exhibited higher frequency cycles during the winter when resources (e.g., water and forage) were relatively poor, as well as during spring, which includes the giant panda's mating season. During the summer and autumn when resources were abundant, pandas exhibited a regular activity pattern with activity peaks every 24 hr. A pregnant individual showed distinct differences in her activity pattern from other giant pandas for several months following parturition. These results indicate that animals adjust activity cycles to adapt to seasonal variation of the resources and unique physiological periods. Wavelet coherency analysis also verified the synchronization of giant panda activity level with air temperature and solar radiation at the 24-hr band. Our study also shows that wavelet analysis is an effective tool for analyzing high-resolution activity pattern data and its relationship to internal and external states, an approach that has the potential to inform wildlife conservation and management across species.
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.
Waddell, J Neil; Payne, Alan G T; Swain, Michael V; Kieser, Jules A
2010-03-01
Soldered or cast bars are used as a standard of care in attachment systems supporting maxillary and mandibular implant overdentures. When failures of these bars occur, currently there is a lack of evidence in relation to their specific etiology, location, or nature. To investigate the failure process of a case series of six failed soldered bars, four intact soldered bars, and one intact cast milled bar, which had been supporting implant overdentures. A total of 11 different overdenture bars were removed from patients with different configuration of opposing arches. A failed bar (FB) group (n = 6) had failed soldered overdenture bars, which were recovered from patients following up to 2 years of wear before requiring prosthodontic maintenance and repair. An intact bar (IB) group (n = 5) had both soldered bars and a single cast milled bar, which had been worn by patients for 2 to 5 years prior to receiving other aspects of prosthodontic maintenance. All bars were examined using scanning electron microscopy to establish the possible mode of failure (FB) or to identify evidence of potential failure in the future (IB). Evidence of a progressive failure mode of corrosion fatigue and creep were observed on all the FB and IB usually around the solder areas and nonoxidizing gold cylinder. Fatigue and creep were also observed in all the IB. Where the level of corrosion was substantial, there was no evidence of wear from the matrices of the attachment system. Evidence of an instantaneous failure mode, ductile and brittle overload, was observed on the fracture surfaces of all the FB, within the solder and the nonoxidizing gold cylinders, at the solder/cylinder interface. Corrosion, followed by corrosion fatigue, appears to be a key factor in the onset of the failure process for overdenture bars in this case series of both maxillary and mandibular overdentures. Limited sample size and lack of standardization identify trends only but prevent broad interpretation of the findings.
Analysis of radiation-induced microchemical evolution in 300 series stainless steel
International Nuclear Information System (INIS)
Brager, H.R.; Garner, F.A.
1980-03-01
The irradiation of 300 series stainless steel by fast neutrons leads to an evolution of alloy microstructures that involves not only the formation of voids and dislocations, but also an extensive repartitioning of elements between various phases. This latter evolution has been shown to be the primary determinant of the alloy behavior in response to the large number of variables which influence void swelling and irradiation creep. The combined use of scanning transmission electron microscopy and energy-dispersive x-ray analysis has been the key element in the study of this phenomenon. Problems associated with the analysis of radioactive specimens are resolved by minor equipment modifications. Problems associated with spatial resolution limitations and the complexity and heterogeneity of the microchemical evolution have been overcome by using several data acquisition techniques. These include the measurement of compositional profiles near sinks, the use of foil-edge analysis, and the statistical sampling of many matrix and precipitate volumes
Time Series Analysis of the Quasar PKS 1749+096
Lam, Michael T.; Balonek, T. J.
2011-01-01
Multiple timescales of variability are observed in quasars at a variety of wavelengths, the nature of which is not fully understood. In 2007 and 2008, the quasar 1749+096 underwent two unprecedented optical outbursts, reaching a brightness never before seen in our twenty years of monitoring. Much lower level activity had been seen prior to these two outbursts. We present an analysis of the timescales of variability over the two regimes using a variety of statistical techniques. An IDL software package developed at Colgate University over the summer of 2010, the Quasar User Interface (QUI), provides effective computation of four time series functions for analyzing underlying trends present in generic, discretely sampled data sets. Using the Autocorrelation Function, Structure Function, and Power Spectrum, we are able to quickly identify possible variability timescales. QUI is also capable of computing the Cross-Correlation Function for comparing variability at different wavelengths. We apply these algorithms to 1749+096 and present our analysis of the timescales for this object. Funding for this project was received from Colgate University, the Justus and Jayne Schlichting Student Research Fund, and the NASA / New York Space Grant.
Analysis of time series and size of equivalent sample
International Nuclear Information System (INIS)
Bernal, Nestor; Molina, Alicia; Pabon, Daniel; Martinez, Jorge
2004-01-01
In a meteorological context, a first approach to the modeling of time series is to use models of autoregressive type. This allows one to take into account the meteorological persistence or temporal behavior, thereby identifying the memory of the analyzed process. This article seeks to pre-sent the concept of the size of an equivalent sample, which helps to identify in the data series sub periods with a similar structure. Moreover, in this article we examine the alternative of adjusting the variance of the series, keeping in mind its temporal structure, as well as an adjustment to the covariance of two time series. This article presents two examples, the first one corresponding to seven simulated series with autoregressive structure of first order, and the second corresponding to seven meteorological series of anomalies of the air temperature at the surface in two Colombian regions
Analysis of electron interactions in dielectric gases
International Nuclear Information System (INIS)
Olivet, Aurelio; Duque, Daniel; Vega, Lourdes F.
2007-01-01
We present and discuss results concerning electron interactions processes of dielectric gases and their relationship with the macroscopic behavior of these gases, in particular, with their dielectric strength. Such analysis is based on calculating energies of reactions for molecular ionization, dissociative ionization, parent negative ion formation, and dissociative electron attachment processes. We hypothesize that the estimation of the required energy for a reduced number of processes that take place in electrically stressed gases could be related to the gas' capability to manage the electron flow during an electrical discharge. All calculations were done with semiempirical quantum chemistry methods, including an initial optimization of molecular geometry and heat of formation of the dielectric gases and all of species that appear during electron interaction reactions. The performance of semiempirical methods Austin model 1 and Parametric model 3 (PM3) was compared for several compounds, PM3 being superior in most cases. Calculations performed for a sample of nine dielectric gases show that electron attachment and detachment processes occur in different energy bands that do not overlap for any value of the dielectric strength. We have also analyzed the relationship between dielectric strength and two physical properties: electron affinity and ionization energy. Calculations performed for 43 dielectric gases show no clear correlation between them, although certain guidelines for the qualitative estimation of dielectric strength can still be assessed
Electronic Health Record Implementation: A SWOT Analysis
Directory of Open Access Journals (Sweden)
Leila Shahmoradi
2017-12-01
Full Text Available Electronic Health Record (EHR is one of the most important achievements of information technology in healthcare domain, and if deployed effectively, it can yield predominant results. The aim of this study was a SWOT (strengths, weaknesses, opportunities, and threats analysis in electronic health record implementation. This is a descriptive, analytical study conducted with the participation of a 90-member work force from Hospitals affiliated to Tehran University of Medical Sciences (TUMS. The data were collected by using a self-structured questionnaire and analyzed by SPSS software. Based on the results, the highest priority in strength analysis was related to timely and quick access to information. However, lack of hardware and infrastructures was the most important weakness. Having the potential to share information between different sectors and access to a variety of health statistics was the significant opportunity of EHR. Finally, the most substantial threats were the lack of strategic planning in the field of electronic health records together with physicians’ and other clinical staff’s resistance in the use of electronic health records. To facilitate successful adoption of electronic health record, some organizational, technical and resource elements contribute; moreover, the consideration of these factors is essential for HER implementation.
Electronic Health Record Implementation: A SWOT Analysis.
Shahmoradi, Leila; Darrudi, Alireza; Arji, Goli; Farzaneh Nejad, Ahmadreza
2017-10-01
Electronic Health Record (EHR) is one of the most important achievements of information technology in healthcare domain, and if deployed effectively, it can yield predominant results. The aim of this study was a SWOT (strengths, weaknesses, opportunities, and threats) analysis in electronic health record implementation. This is a descriptive, analytical study conducted with the participation of a 90-member work force from Hospitals affiliated to Tehran University of Medical Sciences (TUMS). The data were collected by using a self-structured questionnaire and analyzed by SPSS software. Based on the results, the highest priority in strength analysis was related to timely and quick access to information. However, lack of hardware and infrastructures was the most important weakness. Having the potential to share information between different sectors and access to a variety of health statistics was the significant opportunity of EHR. Finally, the most substantial threats were the lack of strategic planning in the field of electronic health records together with physicians' and other clinical staff's resistance in the use of electronic health records. To facilitate successful adoption of electronic health record, some organizational, technical and resource elements contribute; moreover, the consideration of these factors is essential for HER implementation.
Interglacial climate dynamics and advanced time series analysis
Mudelsee, Manfred; Bermejo, Miguel; Köhler, Peter; Lohmann, Gerrit
2013-04-01
Studying the climate dynamics of past interglacials (IGs) helps to better assess the anthropogenically influenced dynamics of the current IG, the Holocene. We select the IG portions from the EPICA Dome C ice core archive, which covers the past 800 ka, to apply methods of statistical time series analysis (Mudelsee 2010). The analysed variables are deuterium/H (indicating temperature) (Jouzel et al. 2007), greenhouse gases (Siegenthaler et al. 2005, Loulergue et al. 2008, L¨ü thi et al. 2008) and a model-co-derived climate radiative forcing (Köhler et al. 2010). We select additionally high-resolution sea-surface-temperature records from the marine sedimentary archive. The first statistical method, persistence time estimation (Mudelsee 2002) lets us infer the 'climate memory' property of IGs. Second, linear regression informs about long-term climate trends during IGs. Third, ramp function regression (Mudelsee 2000) is adapted to look on abrupt climate changes during IGs. We compare the Holocene with previous IGs in terms of these mathematical approaches, interprete results in a climate context, assess uncertainties and the requirements to data from old IGs for yielding results of 'acceptable' accuracy. This work receives financial support from the Deutsche Forschungsgemeinschaft (Project ClimSens within the DFG Research Priority Program INTERDYNAMIK) and the European Commission (Marie Curie Initial Training Network LINC, No. 289447, within the 7th Framework Programme). References Jouzel J, Masson-Delmotte V, Cattani O, Dreyfus G, Falourd S, Hoffmann G, Minster B, Nouet J, Barnola JM, Chappellaz J, Fischer H, Gallet JC, Johnsen S, Leuenberger M, Loulergue L, Luethi D, Oerter H, Parrenin F, Raisbeck G, Raynaud D, Schilt A, Schwander J, Selmo E, Souchez R, Spahni R, Stauffer B, Steffensen JP, Stenni B, Stocker TF, Tison JL, Werner M, Wolff EW (2007) Orbital and millennial Antarctic climate variability over the past 800,000 years. Science 317:793. Köhler P, Bintanja R
The Prediction of Teacher Turnover Employing Time Series Analysis.
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…
Directory of Open Access Journals (Sweden)
Marvin A. H. Berrevoets
2017-08-01
Full Text Available Abstract Background Timely switch from intravenous (iv antibiotics to oral therapy is a key component of antimicrobial stewardship programs in order to improve patient safety, promote early discharge and reduce costs. We have introduced a time-efficient and easily implementable intervention that relies on a computerized trigger tool, which identifies patients who are candidates for an iv to oral antibiotic switch. Methods The intervention was introduced on all internal medicine wards in a teaching hospital. Patients were automatically identified by an electronic trigger tool when parenteral antibiotics were used for >48 h and clinical or pharmacological data did not preclude switch therapy. A weekly educational session was introduced to alert the physicians on the intervention wards. The intervention wards were compared with control wards, which included all other hospital wards. An interrupted time-series analysis was performed to compare the pre-intervention period with the post-intervention period using ‘% of i.v. prescriptions >72 h’ and ‘median duration of iv therapy per prescription’ as outcomes. We performed a detailed prospective evaluation on a subset of 244 prescriptions to evaluate the efficacy and appropriateness of the intervention. Results The number of intravenous prescriptions longer than 72 h was reduced by 19% in the intervention group (n = 1519 (p < 0.01 and the median duration of iv antibiotics was reduced with 0.8 days (p = <0.05. Compared to the control group (n = 4366 the intervention was responsible for an additional decrease of 13% (p < 0.05 in prolonged prescriptions. The detailed prospective evaluation of a subgroup of patients showed that adherence to the electronic reminder was 72%. Conclusions An electronic trigger tool combined with a weekly educational session was effective in reducing the duration of intravenous antimicrobial therapy.
ON THE FOURIER AND WAVELET ANALYSIS OF CORONAL TIME SERIES
International Nuclear Information System (INIS)
Auchère, F.; Froment, C.; Bocchialini, K.; Buchlin, E.; Solomon, J.
2016-01-01
Using Fourier and wavelet analysis, we critically re-assess the significance of our detection of periodic pulsations in coronal loops. We show that the proper identification of the frequency dependence and statistical properties of the different components of the power spectra provides a strong argument against the common practice of data detrending, which tends to produce spurious detections around the cut-off frequency of the filter. In addition, the white and red noise models built into the widely used wavelet code of Torrence and Compo cannot, in most cases, adequately represent the power spectra of coronal time series, thus also possibly causing false positives. Both effects suggest that several reports of periodic phenomena should be re-examined. The Torrence and Compo code nonetheless effectively computes rigorous confidence levels if provided with pertinent models of mean power spectra, and we describe the appropriate manner in which to call its core routines. We recall the meaning of the default confidence levels output from the code, and we propose new Monte-Carlo-derived levels that take into account the total number of degrees of freedom in the wavelet spectra. These improvements allow us to confirm that the power peaks that we detected have a very low probability of being caused by noise.
ON THE FOURIER AND WAVELET ANALYSIS OF CORONAL TIME SERIES
Energy Technology Data Exchange (ETDEWEB)
Auchère, F.; Froment, C.; Bocchialini, K.; Buchlin, E.; Solomon, J., E-mail: frederic.auchere@ias.u-psud.fr [Institut d’Astrophysique Spatiale, CNRS, Univ. Paris-Sud, Université Paris-Saclay, Bât. 121, F-91405 Orsay (France)
2016-07-10
Using Fourier and wavelet analysis, we critically re-assess the significance of our detection of periodic pulsations in coronal loops. We show that the proper identification of the frequency dependence and statistical properties of the different components of the power spectra provides a strong argument against the common practice of data detrending, which tends to produce spurious detections around the cut-off frequency of the filter. In addition, the white and red noise models built into the widely used wavelet code of Torrence and Compo cannot, in most cases, adequately represent the power spectra of coronal time series, thus also possibly causing false positives. Both effects suggest that several reports of periodic phenomena should be re-examined. The Torrence and Compo code nonetheless effectively computes rigorous confidence levels if provided with pertinent models of mean power spectra, and we describe the appropriate manner in which to call its core routines. We recall the meaning of the default confidence levels output from the code, and we propose new Monte-Carlo-derived levels that take into account the total number of degrees of freedom in the wavelet spectra. These improvements allow us to confirm that the power peaks that we detected have a very low probability of being caused by noise.
Prediction of solar cycle 24 using fourier series analysis
International Nuclear Information System (INIS)
Khalid, M.; Sultana, M.; Zaidi, F.
2014-01-01
Predicting the behavior of solar activity has become very significant. It is due to its influence on Earth and the surrounding environment. Apt predictions of the amplitude and timing of the next solar cycle will aid in the estimation of the several results of Space Weather. In the past, many prediction procedures have been used and have been successful to various degrees in the field of solar activity forecast. In this study, Solar cycle 24 is forecasted by the Fourier series method. Comparative analysis has been made by auto regressive integrated moving averages method. From sources, January 2008 was the minimum preceding solar cycle 24, the amplitude and shape of solar cycle 24 is approximate on monthly number of sunspots. This forecast framework approximates a mean solar cycle 24, with the maximum appearing during May 2014 (+- 8 months), with most sunspot of 98 +- 10. Solar cycle 24 will be ending in June 2020 (+- 7 months). The difference between two consecutive peak values of solar cycles (i.e. solar cycle 23 and 24 ) is 165 months(+- 6 months). (author)
Time-series-analysis techniques applied to nuclear-material accounting
International Nuclear Information System (INIS)
Pike, D.H.; Morrison, G.W.; Downing, D.J.
1982-05-01
This document is designed to introduce the reader to the applications of Time Series Analysis techniques to Nuclear Material Accountability data. Time series analysis techniques are designed to extract information from a collection of random variables ordered by time by seeking to identify any trends, patterns, or other structure in the series. Since nuclear material accountability data is a time series, one can extract more information using time series analysis techniques than by using other statistical techniques. Specifically, the objective of this document is to examine the applicability of time series analysis techniques to enhance loss detection of special nuclear materials. An introductory section examines the current industry approach which utilizes inventory differences. The error structure of inventory differences is presented. Time series analysis techniques discussed include the Shewhart Control Chart, the Cumulative Summation of Inventory Differences Statistics (CUSUM) and the Kalman Filter and Linear Smoother
On-line analysis of reactor noise using time-series analysis
International Nuclear Information System (INIS)
McGevna, V.G.
1981-10-01
A method to allow use of time series analysis for on-line noise analysis has been developed. On-line analysis of noise in nuclear power reactors has been limited primarily to spectral analysis and related frequency domain techniques. Time series analysis has many distinct advantages over spectral analysis in the automated processing of reactor noise. However, fitting an autoregressive-moving average (ARMA) model to time series data involves non-linear least squares estimation. Unless a high speed, general purpose computer is available, the calculations become too time consuming for on-line applications. To eliminate this problem, a special purpose algorithm was developed for fitting ARMA models. While it is based on a combination of steepest descent and Taylor series linearization, properties of the ARMA model are used so that the auto- and cross-correlation functions can be used to eliminate the need for estimating derivatives. The number of calculations, per iteration varies lineegardless of the mee 0.2% yield strength displayed anisotropy, with axial and circumferential values being greater than radial. For CF8-CPF8 and CF8M-CPF8M castings to meet current ASME Code S acid fuel cells
Analysis of complex time series using refined composite multiscale entropy
International Nuclear Information System (INIS)
Wu, Shuen-De; Wu, Chiu-Wen; Lin, Shiou-Gwo; Lee, Kung-Yen; Peng, Chung-Kang
2014-01-01
Multiscale entropy (MSE) is an effective algorithm for measuring the complexity of a time series that has been applied in many fields successfully. However, MSE may yield an inaccurate estimation of entropy or induce undefined entropy because the coarse-graining procedure reduces the length of a time series considerably at large scales. Composite multiscale entropy (CMSE) was recently proposed to improve the accuracy of MSE, but it does not resolve undefined entropy. Here we propose a refined composite multiscale entropy (RCMSE) to improve CMSE. For short time series analyses, we demonstrate that RCMSE increases the accuracy of entropy estimation and reduces the probability of inducing undefined entropy.
Unsupervised land cover change detection: meaningful sequential time series analysis
CSIR Research Space (South Africa)
Salmon, BP
2011-06-01
Full Text Available An automated land cover change detection method is proposed that uses coarse spatial resolution hyper-temporal earth observation satellite time series data. The study compared three different unsupervised clustering approaches that operate on short...
International Nuclear Information System (INIS)
Tang You-Fu; Liu Shu-Lin; Jiang Rui-Hong; Liu Ying-Hui
2013-01-01
We study the correlation between detrended fluctuation analysis (DFA) and the Lempel-Ziv complexity (LZC) in nonlinear time series analysis in this paper. Typical dynamic systems including a logistic map and a Duffing model are investigated. Moreover, the influence of Gaussian random noise on both the DFA and LZC are analyzed. The results show a high correlation between the DFA and LZC, which can quantify the non-stationarity and the nonlinearity of the time series, respectively. With the enhancement of the random component, the exponent a and the normalized complexity index C show increasing trends. In addition, C is found to be more sensitive to the fluctuation in the nonlinear time series than α. Finally, the correlation between the DFA and LZC is applied to the extraction of vibration signals for a reciprocating compressor gas valve, and an effective fault diagnosis result is obtained
Advances in Antithetic Time Series Analysis : Separating Fact from Artifact
Directory of Open Access Journals (Sweden)
Dennis Ridley
2016-01-01
Full Text Available The problem of biased time series mathematical model parameter estimates is well known to be insurmountable. When used to predict future values by extrapolation, even a de minimis bias will eventually grow into a large bias, with misleading results. This paper elucidates how combining antithetic time series' solves this baffling problem of bias in the fitted and forecast values by dynamic bias cancellation. Instead of growing to infinity, the average error can converge to a constant. (original abstract
Data imputation analysis for Cosmic Rays time series
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.
Geomechanical time series and its singularity spectrum analysis
Czech Academy of Sciences Publication Activity Database
Lyubushin, Alexei A.; Kaláb, Zdeněk; Lednická, Markéta
2012-01-01
Roč. 47, č. 1 (2012), s. 69-77 ISSN 1217-8977 R&D Projects: GA ČR GA105/09/0089 Institutional research plan: CEZ:AV0Z30860518 Keywords : geomechanical time series * singularity spectrum * time series segmentation * laser distance meter Subject RIV: DC - Siesmology, Volcanology, Earth Structure Impact factor: 0.347, year: 2012 http://www.akademiai.com/content/88v4027758382225/fulltext.pdf
Analysis of electronic circuits using digital computers
International Nuclear Information System (INIS)
Tapu, C.
1968-01-01
Various programmes have been proposed for studying electronic circuits with the help of computers. It is shown here how it possible to use the programme ECAP, developed by I.B.M., for studying the behaviour of an operational amplifier from different point of view: direct current, alternating current and transient state analysis, optimisation of the gain in open loop, study of the reliability. (author) [fr
Time Series Analysis of Wheat flour Price Shocks in Pakistan: A Case Analysis
Asad Raza Abdi; Ali Hassan Halepoto; Aisha Bashir Shah; Faiz M. Shaikh
2013-01-01
The current research investigates the wheat flour Price Shocks in Pakistan: A case analysis. Data was collected by using secondary sources by using Time series Analysis, and data were analyzed by using SPSS-20 version. It was revealed that the price of wheat flour increases from last four decades, and trend of price shocks shows that due to certain market variation and supply and demand shocks also play a positive relationship in price shocks in the wheat prices. It was further revealed th...
Track Irregularity Time Series Analysis and Trend Forecasting
Directory of Open Access Journals (Sweden)
Jia Chaolong
2012-01-01
Full Text Available The combination of linear and nonlinear methods is widely used in the prediction of time series data. This paper analyzes track irregularity time series data by using gray incidence degree models and methods of data transformation, trying to find the connotative relationship between the time series data. In this paper, GM (1,1 is based on first-order, single variable linear differential equations; after an adaptive improvement and error correction, it is used to predict the long-term changing trend of track irregularity at a fixed measuring point; the stochastic linear AR, Kalman filtering model, and artificial neural network model are applied to predict the short-term changing trend of track irregularity at unit section. Both long-term and short-term changes prove that the model is effective and can achieve the expected accuracy.
Energy Technology Data Exchange (ETDEWEB)
Moauro, F. [ENEA, Centro Ricerche Casaccia, Rome (Italy). Dip. Energia
1995-03-01
This paper reports a short term analysis of the Italian demand for energy fonts and a check of a statistic model supposing the industrial demand for energy fonts as a function of prices and production, according to neoclassic neoclassic micro economic theory. To this pourpose monthly time series of industrial consumption of main energy fonts in 6 sectors, industrial production indexes in the same sectors and indexes of energy prices (coal, natural gas, oil products, electricity) have been used. The statistic methodology refers to modern analysis of time series and specifically to transfer function models. These ones permit rigorous identification and representation of the most important dynamic relations between dependent variables (production and prices), as relation of an input-output system. The results have shown an important positive correlation between energy consumption with prices. Furthermore, it has been shown the reliability of forecasts and their use as monthly energy indicators.
Unstable Periodic Orbit Analysis of Histograms of Chaotic Time Series
International Nuclear Information System (INIS)
Zoldi, S.M.
1998-01-01
Using the Lorenz equations, we have investigated whether unstable periodic orbits (UPOs) associated with a strange attractor may predict the occurrence of the robust sharp peaks in histograms of some experimental chaotic time series. Histograms with sharp peaks occur for the Lorenz parameter value r=60.0 but not for r=28.0 , and the sharp peaks for r=60.0 do not correspond to a histogram derived from any single UPO. However, we show that histograms derived from the time series of a non-Axiom-A chaotic system can be accurately predicted by an escape-time weighting of UPO histograms. copyright 1998 The American Physical Society
Minimum entropy density method for the time series analysis
Lee, Jeong Won; Park, Joongwoo Brian; Jo, Hang-Hyun; Yang, Jae-Suk; Moon, Hie-Tae
2009-01-01
The entropy density is an intuitive and powerful concept to study the complicated nonlinear processes derived from physical systems. We develop the minimum entropy density method (MEDM) to detect the structure scale of a given time series, which is defined as the scale in which the uncertainty is minimized, hence the pattern is revealed most. The MEDM is applied to the financial time series of Standard and Poor’s 500 index from February 1983 to April 2006. Then the temporal behavior of structure scale is obtained and analyzed in relation to the information delivery time and efficient market hypothesis.
Dynamic Factor Analysis of Nonstationary Multivariate Time Series.
Molenaar, Peter C. M.; And Others
1992-01-01
The dynamic factor model proposed by P. C. Molenaar (1985) is exhibited, and a dynamic nonstationary factor model (DNFM) is constructed with latent factor series that have time-varying mean functions. The use of a DNFM is illustrated using data from a television viewing habits study. (SLD)
Koopman Operator Framework for Time Series Modeling and Analysis
Surana, Amit
2018-01-01
We propose an interdisciplinary framework for time series classification, forecasting, and anomaly detection by combining concepts from Koopman operator theory, machine learning, and linear systems and control theory. At the core of this framework is nonlinear dynamic generative modeling of time series using the Koopman operator which is an infinite-dimensional but linear operator. Rather than working with the underlying nonlinear model, we propose two simpler linear representations or model forms based on Koopman spectral properties. We show that these model forms are invariants of the generative model and can be readily identified directly from data using techniques for computing Koopman spectral properties without requiring the explicit knowledge of the generative model. We also introduce different notions of distances on the space of such model forms which is essential for model comparison/clustering. We employ the space of Koopman model forms equipped with distance in conjunction with classical machine learning techniques to develop a framework for automatic feature generation for time series classification. The forecasting/anomaly detection framework is based on using Koopman model forms along with classical linear systems and control approaches. We demonstrate the proposed framework for human activity classification, and for time series forecasting/anomaly detection in power grid application.
Complexity analysis of the turbulent environmental fluid flow time series
Mihailović, D. T.; Nikolić-Đorić, E.; Drešković, N.; Mimić, G.
2014-02-01
We have used the Kolmogorov complexities, sample and permutation entropies to quantify the randomness degree in river flow time series of two mountain rivers in Bosnia and Herzegovina, representing the turbulent environmental fluid, for the period 1926-1990. In particular, we have examined the monthly river flow time series from two rivers (the Miljacka and the Bosnia) in the mountain part of their flow and then calculated the Kolmogorov complexity (KL) based on the Lempel-Ziv Algorithm (LZA) (lower-KLL and upper-KLU), sample entropy (SE) and permutation entropy (PE) values for each time series. The results indicate that the KLL, KLU, SE and PE values in two rivers are close to each other regardless of the amplitude differences in their monthly flow rates. We have illustrated the changes in mountain river flow complexity by experiments using (i) the data set for the Bosnia River and (ii) anticipated human activities and projected climate changes. We have explored the sensitivity of considered measures in dependence on the length of time series. In addition, we have divided the period 1926-1990 into three subintervals: (a) 1926-1945, (b) 1946-1965, (c) 1966-1990, and calculated the KLL, KLU, SE, PE values for the various time series in these subintervals. It is found that during the period 1946-1965, there is a decrease in their complexities, and corresponding changes in the SE and PE, in comparison to the period 1926-1990. This complexity loss may be primarily attributed to (i) human interventions, after the Second World War, on these two rivers because of their use for water consumption and (ii) climate change in recent times.
Multiscale multifractal multiproperty analysis of financial time series based on Rényi entropy
Yujun, Yang; Jianping, Li; Yimei, Yang
This paper introduces a multiscale multifractal multiproperty analysis based on Rényi entropy (3MPAR) method to analyze short-range and long-range characteristics of financial time series, and then applies this method to the five time series of five properties in four stock indices. Combining the two analysis techniques of Rényi entropy and multifractal detrended fluctuation analysis (MFDFA), the 3MPAR method focuses on the curves of Rényi entropy and generalized Hurst exponent of five properties of four stock time series, which allows us to study more universal and subtle fluctuation characteristics of financial time series. By analyzing the curves of the Rényi entropy and the profiles of the logarithm distribution of MFDFA of five properties of four stock indices, the 3MPAR method shows some fluctuation characteristics of the financial time series and the stock markets. Then, it also shows a richer information of the financial time series by comparing the profile of five properties of four stock indices. In this paper, we not only focus on the multifractality of time series but also the fluctuation characteristics of the financial time series and subtle differences in the time series of different properties. We find that financial time series is far more complex than reported in some research works using one property of time series.
Comprehensive analysis of electron correlations in three-electron atoms
International Nuclear Information System (INIS)
Morishita, T.; Lin, C.D.
1999-01-01
We study the electron correlations in singly, doubly, and triply excited states of a three-electron atom. While electron correlation in general is weak for singly excited states, correlation plays major roles in determining the characteristics of doubly and triply excited states. Using the adiabatic approximation in hyperspherical coordinates, we show that the distinction between singly, doubly, and triply excited states is determined by the radial correlations, while finer distinctions within doubly or triply excited states lie in the angular correlations. Partial projections of the body-fixed frame wave functions are used to demonstrate the characteristic nodal surfaces which provide clues to the energy ordering of the states. We show that doubly excited states of a three-electron atom exhibit correlations that are similar to the doubly excited states of a two-electron atom. For the triply excited states, we show that the motion of the three electrons resemble approximately that of a symmetric top. copyright 1999 The American Physical Society
Asymptotically exact expression for the energies of the 3Se Rydberg series in a two-electron system
International Nuclear Information System (INIS)
Ivanov, I.A.; Bromley, M.W.J.; Mitroy, J.
2002-01-01
The 1sns 3 S e Rydberg series in a two-electron system with the charge of the nucleus, Z≅1, is treated by means of the quantum-defect theory. Comparison with configuration interaction calculations suggests that the quantum-defect expression for the energy levels becomes asymptotically exact as Z→1. This provides an analytic description of the disappearance of the 1sns 3 S e bound states when Z approaches the critical value of 1
Modeling Philippine Stock Exchange Composite Index Using Time Series Analysis
Gayo, W. S.; Urrutia, J. D.; Temple, J. M. F.; Sandoval, J. R. D.; Sanglay, J. E. A.
2015-06-01
This study was conducted to develop a time series model of the Philippine Stock Exchange Composite Index and its volatility using the finite mixture of ARIMA model with conditional variance equations such as ARCH, GARCH, EG ARCH, TARCH and PARCH models. Also, the study aimed to find out the reason behind the behaviorof PSEi, that is, which of the economic variables - Consumer Price Index, crude oil price, foreign exchange rate, gold price, interest rate, money supply, price-earnings ratio, Producers’ Price Index and terms of trade - can be used in projecting future values of PSEi and this was examined using Granger Causality Test. The findings showed that the best time series model for Philippine Stock Exchange Composite index is ARIMA(1,1,5) - ARCH(1). Also, Consumer Price Index, crude oil price and foreign exchange rate are factors concluded to Granger cause Philippine Stock Exchange Composite Index.
Time series analysis of the behavior of brazilian natural rubber
Directory of Open Access Journals (Sweden)
Antônio Donizette de Oliveira
2009-03-01
Full Text Available The natural rubber is a non-wood product obtained of the coagulation of some lattices of forest species, being Hevea brasiliensis the main one. Native from the Amazon Region, this species was already known by the Indians before the discovery of America. The natural rubber became a product globally valued due to its multiple applications in the economy, being its almost perfect substitute the synthetic rubber derived from the petroleum. Similarly to what happens with other countless products the forecast of future prices of the natural rubber has been object of many studies. The use of models of forecast of univariate timeseries stands out as the more accurate and useful to reduce the uncertainty in the economic decision making process. This studyanalyzed the historical series of prices of the Brazilian natural rubber (R$/kg, in the Jan/99 - Jun/2006 period, in order tocharacterize the rubber price behavior in the domestic market; estimated a model for the time series of monthly natural rubberprices; and foresaw the domestic prices of the natural rubber, in the Jul/2006 - Jun/2007 period, based on the estimated models.The studied models were the ones belonging to the ARIMA family. The main results were: the domestic market of the natural rubberis expanding due to the growth of the world economy; among the adjusted models, the ARIMA (1,1,1 model provided the bestadjustment of the time series of prices of the natural rubber (R$/kg; the prognosis accomplished for the series supplied statistically adequate fittings.
Dynamical analysis and visualization of tornadoes time series.
Directory of Open Access Journals (Sweden)
António M Lopes
Full Text Available In this paper we analyze the behavior of tornado time-series in the U.S. from the perspective of dynamical systems. A tornado is a violently rotating column of air extending from a cumulonimbus cloud down to the ground. Such phenomena reveal features that are well described by power law functions and unveil characteristics found in systems with long range memory effects. Tornado time series are viewed as the output of a complex system and are interpreted as a manifestation of its dynamics. Tornadoes are modeled as sequences of Dirac impulses with amplitude proportional to the events size. First, a collection of time series involving 64 years is analyzed in the frequency domain by means of the Fourier transform. The amplitude spectra are approximated by power law functions and their parameters are read as an underlying signature of the system dynamics. Second, it is adopted the concept of circular time and the collective behavior of tornadoes analyzed. Clustering techniques are then adopted to identify and visualize the emerging patterns.
Dynamical analysis and visualization of tornadoes time series.
Lopes, António M; Tenreiro Machado, J A
2015-01-01
In this paper we analyze the behavior of tornado time-series in the U.S. from the perspective of dynamical systems. A tornado is a violently rotating column of air extending from a cumulonimbus cloud down to the ground. Such phenomena reveal features that are well described by power law functions and unveil characteristics found in systems with long range memory effects. Tornado time series are viewed as the output of a complex system and are interpreted as a manifestation of its dynamics. Tornadoes are modeled as sequences of Dirac impulses with amplitude proportional to the events size. First, a collection of time series involving 64 years is analyzed in the frequency domain by means of the Fourier transform. The amplitude spectra are approximated by power law functions and their parameters are read as an underlying signature of the system dynamics. Second, it is adopted the concept of circular time and the collective behavior of tornadoes analyzed. Clustering techniques are then adopted to identify and visualize the emerging patterns.
Financial time series analysis based on information categorization method
Tian, Qiang; Shang, Pengjian; Feng, Guochen
2014-12-01
The paper mainly applies the information categorization method to analyze the financial time series. The method is used to examine the similarity of different sequences by calculating the distances between them. We apply this method to quantify the similarity of different stock markets. And we report the results of similarity in US and Chinese stock markets in periods 1991-1998 (before the Asian currency crisis), 1999-2006 (after the Asian currency crisis and before the global financial crisis), and 2007-2013 (during and after global financial crisis) by using this method. The results show the difference of similarity between different stock markets in different time periods and the similarity of the two stock markets become larger after these two crises. Also we acquire the results of similarity of 10 stock indices in three areas; it means the method can distinguish different areas' markets from the phylogenetic trees. The results show that we can get satisfactory information from financial markets by this method. The information categorization method can not only be used in physiologic time series, but also in financial time series.
Anonymization of Electronic Medical Records to Support Clinical Analysis
Gkoulalas-Divanis, Aris
2013-01-01
Anonymization of Electronic Medical Records to Support Clinical Analysis closely examines the privacy threats that may arise from medical data sharing, and surveys the state-of-the-art methods developed to safeguard data against these threats. To motivate the need for computational methods, the book first explores the main challenges facing the privacy-protection of medical data using the existing policies, practices and regulations. Then, it takes an in-depth look at the popular computational privacy-preserving methods that have been developed for demographic, clinical and genomic data sharing, and closely analyzes the privacy principles behind these methods, as well as the optimization and algorithmic strategies that they employ. Finally, through a series of in-depth case studies that highlight data from the US Census as well as the Vanderbilt University Medical Center, the book outlines a new, innovative class of privacy-preserving methods designed to ensure the integrity of transferred medical data for su...
Time-Series Analysis of Supergranule Characterstics at Solar Minimum
Williams, Peter E.; Pesnell, W. Dean
2013-01-01
Sixty days of Doppler images from the Solar and Heliospheric Observatory (SOHO) / Michelson Doppler Imager (MDI) investigation during the 1996 and 2008 solar minima have been analyzed to show that certain supergranule characteristics (size, size range, and horizontal velocity) exhibit fluctuations of three to five days. Cross-correlating parameters showed a good, positive correlation between supergranulation size and size range, and a moderate, negative correlation between size range and velocity. The size and velocity do exhibit a moderate, negative correlation, but with a small time lag (less than 12 hours). Supergranule sizes during five days of co-temporal data from MDI and the Solar Dynamics Observatory (SDO) / Helioseismic Magnetic Imager (HMI) exhibit similar fluctuations with a high level of correlation between them. This verifies the solar origin of the fluctuations, which cannot be caused by instrumental artifacts according to these observations. Similar fluctuations are also observed in data simulations that model the evolution of the MDI Doppler pattern over a 60-day period. Correlations between the supergranule size and size range time-series derived from the simulated data are similar to those seen in MDI data. A simple toy-model using cumulative, uncorrelated exponential growth and decay patterns at random emergence times produces a time-series similar to the data simulations. The qualitative similarities between the simulated and the observed time-series suggest that the fluctuations arise from stochastic processes occurring within the solar convection zone. This behavior, propagating to surface manifestations of supergranulation, may assist our understanding of magnetic-field-line advection, evolution, and interaction.
Visibility graph analysis on quarterly macroeconomic series of China based on complex network theory
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
Anatomy of the ICDS series: A bibliometric analysis
International Nuclear Information System (INIS)
Cardona, Manuel; Marx, Werner
2007-01-01
In this article, the proceedings of the International Conferences on Defects in Semiconductors (ICDS) have been analyzed by bibliometric methods. The papers of these conferences have been published as articles in regular journals or special proceedings journals and in books with diverse publishers. The conference name/title changed several times. Many of the proceedings did not appear in the so-called 'source journals' covered by the Thomson/ISI citation databases, in particular by the Science Citation Index (SCI). But the number of citations within these source journals can be determined using the Cited Reference Search mode under the Web of Science (WoS) and the SCI offered by the host STN International. The search functions of both systems were needed to select the papers published as different document types and to cover the full time span of the series. The most cited ICDS papers were identified, and the overall numbers of citations as well as the time-dependent impact of these papers, of single conferences, and of the complete series, was established. The complete of citing papers was analyzed with respect to the countries of the citing authors, the citing journals, and the ISI subject categories
Discontinuous conduction mode analysis of phase-modulated series ...
Indian Academy of Sciences (India)
Utsab Kundu
domain analysis; frequency domain analysis; critical load resistance. 1. Introduction ... DCMSRC design process, requiring repeated circuit simu- lations for design ... Structured derivation of Av is presented, ..... System specifications. L. C r. Lm.
The Analysis Of Personality Disorder On Two Characters In The Animation Series Black Rock Shooter
Ramadhana, Rizki Andrian
2015-01-01
The title of this thesis is The Analysis of Personality Disorder on Two Characters in the Animation Series “Black Rock Shooter” which discusses about the personality disorder of two characters from this series; they are Kagari Izuriha and Yomi Takanashi. The animation series Black Rock Shooter is chosen as the source of data because this animation has psychological genre and represents the complexity of human relationship, especially when build up a friendship. It is because human is a social...
Corzo, H. H.; Velasco, A. M.; Lavín, C.; Ortiz, J. V.
2018-02-01
Vertical excitation energies belonging to several Rydberg series of MgH have been inferred from 3+ electron-propagator calculations of the electron affinities of MgH+ and are in close agreement with experiment. Many electronically excited states with n > 3 are reported for the first time and new insight is given on the assignment of several Rydberg series. Valence and Rydberg excited states of MgH are distinguished respectively by high and low pole strengths corresponding to Dyson orbitals of electron attachment to the cation. By applying the Molecular Quantum Defect Orbital method, oscillator strengths for electronic transitions involving Rydberg states also have been determined.
Applications of electronic noses in meat analysis
Directory of Open Access Journals (Sweden)
Elżbieta GÓRSKA-HORCZYCZAK
2016-01-01
Full Text Available Abstract Electronic noses are devices able to characterize and differentiate the aroma profiles of various food, especially meat and meat products. During recent years e-noses have been widely used in food analysis and proved to provide a fast, simple, non-expensive and non-destructive method of food assessment and quality control. The aim of this study is to summarize the most important features of this analytic tool and to present basic fields and typical areas of e-nose use as well as most commonly used sensor types and patterns for e-nose design. Prospects for the future development of this technique are presented. Methods and research results presented in this manuscript may be a guideline for practical e-nose use.
Extending electronic length frequency analysis in R
DEFF Research Database (Denmark)
Taylor, M. H.; Mildenberger, Tobias K.
2017-01-01
VBGF (soVBGF) requires a more intensive search due to two additional parameters. This work describes the implementation of two optimisation approaches ("simulated annealing" and "genetic algorithm") for growth function fitting using the open-source software "R." Using a generated LFQ data set......Electronic length frequency analysis (ELEFAN) is a system of stock assessment methods using length-frequency (LFQ) data. One step is the estimation of growth from the progression of LFQ modes through time using the von Bertalanffy growth function (VBGF). The option to fit a seasonally oscillating...... of the asymptotic length parameter (L-infinity) are found to have significant effects on parameter estimation error. An outlook provides context as to the significance of the R-based implementation for further testing and development, as well as the general relevance of the method for data-limited stock assessment....
2017-09-01
CAUSES BEHIND HIGH TURNOVER RATES WITHIN THE 0301 SERIES IN THE COMMUNICATIONS- ELECTRONICS COMMAND September 2017 By: Antonia U. Orjih...THE COMMUNICATIONS- ELECTRONICS COMMAND 5. FUNDING NUMBERS 6. AUTHOR(S) Antonia U. Orjih and Shamika M. Fleuranges 7. PERFORMING ORGANIZATION...AGENCY NAME(S) AND ADDRESS(ES) Communications- Electronics Command (CECOM) Aberdeen Proving Ground (APG), Maryland 10. SPONSORING / MONITORING
Multi-Scale Entropy Analysis as a Method for Time-Series Analysis of Climate Data
Directory of Open Access Journals (Sweden)
Heiko Balzter
2015-03-01
Full Text Available Evidence is mounting that the temporal dynamics of the climate system are changing at the same time as the average global temperature is increasing due to multiple climate forcings. A large number of extreme weather events such as prolonged cold spells, heatwaves, droughts and floods have been recorded around the world in the past 10 years. Such changes in the temporal scaling behaviour of climate time-series data can be difficult to detect. While there are easy and direct ways of analysing climate data by calculating the means and variances for different levels of temporal aggregation, these methods can miss more subtle changes in their dynamics. This paper describes multi-scale entropy (MSE analysis as a tool to study climate time-series data and to identify temporal scales of variability and their change over time in climate time-series. MSE estimates the sample entropy of the time-series after coarse-graining at different temporal scales. An application of MSE to Central European, variance-adjusted, mean monthly air temperature anomalies (CRUTEM4v is provided. The results show that the temporal scales of the current climate (1960–2014 are different from the long-term average (1850–1960. For temporal scale factors longer than 12 months, the sample entropy increased markedly compared to the long-term record. Such an increase can be explained by systems theory with greater complexity in the regional temperature data. From 1961 the patterns of monthly air temperatures are less regular at time-scales greater than 12 months than in the earlier time period. This finding suggests that, at these inter-annual time scales, the temperature variability has become less predictable than in the past. It is possible that climate system feedbacks are expressed in altered temporal scales of the European temperature time-series data. A comparison with the variance and Shannon entropy shows that MSE analysis can provide additional information on the
A Multivariate Time Series Method for Monte Carlo Reactor Analysis
International Nuclear Information System (INIS)
Taro Ueki
2008-01-01
A robust multivariate time series method has been established for the Monte Carlo calculation of neutron multiplication problems. The method is termed Coarse Mesh Projection Method (CMPM) and can be implemented using the coarse statistical bins for acquisition of nuclear fission source data. A novel aspect of CMPM is the combination of the general technical principle of projection pursuit in the signal processing discipline and the neutron multiplication eigenvalue problem in the nuclear engineering discipline. CMPM enables reactor physicists to accurately evaluate major eigenvalue separations of nuclear reactors with continuous energy Monte Carlo calculation. CMPM was incorporated in the MCNP Monte Carlo particle transport code of Los Alamos National Laboratory. The great advantage of CMPM over the traditional Fission Matrix method is demonstrated for the three space-dimensional modeling of the initial core of a pressurized water reactor
Directory of Open Access Journals (Sweden)
Dennis A Dean
Full Text Available We present a novel approach for analyzing biological time-series data using a context-free language (CFL representation that allows the extraction and quantification of important features from the time-series. This representation results in Hierarchically AdaPtive (HAP analysis, a suite of multiple complementary techniques that enable rapid analysis of data and does not require the user to set parameters. HAP analysis generates hierarchically organized parameter distributions that allow multi-scale components of the time-series to be quantified and includes a data analysis pipeline that applies recursive analyses to generate hierarchically organized results that extend traditional outcome measures such as pharmacokinetics and inter-pulse interval. Pulsicons, a novel text-based time-series representation also derived from the CFL approach, are introduced as an objective qualitative comparison nomenclature. We apply HAP to the analysis of 24 hours of frequently sampled pulsatile cortisol hormone data, which has known analysis challenges, from 14 healthy women. HAP analysis generated results in seconds and produced dozens of figures for each participant. The results quantify the observed qualitative features of cortisol data as a series of pulse clusters, each consisting of one or more embedded pulses, and identify two ultradian phenotypes in this dataset. HAP analysis is designed to be robust to individual differences and to missing data and may be applied to other pulsatile hormones. Future work can extend HAP analysis to other time-series data types, including oscillatory and other periodic physiological signals.
Energy Technology Data Exchange (ETDEWEB)
Liukkonen, M.; Hentunen, A.; Kyyrae, J. (Department of Electrical Engineering, Helsinki University of Technology, Espoo (Finland)); Suomela, J. (Department of Automation and Systems, Helsinki University of Technology, Espoo (Finland))
2008-07-01
A method for rapid control prototyping of the series-hybrid transmission system is proposed in this paper. The rapid control prototyping needs simulation submodels from all system components in order to develop supervisory control software. The same simulation models can also be used to optimize the drive train. The target framework for the rapid control prototyping method is the original equipment manufacturer (OEM), where the objective is to build devices from subcontractor's components. The machinery industry, as a target group, uses high power ratings for the creation of motion, which leads to high voltage and current values used in the system. Therefore, prototyping is started with careful simulations. This paper also seeks to create a general idea about the structure of the series-hybrid power transmission and assists the start of the process for designing the supervisory control. (orig.)
Time Series in Education: The Analysis of Daily Attendance in Two High Schools
Koopmans, Matthijs
2011-01-01
This presentation discusses the use of a time series approach to the analysis of daily attendance in two urban high schools over the course of one school year (2009-10). After establishing that the series for both schools were stationary, they were examined for moving average processes, autoregression, seasonal dependencies (weekly cycles),…
Mapping air temperature using time series analysis of LST : The SINTESI approach
Alfieri, S.M.; De Lorenzi, F.; Menenti, M.
2013-01-01
This paper presents a new procedure to map time series of air temperature (Ta) at fine spatial resolution using time series analysis of satellite-derived land surface temperature (LST) observations. The method assumes that air temperature is known at a single (reference) location such as in gridded
Time-series analysis of Nigeria rice supply and demand: Error ...
African Journals Online (AJOL)
The study examined a time-series analysis of Nigeria rice supply and demand with a view to determining any long-run equilibrium between them using the Error Correction Model approach (ECM). The data used for the study represents the annual series of 1960-2007 (47 years) for rice supply and demand in Nigeria, ...
Taxation in Public Education. Analysis and Bibliography Series, No. 12.
Ross, Larry L.
Intended for both researchers and practitioners, this analysis and bibliography cites approximately 100 publications on educational taxation, including general texts and reports, statistical reports, taxation guidelines, and alternative proposals for taxation. Topics covered in the analysis section include State and Federal aid, urban and suburban…
Energy Technology Data Exchange (ETDEWEB)
Masrour, R., E-mail: rachidmasrour@hotmail.com [Laboratory of Materials, Processes, Environment and Quality, Cady Ayyed University, National School of Applied Sciences, 63 46000 Safi (Morocco); LMPHE (URAC 12), Faculty of Science, Mohammed V-Agdal University, Rabat (Morocco); Hlil, E.K. [Institut Néel, CNRS et Université Joseph Fourier, BP 166, F-38042 Grenoble cedex 9 (France); Hamedoun, M. [Institute of Nanomaterials and Nanotechnologies, MAScIR, Rabat (Morocco); Benyoussef, A. [LMPHE (URAC 12), Faculty of Science, Mohammed V-Agdal University, Rabat (Morocco); Institute of Nanomaterials and Nanotechnologies, MAScIR, Rabat (Morocco); Hassan II Academy of Science and Technology, Rabat (Morocco)
2014-04-01
Self-consistent ab initio calculations, based on Density Functional Theory (DFT) approach and using Full Potential Linear Augmented Plane Wave (FLAPW) method within GGA+U approximation, are performed to investigate both electronic and magnetic properties of the GdS layers. Polarized spin and spin–orbit coupling are included in calculations within the framework of the antiferromagnetic state between two adjacent Gd layers. Magnetic moment considered to lie along (001) axes are computed. Obtained data from ab initio calculations are used as input for the High Temperature Series Expansions (HTSEs) calculations to compute other magnetic parameters. Using the Heisenberg model, the exchange interactions between the magnetic atoms Gd–Gd in the same layer and between the magnetic atoms in the adjacent bilayers are estimated. This estimate is obtained using the antiferromagnetic and ferromagnetic energies computed by abinitio calculations for GdS layers. The High Temperature Series Expansions (HTSEs) of the magnetic susceptibility of GdS with antiferromagnetic moment (m{sub Gd}) is given up to sixth order series versus of (J{sub 11}(Gd–Gd)/k{sub B}T). The Néel temperature T{sub N} is obtained by mean field theory and by HTSEs of the magnetic susceptibility series using the Padé approximant method. The critical exponent γ associated with the magnetic susceptibility is calculated for GdS layers. - Highlights: • Electronic and magnetic properties of GdS are investigated using the ab initio calculations. • Obtained data from abinitio calculations are used as input for HTSEs to compute other magnetic parameters. • Néel temperature and critical exponent are deduced using HTSE method.
International Nuclear Information System (INIS)
Masrour, R.; Hlil, E.K.; Hamedoun, M.; Benyoussef, A.
2014-01-01
Self-consistent ab initio calculations, based on Density Functional Theory (DFT) approach and using Full Potential Linear Augmented Plane Wave (FLAPW) method within GGA+U approximation, are performed to investigate both electronic and magnetic properties of the GdS layers. Polarized spin and spin–orbit coupling are included in calculations within the framework of the antiferromagnetic state between two adjacent Gd layers. Magnetic moment considered to lie along (001) axes are computed. Obtained data from ab initio calculations are used as input for the High Temperature Series Expansions (HTSEs) calculations to compute other magnetic parameters. Using the Heisenberg model, the exchange interactions between the magnetic atoms Gd–Gd in the same layer and between the magnetic atoms in the adjacent bilayers are estimated. This estimate is obtained using the antiferromagnetic and ferromagnetic energies computed by abinitio calculations for GdS layers. The High Temperature Series Expansions (HTSEs) of the magnetic susceptibility of GdS with antiferromagnetic moment (m Gd ) is given up to sixth order series versus of (J 11 (Gd–Gd)/k B T). The Néel temperature T N is obtained by mean field theory and by HTSEs of the magnetic susceptibility series using the Padé approximant method. The critical exponent γ associated with the magnetic susceptibility is calculated for GdS layers. - Highlights: • Electronic and magnetic properties of GdS are investigated using the ab initio calculations. • Obtained data from abinitio calculations are used as input for HTSEs to compute other magnetic parameters. • Néel temperature and critical exponent are deduced using HTSE method
Institute of Scientific and Technical Information of China (English)
RONG Yan-shu; TU Qi-pu
2005-01-01
It is important and necessary to get a much longer precipitation series in order to research features of drought/flood and climate change.Based on dryness and wetness grades series of 18 stations in Northern China of 533 years from 1470 to 2002, the Moving Cumulative Frequency Method (MCFM) was developed, moving average precipitation series from 1499 to 2002 were reconstructed by testing three kinds of average precipitation, and the features of climate change and dry and wet periods were researched by using reconstructed precipitation series in the present paper.The results showed that there were good relationship between the reconstructed precipitation series and the observation precipitation series since 1954 and their relative root-mean-square error were below 1.89%, that the relation between reconstructed series and the dryness and wetness grades series were nonlinear and this nonlinear relation implied that reconstructed series were reliable and could became foundation data for researching evolution of the drought and flood.Analysis of climate change upon reconstructed precipitation series revealed that although drought intensity of recent dry period from middle 1970s of 20th century until early 21st century was not the strongest in historical climate of Northern China, intensity and duration of wet period was a great deal decreasing and shortening respectively, climate evolve to aridification situation in Northern China.
The Timeseries Toolbox - A Web Application to Enable Accessible, Reproducible Time Series Analysis
Veatch, W.; Friedman, D.; Baker, B.; Mueller, C.
2017-12-01
The vast majority of data analyzed by climate researchers are repeated observations of physical process or time series data. This data lends itself of a common set of statistical techniques and models designed to determine trends and variability (e.g., seasonality) of these repeated observations. Often, these same techniques and models can be applied to a wide variety of different time series data. The Timeseries Toolbox is a web application designed to standardize and streamline these common approaches to time series analysis and modeling with particular attention to hydrologic time series used in climate preparedness and resilience planning and design by the U. S. Army Corps of Engineers. The application performs much of the pre-processing of time series data necessary for more complex techniques (e.g. interpolation, aggregation). With this tool, users can upload any dataset that conforms to a standard template and immediately begin applying these techniques to analyze their time series data.
Financial time series analysis based on effective phase transfer entropy
Yang, Pengbo; Shang, Pengjian; Lin, Aijing
2017-02-01
Transfer entropy is a powerful technique which is able to quantify the impact of one dynamic system on another system. In this paper, we propose the effective phase transfer entropy method based on the transfer entropy method. We use simulated data to test the performance of this method, and the experimental results confirm that the proposed approach is capable of detecting the information transfer between the systems. We also explore the relationship between effective phase transfer entropy and some variables, such as data size, coupling strength and noise. The effective phase transfer entropy is positively correlated with the data size and the coupling strength. Even in the presence of a large amount of noise, it can detect the information transfer between systems, and it is very robust to noise. Moreover, this measure is indeed able to accurately estimate the information flow between systems compared with phase transfer entropy. In order to reflect the application of this method in practice, we apply this method to financial time series and gain new insight into the interactions between systems. It is demonstrated that the effective phase transfer entropy can be used to detect some economic fluctuations in the financial market. To summarize, the effective phase transfer entropy method is a very efficient tool to estimate the information flow between systems.
Stock price forecasting based on time series analysis
Chi, Wan Le
2018-05-01
Using the historical stock price data to set up a sequence model to explain the intrinsic relationship of data, the future stock price can forecasted. The used models are auto-regressive model, moving-average model and autoregressive-movingaverage model. The original data sequence of unit root test was used to judge whether the original data sequence was stationary. The non-stationary original sequence as a first order difference needed further processing. Then the stability of the sequence difference was re-inspected. If it is still non-stationary, the second order differential processing of the sequence is carried out. Autocorrelation diagram and partial correlation diagram were used to evaluate the parameters of the identified ARMA model, including coefficients of the model and model order. Finally, the model was used to forecast the fitting of the shanghai composite index daily closing price with precision. Results showed that the non-stationary original data series was stationary after the second order difference. The forecast value of shanghai composite index daily closing price was closer to actual value, indicating that the ARMA model in the paper was a certain accuracy.
Industrial electricity demand for Turkey: A structural time series analysis
International Nuclear Information System (INIS)
Dilaver, Zafer; Hunt, Lester C.
2011-01-01
This research investigates the relationship between Turkish industrial electricity consumption, industrial value added and electricity prices in order to forecast future Turkish industrial electricity demand. To achieve this, an industrial electricity demand function for Turkey is estimated by applying the structural time series technique to annual data over the period 1960 to 2008. In addition to identifying the size and significance of the price and industrial value added (output) elasticities, this technique also uncovers the electricity Underlying Energy Demand Trend (UEDT) for the Turkish industrial sector and is, as far as is known, the first attempt to do this. The results suggest that output and real electricity prices and a UEDT all have an important role to play in driving Turkish industrial electricity demand. Consequently, they should all be incorporated when modelling Turkish industrial electricity demand and the estimated UEDT should arguably be considered in future energy policy decisions concerning the Turkish electricity industry. The output and price elasticities are estimated to be 0.15 and - 0.16 respectively, with an increasing (but at a decreasing rate) UEDT and based on the estimated equation, and different forecast assumptions, it is predicted that Turkish industrial electricity demand will be somewhere between 97 and 148 TWh by 2020. -- Research Highlights: → Estimated output and price elasticities of 0.15 and -0.16 respectively. → Estimated upward sloping UEDT (i.e. energy using) but at a decreasing rate. → Predicted Turkish industrial electricity demand between 97 and 148 TWh in 2020.
A unified nonlinear stochastic time series analysis for climate science.
Moon, Woosok; Wettlaufer, John S
2017-03-13
Earth's orbit and axial tilt imprint a strong seasonal cycle on climatological data. Climate variability is typically viewed in terms of fluctuations in the seasonal cycle induced by higher frequency processes. We can interpret this as a competition between the orbitally enforced monthly stability and the fluctuations/noise induced by weather. Here we introduce a new time-series method that determines these contributions from monthly-averaged data. We find that the spatio-temporal distribution of the monthly stability and the magnitude of the noise reveal key fingerprints of several important climate phenomena, including the evolution of the Arctic sea ice cover, the El Nio Southern Oscillation (ENSO), the Atlantic Nio and the Indian Dipole Mode. In analogy with the classical destabilising influence of the ice-albedo feedback on summertime sea ice, we find that during some time interval of the season a destabilising process operates in all of these climate phenomena. The interaction between the destabilisation and the accumulation of noise, which we term the memory effect, underlies phase locking to the seasonal cycle and the statistical nature of seasonal predictability.
Methodology Series Module 6: Systematic Reviews and Meta-analysis.
Setia, Maninder Singh
2016-01-01
Systematic reviews and meta-analysis have become an important of biomedical literature, and they provide the "highest level of evidence" for various clinical questions. There are a lot of studies - sometimes with contradictory conclusions - on a particular topic in literature. Hence, as a clinician, which results will you believe? What will you tell your patient? Which drug is better? A systematic review or a meta-analysis may help us answer these questions. In addition, it may also help us understand the quality of the articles in literature or the type of studies that have been conducted and published (example, randomized trials or observational studies). The first step it to identify a research question for systematic review or meta-analysis. The next step is to identify the articles that will be included in the study. This will be done by searching various databases; it is important that the researcher should search for articles in more than one database. It will also be useful to form a group of researchers and statisticians that have expertise in conducting systematic reviews and meta-analysis before initiating them. We strongly encourage the readers to register their proposed review/meta-analysis with PROSPERO. Finally, these studies should be reported according to the Preferred Reporting Items for Systematic Reviews and Meta-analysis checklist.
Using Lasers and X-rays to Reveal the Motion of Atoms and Electrons (LBNL Summer Lecture Series)
Energy Technology Data Exchange (ETDEWEB)
Schoenlein, Robert [Deputy Director, Advanced Light Source
2009-07-07
Summer Lecture Series 2009: The ultrafast motion of atoms and electrons lies at the heart of chemical reactions, advanced materials with exotic properties, and biological processes such as the first event in vision. Bob Schoenlein, Deputy Director for Science at the Advanced Light Source, will discuss how such processes are revealed by using laser pulses spanning a millionth of a billionth of a second, and how a new generation of light sources will bring the penetrating power of x-rays to the world of ultrafast science.
A novel water quality data analysis framework based on time-series data mining.
Deng, Weihui; Wang, Guoyin
2017-07-01
The rapid development of time-series data mining provides an emerging method for water resource management research. In this paper, based on the time-series data mining methodology, we propose a novel and general analysis framework for water quality time-series data. It consists of two parts: implementation components and common tasks of time-series data mining in water quality data. In the first part, we propose to granulate the time series into several two-dimensional normal clouds and calculate the similarities in the granulated level. On the basis of the similarity matrix, the similarity search, anomaly detection, and pattern discovery tasks in the water quality time-series instance dataset can be easily implemented in the second part. We present a case study of this analysis framework on weekly Dissolve Oxygen time-series data collected from five monitoring stations on the upper reaches of Yangtze River, China. It discovered the relationship of water quality in the mainstream and tributary as well as the main changing patterns of DO. The experimental results show that the proposed analysis framework is a feasible and efficient method to mine the hidden and valuable knowledge from water quality historical time-series data. Copyright © 2017 Elsevier Ltd. All rights reserved.
Time series analysis of diverse extreme phenomena: universal features
Eftaxias, K.; Balasis, G.
2012-04-01
The field of study of complex systems holds that the dynamics of complex systems are founded on universal principles that may used to describe a great variety of scientific and technological approaches of different types of natural, artificial, and social systems. We suggest that earthquake, epileptic seizures, solar flares, and magnetic storms dynamics can be analyzed within similar mathematical frameworks. A central property of aforementioned extreme events generation is the occurrence of coherent large-scale collective behavior with very rich structure, resulting from repeated nonlinear interactions among the corresponding constituents. Consequently, we apply the Tsallis nonextensive statistical mechanics as it proves an appropriate framework in order to investigate universal principles of their generation. First, we examine the data in terms of Tsallis entropy aiming to discover common "pathological" symptoms of transition to a significant shock. By monitoring the temporal evolution of the degree of organization in time series we observe similar distinctive features revealing significant reduction of complexity during their emergence. Second, a model for earthquake dynamics coming from a nonextensive Tsallis formalism, starting from first principles, has been recently introduced. This approach leads to an energy distribution function (Gutenberg-Richter type law) for the magnitude distribution of earthquakes, providing an excellent fit to seismicities generated in various large geographic areas usually identified as seismic regions. We show that this function is able to describe the energy distribution (with similar non-extensive q-parameter) of solar flares, magnetic storms, epileptic and earthquake shocks. The above mentioned evidence of a universal statistical behavior suggests the possibility of a common approach for studying space weather, earthquakes and epileptic seizures.
Real analysis series, functions of several variables, and applications
Laczkovich, Miklós
2017-01-01
This book develops the theory of multivariable analysis, building on the single variable foundations established in the companion volume, Real Analysis: Foundations and Functions of One Variable. Together, these volumes form the first English edition of the popular Hungarian original, Valós Analízis I & II, based on courses taught by the authors at Eötvös Loránd University, Hungary, for more than 30 years. Numerous exercises are included throughout, offering ample opportunities to master topics by progressing from routine to difficult problems. Hints or solutions to many of the more challenging exercises make this book ideal for independent study, or further reading. Intended as a sequel to a course in single variable analysis, this book builds upon and expands these ideas into higher dimensions. The modular organization makes this text adaptable for either a semester or year-long introductory course. Topics include: differentiation and integration of functions of several variables; infinite numerica...
Analysis of engineering cycles thermodynamics and fluid mechanics series
Haywood, R W
1980-01-01
Analysis of Engineering Cycles, Third Edition, deals principally with an analysis of the overall performance, under design conditions, of work-producing power plants and work-absorbing refrigerating and gas-liquefaction plants, most of which are either cyclic or closely related thereto. The book is organized into two parts, dealing first with simple power and refrigerating plants and then moving on to more complex plants. The principal modifications in this Third Edition arise from the updating and expansion of material on nuclear plants and on combined and binary plants. In view of increased
International Nuclear Information System (INIS)
Liu Weiqing; Hu Linhua; Dai Songyuan; Guo Lei; Jiang Nianquan; Kou Dongxing
2010-01-01
The influence of the series resistance on the electron transport and recombination processes in dye-sensitized solar cells (DSC) has been investigated. The series resistances induced by some parts of DSC, such as the transparent conductive oxide (TCO), the electrolyte layer and the counter electrode, influence the performance of DSC. By combining three frequency-domain techniques, specifically electrochemical impedance spectroscopy (EIS), intensity modulated photocurrent spectroscopy (IMPS) and intensity modulated photovoltage spectroscopy (IMVS), we studied the relationship between the series resistance and the dynamic response of DSC. The results show that the series resistance induced by the TCO or counter electrode predominantly affects the electron transport under short circuit conditions and has no significant influence on the recombination under open circuit conditions. However, the resistance related to the electrolyte layer not only limits the carrier transport but also influences the recombination. Possible reasons for the influence of the series resistance on the electron transport and recombination processes in DSC are also discussed.
Burns resulting from spontaneous combustion of electronic cigarettes: a case series
Sheckter, Clifford; Chattopadhyay, Arhana; Paro, John; Karanas, Yvonne
2016-01-01
Background Electronic cigarette (e-cigarette) sales have grown rapidly in recent years, coinciding with a public perception that they are a safer alternative to traditional cigarettes. However, there have been numerous media reports of fires associated with e-cigarette spontaneous combustion. Case Presentation Three severe burns caused by spontaneous combustion of e-cigarettes within a 6-month period were treated at the Santa Clara Valley Medical Center Burn Unit. Patients sustained partial a...
Sunde, Jonas Kristoffer
2016-01-01
Throughout this thesis, scanning precession electron diffraction is applied to heat-treated Al-Cu-Li and Al-Mg-Cu-Ag alloys, shedding light on the distribution of phases present and the complex interplay between these microstructural features. The employed technique yielded high quality data sets, which through subsequent data processing enabled a detailed phase mapping of these multi-component Al alloys. Among the main results presented, are virtual dark field images highlighting all separat...
Time series analysis of aerobic bacterial flora during Miso fermentation.
Onda, T; Yanagida, F; Tsuji, M; Shinohara, T; Yokotsuka, K
2003-01-01
This article reports a microbiological study of aerobic mesophilic bacteria that are present during the fermentation process of Miso. Aerobic bacteria were enumerated and isolated from Miso during fermentation and divided into nine groups using traditional phenotypic tests. The strains were identified by biochemical analysis and 16S rRNA sequence analysis. They were identified as Bacillus subtilis, B. amyloliquefaciens, Kocuria kristinae, Staphylococcus gallinarum and S. kloosii. All strains were sensitive to the bacteriocins produced by the lactic acid bacteria isolated from Miso. The dominant species among the undesirable species throughout the fermentation process were B. subtilis and B. amyloliquefaciens. It is suggested that bacteriocin-producing lactic acid bacteria are effective in the growth prevention of aerobic bacteria in Miso. This study has provided useful information for controlling of bacterial flora during Miso fermentation.
Cluster analysis of activity-time series in motor learning
DEFF Research Database (Denmark)
Balslev, Daniela; Nielsen, Finn Årup; Frutiger, Sally A.
2002-01-01
Neuroimaging studies of learning focus on brain areas where the activity changes as a function of time. To circumvent the difficult problem of model selection, we used a data-driven analytic tool, cluster analysis, which extracts representative temporal and spatial patterns from the voxel...... practice-related activity in a fronto-parieto-cerebellar network, in agreement with previous studies of motor learning. These voxels were separated from a group of voxels showing an unspecific time-effect and another group of voxels, whose activation was an artifact from smoothing. Hum. Brain Mapping 15...
Burns resulting from spontaneous combustion of electronic cigarettes: a case series.
Sheckter, Clifford; Chattopadhyay, Arhana; Paro, John; Karanas, Yvonne
2016-01-01
Electronic cigarette (e-cigarette) sales have grown rapidly in recent years, coinciding with a public perception that they are a safer alternative to traditional cigarettes. However, there have been numerous media reports of fires associated with e-cigarette spontaneous combustion. Three severe burns caused by spontaneous combustion of e-cigarettes within a 6-month period were treated at the Santa Clara Valley Medical Center Burn Unit. Patients sustained partial and full-thickness burns. Two required hospitalization and surgical treatment. E-cigarettes are dangerous devices and have the potential to cause significant burns. Consumers and the general public should be made aware of these life-threatening devices.
Pal, Mayukha; Madhusudana Rao, P.; Manimaran, P.
2014-12-01
We apply the recently developed multifractal detrended cross-correlation analysis method to investigate the cross-correlation behavior and fractal nature between two non-stationary time series. We analyze the daily return price of gold, West Texas Intermediate and Brent crude oil, foreign exchange rate data, over a period of 18 years. The cross correlation has been measured from the Hurst scaling exponents and the singularity spectrum quantitatively. From the results, the existence of multifractal cross-correlation between all of these time series is found. We also found that the cross correlation between gold and oil prices possess uncorrelated behavior and the remaining bivariate time series possess persistent behavior. It was observed for five bivariate series that the cross-correlation exponents are less than the calculated average generalized Hurst exponents (GHE) for q0 and for one bivariate series the cross-correlation exponent is greater than GHE for all q values.
A Reception Analysis on the Youth Audiences of TV Series in Marivan
Directory of Open Access Journals (Sweden)
Omid Karimi
2014-03-01
Full Text Available The aim of this article is to describe the role of foreign media as the agitators of popular culture. For that with reception analysis it’s pay to describe decoding of youth audiences about this series. Globalization theory and Reception in Communication theory are formed the theoretical system of current article. The methodology in this research is qualitative one, and two techniques as in-depth interview and observation are used for data collection. The results show different people based on individual features, social and cultural backgrounds have inclination toward special characters and identify with them. This inclination so far the audience fallow the series because of his/her favorite character. Also there is a great compatibility between audience backgrounds and their receptions. A number of audience have criticized the series and point out the negative consequences on its society. However, seeing the series continue; really they prefer watching series enjoying to risks of it.
ITS Version 6 : the integrated TIGER series of coupled electron/photon Monte Carlo transport codes.
Energy Technology Data Exchange (ETDEWEB)
Franke, Brian Claude; Kensek, Ronald Patrick; Laub, Thomas William
2008-04-01
ITS is a powerful and user-friendly software package permitting state-of-the-art Monte Carlo solution of lineartime-independent coupled electron/photon radiation transport problems, with or without the presence of macroscopic electric and magnetic fields of arbitrary spatial dependence. Our goal has been to simultaneously maximize operational simplicity and physical accuracy. Through a set of preprocessor directives, the user selects one of the many ITS codes. The ease with which the makefile system is applied combines with an input scheme based on order-independent descriptive keywords that makes maximum use of defaults and internal error checking to provide experimentalists and theorists alike with a method for the routine but rigorous solution of sophisticated radiation transport problems. Physical rigor is provided by employing accurate cross sections, sampling distributions, and physical models for describing the production and transport of the electron/photon cascade from 1.0 GeV down to 1.0 keV. The availability of source code permits the more sophisticated user to tailor the codes to specific applications and to extend the capabilities of the codes to more complex applications. Version 6, the latest version of ITS, contains (1) improvements to the ITS 5.0 codes, and (2) conversion to Fortran 90. The general user friendliness of the software has been enhanced through memory allocation to reduce the need for users to modify and recompile the code.
Cerebral venous sinus thrombosis on MRI: A case series analysis
Directory of Open Access Journals (Sweden)
Sanjay M Khaladkar
2014-01-01
Full Text Available Background: Cerebral venous sinus thrombosis (CVST is a rare form of stroke seen in young and middle aged group, especially in women due to thrombus of dural venous sinuses and can cause acute neurological deterioration with increased morbidity and mortality if not diagnosed in early stage. Neurological deficit occurs due to focal or diffuse cerebral edema and venous non-hemorrhagic or hemorrhagic infarct. Aim and Objectives: To assess/evaluate the role of Magnetic Resonance Imaging (MRI and Magnetic Resonance Venography (MRV as an imaging modality for early diagnosis of CVST and to study patterns of venous thrombosis, in detecting changes in brain parenchyma and residual effects of CVST using MRI. Materials and Methods: Retrospective descriptive analysis of 40 patients of CVST diagnosed on MRI brain and MRV was done. Results: 29/40 (72.5% were males and 11/40 (27.5% were females. Most of the patients were in the age group of 21-40 years (23/40-57.5%. Most of the patients 16/40 (40% presented within 7 days. No definite cause of CVST was found in 24 (60% patients in spite of detailed history. In 36/40 (90% of cases major sinuses were involved, deep venous system were involved in 7/40 (17.5% cases, superficial cortical vein was involved in 1/40 (2.5% cases. Analysis of stage of thrombus (acute, subacute, chronic was done based on its appearance on T1 and T2WI. 31/40 (77.5% patients showed complete absence of flow on MRV, while 9/40 (22.5% cases showed partial flow on MR venogram. Brain parenchyma was normal in 20/40 (50% patients while 6/40 (15% cases had non-hemorrhagic infarct and 14/40 (35% patients presented with hemorrhagic infarct. Conclusion: Our study concluded that MRI brain with MRV is sensitive in diagnosing both direct signs (evidence of thrombus inside the affected veins and indirect signs (parenchymal changes of CVST and their follow up.
Energy Technology Data Exchange (ETDEWEB)
Dröge, W.; Kartavykh, Y. Y. [Institut für Theoretische Physik und Astrophysik, Universität Würzburg, D-97074 Würzburg (Germany); Dresing, N.; Klassen, A. [Institut für Experimentelle und Angewandte Physik, Universität Kiel, D-24118 Kiel (Germany)
2016-08-01
During 2010 August a series of solar particle events was observed by the two STEREO spacecraft as well as near-Earth spacecraft. The events, occurring on August 7, 14, and 18, originated from active regions 11093 and 11099. We combine in situ and remote-sensing observations with predictions from our model of three-dimensional anisotropic particle propagation in order to investigate the physical processes that caused the large angular spreads of energetic electrons during these events. In particular, we address the effects of the lateral transport of the electrons in the solar corona that is due to diffusion perpendicular to the average magnetic field in the interplanetary medium. We also study the influence of two coronal mass ejections and associated shock waves on the electron propagation, and a possible time variation of the transport conditions during the above period. For the August 18 event we also utilize electron observations from the MESSENGER spacecraft at a distance of 0.31 au from the Sun for an attempt to separate between radial and longitudinal dependencies in the transport process. Our modelings show that the parallel and perpendicular diffusion mean free paths of electrons can vary significantly not only as a function of the radial distance, but also of the heliospheric longitude. Normalized to a distance of 1 au, we derive values of λ {sub ∥} in the range of 0.15–0.6 au, and values of λ {sub ⊥} in the range of 0.005–0.01 au. We discuss how our results relate to various theoretical models for perpendicular diffusion, and whether there might be a functional relationship between the perpendicular and the parallel mean free path.
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.
Financing Human Development for Sectorial Growth: A Time Series Analysis
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Shobande Abdul Olatunji
2017-06-01
Full Text Available The role which financing human development plays in fostering the sectorial growth of an economy cannot be undermined. It is a key instrument which can be utilized to alleviate poverty, create employment and ensure the sustenance of economic growth and development. Thus financing human development for sectorial growth has taken the center stage of economic growth and development strategies in most countries. In a constructive effort to examine the in-depth relationship between the variables in the Nigerian space, this paper provides evidence on the impact of financing human development and sectorial growth in Nigeria between 1982 and 2016, using the Johansen co-integration techniques to test for co-integration among the variables and the Vector Error Correction Model (VECM to ascertain the speed of adjustment of the variables to their long run equilibrium position. The analysis shows that a long and short run relationship exists between financing human capital development and sectorial growth during the period reviewed. Therefore, the paper argues that for an active foundation for sustainable sectorial growth and development, financing human capital development across each unit is urgently required through increased budgetary allocation for both health and educational sectors since they are key components of human capital development in a nation.
Center Line Slope Analysis in Two-Dimensional Electronic Spectroscopy
?anda, Franti?ek; Perl?k, V?clav; Lincoln, Craig N.; Hauer, J?rgen
2015-01-01
Center line slope (CLS) analysis in 2D infrared spectroscopy has been extensively used to extract frequency?frequency correlation functions of vibrational transitions. We apply this concept to 2D electronic spectroscopy, where CLS is a measure of electronic gap fluctuations. The two domains, infrared and electronic, possess differences: In the infrared, the frequency fluctuations are classical, often slow and Gaussian. In contrast, electronic spectra are subject to fast spectral diffusion and...
Spatially adaptive mixture modeling for analysis of FMRI time series.
Vincent, Thomas; Risser, Laurent; Ciuciu, Philippe
2010-04-01
Within-subject analysis in fMRI essentially addresses two problems, the detection of brain regions eliciting evoked activity and the estimation of the underlying dynamics. In Makni et aL, 2005 and Makni et aL, 2008, a detection-estimation framework has been proposed to tackle these problems jointly, since they are connected to one another. In the Bayesian formalism, detection is achieved by modeling activating and nonactivating voxels through independent mixture models (IMM) within each region while hemodynamic response estimation is performed at a regional scale in a nonparametric way. Instead of IMMs, in this paper we take advantage of spatial mixture models (SMM) for their nonlinear spatial regularizing properties. The proposed method is unsupervised and spatially adaptive in the sense that the amount of spatial correlation is automatically tuned from the data and this setting automatically varies across brain regions. In addition, the level of regularization is specific to each experimental condition since both the signal-to-noise ratio and the activation pattern may vary across stimulus types in a given brain region. These aspects require the precise estimation of multiple partition functions of underlying Ising fields. This is addressed efficiently using first path sampling for a small subset of fields and then using a recently developed fast extrapolation technique for the large remaining set. Simulation results emphasize that detection relying on supervised SMM outperforms its IMM counterpart and that unsupervised spatial mixture models achieve similar results without any hand-tuning of the correlation parameter. On real datasets, the gain is illustrated in a localizer fMRI experiment: brain activations appear more spatially resolved using SMM in comparison with classical general linear model (GLM)-based approaches, while estimating a specific parcel-based HRF shape. Our approach therefore validates the treatment of unsmoothed fMRI data without fixed GLM
International Nuclear Information System (INIS)
Hashimoto, Tetsuo; Sanada, Yukihisa; Uezu, Yasuhiro
2004-01-01
A delayed coincidence method, time-interval analysis (TIA), has been applied to successive α-α decay events on the millisecond time-scale. Such decay events are part of the 220 Rn→ 216 Po (T 1/2 145 ms) (Th-series) and 219 Rn→ 215 Po (T 1/2 1.78 ms) (Ac-series). By using TIA in addition to measurement of 226 Ra (U-series) from α-spectrometry by liquid scintillation counting (LSC), two natural decay series could be identified and separated. The TIA detection efficiency was improved by using the pulse-shape discrimination technique (PSD) to reject β-pulses, by solvent extraction of Ra combined with simple chemical separation, and by purging the scintillation solution with dry N 2 gas. The U- and Th-series together with the Ac-series were determined, respectively, from alpha spectra and TIA carried out immediately after Ra-extraction. Using the 221 Fr→ 217 At (T 1/2 32.3 ms) decay process as a tracer, overall yields were estimated from application of TIA to the 225 Ra (Np-decay series) at the time of maximum growth. The present method has proven useful for simultaneous determination of three radioactive decay series in environmental samples. (orig.)
Time series analysis of wind speed using VAR and the generalized impulse response technique
Energy Technology Data Exchange (ETDEWEB)
Ewing, Bradley T. [Area of Information Systems and Quantitative Sciences, Rawls College of Business and Wind Science and Engineering Research Center, Texas Tech University, Lubbock, TX 79409-2101 (United States); Kruse, Jamie Brown [Center for Natural Hazard Research, East Carolina University, Greenville, NC (United States); Schroeder, John L. [Department of Geosciences and Wind Science and Engineering Research Center, Texas Tech University, Lubbock, TX (United States); Smith, Douglas A. [Department of Civil Engineering and Wind Science and Engineering Research Center, Texas Tech University, Lubbock, TX (United States)
2007-03-15
This research examines the interdependence in time series wind speed data measured in the same location at four different heights. A multiple-equation system known as a vector autoregression is proposed for characterizing the time series dynamics of wind. Additionally, the recently developed method of generalized impulse response analysis provides insight into the cross-effects of the wind series and their responses to shocks. Findings are based on analysis of contemporaneous wind speed time histories taken at 13, 33, 70 and 160 ft above ground level with a sampling rate of 10 Hz. The results indicate that wind speeds measured at 70 ft was the most variable. Further, the turbulence persisted longer at the 70-ft measurement than at the other heights. The greatest interdependence is observed at 13 ft. Gusts at 160 ft led to the greatest persistence to an 'own' shock and led to greatest persistence in the responses of the other wind series. (author)
Hayashi, Hideaki; Shima, Keisuke; Shibanoki, Taro; Kurita, Yuichi; Tsuji, Toshio
2013-01-01
This paper outlines a probabilistic neural network developed on the basis of time-series discriminant component analysis (TSDCA) that can be used to classify high-dimensional time-series patterns. TSDCA involves the compression of high-dimensional time series into a lower-dimensional space using a set of orthogonal transformations and the calculation of posterior probabilities based on a continuous-density hidden Markov model that incorporates a Gaussian mixture model expressed in the reduced-dimensional space. The analysis can be incorporated into a neural network so that parameters can be obtained appropriately as network coefficients according to backpropagation-through-time-based training algorithm. The network is considered to enable high-accuracy classification of high-dimensional time-series patterns and to reduce the computation time taken for network training. In the experiments conducted during the study, the validity of the proposed network was demonstrated for EEG signals.
Fractal analysis and nonlinear forecasting of indoor 222Rn time series
International Nuclear Information System (INIS)
Pausch, G.; Bossew, P.; Hofmann, W.; Steger, F.
1998-01-01
Fractal analyses of indoor 222 Rn time series were performed using different chaos theory based measurements such as time delay method, Hurst's rescaled range analysis, capacity (fractal) dimension, and Lyapunov exponent. For all time series we calculated only positive Lyapunov exponents which is a hint to chaos, while the Hurst exponents were well below 0.5, indicating antipersistent behaviour (past trends tend to reverse in the future). These time series were also analyzed with a nonlinear prediction method which allowed an estimation of the embedding dimensions with some restrictions, limiting the prediction to about three relative time steps. (orig.)
Analysis and simulation of BGK electron holes
Directory of Open Access Journals (Sweden)
L. Muschietti
1999-01-01
Full Text Available Recent observations from satellites crossing regions of magnetic-field-aligned electron streams reveal solitary potential structures that move at speeds much greater than the ion acoustic/thermal velocity. The structures appear as positive potential pulses rapidly drifting along the magnetic field, and are electrostatic in their rest frame. We interpret them as BGK electron holes supported by a drifting population of trapped electrons. Using Laplace transforms, we analyse the behavior of one phase-space electron hole. The resulting potential shapes and electron distribution functions are self-consistent and compatible with the field and particle data associated with the observed pulses. In particular, the spatial width increases with increasing amplitude. The stability of the analytic solution is tested by means of a two-dimensional particle-in-cell simulation code with open boundaries. We consider a strongly magnetized parameter regime in which the bounce frequency of the trapped electrons is much less than their gyrofrequency. Our investigation includes the influence of the ions, which in the frame of the hole appear as an incident beam, and impinge on the BGK potential with considerable energy. The nonlinear structure is remarkably resilient
International Nuclear Information System (INIS)
Habuer,; Nakatani, Jun; Moriguchi, Yuichi
2014-01-01
Highlights: • We estimate the possession and obsolescence of household appliances (HAs) in China. • Over 4.8–5.1 billion units of major HAs will be discarded in the next 20 years. • We calculate the amounts of substances contained in end-of-life (EoL) TV sets. • Less common metals will tend to decrease in content in generation of EoL TV sets. • Precious metals will tend to increase in content in EoL TV sets in 2015–2030. - Abstract: Given the amounts of end-of-life electrical and electronic equipment (EoL-EEE) being generated and their contents of both harmful and valuable materials, the EoL-EEE issue should be regarded not only as an emerging environmental problem but also as a resource management strategy in China. At present, in order to provide the basis for managing EoL-EEE at both product and substance levels in China, it is necessary to carry out a quantitative analysis on EoL-EEE and to determine how much of it will be generated and how much materials and substances it contains. In this study, the possession and obsolescence amounts of five types of household appliance (HA) including television (TV) sets and the amounts of substances contained in EoL TV sets were estimated using time-series product flow analysis (PFA) and substance flow analysis (SFA). The results of PFA indicated that the total possession amounts of those five types of HAs will exceed 3.1 billion units in 2030, which will be two times higher than those in 2010. In addition, it was estimated that cumulatively over 4.8–5.1 billion units of these five types of EoL HA would be obsoleted between 2010–2030. The results of SFA on TV sets indicated that the generated amounts of most of the less common metals and a part of common metals such as copper (Cu) would tend to decrease, whereas those of other common metals such as iron (Fe) as well as precious metals would tend to increase in EoL TV sets in 2015–2030. The results of this study provide a quantitative basis for helping
Energy Technology Data Exchange (ETDEWEB)
Habuer,, E-mail: habuer@env.t.u-tokyo.ac.jp; Nakatani, Jun; Moriguchi, Yuichi
2014-02-15
Highlights: • We estimate the possession and obsolescence of household appliances (HAs) in China. • Over 4.8–5.1 billion units of major HAs will be discarded in the next 20 years. • We calculate the amounts of substances contained in end-of-life (EoL) TV sets. • Less common metals will tend to decrease in content in generation of EoL TV sets. • Precious metals will tend to increase in content in EoL TV sets in 2015–2030. - Abstract: Given the amounts of end-of-life electrical and electronic equipment (EoL-EEE) being generated and their contents of both harmful and valuable materials, the EoL-EEE issue should be regarded not only as an emerging environmental problem but also as a resource management strategy in China. At present, in order to provide the basis for managing EoL-EEE at both product and substance levels in China, it is necessary to carry out a quantitative analysis on EoL-EEE and to determine how much of it will be generated and how much materials and substances it contains. In this study, the possession and obsolescence amounts of five types of household appliance (HA) including television (TV) sets and the amounts of substances contained in EoL TV sets were estimated using time-series product flow analysis (PFA) and substance flow analysis (SFA). The results of PFA indicated that the total possession amounts of those five types of HAs will exceed 3.1 billion units in 2030, which will be two times higher than those in 2010. In addition, it was estimated that cumulatively over 4.8–5.1 billion units of these five types of EoL HA would be obsoleted between 2010–2030. The results of SFA on TV sets indicated that the generated amounts of most of the less common metals and a part of common metals such as copper (Cu) would tend to decrease, whereas those of other common metals such as iron (Fe) as well as precious metals would tend to increase in EoL TV sets in 2015–2030. The results of this study provide a quantitative basis for helping
CROSAT: A digital computer program for statistical-spectral analysis of two discrete time series
International Nuclear Information System (INIS)
Antonopoulos Domis, M.
1978-03-01
The program CROSAT computes directly from two discrete time series auto- and cross-spectra, transfer and coherence functions, using a Fast Fourier Transform subroutine. Statistical analysis of the time series is optional. While of general use the program is constructed to be immediately compatible with the ICL 4-70 and H316 computers at AEE Winfrith, and perhaps with minor modifications, with any other hardware system. (author)
Security analysis of electronic voting and online banking systems
Tjøstheim, Thomas
2007-01-01
The main focus of this dissertation is on security analysis of electronic voting and online banking systems. Six papers form the basis of the thesis and include the following topics: a model for analysis of voting systems, a case study where we apply the proposed model, a new scheme for remote electronic voting, and three case studies of commercial online banking solutions in Norway.
Electronic influences in the diffusion of hydrogen in the alloy series of palladium
International Nuclear Information System (INIS)
Buchold, H.; Sicking, G.; Wicke, E.
1976-01-01
The mobility of tritium in Pd-alloys with Ag, V and Ni has been investigated by time-lag measurements, where the β-radiation of the tritium decay was taken as measuring signal; this method allows the determination of internal concentration shifts without disturbance by inhibiting effects of interface transfer. It has been found, that small additions of the alloying components do not change the activation energy of tritium diffusion; higher concentrations of Ag and V, however, lead to steep rises of the activation energy, whereas the isoelectronic Ni as alloying partner does not influence the activation energy within the limits of experimental error. For interpretation of the results the activation energy of diffusion is divided into a basic contribution of the Pd host lattice and an additional electronic term. This term is closely connected with the VEC, and can be calculated from the screening potential of the impurity atoms. The basic part of the activation energy can approximately be identified with the energy of elastic strain of the Pd lattice brought about by the diffusion jump. (orig.) [de
An Interactive Analysis of Hyperboles in a British TV Series: Implications For EFL Classes
Sert, Olcay
2008-01-01
This paper, part of an ongoing study on the analysis of hyperboles in a British TV series, reports findings drawing upon a 90,000 word corpus. The findings are compared to the ones from CANCODE (McCarthy and Carter 2004), a five-million word corpus of spontaneous speech, in order to identify similarities between the two. The analysis showed that…
Analysis of emissions from prebunched electron beams
Directory of Open Access Journals (Sweden)
Jia Qika
2017-07-01
Full Text Available The emissions of the prebunched electron beam, including the coherent spontaneous emission and the self-amplified stimulated emission, are analyzed by using one-dimensional FEL theory. Neglecting the interaction of the electrons and the radiation field, the formula of the coherent spontaneous emission is given, the power of which is proportional to the square of the initial bunching factor and of the undulator length. For the general emission case of the prebunched electron beam, the evolution equation of the optical field is deducted. Then the analytical expression of the emission power is obtained for the resonant case; it is applicable to the regions from the low gain to the high gain. It is found that when the undulator length is shorter than four gain lengths, the emission is just the coherent spontaneous emission, and conversely, it is the self-amplified stimulated emission growing exponentially. For the nonresonant prebunched electron beam, the variations of the emission intensity with the detuning parameter for different interaction length are presented. The radiation field characters of the prebunched electron beam are discussed and compared with that of the seeded FEL amplifier.
Elkhatib, Tamer A.; Kachorovskiǐ, Valentin Yu; Stillman, William J.; Veksler, Dmitry B.; Salama, Khaled N.; Zhang, Xicheng; Shur, Michael S.
2010-01-01
We report on enhanced room-temperature detection of terahertz radiation by several connected field-effect transistors. For this enhanced nonresonant detection, we have designed, fabricated, and tested plasmonic structures consisting of multiple InGaAs/GaAs pseudomorphic high electron-mobility transistors connected in series. Results show a 1.63-THz response that is directly proportional to the number of detecting transistors biased by a direct drain current at the same gate-to-source bias voltages. The responsivity in the saturation regime was found to be 170 V/W with the noise equivalent power in the range of 10-7 W/Hz0.5. The experimental data are in agreement with the detection mechanism based on the rectification of overdamped plasma waves excited by terahertz radiation in the transistor channel. © 2010 IEEE.
Elkhatib, Tamer A.
2010-02-01
We report on enhanced room-temperature detection of terahertz radiation by several connected field-effect transistors. For this enhanced nonresonant detection, we have designed, fabricated, and tested plasmonic structures consisting of multiple InGaAs/GaAs pseudomorphic high electron-mobility transistors connected in series. Results show a 1.63-THz response that is directly proportional to the number of detecting transistors biased by a direct drain current at the same gate-to-source bias voltages. The responsivity in the saturation regime was found to be 170 V/W with the noise equivalent power in the range of 10-7 W/Hz0.5. The experimental data are in agreement with the detection mechanism based on the rectification of overdamped plasma waves excited by terahertz radiation in the transistor channel. © 2010 IEEE.
Isotope analysis in the transmission electron microscope.
Susi, Toma; Hofer, Christoph; Argentero, Giacomo; Leuthner, Gregor T; Pennycook, Timothy J; Mangler, Clemens; Meyer, Jannik C; Kotakoski, Jani
2016-10-10
The Ångström-sized probe of the scanning transmission electron microscope can visualize and collect spectra from single atoms. This can unambiguously resolve the chemical structure of materials, but not their isotopic composition. Here we differentiate between two isotopes of the same element by quantifying how likely the energetic imaging electrons are to eject atoms. First, we measure the displacement probability in graphene grown from either 12 C or 13 C and describe the process using a quantum mechanical model of lattice vibrations coupled with density functional theory simulations. We then test our spatial resolution in a mixed sample by ejecting individual atoms from nanoscale areas spanning an interface region that is far from atomically sharp, mapping the isotope concentration with a precision better than 20%. Although we use a scanning instrument, our method may be applicable to any atomic resolution transmission electron microscope and to other low-dimensional materials.
International Nuclear Information System (INIS)
Winkler, Hanspeter; Taylor, Kenneth A.
2006-01-01
An image alignment method for electron tomography is presented which is based on cross-correlation techniques and which includes a simultaneous refinement of the tilt geometry. A coarsely aligned tilt series is iteratively refined with a procedure consisting of two steps for each cycle: area matching and subsequent geometry correction. The first step, area matching, brings into register equivalent specimen regions in all images of the tilt series. It determines four parameters of a linear two-dimensional transformation, not just translation and rotation as is done during the preceding coarse alignment with conventional methods. The refinement procedure also differs from earlier methods in that the alignment references are now computed from already aligned images by reprojection of a backprojected volume. The second step, geometry correction, refines the initially inaccurate estimates of the geometrical parameters, including the direction of the tilt axis, a tilt angle offset, and the inclination of the specimen with respect to the support film or specimen holder. The correction values serve as an indicator for the progress of the refinement. For each new iteration, the correction values are used to compute an updated set of geometry parameters by a least squares fit. Model calculations show that it is essential to refine the geometrical parameters as well as the accurate alignment of the images to obtain a faithful map of the original structure
A Markovian Entropy Measure for the Analysis of Calcium Activity Time Series.
Marken, John P; Halleran, Andrew D; Rahman, Atiqur; Odorizzi, Laura; LeFew, Michael C; Golino, Caroline A; Kemper, Peter; Saha, Margaret S
2016-01-01
Methods to analyze the dynamics of calcium activity often rely on visually distinguishable features in time series data such as spikes, waves, or oscillations. However, systems such as the developing nervous system display a complex, irregular type of calcium activity which makes the use of such methods less appropriate. Instead, for such systems there exists a class of methods (including information theoretic, power spectral, and fractal analysis approaches) which use more fundamental properties of the time series to analyze the observed calcium dynamics. We present a new analysis method in this class, the Markovian Entropy measure, which is an easily implementable calcium time series analysis method which represents the observed calcium activity as a realization of a Markov Process and describes its dynamics in terms of the level of predictability underlying the transitions between the states of the process. We applied our and other commonly used calcium analysis methods on a dataset from Xenopus laevis neural progenitors which displays irregular calcium activity and a dataset from murine synaptic neurons which displays activity time series that are well-described by visually-distinguishable features. We find that the Markovian Entropy measure is able to distinguish between biologically distinct populations in both datasets, and that it can separate biologically distinct populations to a greater extent than other methods in the dataset exhibiting irregular calcium activity. These results support the benefit of using the Markovian Entropy measure to analyze calcium dynamics, particularly for studies using time series data which do not exhibit easily distinguishable features.
A Markovian Entropy Measure for the Analysis of Calcium Activity Time Series.
Directory of Open Access Journals (Sweden)
John P Marken
Full Text Available Methods to analyze the dynamics of calcium activity often rely on visually distinguishable features in time series data such as spikes, waves, or oscillations. However, systems such as the developing nervous system display a complex, irregular type of calcium activity which makes the use of such methods less appropriate. Instead, for such systems there exists a class of methods (including information theoretic, power spectral, and fractal analysis approaches which use more fundamental properties of the time series to analyze the observed calcium dynamics. We present a new analysis method in this class, the Markovian Entropy measure, which is an easily implementable calcium time series analysis method which represents the observed calcium activity as a realization of a Markov Process and describes its dynamics in terms of the level of predictability underlying the transitions between the states of the process. We applied our and other commonly used calcium analysis methods on a dataset from Xenopus laevis neural progenitors which displays irregular calcium activity and a dataset from murine synaptic neurons which displays activity time series that are well-described by visually-distinguishable features. We find that the Markovian Entropy measure is able to distinguish between biologically distinct populations in both datasets, and that it can separate biologically distinct populations to a greater extent than other methods in the dataset exhibiting irregular calcium activity. These results support the benefit of using the Markovian Entropy measure to analyze calcium dynamics, particularly for studies using time series data which do not exhibit easily distinguishable features.
Role of diffraction and electron analysis in the fast reactor programme
Energy Technology Data Exchange (ETDEWEB)
Ferguson, I. F. [ed.
1975-09-15
After first discussing irradiation damage, the whole range of new methods of probe analysis were reviewed with a special reference to the study of surfaces. Further papers discussed scanning auger microscopy and the nuclear microprobe. Current diffraction studies were then described on uranium dioxide and the neutron poisons: boron carbide and europia. Finally, new techniques were covered with special reference to the scanning electron microscope and the application of the Harwell 6000 series electronics to x-ray diffraction. Separate records were prepared for each paper covered.
Analysis on a electron gun for metal fusion
International Nuclear Information System (INIS)
Paes, A.C.J.; Galvao, R.M.O.; Boscolo, P.; Passaro, A.
1987-09-01
The characteristics of the electron beam of the HK-011600 Δ, electron gun for metal fusion at the 'Divisao de Materiais do Instituto de Pesquisa e Desenvolvimento do CTA (PMR/IPD/CTA)', is analyzed. In this analysis, the Pierce gun model and the SLAC computational code for electron optics are used. The electron beam R and Z profiles are obtained in the gun region and in the magnetic lenses region. The behaviour of the electron beam in the prism region is also discussed using a simple model. (author) [pt
ESTIMATING RELIABILITY OF DISTURBANCES IN SATELLITE TIME SERIES DATA BASED ON STATISTICAL ANALYSIS
Directory of Open Access Journals (Sweden)
Z.-G. Zhou
2016-06-01
Full Text Available Normally, the status of land cover is inherently dynamic and changing continuously on temporal scale. However, disturbances or abnormal changes of land cover — caused by such as forest fire, flood, deforestation, and plant diseases — occur worldwide at unknown times and locations. Timely detection and characterization of these disturbances is of importance for land cover monitoring. Recently, many time-series-analysis methods have been developed for near real-time or online disturbance detection, using satellite image time series. However, the detection results were only labelled with “Change/ No change” by most of the present methods, while few methods focus on estimating reliability (or confidence level of the detected disturbances in image time series. To this end, this paper propose a statistical analysis method for estimating reliability of disturbances in new available remote sensing image time series, through analysis of full temporal information laid in time series data. The method consists of three main steps. (1 Segmenting and modelling of historical time series data based on Breaks for Additive Seasonal and Trend (BFAST. (2 Forecasting and detecting disturbances in new time series data. (3 Estimating reliability of each detected disturbance using statistical analysis based on Confidence Interval (CI and Confidence Levels (CL. The method was validated by estimating reliability of disturbance regions caused by a recent severe flooding occurred around the border of Russia and China. Results demonstrated that the method can estimate reliability of disturbances detected in satellite image with estimation error less than 5% and overall accuracy up to 90%.
Suhaila, Jamaludin; Yusop, Zulkifli
2017-06-01
Most of the trend analysis that has been conducted has not considered the existence of a change point in the time series analysis. If these occurred, then the trend analysis will not be able to detect an obvious increasing or decreasing trend over certain parts of the time series. Furthermore, the lack of discussion on the possible factors that influenced either the decreasing or the increasing trend in the series needs to be addressed in any trend analysis. Hence, this study proposes to investigate the trends, and change point detection of mean, maximum and minimum temperature series, both annually and seasonally in Peninsular Malaysia and determine the possible factors that could contribute to the significance trends. In this study, Pettitt and sequential Mann-Kendall (SQ-MK) tests were used to examine the occurrence of any abrupt climate changes in the independent series. The analyses of the abrupt changes in temperature series suggested that most of the change points in Peninsular Malaysia were detected during the years 1996, 1997 and 1998. These detection points captured by Pettitt and SQ-MK tests are possibly related to climatic factors, such as El Niño and La Niña events. The findings also showed that the majority of the significant change points that exist in the series are related to the significant trend of the stations. Significant increasing trends of annual and seasonal mean, maximum and minimum temperatures in Peninsular Malaysia were found with a range of 2-5 °C/100 years during the last 32 years. It was observed that the magnitudes of the increasing trend in minimum temperatures were larger than the maximum temperatures for most of the studied stations, particularly at the urban stations. These increases are suspected to be linked with the effect of urban heat island other than El Niño event.
Electromagnetic Pulse Coupling Analysis of Electronic Equipment
Hong Lei; Qingying LI
2017-01-01
High-intensity nuclear explosion caused by high-altitude nuclear electromagnetic pulse through the antenna, metal cables, holes and other channels, coupled with very high energy into the electronic device, and cause serious threats. In this paper, the mechanism, waveform, coupling path and damage effect of nuclear electromagnetic pulse is analyzed, and the coupling mechanism of nuclear electromagnetic pulse is studied.
Multivariate stochastic analysis for Monthly hydrological time series at Cuyahoga River Basin
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
Energy dispersive X-ray analysis in the electron microscope
Bell, DC
2003-01-01
This book provides an in-depth description of x-ray microanalysis in the electron microscope. It is sufficiently detailed to ensure that novices will understand the nuances of high-quality EDX analysis. Includes information about hardware design as well as the physics of x-ray generation, absorption and detection, and most post-detection data processing. Details on electron optics and electron probe formation allow the novice to make sensible adjustments to the electron microscope in order to set up a system which optimises analysis. It also helps the reader determine which microanalytical me
International Nuclear Information System (INIS)
Oikawa, Tetsuo
1999-01-01
Properties and application of the imaging plate (IP) in transmission electron microscopy (TEM) are reviewed. TEM has the resolution level of around 0.2 nm, which enables direct observation of molecules and atoms. In TEM, there are such recording systems as photographic film, TV camera, slow-scan CCD camera and IP. IP, to the electron beam, has the higher sensitivity than the film and has the broad dynamic range. Linearity between the input beam intensity and output signal is good, which makes it possible to record the image even with the small electron dose. Signal/noise ratio and detective quantum efficiency are important factors for precise image analysis. Fading phenomenon is a defect of IP, which weakens the signal output as time passing. For instance of application, IP is used for imaging of AgBr crystal fragile to strong electron beam required for the film. IP is necessary for quantitative analysis of TEM images and for the recently developed energy-filter TEM. (K.H.)
Radhakrishnan, Srinivasan; Duvvuru, Arjun; Sultornsanee, Sivarit; Kamarthi, Sagar
2016-02-01
The cross correlation coefficient has been widely applied in financial time series analysis, in specific, for understanding chaotic behaviour in terms of stock price and index movements during crisis periods. To better understand time series correlation dynamics, the cross correlation matrices are represented as networks, in which a node stands for an individual time series and a link indicates cross correlation between a pair of nodes. These networks are converted into simpler trees using different schemes. In this context, Minimum Spanning Trees (MST) are the most favoured tree structures because of their ability to preserve all the nodes and thereby retain essential information imbued in the network. Although cross correlations underlying MSTs capture essential information, they do not faithfully capture dynamic behaviour embedded in the time series data of financial systems because cross correlation is a reliable measure only if the relationship between the time series is linear. To address the issue, this work investigates a new measure called phase synchronization (PS) for establishing correlations among different time series which relate to one another, linearly or nonlinearly. In this approach the strength of a link between a pair of time series (nodes) is determined by the level of phase synchronization between them. We compare the performance of phase synchronization based MST with cross correlation based MST along selected network measures across temporal frame that includes economically good and crisis periods. We observe agreement in the directionality of the results across these two methods. They show similar trends, upward or downward, when comparing selected network measures. Though both the methods give similar trends, the phase synchronization based MST is a more reliable representation of the dynamic behaviour of financial systems than the cross correlation based MST because of the former's ability to quantify nonlinear relationships among time
International Nuclear Information System (INIS)
Franke, B.C.; Kensek, R.P.; Prinja, A.K.
2013-01-01
Stochastic-media simulations require numerous boundary crossings. We consider two Monte Carlo electron transport approaches and evaluate accuracy with numerous material boundaries. In the condensed-history method, approximations are made based on infinite-medium solutions for multiple scattering over some track length. Typically, further approximations are employed for material-boundary crossings where infinite-medium solutions become invalid. We have previously explored an alternative 'condensed transport' formulation, a Generalized Boltzmann-Fokker-Planck (GBFP) method, which requires no special boundary treatment but instead uses approximations to the electron-scattering cross sections. Some limited capabilities for analog transport and a GBFP method have been implemented in the Integrated Tiger Series (ITS) codes. Improvements have been made to the condensed history algorithm. The performance of the ITS condensed-history and condensed-transport algorithms are assessed for material-boundary crossings. These assessments are made both by introducing artificial material boundaries and by comparison to analog Monte Carlo simulations. (authors)
Timing analysis of two-electron photoemission
International Nuclear Information System (INIS)
Kheifets, A S; Ivanov, I A; Bray, Igor
2011-01-01
We predict a significant delay of two-electron photoemission from the helium atom after absorption of an attosecond XUV pulse. We establish this delay by solving the time-dependent Schroedinger equation and by subsequently tracing the field-free evolution of the two-electron wave packet. This delay can also be related to the energy derivative of the phase of the complex double-photoionization (DPI) amplitude which we evaluate by using the convergent close-coupling method. Our observations indicate that future attosecond time delay measurements on DPI of He can provide information on the absolute quantum phase and elucidate various mechanisms of this strongly correlated ionization process. (fast track communication)
Methods of Analysis of Electronic Money in Banks
Directory of Open Access Journals (Sweden)
Melnychenko Oleksandr V.
2014-03-01
Full Text Available The article identifies methods of analysis of electronic money, formalises its instruments and offers an integral indicator, which should be calculated by issuing banks and those banks, which carry out operations with electronic money, issued by other banks. Calculation of the integral indicator would allow complex assessment of activity of the studied bank with electronic money and would allow comparison of parameters of different banks by the aggregate of indicators for the study of the electronic money market, its level of development, etc. The article presents methods which envisage economic analysis of electronic money in banks by the following directions: solvency and liquidity, efficiency of electronic money issue, business activity of the bank and social responsibility. Moreover, the proposed indicators by each of the directions are offered to be taken into account when building integral indicators, with the help of which banks are studied: business activity, profitability, solvency, liquidity and so on.
Silicon radiation detector analysis using back electron beam induced current
International Nuclear Information System (INIS)
Guye, R.
1987-01-01
A new technique for the observation and analysis of defects in silicon radiation detectors is described. This method uses an electron beam from a scanning electron microscope (SEM) impinging on the rear side of the p + n junction of the silicon detector, which itself is active and detects the electron beam induced current (EBIC). It is shown that this current is a sensitive probe of localized trapping centers, either at the junction surface or somewhere in the volume of the silicon crystal. (orig.)
Time Series Data Analysis of Wireless Sensor Network Measurements of Temperature.
Bhandari, Siddhartha; Bergmann, Neil; Jurdak, Raja; Kusy, Branislav
2017-05-26
Wireless sensor networks have gained significant traction in environmental signal monitoring and analysis. The cost or lifetime of the system typically depends on the frequency at which environmental phenomena are monitored. If sampling rates are reduced, energy is saved. Using empirical datasets collected from environmental monitoring sensor networks, this work performs time series analyses of measured temperature time series. Unlike previous works which have concentrated on suppressing the transmission of some data samples by time-series analysis but still maintaining high sampling rates, this work investigates reducing the sampling rate (and sensor wake up rate) and looks at the effects on accuracy. Results show that the sampling period of the sensor can be increased up to one hour while still allowing intermediate and future states to be estimated with interpolation RMSE less than 0.2 °C and forecasting RMSE less than 1 °C.
Gavrishchaka, Valeriy; Senyukova, Olga; Davis, Kristina
2015-01-01
Previously, we have proposed to use complementary complexity measures discovered by boosting-like ensemble learning for the enhancement of quantitative indicators dealing with necessarily short physiological time series. We have confirmed robustness of such multi-complexity measures for heart rate variability analysis with the emphasis on detection of emerging and intermittent cardiac abnormalities. Recently, we presented preliminary results suggesting that such ensemble-based approach could be also effective in discovering universal meta-indicators for early detection and convenient monitoring of neurological abnormalities using gait time series. Here, we argue and demonstrate that these multi-complexity ensemble measures for gait time series analysis could have significantly wider application scope ranging from diagnostics and early detection of physiological regime change to gait-based biometrics applications.
Directory of Open Access Journals (Sweden)
T.E. Danova
2016-06-01
Full Text Available The results of the investigations of a transformed series of reconstructed air temperature data for the central part of Greenland with an increment of 30 years have been presented. Stationarization of a ~ 50,000-years’ series of the reconstructed air temperature in the central part of Greenland according to ice core data has been performed using mathematical expectation. To obtain mathematical expectation estimation, the smoothing procedure by the methods of moving average and wavelet analysis has been carried out. Fourier’s transformation has been applied repeatedly to the stationarized series with changing the averaging time in the process of smoothing. Three averaging time values have been selected for the investigations: ~ 400–500 years, ~ 2,000 years, and ~ 4,000 years. Stationarization of the reconstructed temperature series with the help of wavelet transformation showed the best results when applying the averaging time of ~ 400 and ~ 2000 years, the trends well characterize the initial temperature series, there-by revealing the main patterns of its dynamics. Using the period with the averaging time of ~ 4,000 years showed the worst result: significant events of the main temperature series were lost in the process of averaging. The obtained results well correspond to cycling known to be inherent to the climatic system of the planet; the detected modes of 1,470 ± 500 years are comparable to the Dansgaard–Oeschger and Bond oscillations.
Properties of Asymmetric Detrended Fluctuation Analysis in the time series of RR intervals
Piskorski, J.; Kosmider, M.; Mieszkowski, D.; Krauze, T.; Wykretowicz, A.; Guzik, P.
2018-02-01
Heart rate asymmetry is a phenomenon by which the accelerations and decelerations of heart rate behave differently, and this difference is consistent and unidirectional, i.e. in most of the analyzed recordings the inequalities have the same directions. So far, it has been established for variance and runs based types of descriptors of RR intervals time series. In this paper we apply the newly developed method of Asymmetric Detrended Fluctuation Analysis, which so far has mainly been used with economic time series, to the set of 420 stationary 30 min time series of RR intervals from young, healthy individuals aged between 20 and 40. This asymmetric approach introduces separate scaling exponents for rising and falling trends. We systematically study the presence of asymmetry in both global and local versions of this method. In this study global means "applying to the whole time series" and local means "applying to windows jumping along the recording". It is found that the correlation structure of the fluctuations left over after detrending in physiological time series shows strong asymmetric features in both magnitude, with α+ physiological data after shuffling or with a group of symmetric synthetic time series.
The application of complex network time series analysis in turbulent heated jets
International Nuclear Information System (INIS)
Charakopoulos, A. K.; Karakasidis, T. E.; Liakopoulos, A.; Papanicolaou, P. N.
2014-01-01
In the present study, we applied the methodology of the complex network-based time series analysis to experimental temperature time series from a vertical turbulent heated jet. More specifically, we approach the hydrodynamic problem of discriminating time series corresponding to various regions relative to the jet axis, i.e., time series corresponding to regions that are close to the jet axis from time series originating at regions with a different dynamical regime based on the constructed network properties. Applying the transformation phase space method (k nearest neighbors) and also the visibility algorithm, we transformed time series into networks and evaluated the topological properties of the networks such as degree distribution, average path length, diameter, modularity, and clustering coefficient. The results show that the complex network approach allows distinguishing, identifying, and exploring in detail various dynamical regions of the jet flow, and associate it to the corresponding physical behavior. In addition, in order to reject the hypothesis that the studied networks originate from a stochastic process, we generated random network and we compared their statistical properties with that originating from the experimental data. As far as the efficiency of the two methods for network construction is concerned, we conclude that both methodologies lead to network properties that present almost the same qualitative behavior and allow us to reveal the underlying system dynamics
Xiong, Lihua; Jiang, Cong; Du, Tao
2014-01-01
Time-varying moments models based on Pearson Type III and normal distributions respectively are built under the generalized additive model in location, scale and shape (GAMLSS) framework to analyze the nonstationarity of the annual runoff series of the Weihe River, the largest tributary of the Yellow River. The detection of nonstationarities in hydrological time series (annual runoff, precipitation and temperature) from 1960 to 2009 is carried out using a GAMLSS model, and then the covariate analysis for the annual runoff series is implemented with GAMLSS. Finally, the attribution of each covariate to the nonstationarity of annual runoff is analyzed quantitatively. The results demonstrate that (1) obvious change-points exist in all three hydrological series, (2) precipitation, temperature and irrigated area are all significant covariates of the annual runoff series, and (3) temperature increase plays the main role in leading to the reduction of the annual runoff series in the study basin, followed by the decrease of precipitation and the increase of irrigated area.
International Nuclear Information System (INIS)
Bordenave-Montesquieu, A; Moretto-Capelle, P; Bordenave-Montesquieu, D
2003-01-01
A complete and accurate experimental test of theoretical spectroscopic data sets (state positions, lifetimes) available for the n=3-5 terms of the 1s 2 3lnl' Rydberg series of oxygen and neon ions is presented in a series of two papers. This result was achieved by fitting our high-resolution electron spectra with post-collisional lineshapes calculated with the help of these spectroscopic data. In this second paper we apply the fitting procedure described in the preceding companion paper (I) to the analysis of high-resolution electron spectra measured in O 6+ (1s 2 ) + He, H 2 and Ne 8+ (1s 2 ) + He collisional systems at 10 qkeV collision energy (q is the ion charge). Singlet states alone are found to be excited in oxygen; they also explain most of the neon lines; in the latter case a possible contribution of triplet states is discussed. Many 1s 2 3lnl' 1 L transitions are identified for the first time. A quantitative comparison between measured and calculated positions clearly points to the best theoretical data currently available. Finally, a first identification of some 4l4l' 1 L transitions observed in the neon spectrum is also proposed. From this huge spectroscopic work, we extract the first experimental partial branching ratios for autoionization into the 1s 2 2l ionization continua for a large number of 1s 2 3lnl' 1 L states, which are compared with the total ones calculated by other authors; we deduce that populations of |M L vertical bar = 0 and 1 magnetic sublevels are nearly identical. The double-capture process is also briefly characterized by comparing relative populations of many n=3-5 states; it is found that the same states are populated in O 6+ +H 2 and Ne 8+ +He collisional systems with the same relative populations
On statistical inference in time series analysis of the evolution of road safety.
Commandeur, Jacques J F; Bijleveld, Frits D; Bergel-Hayat, Ruth; Antoniou, Constantinos; Yannis, George; Papadimitriou, Eleonora
2013-11-01
Data collected for building a road safety observatory usually include observations made sequentially through time. Examples of such data, called time series data, include annual (or monthly) number of road traffic accidents, traffic fatalities or vehicle kilometers driven in a country, as well as the corresponding values of safety performance indicators (e.g., data on speeding, seat belt use, alcohol use, etc.). Some commonly used statistical techniques imply assumptions that are often violated by the special properties of time series data, namely serial dependency among disturbances associated with the observations. The first objective of this paper is to demonstrate the impact of such violations to the applicability of standard methods of statistical inference, which leads to an under or overestimation of the standard error and consequently may produce erroneous inferences. Moreover, having established the adverse consequences of ignoring serial dependency issues, the paper aims to describe rigorous statistical techniques used to overcome them. In particular, appropriate time series analysis techniques of varying complexity are employed to describe the development over time, relating the accident-occurrences to explanatory factors such as exposure measures or safety performance indicators, and forecasting the development into the near future. Traditional regression models (whether they are linear, generalized linear or nonlinear) are shown not to naturally capture the inherent dependencies in time series data. Dedicated time series analysis techniques, such as the ARMA-type and DRAG approaches are discussed next, followed by structural time series models, which are a subclass of state space methods. The paper concludes with general recommendations and practice guidelines for the use of time series models in road safety research. Copyright © 2012 Elsevier Ltd. All rights reserved.
A Filtering of Incomplete GNSS Position Time Series with Probabilistic Principal Component Analysis
Gruszczynski, Maciej; Klos, Anna; Bogusz, Janusz
2018-04-01
For the first time, we introduced the probabilistic principal component analysis (pPCA) regarding the spatio-temporal filtering of Global Navigation Satellite System (GNSS) position time series to estimate and remove Common Mode Error (CME) without the interpolation of missing values. We used data from the International GNSS Service (IGS) stations which contributed to the latest International Terrestrial Reference Frame (ITRF2014). The efficiency of the proposed algorithm was tested on the simulated incomplete time series, then CME was estimated for a set of 25 stations located in Central Europe. The newly applied pPCA was compared with previously used algorithms, which showed that this method is capable of resolving the problem of proper spatio-temporal filtering of GNSS time series characterized by different observation time span. We showed, that filtering can be carried out with pPCA method when there exist two time series in the dataset having less than 100 common epoch of observations. The 1st Principal Component (PC) explained more than 36% of the total variance represented by time series residuals' (series with deterministic model removed), what compared to the other PCs variances (less than 8%) means that common signals are significant in GNSS residuals. A clear improvement in the spectral indices of the power-law noise was noticed for the Up component, which is reflected by an average shift towards white noise from - 0.98 to - 0.67 (30%). We observed a significant average reduction in the accuracy of stations' velocity estimated for filtered residuals by 35, 28 and 69% for the North, East, and Up components, respectively. CME series were also subjected to analysis in the context of environmental mass loading influences of the filtering results. Subtraction of the environmental loading models from GNSS residuals provides to reduction of the estimated CME variance by 20 and 65% for horizontal and vertical components, respectively.
Hayashi, Hideaki; Shibanoki, Taro; Shima, Keisuke; Kurita, Yuichi; Tsuji, Toshio
2015-12-01
This paper proposes a probabilistic neural network (NN) developed on the basis of time-series discriminant component analysis (TSDCA) that can be used to classify high-dimensional time-series patterns. TSDCA involves the compression of high-dimensional time series into a lower dimensional space using a set of orthogonal transformations and the calculation of posterior probabilities based on a continuous-density hidden Markov model with a Gaussian mixture model expressed in the reduced-dimensional space. The analysis can be incorporated into an NN, which is named a time-series discriminant component network (TSDCN), so that parameters of dimensionality reduction and classification can be obtained simultaneously as network coefficients according to a backpropagation through time-based learning algorithm with the Lagrange multiplier method. The TSDCN is considered to enable high-accuracy classification of high-dimensional time-series patterns and to reduce the computation time taken for network training. The validity of the TSDCN is demonstrated for high-dimensional artificial data and electroencephalogram signals in the experiments conducted during the study.
International Nuclear Information System (INIS)
Jafri, Y.Z.; Kamal, L.
2007-01-01
Various statistical techniques was used on five-year data from 1998-2002 of average humidity, rainfall, maximum and minimum temperatures, respectively. The relationships to regression analysis time series (RATS) were developed for determining the overall trend of these climate parameters on the basis of which forecast models can be corrected and modified. We computed the coefficient of determination as a measure of goodness of fit, to our polynomial regression analysis time series (PRATS). The correlation to multiple linear regression (MLR) and multiple linear regression analysis time series (MLRATS) were also developed for deciphering the interdependence of weather parameters. Spearman's rand correlation and Goldfeld-Quandt test were used to check the uniformity or non-uniformity of variances in our fit to polynomial regression (PR). The Breusch-Pagan test was applied to MLR and MLRATS, respectively which yielded homoscedasticity. We also employed Bartlett's test for homogeneity of variances on a five-year data of rainfall and humidity, respectively which showed that the variances in rainfall data were not homogenous while in case of humidity, were homogenous. Our results on regression and regression analysis time series show the best fit to prediction modeling on climatic data of Quetta, Pakistan. (author)
Bayesian near-boundary analysis in basic macroeconomic time series models
M.D. de Pooter (Michiel); F. Ravazzolo (Francesco); R. Segers (René); H.K. van Dijk (Herman)
2008-01-01
textabstractSeveral lessons learnt from a Bayesian analysis of basic macroeconomic time series models are presented for the situation where some model parameters have substantial posterior probability near the boundary of the parameter region. This feature refers to near-instability within dynamic
A Comparison of Missing-Data Procedures for Arima Time-Series Analysis
Velicer, Wayne F.; Colby, Suzanne M.
2005-01-01
Missing data are a common practical problem for longitudinal designs. Time-series analysis is a longitudinal method that involves a large number of observations on a single unit. Four different missing-data methods (deletion, mean substitution, mean of adjacent observations, and maximum likelihood estimation) were evaluated. Computer-generated…
DEFF Research Database (Denmark)
Nasri, Amin; Eriksson, Robert; Ghandhar, Mehrdad
2014-01-01
This paper proposes an approach based on trajectory sensitivity analysis (TSA) to find most suitable placement of series compensators in the power system. The main objective is to maximize the benefit of these devices in order to enhance the rotor angle stability. This approach is formulated...
Qian, Xi-Yuan; Liu, Ya-Min; Jiang, Zhi-Qiang; Podobnik, Boris; Zhou, Wei-Xing; Stanley, H. Eugene
2015-06-01
When common factors strongly influence two power-law cross-correlated time series recorded in complex natural or social systems, using detrended cross-correlation analysis (DCCA) without considering these common factors will bias the results. We use detrended partial cross-correlation analysis (DPXA) to uncover the intrinsic power-law cross correlations between two simultaneously recorded time series in the presence of nonstationarity after removing the effects of other time series acting as common forces. The DPXA method is a generalization of the detrended cross-correlation analysis that takes into account partial correlation analysis. We demonstrate the method by using bivariate fractional Brownian motions contaminated with a fractional Brownian motion. We find that the DPXA is able to recover the analytical cross Hurst indices, and thus the multiscale DPXA coefficients are a viable alternative to the conventional cross-correlation coefficient. We demonstrate the advantage of the DPXA coefficients over the DCCA coefficients by analyzing contaminated bivariate fractional Brownian motions. We calculate the DPXA coefficients and use them to extract the intrinsic cross correlation between crude oil and gold futures by taking into consideration the impact of the U.S. dollar index. We develop the multifractal DPXA (MF-DPXA) method in order to generalize the DPXA method and investigate multifractal time series. We analyze multifractal binomial measures masked with strong white noises and find that the MF-DPXA method quantifies the hidden multifractal nature while the multifractal DCCA method fails.
Directory of Open Access Journals (Sweden)
Peter Dzurko
2007-01-01
Full Text Available Operation states analysis of a series-parallel converter working above resonance frequency is described in the paper. Principal equations are derived for individual operation states. On the basis of them the diagrams are made out. The diagrams give the complex image of the converter behaviour for individual circuit parameters. The waveforms may be utilised at designing the inverter individual parts.
Haddock, Shelley A.; MacPhee, David; Zimmerman, Toni Schindler
2001-01-01
Content analysis of 23 American Association for Marriage and Family Therapy Master Series tapes was used to determine how well feminist behaviors have been incorporated into ideal family therapy practice. Feminist behaviors were infrequent, being evident in fewer than 3% of time blocks in event sampling and 10 of 39 feminist behaviors of the…
Molenaar, P.C.M.
1987-01-01
Outlines a frequency domain analysis of the dynamic factor model and proposes a solution to the problem of constructing a causal filter of lagged factor loadings. The method is illustrated with applications to simulated and real multivariate time series. The latter applications involve topographic
Harmonic analysis of dense time series of landsat imagery for modeling change in forest conditions
Barry Tyler. Wilson
2015-01-01
This study examined the utility of dense time series of Landsat imagery for small area estimation and mapping of change in forest conditions over time. The study area was a region in north central Wisconsin for which Landsat 7 ETM+ imagery and field measurements from the Forest Inventory and Analysis program are available for the decade of 2003 to 2012. For the periods...
Economic Conditions and the Divorce Rate: A Time-Series Analysis of the Postwar United States.
South, Scott J.
1985-01-01
Challenges the belief that the divorce rate rises during prosperity and falls during economic recessions. Time-series regression analysis of postwar United States reveals small but positive effects of unemployment on divorce rate. Stronger influences on divorce rates are changes in age structure and labor-force participation rate of women.…
Operation Analysis of the Series-Parallel Resonant Converter Working above Resonance Frequency
Directory of Open Access Journals (Sweden)
Peter Dzurko
2006-01-01
Full Text Available The present article deals with theoretical analysis of operation of a series-parallel converter working above resonance frequency. Derived are principal equations for individual operation intervals. Based on these made out are waveforms of individual quantities during both the inverter operation at load and no-load operation. The waveforms may be utilised at designing the inverter individual parts.
Analysis of an array of piezoelectric energy harvesters connected in series
International Nuclear Information System (INIS)
Lin, H C; Wu, P H; Lien, I C; Shu, Y C
2013-01-01
This paper investigates the electrical response of a series connection of piezoelectric energy harvesters (PEHs) attached to various interface electronics, including standard and parallel-/series-SSHI (synchronized switch harvesting on inductor) circuits. In contrast to the case of parallel connection of multiple oscillators, the system response is determined by the matrix formulation of charging on a capacitance. In addition, the adoption of an equivalent impedance approach shows that the capacitance matrix can be explicitly expressed in terms of the relevant load impedance. A model problem is proposed for performance evaluation of harvested power under different choices of interface circuits. The result demonstrates that the parallel-SSHI array system exhibits higher power output with moderate bandwidth improvement, while the series-SSHI system delivers a pronounced wideband at the cost of peak harvested power. The standard array system shows a mild ability in power harvesting between these two SSHI systems. Finally, comparisons between the series and parallel connection of oscillators are made, showing the striking contrast of these two cases. (paper)
Electron microprobe analysis of tantalum--nitride thin films
International Nuclear Information System (INIS)
Stoltz, D.L.; Starkey, J.P.
1979-06-01
Quantitative chemical analysis of 500- and 2000-angstrom tantalum--nitride films on glass substrates has been accomplished using an electron microprobe x-ray analyzer. In order to achieve this analysis, modifications to the microprobe were necessary. A description of the calibration procedure, the method of analysis, and the quantitative results are discussed
Donges, Jonathan; Heitzig, Jobst; Beronov, Boyan; Wiedermann, Marc; Runge, Jakob; Feng, Qing Yi; Tupikina, Liubov; Stolbova, Veronika; Donner, Reik; Marwan, Norbert; Dijkstra, Henk; Kurths, Jürgen
2016-04-01
We introduce the pyunicorn (Pythonic unified complex network and recurrence analysis toolbox) open source software package for applying and combining modern methods of data analysis and modeling from complex network theory and nonlinear time series analysis. pyunicorn is a fully object-oriented and easily parallelizable package written in the language Python. It allows for the construction of functional networks such as climate networks in climatology or functional brain networks in neuroscience representing the structure of statistical interrelationships in large data sets of time series and, subsequently, investigating this structure using advanced methods of complex network theory such as measures and models for spatial networks, networks of interacting networks, node-weighted statistics, or network surrogates. Additionally, pyunicorn provides insights into the nonlinear dynamics of complex systems as recorded in uni- and multivariate time series from a non-traditional perspective by means of recurrence quantification analysis, recurrence networks, visibility graphs, and construction of surrogate time series. The range of possible applications of the library is outlined, drawing on several examples mainly from the field of climatology. pyunicorn is available online at https://github.com/pik-copan/pyunicorn. Reference: J.F. Donges, J. Heitzig, B. Beronov, M. Wiedermann, J. Runge, Q.-Y. Feng, L. Tupikina, V. Stolbova, R.V. Donner, N. Marwan, H.A. Dijkstra, and J. Kurths, Unified functional network and nonlinear time series analysis for complex systems science: The pyunicorn package, Chaos 25, 113101 (2015), DOI: 10.1063/1.4934554, Preprint: arxiv.org:1507.01571 [physics.data-an].
Time Series Imputation via L1 Norm-Based Singular Spectrum Analysis
Kalantari, Mahdi; Yarmohammadi, Masoud; Hassani, Hossein; Silva, Emmanuel Sirimal
Missing values in time series data is a well-known and important problem which many researchers have studied extensively in various fields. In this paper, a new nonparametric approach for missing value imputation in time series is proposed. The main novelty of this research is applying the L1 norm-based version of Singular Spectrum Analysis (SSA), namely L1-SSA which is robust against outliers. The performance of the new imputation method has been compared with many other established methods. The comparison is done by applying them to various real and simulated time series. The obtained results confirm that the SSA-based methods, especially L1-SSA can provide better imputation in comparison to other methods.
Analysis of Land Subsidence Monitoring in Mining Area with Time-Series Insar Technology
Sun, N.; Wang, Y. J.
2018-04-01
Time-series InSAR technology has become a popular land subsidence monitoring method in recent years, because of its advantages such as high accuracy, wide area, low expenditure, intensive monitoring points and free from accessibility restrictions. In this paper, we applied two kinds of satellite data, ALOS PALSAR and RADARSAT-2, to get the subsidence monitoring results of the study area in two time periods by time-series InSAR technology. By analyzing the deformation range, rate and amount, the time-series analysis of land subsidence in mining area was realized. The results show that InSAR technology could be used to monitor land subsidence in large area and meet the demand of subsidence monitoring in mining area.
Dauguet, Julien; Bock, Davi; Reid, R Clay; Warfield, Simon K
2007-01-01
3D reconstruction from serial 2D microscopy images depends on non-linear alignment of serial sections. For some structures, such as the neuronal circuitry of the brain, very large images at very high resolution are necessary to permit reconstruction. These very large images prevent the direct use of classical registration methods. We propose in this work a method to deal with the non-linear alignment of arbitrarily large 2D images using the finite support properties of cubic B-splines. After initial affine alignment, each large image is split into a grid of smaller overlapping sub-images, which are individually registered using cubic B-splines transformations. Inside the overlapping regions between neighboring sub-images, the coefficients of the knots controlling the B-splines deformations are blended, to create a virtual large grid of knots for the whole image. The sub-images are resampled individually, using the new coefficients, and assembled together into a final large aligned image. We evaluated the method on a series of large transmission electron microscopy images and our results indicate significant improvements compared to both manual and affine alignment.
Korantzopoulos, Panagiotis; Plakoutsi, Sofia; Florou, Elizabeth; Bechlioulis, Aris
2018-05-21
The early and correct diagnosis of cardiac implantable electronic device (CIED) infections is critical given that early aggressive treatment with complete removal of the system along with antimicrobial therapy dramatically improves outcomes. Pocket infection manifested by local signs of inflammation is the most common form of CIED infections. Conditions mimicking pocket infection have been described in the literature. These include various types of malignancy and rarely allergic reactions/contact dermatitis to pacemaker compounds. We aimed to describe skin lesions and disorders over the pocket area that mimic CIED infection. We present a series of 5 cases with skin lesions that mimic pocket infection. We document these cases with corresponding photographs. Most of them have not been described in this setting. We report the following cases of conditions that proved not to be CIED infection: One case of superficial cellulitis, one case of herpes zoster over the pocket area, one case of spontaneous bruising over the pocket a long time after implantation in a patient taking oral anticoagulation, and 2 cases of contact dermatitis due to prolonged postoperative application of povidone iodine. All cases had favorable outcome after conservative treatment and no CIED infection was developed during follow-up. Clinicians should be aware of rare conditions that mimic CIED infection. Incorrect diagnosis of these disorders may falsely lead to CIED extraction. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.
Sensitivity analysis of machine-learning models of hydrologic time series
O'Reilly, A. M.
2017-12-01
Sensitivity analysis traditionally has been applied to assessing model response to perturbations in model parameters, where the parameters are those model input variables adjusted during calibration. Unlike physics-based models where parameters represent real phenomena, the equivalent of parameters for machine-learning models are simply mathematical "knobs" that are automatically adjusted during training/testing/verification procedures. Thus the challenge of extracting knowledge of hydrologic system functionality from machine-learning models lies in their very nature, leading to the label "black box." Sensitivity analysis of the forcing-response behavior of machine-learning models, however, can provide understanding of how the physical phenomena represented by model inputs affect the physical phenomena represented by model outputs.As part of a previous study, hybrid spectral-decomposition artificial neural network (ANN) models were developed to simulate the observed behavior of hydrologic response contained in multidecadal datasets of lake water level, groundwater level, and spring flow. Model inputs used moving window averages (MWA) to represent various frequencies and frequency-band components of time series of rainfall and groundwater use. Using these forcing time series, the MWA-ANN models were trained to predict time series of lake water level, groundwater level, and spring flow at 51 sites in central Florida, USA. A time series of sensitivities for each MWA-ANN model was produced by perturbing forcing time-series and computing the change in response time-series per unit change in perturbation. Variations in forcing-response sensitivities are evident between types (lake, groundwater level, or spring), spatially (among sites of the same type), and temporally. Two generally common characteristics among sites are more uniform sensitivities to rainfall over time and notable increases in sensitivities to groundwater usage during significant drought periods.
Application of the Allan Variance to Time Series Analysis in Astrometry and Geodesy: A Review.
Malkin, Zinovy
2016-04-01
The Allan variance (AVAR) was introduced 50 years ago as a statistical tool for assessing the frequency standards deviations. For the past decades, AVAR has increasingly been used in geodesy and astrometry to assess the noise characteristics in geodetic and astrometric time series. A specific feature of astrometric and geodetic measurements, as compared with clock measurements, is that they are generally associated with uncertainties; thus, an appropriate weighting should be applied during data analysis. In addition, some physically connected scalar time series naturally form series of multidimensional vectors. For example, three station coordinates time series X, Y, and Z can be combined to analyze 3-D station position variations. The classical AVAR is not intended for processing unevenly weighted and/or multidimensional data. Therefore, AVAR modifications, namely weighted AVAR (WAVAR), multidimensional AVAR (MAVAR), and weighted multidimensional AVAR (WMAVAR), were introduced to overcome these deficiencies. In this paper, a brief review is given of the experience of using AVAR and its modifications in processing astrogeodetic time series.
Social network analysis of character interaction in the Stargate and Star Trek television series
Tan, Melody Shi Ai; Ujum, Ephrance Abu; Ratnavelu, Kuru
This paper undertakes a social network analysis of two science fiction television series, Stargate and Star Trek. Television series convey stories in the form of character interaction, which can be represented as “character networks”. We connect each pair of characters that exchanged spoken dialogue in any given scene demarcated in the television series transcripts. These networks are then used to characterize the overall structure and topology of each series. We find that the character networks of both series have similar structure and topology to that found in previous work on mythological and fictional networks. The character networks exhibit the small-world effects but found no significant support for power-law. Since the progression of an episode depends to a large extent on the interaction between each of its characters, the underlying network structure tells us something about the complexity of that episode’s storyline. We assessed the complexity using techniques from spectral graph theory. We found that the episode networks are structured either as (1) closed networks, (2) those containing bottlenecks that connect otherwise disconnected clusters or (3) a mixture of both.
Nordemann, D. J. R.; Rigozo, N. R.; de Souza Echer, M. P.; Echer, E.
2008-11-01
We present here an implementation of a least squares iterative regression method applied to the sine functions embedded in the principal components extracted from geophysical time series. This method seems to represent a useful improvement for the non-stationary time series periodicity quantitative analysis. The principal components determination followed by the least squares iterative regression method was implemented in an algorithm written in the Scilab (2006) language. The main result of the method is to obtain the set of sine functions embedded in the series analyzed in decreasing order of significance, from the most important ones, likely to represent the physical processes involved in the generation of the series, to the less important ones that represent noise components. Taking into account the need of a deeper knowledge of the Sun's past history and its implication to global climate change, the method was applied to the Sunspot Number series (1750-2004). With the threshold and parameter values used here, the application of the method leads to a total of 441 explicit sine functions, among which 65 were considered as being significant and were used for a reconstruction that gave a normalized mean squared error of 0.146.
Jandoc, Racquel; Burden, Andrea M; Mamdani, Muhammad; Lévesque, Linda E; Cadarette, Suzanne M
2015-08-01
To describe the use and reporting of interrupted time series methods in drug utilization research. We completed a systematic search of MEDLINE, Web of Science, and reference lists to identify English language articles through to December 2013 that used interrupted time series methods in drug utilization research. We tabulated the number of studies by publication year and summarized methodological detail. We identified 220 eligible empirical applications since 1984. Only 17 (8%) were published before 2000, and 90 (41%) were published since 2010. Segmented regression was the most commonly applied interrupted time series method (67%). Most studies assessed drug policy changes (51%, n = 112); 22% (n = 48) examined the impact of new evidence, 18% (n = 39) examined safety advisories, and 16% (n = 35) examined quality improvement interventions. Autocorrelation was considered in 66% of studies, 31% reported adjusting for seasonality, and 15% accounted for nonstationarity. Use of interrupted time series methods in drug utilization research has increased, particularly in recent years. Despite methodological recommendations, there is large variation in reporting of analytic methods. Developing methodological and reporting standards for interrupted time series analysis is important to improve its application in drug utilization research, and we provide recommendations for consideration. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.
BiGGEsTS: integrated environment for biclustering analysis of time series gene expression data
Directory of Open Access Journals (Sweden)
Madeira Sara C
2009-07-01
Full Text Available Abstract Background The ability to monitor changes in expression patterns over time, and to observe the emergence of coherent temporal responses using expression time series, is critical to advance our understanding of complex biological processes. Biclustering has been recognized as an effective method for discovering local temporal expression patterns and unraveling potential regulatory mechanisms. The general biclustering problem is NP-hard. In the case of time series this problem is tractable, and efficient algorithms can be used. However, there is still a need for specialized applications able to take advantage of the temporal properties inherent to expression time series, both from a computational and a biological perspective. Findings BiGGEsTS makes available state-of-the-art biclustering algorithms for analyzing expression time series. Gene Ontology (GO annotations are used to assess the biological relevance of the biclusters. Methods for preprocessing expression time series and post-processing results are also included. The analysis is additionally supported by a visualization module capable of displaying informative representations of the data, including heatmaps, dendrograms, expression charts and graphs of enriched GO terms. Conclusion BiGGEsTS is a free open source graphical software tool for revealing local coexpression of genes in specific intervals of time, while integrating meaningful information on gene annotations. It is freely available at: http://kdbio.inesc-id.pt/software/biggests. We present a case study on the discovery of transcriptional regulatory modules in the response of Saccharomyces cerevisiae to heat stress.
Scanning transmission electron microscopy imaging and analysis
Pennycook, Stephen J
2011-01-01
Provides the first comprehensive treatment of the physics and applications of this mainstream technique for imaging and analysis at the atomic level Presents applications of STEM in condensed matter physics, materials science, catalysis, and nanoscience Suitable for graduate students learning microscopy, researchers wishing to utilize STEM, as well as for specialists in other areas of microscopy Edited and written by leading researchers and practitioners
Definition of distance for nonlinear time series analysis of marked point process data
Energy Technology Data Exchange (ETDEWEB)
Iwayama, Koji, E-mail: koji@sat.t.u-tokyo.ac.jp [Research Institute for Food and Agriculture, Ryukoku Univeristy, 1-5 Yokotani, Seta Oe-cho, Otsu-Shi, Shiga 520-2194 (Japan); Hirata, Yoshito; Aihara, Kazuyuki [Institute of Industrial Science, The University of Tokyo, 4-6-1 Komaba, Meguro-ku, Tokyo 153-8505 (Japan)
2017-01-30
Marked point process data are time series of discrete events accompanied with some values, such as economic trades, earthquakes, and lightnings. A distance for marked point process data allows us to apply nonlinear time series analysis to such data. We propose a distance for marked point process data which can be calculated much faster than the existing distance when the number of marks is small. Furthermore, under some assumptions, the Kullback–Leibler divergences between posterior distributions for neighbors defined by this distance are small. We performed some numerical simulations showing that analysis based on the proposed distance is effective. - Highlights: • A new distance for marked point process data is proposed. • The distance can be computed fast enough for a small number of marks. • The method to optimize parameter values of the distance is also proposed. • Numerical simulations indicate that the analysis based on the distance is effective.
Role of scanning electron microscope )SEM) in metal failure analysis
International Nuclear Information System (INIS)
Shaiful Rizam Shamsudin; Hafizal Yazid; Mohd Harun; Siti Selina Abd Hamid; Nadira Kamarudin; Zaiton Selamat; Mohd Shariff Sattar; Muhamad Jalil
2005-01-01
Scanning electron microscope (SEM) is a scientific instrument that uses a beam of highly energetic electrons to examine the surface and phase distribution of specimens on a micro scale through the live imaging of secondary electrons (SE) and back-scattered electrons (BSE) images. One of the main activities of SEM Laboratory at MINT is for failure analysis on metal part and components. The capability of SEM is excellent for determining the root cause of metal failures such as ductility or brittleness, stress corrosion, fatigue and other types of failures. Most of our customers that request for failure analysis are from local petrochemical plants, manufacturers of automotive components, pipeline maintenance personnel and engineers who involved in the development of metal parts and component. This paper intends to discuss some of the technical concepts in failure analysis associated with SEM. (Author)
Application of Time Series Analysis in Determination of Lag Time in Jahanbin Basin
Directory of Open Access Journals (Sweden)
Seied Yahya Mirzaee
2005-11-01
One of the important issues that have significant role in study of hydrology of basin is determination of lag time. Lag time has significant role in hydrological studies. Quantity of rainfall related lag time depends on several factors, such as permeability, vegetation cover, catchments slope, rainfall intensity, storm duration and type of rain. Determination of lag time is important parameter in many projects such as dam design and also water resource studies. Lag time of basin could be calculated using various methods. One of these methods is time series analysis of spectral density. The analysis is based on fouries series. The time series is approximated with Sinuous and Cosines functions. In this method harmonically significant quantities with individual frequencies are presented. Spectral density under multiple time series could be used to obtain basin lag time for annual runoff and short-term rainfall fluctuation. A long lag time could be due to snowmelt as well as melting ice due to rainfalls in freezing days. In this research the lag time of Jahanbin basin has been determined using spectral density method. The catchments is subjected to both rainfall and snowfall. For short term rainfall fluctuation with a return period 2, 3, 4 months, the lag times were found 0.18, 0.5 and 0.083 month, respectively.
Loredo, Thomas; Budavari, Tamas; Scargle, Jeffrey D.
2018-01-01
This presentation provides an overview of open-source software packages addressing two challenging classes of astrostatistics problems. (1) CUDAHM is a C++ framework for hierarchical Bayesian modeling of cosmic populations, leveraging graphics processing units (GPUs) to enable applying this computationally challenging paradigm to large datasets. CUDAHM is motivated by measurement error problems in astronomy, where density estimation and linear and nonlinear regression must be addressed for populations of thousands to millions of objects whose features are measured with possibly complex uncertainties, potentially including selection effects. An example calculation demonstrates accurate GPU-accelerated luminosity function estimation for simulated populations of $10^6$ objects in about two hours using a single NVIDIA Tesla K40c GPU. (2) Time Series Explorer (TSE) is a collection of software in Python and MATLAB for exploratory analysis and statistical modeling of astronomical time series. It comprises a library of stand-alone functions and classes, as well as an application environment for interactive exploration of times series data. The presentation will summarize key capabilities of this emerging project, including new algorithms for analysis of irregularly-sampled time series.
Márquez, G; Pinto, A; Alamo, L; Baumann, B; Ye, F; Winkler, H; Taylor, K; Padrón, R
2014-05-01
Myosin interacting-heads (MIH) motifs are visualized in 3D-reconstructions of thick filaments from striated muscle. These reconstructions are calculated by averaging methods using images from electron micrographs of grids prepared using numerous filament preparations. Here we propose an alternative method to calculate the 3D-reconstruction of a single thick filament using only a tilt series images recorded by electron tomography. Relaxed thick filaments, prepared from tarantula leg muscle homogenates, were negatively stained. Single-axis tilt series of single isolated thick filaments were obtained with the electron microscope at a low electron dose, and recorded on a CCD camera by electron tomography. An IHRSR 3D-recontruction was calculated from the tilt series images of a single thick filament. The reconstruction was enhanced by including in the search stage dual tilt image segments while only single tilt along the filament axis is usually used, as well as applying a band pass filter just before the back projection. The reconstruction from a single filament has a 40 Å resolution and clearly shows the presence of MIH motifs. In contrast, the electron tomogram 3D-reconstruction of the same thick filament - calculated without any image averaging and/or imposition of helical symmetry - only reveals MIH motifs infrequently. This is - to our knowledge - the first application of the IHRSR method to calculate a 3D reconstruction from tilt series images. This single filament IHRSR reconstruction method (SF-IHRSR) should provide a new tool to assess structural differences between well-ordered thick (or thin) filaments in a grid by recording separately their electron tomograms. Copyright © 2014 Elsevier Inc. All rights reserved.
Fractal time series analysis of postural stability in elderly and control subjects
Directory of Open Access Journals (Sweden)
Doussot Michel
2007-05-01
Full Text Available Abstract Background The study of balance using stabilogram analysis is of particular interest in the study of falls. Although simple statistical parameters derived from the stabilogram have been shown to predict risk of falls, such measures offer little insight into the underlying control mechanisms responsible for degradation in balance. In contrast, fractal and non-linear time-series analysis of stabilograms, such as estimations of the Hurst exponent (H, may provide information related to the underlying motor control strategies governing postural stability. In order to be adapted for a home-based follow-up of balance, such methods need to be robust, regardless of the experimental protocol, while producing time-series that are as short as possible. The present study compares two methods of calculating H: Detrended Fluctuation Analysis (DFA and Stabilogram Diffusion Analysis (SDA for elderly and control subjects, as well as evaluating the effect of recording duration. Methods Centre of pressure signals were obtained from 90 young adult subjects and 10 elderly subjects. Data were sampled at 100 Hz for 30 s, including stepping onto and off the force plate. Estimations of H were made using sliding windows of 10, 5, and 2.5 s durations, with windows slid forward in 1-s increments. Multivariate analysis of variance was used to test for the effect of time, age and estimation method on the Hurst exponent, while the intra-class correlation coefficient (ICC was used as a measure of reliability. Results Both SDA and DFA methods were able to identify differences in postural stability between control and elderly subjects for time series as short as 5 s, with ICC values as high as 0.75 for DFA. Conclusion Both methods would be well-suited to non-invasive longitudinal assessment of balance. In addition, reliable estimations of H were obtained from time series as short as 5 s.
A scanning electron microscope method for automated, quantitative analysis of mineral matter in coal
Energy Technology Data Exchange (ETDEWEB)
Creelman, R.A.; Ward, C.R. [R.A. Creelman and Associates, Epping, NSW (Australia)
1996-07-01
Quantitative mineralogical analysis has been carried out in a series of nine coal samples from Australia, South Africa and China using a newly-developed automated image analysis system coupled to a scanning electron microscopy. The image analysis system (QEM{asterisk}SEM) gathers X-ray spectra and backscattered electron data from a number of points on a conventional grain-mount polished section under the SEM, and interprets the data from each point in mineralogical terms. The cumulative data in each case was integrated to provide a volumetric modal analysis of the species present in the coal samples, expressed as percentages of the respective coals` mineral matter. Comparison was made of the QEM{asterisk}SEM results to data obtained from the same samples using other methods of quantitative mineralogical analysis, namely X-ray diffraction of the low-temperature oxygen-plasma ash and normative calculation from the (high-temperature) ash analysis and carbonate CO{sub 2} data. Good agreement was obtained from all three methods for quartz in the coals, and also for most of the iron-bearing minerals. The correlation between results from the different methods was less strong, however, for individual clay minerals, or for minerals such as calcite, dolomite and phosphate species that made up only relatively small proportions of the mineral matter. The image analysis approach, using the electron microscope for mineralogical studies, has significant potential as a supplement to optical microscopy in quantitative coal characterisation. 36 refs., 3 figs., 4 tabs.
Teaching Case: Analysis of an Electronic Voting System
Thompson, Nik; Toohey, Danny
2014-01-01
This teaching case discusses the analysis of an electronic voting system. The development of the case was motivated by research into information security and management, but as it includes procedural aspects, organizational structure and personnel, it is a suitable basis for all aspects of systems analysis, planning and design tasks. The material…
Economic analysis of evolution/devolution of electronic devices functionality
Directory of Open Access Journals (Sweden)
Esipov A. S.
2017-12-01
Full Text Available the researcher of this article has presented the analysis of evolution/devolution of electronic devices functionality as well as the analysis of the current situation at the computers and mobile devices market, and some thoughts about new products. Is a newer device better? Are corporations producing really new devices or they are only the improvement of old ones.
Adventures in Modern Time Series Analysis: From the Sun to the Crab Nebula and Beyond
Scargle, Jeffrey
2014-01-01
With the generation of long, precise, and finely sampled time series the Age of Digital Astronomy is uncovering and elucidating energetic dynamical processes throughout the Universe. Fulfilling these opportunities requires data effective analysis techniques rapidly and automatically implementing advanced concepts. The Time Series Explorer, under development in collaboration with Tom Loredo, provides tools ranging from simple but optimal histograms to time and frequency domain analysis for arbitrary data modes with any time sampling. Much of this development owes its existence to Joe Bredekamp and the encouragement he provided over several decades. Sample results for solar chromospheric activity, gamma-ray activity in the Crab Nebula, active galactic nuclei and gamma-ray bursts will be displayed.
Flood Frequency Analysis For Partial Duration Series In Ganjiang River Basin
zhangli, Sun; xiufang, Zhu; yaozhong, Pan
2016-04-01
Accurate estimation of flood frequency is key to effective, nationwide flood damage abatement programs. The partial duration series (PDS) method is widely used in hydrologic studies because it considers all events above a certain threshold level as compared to the annual maximum series (AMS) method, which considers only the annual maximum value. However, the PDS has a drawback in that it is difficult to define the thresholds and maintain an independent and identical distribution of the partial duration time series; this drawback is discussed in this paper. The Ganjiang River is the seventh largest tributary of the Yangtze River, the longest river in China. The Ganjiang River covers a drainage area of 81,258 km2 at the Wanzhou hydrologic station as the basin outlet. In this work, 56 years of daily flow data (1954-2009) from the Wanzhou station were used to analyze flood frequency, and the Pearson-III model was employed as the hydrologic probability distribution. Generally, three tasks were accomplished: (1) the threshold of PDS by percentile rank of daily runoff was obtained; (2) trend analysis of the flow series was conducted using PDS; and (3) flood frequency analysis was conducted for partial duration flow series. The results showed a slight upward trend of the annual runoff in the Ganjiang River basin. The maximum flow with a 0.01 exceedance probability (corresponding to a 100-year flood peak under stationary conditions) was 20,000 m3/s, while that with a 0.1 exceedance probability was 15,000 m3/s. These results will serve as a guide to hydrological engineering planning, design, and management for policymakers and decision makers associated with hydrology.
Time-series analysis of climatologic measurements: a method to distinguish future climatic changes
International Nuclear Information System (INIS)
Duband, D.
1992-01-01
Time-series analysis of climatic parameters as air temperature, rivers flow rate, lakes or seas level is an indispensable basis to detect a possible significant climatic change. These observations, when they are carefully analyzed and criticized, constitute the necessary reference for testing and validation numerical climatic models which try to simulate the physical and dynamical process of the ocean-atmosphere couple, taking continents into account. 32 refs., 13 figs
Chernobyl effects on domestic and inbound tourism in Sweden. A time series analysis
International Nuclear Information System (INIS)
Hultkrantz, L.; Olsson, C.
1997-01-01
This paper estimates the impact of the Chernobyl nuclear accident on domestic and international tourism in Sweden. From ARIMA time series forecasts, outlier search, and intervention analysis based on regional monthly accommodation data from 1978-1989, no effect on domestic tourism is found. However, there is an enduring deterrence effect on incoming tourism. The loss of gross revenue from incoming tourism because of the Chernobyl accident, is estimated to 2.5 billion SEK. 5 figs., 7 tabs., 1 appendix, 27 refs
On-line condition monitoring of nuclear systems via symbolic time series analysis
International Nuclear Information System (INIS)
Rajagopalan, V.; Ray, A.; Garcia, H. E.
2006-01-01
This paper provides a symbolic time series analysis approach to fault diagnostics and condition monitoring. The proposed technique is built upon concepts from wavelet theory, symbolic dynamics and pattern recognition. Various aspects of the methodology such as wavelet selection, choice of alphabet and determination of depth of D-Markov Machine are explained in the paper. The technique is validated with experiments performed in a Machine Condition Monitoring (MCM) test bed at the Idaho National Laboratory. (authors)
A Time Series Analysis to Asymmetric Marketing Competition Within a Market Structure
Francisco F. R. Ramos
1996-01-01
As a complementary to the existing studies of competitive market structure analysis, the present paper proposed a time series methodology to provide a more detailed picture of marketing competition in relation to competitive market structure. Two major hypotheses were tested as part of this project. First, it was found that some significant cross- lead and lag effects of marketing variables on sales between brands existed even between differents submarkets. second, it was found that high qual...
Time series analysis in road safety research uisng state space methods
BIJLEVELD, FD
2008-01-01
In this thesis we present a comprehensive study into novel time series models for aggregated road safety data. The models are mainly intended for analysis of indicators relevant to road safety, with a particular focus on how to measure these factors. Such developments may need to be related to or explained by external influences. It is also possible to make forecasts using the models. Relevant indicators include the number of persons killed permonth or year. These statistics are closely watch...
Chernobyl effects on domestic and inbound tourism in Sweden. A time series analysis
Energy Technology Data Exchange (ETDEWEB)
Hultkrantz, L. [Department of Economics, University of Uppsala, Uppsala (Sweden); Olsson, C. [Department of Economics, Umeaa University, Umeaa (Sweden)
1997-03-01
This paper estimates the impact of the Chernobyl nuclear accident on domestic and international tourism in Sweden. From ARIMA time series forecasts, outlier search, and intervention analysis based on regional monthly accommodation data from 1978-1989, no effect on domestic tourism is found. However, there is an enduring deterrence effect on incoming tourism. The loss of gross revenue from incoming tourism because of the Chernobyl accident, is estimated to 2.5 billion SEK. 5 figs., 7 tabs., 1 appendix, 27 refs.
Time Series Modeling of Army Mission Command Communication Networks: An Event-Driven Analysis
2013-06-01
Lehmann, D. R. (1984). How advertising affects sales: Meta- analysis of econometric results. Journal of Marketing Research , 21, 65-74. Barabási, A. L...317-357. Leone, R. P. (1983). Modeling sales-advertising relationships: An integrated time series- econometric approach. Journal of Marketing ... Research , 20, 291-295. McGrath, J. E., & Kravitz, D. A. (1982). Group research. Annual Review of Psychology, 33, 195- 230. Monge, P. R., & Contractor
Transcriptomic and genetic analysis of direct interspecies electron transfer
DEFF Research Database (Denmark)
Shrestha, Pravin Malla; Rotaru, Amelia-Elena; Summers, Zarath M
2013-01-01
The possibility that metatranscriptomic analysis could distinguish between direct interspecies electron transfer (DIET) and H2 interspecies transfer (HIT) in anaerobic communities was investigated by comparing gene transcript abundance in cocultures in which Geobacter sulfurreducens....... These results demonstrate that there are unique gene expression patterns that distinguish DIET from HIT and suggest that metatranscriptomics may be a promising route to investigate interspecies electron transfer pathways in more-complex environments....
Dabbakuti, J. R. K. Kumar; Venkata Ratnam, D.
2017-10-01
Precise modeling of the ionospheric Total Electron Content (TEC) is a critical aspect of Positioning, Navigation, and Timing (PNT) services intended for the Global Navigation Satellite Systems (GNSS) applications as well as Earth Observation System (EOS), satellite communication, and space weather forecasting applications. In this paper, linear time series modeling has been carried out on ionospheric TEC at two different locations at Koneru Lakshmaiah University (KLU), Guntur (geographic 16.44° N, 80.62° E; geomagnetic 7.55° N) and Bangalore (geographic 12.97° N, 77.59° E; geomagnetic 4.53° N) at the northern low-latitude region, for the year 2013 in the 24th solar cycle. The impact of the solar and geomagnetic activity on periodic oscillations of TEC has been investigated. Results confirm that the correlation coefficient of the estimated TEC from the linear model TEC and the observed GPS-TEC is around 93%. Solar activity is the key component that influences ionospheric daily averaged TEC while periodic component reveals the seasonal dependency of TEC. Furthermore, it is observed that the influence of geomagnetic activity component on TEC is different at both the latitudes. The accuracy of the model has been assessed by comparing the International Reference Ionosphere (IRI) 2012 model TEC and TEC measurements. Moreover, the absence of winter anomaly is remarkable, as determined by the Root Mean Square Error (RMSE) between the linear model TEC and GPS-TEC. On the contrary, the IRI2012 model TEC evidently failed to predict the absence of winter anomaly in the Equatorial Ionization Anomaly (EIA) crest region. The outcome of this work will be useful for improving the ionospheric now-casting models under various geophysical conditions.
TIME SERIES ANALYSIS ON STOCK MARKET FOR TEXT MINING CORRELATION OF ECONOMY NEWS
Directory of Open Access Journals (Sweden)
Sadi Evren SEKER
2014-01-01
Full Text Available This paper proposes an information retrieval methodfor the economy news. Theeffect of economy news, are researched in the wordlevel and stock market valuesare considered as the ground proof.The correlation between stock market prices and economy news is an already ad-dressed problem for most of the countries. The mostwell-known approach is ap-plying the text mining approaches to the news and some time series analysis tech-niques over stock market closing values in order toapply classification or cluster-ing algorithms over the features extracted. This study goes further and tries to askthe question what are the available time series analysis techniques for the stockmarket closing values and which one is the most suitable? In this study, the newsand their dates are collected into a database and text mining is applied over thenews, the text mining part has been kept simple with only term frequency – in-verse document frequency method. For the time series analysis part, we havestudied 10 different methods such as random walk, moving average, acceleration,Bollinger band, price rate of change, periodic average, difference, momentum orrelative strength index and their variation. In this study we have also explainedthese techniques in a comparative way and we have applied the methods overTurkish Stock Market closing values for more than a2 year period. On the otherhand, we have applied the term frequency – inversedocument frequency methodon the economy news of one of the high-circulatingnewspapers in Turkey.
The Fourier decomposition method for nonlinear and non-stationary time series analysis.
Singh, Pushpendra; Joshi, Shiv Dutt; Patney, Rakesh Kumar; Saha, Kaushik
2017-03-01
for many decades, there has been a general perception in the literature that Fourier methods are not suitable for the analysis of nonlinear and non-stationary data. In this paper, we propose a novel and adaptive Fourier decomposition method (FDM), based on the Fourier theory, and demonstrate its efficacy for the analysis of nonlinear and non-stationary time series. The proposed FDM decomposes any data into a small number of 'Fourier intrinsic band functions' (FIBFs). The FDM presents a generalized Fourier expansion with variable amplitudes and variable frequencies of a time series by the Fourier method itself. We propose an idea of zero-phase filter bank-based multivariate FDM (MFDM), for the analysis of multivariate nonlinear and non-stationary time series, using the FDM. We also present an algorithm to obtain cut-off frequencies for MFDM. The proposed MFDM generates a finite number of band-limited multivariate FIBFs (MFIBFs). The MFDM preserves some intrinsic physical properties of the multivariate data, such as scale alignment, trend and instantaneous frequency. The proposed methods provide a time-frequency-energy (TFE) distribution that reveals the intrinsic structure of a data. Numerical computations and simulations have been carried out and comparison is made with the empirical mode decomposition algorithms.
McKenna, Thomas M; Bawa, Gagandeep; Kumar, Kamal; Reifman, Jaques
2007-04-01
The physiology analysis system (PAS) was developed as a resource to support the efficient warehousing, management, and analysis of physiology data, particularly, continuous time-series data that may be extensive, of variable quality, and distributed across many files. The PAS incorporates time-series data collected by many types of data-acquisition devices, and it is designed to free users from data management burdens. This Web-based system allows both discrete (attribute) and time-series (ordered) data to be manipulated, visualized, and analyzed via a client's Web browser. All processes occur on a server, so that the client does not have to download data or any application programs, and the PAS is independent of the client's computer operating system. The PAS contains a library of functions, written in different computer languages that the client can add to and use to perform specific data operations. Functions from the library are sequentially inserted into a function chain-based logical structure to construct sophisticated data operators from simple function building blocks, affording ad hoc query and analysis of time-series data. These features support advanced mining of physiology data.
Visser, H.; Molenaar, J.
1995-05-01
The detection of trends in climatological data has become central to the discussion on climate change due to the enhanced greenhouse effect. To prove detection, a method is needed (i) to make inferences on significant rises or declines in trends, (ii) to take into account natural variability in climate series, and (iii) to compare output from GCMs with the trends in observed climate data. To meet these requirements, flexible mathematical tools are needed. A structural time series model is proposed with which a stochastic trend, a deterministic trend, and regression coefficients can be estimated simultaneously. The stochastic trend component is described using the class of ARIMA models. The regression component is assumed to be linear. However, the regression coefficients corresponding with the explanatory variables may be time dependent to validate this assumption. The mathematical technique used to estimate this trend-regression model is the Kaiman filter. The main features of the filter are discussed.Examples of trend estimation are given using annual mean temperatures at a single station in the Netherlands (1706-1990) and annual mean temperatures at Northern Hemisphere land stations (1851-1990). The inclusion of explanatory variables is shown by regressing the latter temperature series on four variables: Southern Oscillation index (SOI), volcanic dust index (VDI), sunspot numbers (SSN), and a simulated temperature signal, induced by increasing greenhouse gases (GHG). In all analyses, the influence of SSN on global temperatures is found to be negligible. The correlations between temperatures and SOI and VDI appear to be negative. For SOI, this correlation is significant, but for VDI it is not, probably because of a lack of volcanic eruptions during the sample period. The relation between temperatures and GHG is positive, which is in agreement with the hypothesis of a warming climate because of increasing levels of greenhouse gases. The prediction performance of
Kennedy, Curtis E; Turley, James P
2011-10-24
Thousands of children experience cardiac arrest events every year in pediatric intensive care units. Most of these children die. Cardiac arrest prediction tools are used as part of medical emergency team evaluations to identify patients in standard hospital beds that are at high risk for cardiac arrest. There are no models to predict cardiac arrest in pediatric intensive care units though, where the risk of an arrest is 10 times higher than for standard hospital beds. Current tools are based on a multivariable approach that does not characterize deterioration, which often precedes cardiac arrests. Characterizing deterioration requires a time series approach. The purpose of this study is to propose a method that will allow for time series data to be used in clinical prediction models. Successful implementation of these methods has the potential to bring arrest prediction to the pediatric intensive care environment, possibly allowing for interventions that can save lives and prevent disabilities. We reviewed prediction models from nonclinical domains that employ time series data, and identified the steps that are necessary for building predictive models using time series clinical data. We illustrate the method by applying it to the specific case of building a predictive model for cardiac arrest in a pediatric intensive care unit. Time course analysis studies from genomic analysis provided a modeling template that was compatible with the steps required to develop a model from clinical time series data. The steps include: 1) selecting candidate variables; 2) specifying measurement parameters; 3) defining data format; 4) defining time window duration and resolution; 5) calculating latent variables for candidate variables not directly measured; 6) calculating time series features as latent variables; 7) creating data subsets to measure model performance effects attributable to various classes of candidate variables; 8) reducing the number of candidate features; 9
Energy Technology Data Exchange (ETDEWEB)
Lutaif, N.A. [Departamento de Clínica Médica, Faculdade de Ciências Médicas, Universidade Estadual de Campinas, Campinas, SP (Brazil); Palazzo, R. Jr [Departamento de Telemática, Faculdade de Engenharia Elétrica e Computação, Universidade Estadual de Campinas, Campinas, SP (Brazil); Gontijo, J.A.R. [Departamento de Clínica Médica, Faculdade de Ciências Médicas, Universidade Estadual de Campinas, Campinas, SP (Brazil)
2014-01-17
Maintenance of thermal homeostasis in rats fed a high-fat diet (HFD) is associated with changes in their thermal balance. The thermodynamic relationship between heat dissipation and energy storage is altered by the ingestion of high-energy diet content. Observation of thermal registers of core temperature behavior, in humans and rodents, permits identification of some characteristics of time series, such as autoreference and stationarity that fit adequately to a stochastic analysis. To identify this change, we used, for the first time, a stochastic autoregressive model, the concepts of which match those associated with physiological systems involved and applied in male HFD rats compared with their appropriate standard food intake age-matched male controls (n=7 per group). By analyzing a recorded temperature time series, we were able to identify when thermal homeostasis would be affected by a new diet. The autoregressive time series model (AR model) was used to predict the occurrence of thermal homeostasis, and this model proved to be very effective in distinguishing such a physiological disorder. Thus, we infer from the results of our study that maximum entropy distribution as a means for stochastic characterization of temperature time series registers may be established as an important and early tool to aid in the diagnosis and prevention of metabolic diseases due to their ability to detect small variations in thermal profile.
International Nuclear Information System (INIS)
Lutaif, N.A.; Palazzo, R. Jr; Gontijo, J.A.R.
2014-01-01
Maintenance of thermal homeostasis in rats fed a high-fat diet (HFD) is associated with changes in their thermal balance. The thermodynamic relationship between heat dissipation and energy storage is altered by the ingestion of high-energy diet content. Observation of thermal registers of core temperature behavior, in humans and rodents, permits identification of some characteristics of time series, such as autoreference and stationarity that fit adequately to a stochastic analysis. To identify this change, we used, for the first time, a stochastic autoregressive model, the concepts of which match those associated with physiological systems involved and applied in male HFD rats compared with their appropriate standard food intake age-matched male controls (n=7 per group). By analyzing a recorded temperature time series, we were able to identify when thermal homeostasis would be affected by a new diet. The autoregressive time series model (AR model) was used to predict the occurrence of thermal homeostasis, and this model proved to be very effective in distinguishing such a physiological disorder. Thus, we infer from the results of our study that maximum entropy distribution as a means for stochastic characterization of temperature time series registers may be established as an important and early tool to aid in the diagnosis and prevention of metabolic diseases due to their ability to detect small variations in thermal profile
Time series analysis of infrared satellite data for detecting thermal anomalies: a hybrid approach
Koeppen, W. C.; Pilger, E.; Wright, R.
2011-07-01
We developed and tested an automated algorithm that analyzes thermal infrared satellite time series data to detect and quantify the excess energy radiated from thermal anomalies such as active volcanoes. Our algorithm enhances the previously developed MODVOLC approach, a simple point operation, by adding a more complex time series component based on the methods of the Robust Satellite Techniques (RST) algorithm. Using test sites at Anatahan and Kīlauea volcanoes, the hybrid time series approach detected ~15% more thermal anomalies than MODVOLC with very few, if any, known false detections. We also tested gas flares in the Cantarell oil field in the Gulf of Mexico as an end-member scenario representing very persistent thermal anomalies. At Cantarell, the hybrid algorithm showed only a slight improvement, but it did identify flares that were undetected by MODVOLC. We estimate that at least 80 MODIS images for each calendar month are required to create good reference images necessary for the time series analysis of the hybrid algorithm. The improved performance of the new algorithm over MODVOLC will result in the detection of low temperature thermal anomalies that will be useful in improving our ability to document Earth's volcanic eruptions, as well as detecting low temperature thermal precursors to larger eruptions.
Spatial analysis of precipitation time series over the Upper Indus Basin
Latif, Yasir; Yaoming, Ma; Yaseen, Muhammad
2018-01-01
The upper Indus basin (UIB) holds one of the most substantial river systems in the world, contributing roughly half of the available surface water in Pakistan. This water provides necessary support for agriculture, domestic consumption, and hydropower generation; all critical for a stable economy in Pakistan. This study has identified trends, analyzed variability, and assessed changes in both annual and seasonal precipitation during four time series, identified herein as: (first) 1961-2013, (second) 1971-2013, (third) 1981-2013, and (fourth) 1991-2013, over the UIB. This study investigated spatial characteristics of the precipitation time series over 15 weather stations and provides strong evidence of annual precipitation by determining significant trends at 6 stations (Astore, Chilas, Dir, Drosh, Gupis, and Kakul) out of the 15 studied stations, revealing a significant negative trend during the fourth time series. Our study also showed significantly increased precipitation at Bunji, Chitral, and Skardu, whereas such trends at the rest of the stations appear insignificant. Moreover, our study found that seasonal precipitation decreased at some locations (at a high level of significance), as well as periods of scarce precipitation during all four seasons. The observed decreases in precipitation appear stronger and more significant in autumn; having 10 stations exhibiting decreasing precipitation during the fourth time series, with respect to time and space. Furthermore, the observed decreases in precipitation appear robust and more significant for regions at high elevation (>1300 m). This analysis concludes that decreasing precipitation dominated the UIB, both temporally and spatially including in the higher areas.
Directory of Open Access Journals (Sweden)
Sérgio Roberto da Silva
2016-06-01
Full Text Available Colombia has been one of the first countries to introduce electronic billing process on a voluntary basis, from a traditional to a digital version. In this context, the article analyzes the electronic billing process implemented in Colombia and the advantages. Methodological research is applied, qualitative, descriptive and documentary; where the regulatory framework and the conceptualization of the model is identified; the process of adoption of electronic billing is analyzed, and finally the advantages and disadvantages of its implementation is analyzed. The findings indicate that the model applied in Colombia to issue an electronic billing in sending and receiving process, is not complex, but it requires a small adequate infrastructure and trained personnel to reach all sectors, especially the micro and business which is the largest business network in the country.
Energy Technology Data Exchange (ETDEWEB)
Pardo-Iguzquiza, E.; Rodriguez-Tovar, F. J.
2013-06-01
In geosciences the sampling of a time series tends to afford uneven results, sometimes because the sampling itself is random or because of hiatuses or even completely missing data or due to difficulties involved in the conversion of data from a spatial to a time scale when the sedimentation rate was not constant. Whatever the case, the best solution does not lie in interpolation but rather in resorting to a method that deals with the irregular data. We show here how the use of the smoothed Lomb-Scargle periodogram is both a practical and efficient choice. We describe the effects on the estimated power spectrum of the type of irregular sampling, the number of data, interpolation, and the presence of drift. We propose the permutation test as being an efficient way of calculating statistical confidence levels. By applying the Lomb-Scargle periodogram to a synthetic series with a known spectral content we are able to confirm the validity of this method in the face of the difficulties mentioned above. A case study with real data, including hiatuses, representing the thickness of the annual banding in a stalagmite, is chosen to demonstrate an application using the statistical and physical interpretation of spectral peaks. (Author)
Studies in astronomical time series analysis. I - Modeling random processes in the time domain
Scargle, J. D.
1981-01-01
Several random process models in the time domain are defined and discussed. Attention is given to the moving average model, the autoregressive model, and relationships between and combinations of these models. Consideration is then given to methods for investigating pulse structure, procedures of model construction, computational methods, and numerical experiments. A FORTRAN algorithm of time series analysis has been developed which is relatively stable numerically. Results of test cases are given to study the effect of adding noise and of different distributions for the pulse amplitudes. A preliminary analysis of the light curve of the quasar 3C 272 is considered as an example.
The Real-time Frequency Spectrum Analysis of Neutron Pulse Signal Series
International Nuclear Information System (INIS)
Tang Yuelin; Ren Yong; Wei Biao; Feng Peng; Mi Deling; Pan Yingjun; Li Jiansheng; Ye Cenming
2009-01-01
The frequency spectrum analysis of neutron pulse signal is a very important method in nuclear stochastic signal processing Focused on the special '0' and '1' of neutron pulse signal series, this paper proposes new rotation-table and realizes a real-time frequency spectrum algorithm under 1G Hz sample rate based on PC with add, address and SSE. The numerical experimental results show that under the count rate of 3X10 6 s -1 , this algorithm is superior to FFTW in time-consumption and can meet the real-time requirement of frequency spectrum analysis. (authors)
On the Impact of a Quadratic Acceleration Term in the Analysis of Position Time Series
Bogusz, Janusz; Klos, Anna; Bos, Machiel Simon; Hunegnaw, Addisu; Teferle, Felix Norman
2016-04-01
The analysis of Global Navigation Satellite System (GNSS) position time series generally assumes that each of the coordinate component series is described by the sum of a linear rate (velocity) and various periodic terms. The residuals, the deviations between the fitted model and the observations, are then a measure of the epoch-to-epoch scatter and have been used for the analysis of the stochastic character (noise) of the time series. Often the parameters of interest in GNSS position time series are the velocities and their associated uncertainties, which have to be determined with the highest reliability. It is clear that not all GNSS position time series follow this simple linear behaviour. Therefore, we have added an acceleration term in the form of a quadratic polynomial function to the model in order to better describe the non-linear motion in the position time series. This non-linear motion could be a response to purely geophysical processes, for example, elastic rebound of the Earth's crust due to ice mass loss in Greenland, artefacts due to deficiencies in bias mitigation models, for example, of the GNSS satellite and receiver antenna phase centres, or any combination thereof. In this study we have simulated 20 time series with different stochastic characteristics such as white, flicker or random walk noise of length of 23 years. The noise amplitude was assumed at 1 mm/y-/4. Then, we added the deterministic part consisting of a linear trend of 20 mm/y (that represents the averaged horizontal velocity) and accelerations ranging from minus 0.6 to plus 0.6 mm/y2. For all these data we estimated the noise parameters with Maximum Likelihood Estimation (MLE) using the Hector software package without taken into account the non-linear term. In this way we set the benchmark to then investigate how the noise properties and velocity uncertainty may be affected by any un-modelled, non-linear term. The velocities and their uncertainties versus the accelerations for
Lhermitte, S.; Tips, M.; Verbesselt, J.; Jonckheere, I.; Van Aardt, J.; Coppin, Pol
2005-10-01
Large-scale wild fires have direct impacts on natural ecosystems and play a major role in the vegetation ecology and carbon budget. Accurate methods for describing post-fire development of vegetation are therefore essential for the understanding and monitoring of terrestrial ecosystems. Time series analysis of satellite imagery offers the potential to quantify these parameters with spatial and temporal accuracy. Current research focuses on the potential of time series analysis of SPOT Vegetation S10 data (1999-2001) to quantify the vegetation recovery of large-scale burns detected in the framework of GBA2000. The objective of this study was to provide quantitative estimates of the spatio-temporal variation of vegetation recovery based on remote sensing indicators. Southern Africa was used as a pilot study area, given the availability of ground and satellite data. An automated technique was developed to extract consistent indicators of vegetation recovery from the SPOT-VGT time series. Reference areas were used to quantify the vegetation regrowth by means of Regeneration Indices (RI). Two kinds of recovery indicators (time and value- based) were tested for RI's of NDVI, SR, SAVI, NDWI, and pure band information. The effects of vegetation structure and temporal fire regime features on the recovery indicators were subsequently analyzed. Statistical analyses were conducted to assess whether the recovery indicators were different for different vegetation types and dependent on timing of the burning season. Results highlighted the importance of appropriate reference areas and the importance of correct normalization of the SPOT-VGT data.
Li, Shuying; Zhuang, Jun; Shen, Shifei
2017-07-01
In recent years, various types of terrorist attacks occurred, causing worldwide catastrophes. According to the Global Terrorism Database (GTD), among all attack tactics, bombing attacks happened most frequently, followed by armed assaults. In this article, a model for analyzing and forecasting the conditional probability of bombing attacks (CPBAs) based on time-series methods is developed. In addition, intervention analysis is used to analyze the sudden increase in the time-series process. The results show that the CPBA increased dramatically at the end of 2011. During that time, the CPBA increased by 16.0% in a two-month period to reach the peak value, but still stays 9.0% greater than the predicted level after the temporary effect gradually decays. By contrast, no significant fluctuation can be found in the conditional probability process of armed assault. It can be inferred that some social unrest, such as America's troop withdrawal from Afghanistan and Iraq, could have led to the increase of the CPBA in Afghanistan, Iraq, and Pakistan. The integrated time-series and intervention model is used to forecast the monthly CPBA in 2014 and through 2064. The average relative error compared with the real data in 2014 is 3.5%. The model is also applied to the total number of attacks recorded by the GTD between 2004 and 2014. © 2016 Society for Risk Analysis.
Comparative performance analysis of shunt and series passive filter for LED lamp
Sarwono, Edi; Facta, Mochammad; Handoko, Susatyo
2018-03-01
Light Emitting Diode lamp or LED lamp nowadays is widely used by consumers as a new innovation in the lighting technologies due to its energy saving for low power consumption lamps for brighter light intensity. How ever, the LED lamp produce an electric pollutant known as harmonics. The harmonics is generated by rectifier as part of LED lamp circuit. The present of harmonics in current or voltage has made the source waveform from the grid is distorted. This distortion may cause inacurrate measurement, mall function, and excessive heating for any element at the grid. This paper present an analysis work of shunt and series filters to suppress the harmonics generated by the LED lamp circuit. The work was initiated by conducting several tests to investigate the harmonic content of voltage and currents. The measurements in this work were carried out by using HIOKI Power Quality Analyzer 3197. The measurement results showed that the harmonics current of tested LED lamps were above the limit of IEEE standard 519-2014. Based on the measurement results shunt and series filters were constructed as low pass filters. The bode analysis were appled during construction and prediction of the filters performance. Based on experimental results, the application of shunt filter at input side of LED lamp has reduced THD current up to 88%. On the other hand, the series filter has significantly reduced THD current up to 92%.
Work-related accidents among the Iranian population: a time series analysis, 2000-2011.
Karimlou, Masoud; Salehi, Masoud; Imani, Mehdi; Hosseini, Agha-Fatemeh; Dehnad, Afsaneh; Vahabi, Nasim; Bakhtiyari, Mahmood
2015-01-01
Work-related accidents result in human suffering and economic losses and are considered as a major health problem worldwide, especially in the economically developing world. To introduce seasonal autoregressive moving average (ARIMA) models for time series analysis of work-related accident data for workers insured by the Iranian Social Security Organization (ISSO) between 2000 and 2011. In this retrospective study, all insured people experiencing at least one work-related accident during a 10-year period were included in the analyses. We used Box-Jenkins modeling to develop a time series model of the total number of accidents. There was an average of 1476 accidents per month (1476·05±458·77, mean±SD). The final ARIMA (p,d,q) (P,D,Q)s model for fitting to data was: ARIMA(1,1,1)×(0,1,1)12 consisting of the first ordering of the autoregressive, moving average and seasonal moving average parameters with 20·942 mean absolute percentage error (MAPE). The final model showed that time series analysis of ARIMA models was useful for forecasting the number of work-related accidents in Iran. In addition, the forecasted number of work-related accidents for 2011 explained the stability of occurrence of these accidents in recent years, indicating a need for preventive occupational health and safety policies such as safety inspection.
Work-related accidents among the Iranian population: a time series analysis, 2000–2011
Karimlou, Masoud; Imani, Mehdi; Hosseini, Agha-Fatemeh; Dehnad, Afsaneh; Vahabi, Nasim; Bakhtiyari, Mahmood
2015-01-01
Background Work-related accidents result in human suffering and economic losses and are considered as a major health problem worldwide, especially in the economically developing world. Objectives To introduce seasonal autoregressive moving average (ARIMA) models for time series analysis of work-related accident data for workers insured by the Iranian Social Security Organization (ISSO) between 2000 and 2011. Methods In this retrospective study, all insured people experiencing at least one work-related accident during a 10-year period were included in the analyses. We used Box–Jenkins modeling to develop a time series model of the total number of accidents. Results There was an average of 1476 accidents per month (1476·05±458·77, mean±SD). The final ARIMA (p,d,q) (P,D,Q)s model for fitting to data was: ARIMA(1,1,1)×(0,1,1)12 consisting of the first ordering of the autoregressive, moving average and seasonal moving average parameters with 20·942 mean absolute percentage error (MAPE). Conclusions The final model showed that time series analysis of ARIMA models was useful for forecasting the number of work-related accidents in Iran. In addition, the forecasted number of work-related accidents for 2011 explained the stability of occurrence of these accidents in recent years, indicating a need for preventive occupational health and safety policies such as safety inspection. PMID:26119774
DEFF Research Database (Denmark)
Lu, Dapeng; Wang, Xiongfei; Bai, Haofeng
2016-01-01
resistance through detection and resonant controller, the series active damper can suppress the resonance with its external damping character in closed-loop damping character are carried out. Simulation and experimental results are presented to verify the effectiveness of the proposed series active damper....
Empirical mode decomposition and long-range correlation analysis of sunspot time series
International Nuclear Information System (INIS)
Zhou, Yu; Leung, Yee
2010-01-01
Sunspots, which are the best known and most variable features of the solar surface, affect our planet in many ways. The number of sunspots during a period of time is highly variable and arouses strong research interest. When multifractal detrended fluctuation analysis (MF-DFA) is employed to study the fractal properties and long-range correlation of the sunspot series, some spurious crossover points might appear because of the periodic and quasi-periodic trends in the series. However many cycles of solar activities can be reflected by the sunspot time series. The 11-year cycle is perhaps the most famous cycle of the sunspot activity. These cycles pose problems for the investigation of the scaling behavior of sunspot time series. Using different methods to handle the 11-year cycle generally creates totally different results. Using MF-DFA, Movahed and co-workers employed Fourier truncation to deal with the 11-year cycle and found that the series is long-range anti-correlated with a Hurst exponent, H, of about 0.12. However, Hu and co-workers proposed an adaptive detrending method for the MF-DFA and discovered long-range correlation characterized by H≈0.74. In an attempt to get to the bottom of the problem in the present paper, empirical mode decomposition (EMD), a data-driven adaptive method, is applied to first extract the components with different dominant frequencies. MF-DFA is then employed to study the long-range correlation of the sunspot time series under the influence of these components. On removing the effects of these periods, the natural long-range correlation of the sunspot time series can be revealed. With the removal of the 11-year cycle, a crossover point located at around 60 months is discovered to be a reasonable point separating two different time scale ranges, H≈0.72 and H≈1.49. And on removing all cycles longer than 11 years, we have H≈0.69 and H≈0.28. The three cycle-removing methods—Fourier truncation, adaptive detrending and the
The regulation of peculiarities of electronic contracting: comparative analysis
Directory of Open Access Journals (Sweden)
Наталія Юліївна Філатова
2017-12-01
Full Text Available Contract formation by electronic means nowadays is a widespread phenomenon. Nevertheless electronic contracting has been thoroughly explored by scholars all over the world and regulated both internationally and domestically, there still remain some issues which need to be carefully analyzed. In our view, the most essential question raised by electronic contracting is whether there is a need to amend substantial contract law provisions with regard to peculiarities of contracts concluded by electronic means. Seeking the answer to this question several approaches have been formulated, but none of them seems to be completely appropriate. In this paper the answer is also attempted to be found. For this purpose a comparative analysis of doctrine, legislation and judicial practice of certain states is performed. Particularly, offer, acceptance and moment of electronic contract formation are explored. On the basis of this research the following conclusion is done: amendments to substantial contract law provisions are not always necessary to improve the regulation of electronic contracting. Nevertheless the provisions of law should be applied correctly to the disputes arising from electronic contract formation taking into account the peculiarities of such contracts.
Detrended fluctuation analysis based on higher-order moments of financial time series
Teng, Yue; Shang, Pengjian
2018-01-01
In this paper, a generalized method of detrended fluctuation analysis (DFA) is proposed as a new measure to assess the complexity of a complex dynamical system such as stock market. We extend DFA and local scaling DFA to higher moments such as skewness and kurtosis (labeled SMDFA and KMDFA), so as to investigate the volatility scaling property of financial time series. Simulations are conducted over synthetic and financial data for providing the comparative study. We further report the results of volatility behaviors in three American countries, three Chinese and three European stock markets by using DFA and LSDFA method based on higher moments. They demonstrate the dynamics behaviors of time series in different aspects, which can quantify the changes of complexity for stock market data and provide us with more meaningful information than single exponent. And the results reveal some higher moments volatility and higher moments multiscale volatility details that cannot be obtained using the traditional DFA method.
Time series analysis of pressure fluctuation in gas-solid fluidized beds
Directory of Open Access Journals (Sweden)
C. Alberto S. Felipe
2004-09-01
Full Text Available The purpose of the present work was to study the differentiation of states of typical fluidization (single bubble, multiple bubble and slugging in a gas-solid fluidized bed, using spectral analysis of pressure fluctuation time series. The effects of the method of measuring (differential and absolute pressure fluctuations and the axial position of the probes in the fluidization column on the identification of each of the regimes studied were evaluated. Fast Fourier Transform (FFT was the mathematic tool used to analysing the data of pressure fluctuations, which expresses the behavior of a time series in the frequency domain. Results indicated that the plenum chamber was a place for reliable measurement and that care should be taken in measurement in the dense phase. The method allowed fluid dynamic regimes to be differentiated by their dominant frequency characteristics.
Analysis of Data from a Series of Events by a Geometric Process Model
Institute of Scientific and Technical Information of China (English)
Yeh Lam; Li-xing Zhu; Jennifer S. K. Chan; Qun Liu
2004-01-01
Geometric process was first introduced by Lam[10,11]. A stochastic process {Xi, i = 1, 2,…} is called a geometric process (GP) if, for some a > 0, {ai-1Xi, i = 1, 2,…} forms a renewal process. In thispaper, the GP is used to analyze the data from a series of events. A nonparametric method is introduced forthe estimation of the three parameters in the GP. The limiting distributions of the three estimators are studied.Through the analysis of some real data sets, the GP model is compared with other three homogeneous andnonhomogeneous Poisson models. It seems that on average the GP model is the best model among these fourmodels in analyzing the data from a series of events.
The Relative Importance of the Service Sector in the Mexican Economy: A Time Series Analysis
Directory of Open Access Journals (Sweden)
Carlos Alberto Flores
2014-01-01
Full Text Available We conduct a study of the secondary and tertiary sectors with the goal of highlighting the relative im-portance of services in the Mexican economy. We consider a time series analysis approach designed to identify the stochastic nature of the series, as well as to define their long-run and-short run relationships with Gross Domestic Product (GDP. The results of cointegration tests suggest that, for the most part, activities in the secondary and tertiary sectors share a common trend with GDP. Interestingly, the long-run elasticities of GDP with respect to services are on average larger than those with respect to secondary activities. Common cycle tests results identify the existence of common cycles between GDP and the disaggregated sectors, as well as with manufacturing, commerce, real estate and transportation. In this case, the short-run elasticities of secondary activities are on average larger than those corresponding to services.
Investigation of interfacial wave structure using time-series analysis techniques
International Nuclear Information System (INIS)
Jayanti, S.; Hewitt, G.F.; Cliffe, K.A.
1990-09-01
The report presents an investigation into the interfacial structure in horizontal annular flow using spectral and time-series analysis techniques. Film thickness measured using conductance probes shows an interesting transition in wave pattern from a continuous low-frequency wave pattern to an intermittent, high-frequency one. From the autospectral density function of the film thickness, it appears that this transition is caused by the breaking up of long waves into smaller ones. To investigate the possibility of the wave structure being represented as a low order chaotic system, phase portraits of the time series were constructed using the technique developed by Broomhead and co-workers (1986, 1987 and 1989). These showed a banded structure when waves of relatively high frequency were filtered out. Although these results are encouraging, further work is needed to characterise the attractor. (Author)
Optical polarimeter based on Fourier analysis and electronic control
International Nuclear Information System (INIS)
Vilardy, J; Salas, V.; Torres, C.
2016-01-01
In this paper, we show the design and implementation of an optical polarimeter using electronic control and the Fourier analysis. The polarimeter prototype will be used as a main tool for the students of the Universidad Popular del Cesar that belong to the following university programs: Electronics engineering (optoelectronics area), Math and Physics degree and the Master in Physics Sciences, in order to learning the theory and experimental aspects of the state of optical polarization via the Stokes vector measurement. Using the electronic polarimeter proposed in this paper, the students will be able to observe (in an optical bench) and understand the different interactions of the states of optical polarization when the optical waves pass through to the polarizers and retarder waves plates. The electronic polarimeter has a software that captures the optical intensity measurement and evaluates the Stokes vector. (Author)
Causality as a Rigorous Notion and Quantitative Causality Analysis with Time Series
Liang, X. S.
2017-12-01
Given two time series, can one faithfully tell, in a rigorous and quantitative way, the cause and effect between them? Here we show that this important and challenging question (one of the major challenges in the science of big data), which is of interest in a wide variety of disciplines, has a positive answer. Particularly, for linear systems, the maximal likelihood estimator of the causality from a series X2 to another series X1, written T2→1, turns out to be concise in form: T2→1 = [C11 C12 C2,d1 — C112 C1,d1] / [C112 C22 — C11C122] where Cij (i,j=1,2) is the sample covariance between Xi and Xj, and Ci,dj the covariance between Xi and ΔXj/Δt, the difference approximation of dXj/dt using the Euler forward scheme. An immediate corollary is that causation implies correlation, but not vice versa, resolving the long-standing debate over causation versus correlation. The above formula has been validated with touchstone series purportedly generated with one-way causality that evades the classical approaches such as Granger causality test and transfer entropy analysis. It has also been applied successfully to the investigation of many real problems. Through a simple analysis with the stock series of IBM and GE, an unusually strong one-way causality is identified from the former to the latter in their early era, revealing to us an old story, which has almost faded into oblivion, about "Seven Dwarfs" competing with a "Giant" for the computer market. Another example presented here regards the cause-effect relation between the two climate modes, El Niño and Indian Ocean Dipole (IOD). In general, these modes are mutually causal, but the causality is asymmetric. To El Niño, the information flowing from IOD manifests itself as a propagation of uncertainty from the Indian Ocean. In the third example, an unambiguous one-way causality is found between CO2 and the global mean temperature anomaly. While it is confirmed that CO2 indeed drives the recent global warming
Phase correction and error estimation in InSAR time series analysis
Zhang, Y.; Fattahi, H.; Amelung, F.
2017-12-01
During the last decade several InSAR time series approaches have been developed in response to the non-idea acquisition strategy of SAR satellites, such as large spatial and temporal baseline with non-regular acquisitions. The small baseline tubes and regular acquisitions of new SAR satellites such as Sentinel-1 allows us to form fully connected networks of interferograms and simplifies the time series analysis into a weighted least square inversion of an over-determined system. Such robust inversion allows us to focus more on the understanding of different components in InSAR time-series and its uncertainties. We present an open-source python-based package for InSAR time series analysis, called PySAR (https://yunjunz.github.io/PySAR/), with unique functionalities for obtaining unbiased ground displacement time-series, geometrical and atmospheric correction of InSAR data and quantifying the InSAR uncertainty. Our implemented strategy contains several features including: 1) improved spatial coverage using coherence-based network of interferograms, 2) unwrapping error correction using phase closure or bridging, 3) tropospheric delay correction using weather models and empirical approaches, 4) DEM error correction, 5) optimal selection of reference date and automatic outlier detection, 6) InSAR uncertainty due to the residual tropospheric delay, decorrelation and residual DEM error, and 7) variance-covariance matrix of final products for geodetic inversion. We demonstrate the performance using SAR datasets acquired by Cosmo-Skymed and TerraSAR-X, Sentinel-1 and ALOS/ALOS-2, with application on the highly non-linear volcanic deformation in Japan and Ecuador (figure 1). Our result shows precursory deformation before the 2015 eruptions of Cotopaxi volcano, with a maximum uplift of 3.4 cm on the western flank (fig. 1b), with a standard deviation of 0.9 cm (fig. 1a), supporting the finding by Morales-Rivera et al. (2017, GRL); and a post-eruptive subsidence on the same
He, Jiayi; Shang, Pengjian; Xiong, Hui
2018-06-01
Stocks, as the concrete manifestation of financial time series with plenty of potential information, are often used in the study of financial time series. In this paper, we utilize the stock data to recognize their patterns through out the dissimilarity matrix based on modified cross-sample entropy, then three-dimensional perceptual maps of the results are provided through multidimensional scaling method. Two modified multidimensional scaling methods are proposed in this paper, that is, multidimensional scaling based on Kronecker-delta cross-sample entropy (MDS-KCSE) and multidimensional scaling based on permutation cross-sample entropy (MDS-PCSE). These two methods use Kronecker-delta based cross-sample entropy and permutation based cross-sample entropy to replace the distance or dissimilarity measurement in classical multidimensional scaling (MDS). Multidimensional scaling based on Chebyshev distance (MDSC) is employed to provide a reference for comparisons. Our analysis reveals a clear clustering both in synthetic data and 18 indices from diverse stock markets. It implies that time series generated by the same model are easier to have similar irregularity than others, and the difference in the stock index, which is caused by the country or region and the different financial policies, can reflect the irregularity in the data. In the synthetic data experiments, not only the time series generated by different models can be distinguished, the one generated under different parameters of the same model can also be detected. In the financial data experiment, the stock indices are clearly divided into five groups. Through analysis, we find that they correspond to five regions, respectively, that is, Europe, North America, South America, Asian-Pacific (with the exception of mainland China), mainland China and Russia. The results also demonstrate that MDS-KCSE and MDS-PCSE provide more effective divisions in experiments than MDSC.
Radial artery pulse waveform analysis based on curve fitting using discrete Fourier series.
Jiang, Zhixing; Zhang, David; Lu, Guangming
2018-04-19
Radial artery pulse diagnosis has been playing an important role in traditional Chinese medicine (TCM). For its non-invasion and convenience, the pulse diagnosis has great significance in diseases analysis of modern medicine. The practitioners sense the pulse waveforms in patients' wrist to make diagnoses based on their non-objective personal experience. With the researches of pulse acquisition platforms and computerized analysis methods, the objective study on pulse diagnosis can help the TCM to keep up with the development of modern medicine. In this paper, we propose a new method to extract feature from pulse waveform based on discrete Fourier series (DFS). It regards the waveform as one kind of signal that consists of a series of sub-components represented by sine and cosine (SC) signals with different frequencies and amplitudes. After the pulse signals are collected and preprocessed, we fit the average waveform for each sample using discrete Fourier series by least squares. The feature vector is comprised by the coefficients of discrete Fourier series function. Compared with the fitting method using Gaussian mixture function, the fitting errors of proposed method are smaller, which indicate that our method can represent the original signal better. The classification performance of proposed feature is superior to the other features extracted from waveform, liking auto-regression model and Gaussian mixture model. The coefficients of optimized DFS function, who is used to fit the arterial pressure waveforms, can obtain better performance in modeling the waveforms and holds more potential information for distinguishing different psychological states. Copyright © 2018 Elsevier B.V. All rights reserved.
Analysis of cyclical behavior in time series of stock market returns
Stratimirović, Djordje; Sarvan, Darko; Miljković, Vladimir; Blesić, Suzana
2018-01-01
In this paper we have analyzed scaling properties and cyclical behavior of the three types of stock market indexes (SMI) time series: data belonging to stock markets of developed economies, emerging economies, and of the underdeveloped or transitional economies. We have used two techniques of data analysis to obtain and verify our findings: the wavelet transform (WT) spectral analysis to identify cycles in the SMI returns data, and the time-dependent detrended moving average (tdDMA) analysis to investigate local behavior around market cycles and trends. We found cyclical behavior in all SMI data sets that we have analyzed. Moreover, the positions and the boundaries of cyclical intervals that we found seam to be common for all markets in our dataset. We list and illustrate the presence of nine such periods in our SMI data. We report on the possibilities to differentiate between the level of growth of the analyzed markets by way of statistical analysis of the properties of wavelet spectra that characterize particular peak behaviors. Our results show that measures like the relative WT energy content and the relative WT amplitude of the peaks in the small scales region could be used to partially differentiate between market economies. Finally, we propose a way to quantify the level of development of a stock market based on estimation of local complexity of market's SMI series. From the local scaling exponents calculated for our nine peak regions we have defined what we named the Development Index, which proved, at least in the case of our dataset, to be suitable to rank the SMI series that we have analyzed in three distinct groups.
Time series analysis of soil Radon-222 recorded at Kutch region, Gujarat, India
International Nuclear Information System (INIS)
Madhusudan Rao, K.; Rastogi, B.K.; Barman, Chiranjib; Chaudhuri, Hirok
2013-01-01
Kutch region in Gujarat lies in a seismic vulnerable zone (seismic zone-v). After the devastating Bhuj earthquake (7.7M) of January 26, 2001 in the Kutch region several researcher focused their attention to monitor geophysical and geochemical precursors for earthquakes in the region. In order to find out the possible geochemical precursory signals for earthquake events, we monitored radioactive gas radon-222 in sub surface soil gas at Kutch region. We have analysed the recorded soil radon-222 time series by means of nonlinear techniques such as FFT power spectral analysis, empirical mode decomposition, multi-fractal analysis along with other linear statistical methods. Some fascinating and fruitful results originated out the nonlinear analysis of the said time series have been discussed in the present paper. The entire analytical method aided us to recognize the nature and pattern of soil radon-222 emanation process. Moreover the recording and statistical and non-linear analysis of soil radon data at Kutch region will assist us to understand the preparation phase of an imminent seismic event in the region. (author)
Arab drama series content analysis from a transnational Arab identity perspective
Directory of Open Access Journals (Sweden)
Joelle Chamieh
2016-04-01
Full Text Available The scientific contribution in deciphering drama series falls under the discipline of understanding the narratology of distinctive cultures and traditions within specific contexts of certain societies. This article spells out the interferences deployed by the provocations that are induced through the functions of values in modeling societies which are projected through the transmission of media. The proposed operational model consists of providing an à priori design of common Arab values assimilated into an innovative grid analysis code book that has enabled the execution of a systematic and reliable approach to the quantitative content analysis performance. Additionally, a more thorough qualitative content analysis has been implemented in terms of narratolgy where actions have been evaluated based on the grid analysis code book for a clearer perception of Arab values depicted in terms of their context within the Arab drama milieu. This approach has been deployed on four Arab drama series covering the transnational/national and non-divisive/divisive media aspects in the intention of extracting the transmitted values from a common identity perspective for cause of divulging Arab people’s expectancies.
Beam lifetime measurement and analysis in Indus-2 electron ...
Indian Academy of Sciences (India)
In this paper, the beam lifetime measurement and its theoretical analysis are presented using measured vacuum pressure and applied radio frequency (RF) cavity voltage in Indus-2 electron storage ring at 2 GeV beam energy. Experimental studies of the effect of RF cavity voltage and bunched beam filling pattern on beam ...
The quantum mechanical analysis of the free electron laser
International Nuclear Information System (INIS)
Dattoli, G.; Renieri, A.
1985-01-01
A quantum analysis of the Free Electron Laser is presented. The theory is developed both in single and longitudinal multimode regimes. Finally a self-consistent procedure to study the growth of the laser signal from the vacuum to the macroscopic level is presented
Image formation and image analysis in electron microscopy
International Nuclear Information System (INIS)
Heel, M. van.
1981-01-01
This thesis covers various aspects of image formation and image analysis in electron microscopy. The imaging of relatively strong objects in partially coherent illumination, the coherence properties of thermionic emission sources and the detection of objects in quantum noise limited images are considered. IMAGIC, a fast, flexible and friendly image analysis software package is described. Intelligent averaging of molecular images is discussed. (C.F.)
Energy Technology Data Exchange (ETDEWEB)
Yubero, C. [Grupo de Física de Plasmas: Diagnosis, Modelos y Aplicaciones (FQM-136), Edificio A. Einstein (C-2), Campus de Rabanales, Universidad de Córdoba, 14071 Córdoba (Spain); García, M.C., E-mail: fa1gamam@uco.es [Grupo de Física de Plasmas: Diagnosis, Modelos y Aplicaciones (FQM-136), Edificio A. Einstein (C-2), Campus de Rabanales, Universidad de Córdoba, 14071 Córdoba (Spain); Dimitrijevic, M.S. [Astronomical Observatory, Volgina 7, 11060 Belgrade (Serbia); Sola, A.; Gamero, A. [Grupo de Física de Plasmas: Diagnosis, Modelos y Aplicaciones (FQM-136), Edificio A. Einstein (C-2), Campus de Rabanales, Universidad de Córdoba, 14071 Córdoba (Spain)
2015-05-01
We present an alternative optical emission spectroscopy method to measure the plasma electron density from the difference of widths of two Balmer series hydrogen lines (H{sub α} and H{sub β}), especially convenient for non-thermal plasmas since with this method, there is no need to know either the gas temperature or the van der Waals contribution to the Lorentzian part of the line. In this paper it has been assumed that the part of full width at half maximum due to Stark broadening can be determined with the approximation of Lorentzian line shape. The method has been applied to the determination of the electron density in an argon microwave-induced plasma maintained at atmospheric pressure, and comparison with the results obtained using other diagnostic methods has been done. - Highlights: • An alternative method to measure the electron density in plasmas from two Balmer series hydrogen lines (H{sub α} and H{sub β}) is presented. • The method is very convenient for plasmas with electron densities of the order of 10{sup 14} cm{sup −3} and above, at low gas temperatures. • It has been applied to the determination of the electron density of an argon microwave plasma at atmospheric pressure. • Results from it are in good agreement with previous ones obtained using other diagnostic methods.
Directory of Open Access Journals (Sweden)
Benoit Parmentier
2014-12-01
Full Text Available Characterizing biophysical changes in land change areas over large regions with short and noisy multivariate time series and multiple temporal parameters remains a challenging task. Most studies focus on detection rather than the characterization, i.e., the manner by which surface state variables are altered by the process of changes. In this study, a procedure is presented to extract and characterize simultaneous temporal changes in MODIS multivariate times series from three surface state variables the Normalized Difference Vegetation Index (NDVI, land surface temperature (LST and albedo (ALB. The analysis involves conducting a seasonal trend analysis (STA to extract three seasonal shape parameters (Amplitude 0, Amplitude 1 and Amplitude 2 and using principal component analysis (PCA to contrast trends in change and no-change areas. We illustrate the method by characterizing trends in burned and unburned pixels in Alaska over the 2001–2009 time period. Findings show consistent and meaningful extraction of temporal patterns related to fire disturbances. The first principal component (PC1 is characterized by a decrease in mean NDVI (Amplitude 0 with a concurrent increase in albedo (the mean and the annual amplitude and an increase in LST annual variability (Amplitude 1. These results provide systematic empirical evidence of surface changes associated with one type of land change, fire disturbances, and suggest that STA with PCA may be used to characterize many other types of land transitions over large landscape areas using multivariate Earth observation time series.
Forecasting malaria cases using climatic factors in delhi, India: a time series analysis.
Kumar, Varun; Mangal, Abha; Panesar, Sanjeet; Yadav, Geeta; Talwar, Richa; Raut, Deepak; Singh, Saudan
2014-01-01
Background. Malaria still remains a public health problem in developing countries and changing environmental and climatic factors pose the biggest challenge in fighting against the scourge of malaria. Therefore, the study was designed to forecast malaria cases using climatic factors as predictors in Delhi, India. Methods. The total number of monthly cases of malaria slide positives occurring from January 2006 to December 2013 was taken from the register maintained at the malaria clinic at Rural Health Training Centre (RHTC), Najafgarh, Delhi. Climatic data of monthly mean rainfall, relative humidity, and mean maximum temperature were taken from Regional Meteorological Centre, Delhi. Expert modeler of SPSS ver. 21 was used for analyzing the time series data. Results. Autoregressive integrated moving average, ARIMA (0,1,1) (0,1,0)(12), was the best fit model and it could explain 72.5% variability in the time series data. Rainfall (P value = 0.004) and relative humidity (P value = 0.001) were found to be significant predictors for malaria transmission in the study area. Seasonal adjusted factor (SAF) for malaria cases shows peak during the months of August and September. Conclusion. ARIMA models of time series analysis is a simple and reliable tool for producing reliable forecasts for malaria in Delhi, India.
Capturing Context-Related Change in Emotional Dynamics via Fixed Moderated Time Series Analysis.
Adolf, Janne K; Voelkle, Manuel C; Brose, Annette; Schmiedek, Florian
2017-01-01
Much of recent affect research relies on intensive longitudinal studies to assess daily emotional experiences. The resulting data are analyzed with dynamic models to capture regulatory processes involved in emotional functioning. Daily contexts, however, are commonly ignored. This may not only result in biased parameter estimates and wrong conclusions, but also ignores the opportunity to investigate contextual effects on emotional dynamics. With fixed moderated time series analysis, we present an approach that resolves this problem by estimating context-dependent change in dynamic parameters in single-subject time series models. The approach examines parameter changes of known shape and thus addresses the problem of observed intra-individual heterogeneity (e.g., changes in emotional dynamics due to observed changes in daily stress). In comparison to existing approaches to unobserved heterogeneity, model estimation is facilitated and different forms of change can readily be accommodated. We demonstrate the approach's viability given relatively short time series by means of a simulation study. In addition, we present an empirical application, targeting the joint dynamics of affect and stress and how these co-vary with daily events. We discuss potentials and limitations of the approach and close with an outlook on the broader implications for understanding emotional adaption and development.
International Nuclear Information System (INIS)
Zhang, Wenchao; Tan, Sichao; Gao, Puzhen; Wang, Zhanwei; Zhang, Liansheng; Zhang, Hong
2014-01-01
Highlights: • Natural circulation flow instabilities in rolling motion are studied. • The method of non-linear time series analysis is used. • Non-linear evolution characteristic of flow instability is analyzed. • Irregular complex flow oscillations are chaotic oscillations. • The effect of rolling parameter on the threshold of chaotic oscillation is studied. - Abstract: Non-linear characteristics of natural circulation flow instabilities under rolling motion conditions were studied by the method of non-linear time series analysis. Experimental flow time series of different dimensionless power and rolling parameters were analyzed based on phase space reconstruction theory. Attractors which were reconstructed in phase space and the geometric invariants, including correlation dimension, Kolmogorov entropy and largest Lyapunov exponent, were determined. Non-linear characteristics of natural circulation flow instabilities under rolling motion conditions was studied based on the results of the geometric invariant analysis. The results indicated that the values of the geometric invariants first increase and then decrease as dimensionless power increases which indicated the non-linear characteristics of the system first enhance and then weaken. The irregular complex flow oscillation is typical chaotic oscillation because the value of geometric invariants is at maximum. The threshold of chaotic oscillation becomes larger as the rolling frequency or rolling amplitude becomes big. The main influencing factors that influence the non-linear characteristics of the natural circulation system under rolling motion are thermal driving force, flow resistance and the additional forces caused by rolling motion. The non-linear characteristics of the natural circulation system under rolling motion changes caused by the change of the feedback and coupling degree among these influencing factors when the dimensionless power or rolling parameters changes
Seasonal and annual precipitation time series trend analysis in North Carolina, United States
Sayemuzzaman, Mohammad; Jha, Manoj K.
2014-02-01
The present study performs the spatial and temporal trend analysis of the annual and seasonal time-series of a set of uniformly distributed 249 stations precipitation data across the state of North Carolina, United States over the period of 1950-2009. The Mann-Kendall (MK) test, the Theil-Sen approach (TSA) and the Sequential Mann-Kendall (SQMK) test were applied to quantify the significance of trend, magnitude of trend, and the trend shift, respectively. Regional (mountain, piedmont and coastal) precipitation trends were also analyzed using the above-mentioned tests. Prior to the application of statistical tests, the pre-whitening technique was used to eliminate the effect of autocorrelation of precipitation data series. The application of the above-mentioned procedures has shown very notable statewide increasing trend for winter and decreasing trend for fall precipitation. Statewide mixed (increasing/decreasing) trend has been detected in annual, spring, and summer precipitation time series. Significant trends (confidence level ≥ 95%) were detected only in 8, 7, 4 and 10 nos. of stations (out of 249 stations) in winter, spring, summer, and fall, respectively. Magnitude of the highest increasing (decreasing) precipitation trend was found about 4 mm/season (- 4.50 mm/season) in fall (summer) season. Annual precipitation trend magnitude varied between - 5.50 mm/year and 9 mm/year. Regional trend analysis found increasing precipitation in mountain and coastal regions in general except during the winter. Piedmont region was found to have increasing trends in summer and fall, but decreasing trend in winter, spring and on an annual basis. The SQMK test on "trend shift analysis" identified a significant shift during 1960 - 70 in most parts of the state. Finally, the comparison between winter (summer) precipitations with the North Atlantic Oscillation (Southern Oscillation) indices concluded that the variability and trend of precipitation can be explained by the
Galván, Jorge E.; Gil, Diego M.; Lanús, Hernán E.; Altabef, Aida Ben
2015-02-01
The fourth member of the series of compounds of the type POX3 with X = I was synthesized and characterized by infrared spectroscopy. The geometrical parameters and vibrational properties of POX3 (X = F, Cl, Br, I) molecules were investigated theoretically by means DFT and ab initio methods. Available geometrical and vibrational data were used together with theoretical calculations in order to obtain a set of scaled force constants. The observed trends in geometrical parameters are analyzed and compared with those obtained in a previous work for the VOX3 (X = F, Cl, Br, I) series of compounds. NBO analysis was performed in order to know the hyper-conjugative interactions that favor one structure over another. The molecular properties such as ionization potential, electron affinity, electronegativity, chemical potential, chemical hardness, softness and global electrophilicity index have been deduced from HOMO-LUMO analysis.
FREQUENCY ANALYSIS OF MODIS NDVI TIME SERIES FOR DETERMINING HOTSPOT OF LAND DEGRADATION IN MONGOLIA
Directory of Open Access Journals (Sweden)
E. Nasanbat
2018-04-01
Full Text Available This study examines MODIS NDVI satellite imagery time series can be used to determine hotspot of land degradation area in whole Mongolia. The trend statistical analysis of Mann-Kendall was applied to a 16-year MODIS NDVI satellite imagery record, based on 16-day composited temporal data (from May to September for growing seasons and from 2000 to 2016. We performed to frequency analysis that resulting NDVI residual trend pattern would enable successful determined of negative and positive changes in photo synthetically health vegetation. Our result showed that negative and positive values and generated a map of significant trends. Also, we examined long-term of meteorological parameters for the same period. The result showed positive and negative NDVI trends concurred with land cover types change representing an improve or a degrade in vegetation, respectively. Also, integrated the climate parameters which were precipitation and air temperature changes in the same time period seem to have had an affecting on huge NDVI trend area. The time series trend analysis approach applied successfully determined hotspot of an improvement and a degraded area due to land degradation and desertification.
Frequency Analysis of Modis Ndvi Time Series for Determining Hotspot of Land Degradation in Mongolia
Nasanbat, E.; Sharav, S.; Sanjaa, T.; Lkhamjav, O.; Magsar, E.; Tuvdendorj, B.
2018-04-01
This study examines MODIS NDVI satellite imagery time series can be used to determine hotspot of land degradation area in whole Mongolia. The trend statistical analysis of Mann-Kendall was applied to a 16-year MODIS NDVI satellite imagery record, based on 16-day composited temporal data (from May to September) for growing seasons and from 2000 to 2016. We performed to frequency analysis that resulting NDVI residual trend pattern would enable successful determined of negative and positive changes in photo synthetically health vegetation. Our result showed that negative and positive values and generated a map of significant trends. Also, we examined long-term of meteorological parameters for the same period. The result showed positive and negative NDVI trends concurred with land cover types change representing an improve or a degrade in vegetation, respectively. Also, integrated the climate parameters which were precipitation and air temperature changes in the same time period seem to have had an affecting on huge NDVI trend area. The time series trend analysis approach applied successfully determined hotspot of an improvement and a degraded area due to land degradation and desertification.
Wet tropospheric delays forecast based on Vienna Mapping Function time series analysis
Rzepecka, Zofia; Kalita, Jakub
2016-04-01
It is well known that the dry part of the zenith tropospheric delay (ZTD) is much easier to model than the wet part (ZTW). The aim of the research is applying stochastic modeling and prediction of ZTW using time series analysis tools. Application of time series analysis enables closer understanding of ZTW behavior as well as short-term prediction of future ZTW values. The ZTW data used for the studies were obtained from the GGOS service hold by Vienna technical University. The resolution of the data is six hours. ZTW for the years 2010 -2013 were adopted for the study. The International GNSS Service (IGS) permanent stations LAMA and GOPE, located in mid-latitudes, were admitted for the investigations. Initially the seasonal part was separated and modeled using periodic signals and frequency analysis. The prominent annual and semi-annual signals were removed using sines and consines functions. The autocorrelation of the resulting signal is significant for several days (20-30 samples). The residuals of this fitting were further analyzed and modeled with ARIMA processes. For both the stations optimal ARMA processes based on several criterions were obtained. On this basis predicted ZTW values were computed for one day ahead, leaving the white process residuals. Accuracy of the prediction can be estimated at about 3 cm.
Time series analysis of reference crop evapotranspiration for Bokaro District, Jharkhand, India
Directory of Open Access Journals (Sweden)
Gautam Ratnesh
2016-09-01
Full Text Available Evapotranspiration is the one of the major role playing element in water cycle. More accurate measurement and forecasting of Evapotranspiration would enable more efficient water resources management. This study, is therefore, particularly focused on evapotranspiration modelling and forecasting, since forecasting would provide better information for optimal water resources management. There are numerous techniques of evapotranspiration forecasting that include autoregressive (AR and moving average (MA, autoregressive moving average (ARMA, autoregressive integrated moving average (ARIMA, Thomas Feiring, etc. Out of these models ARIMA model has been found to be more suitable for analysis and forecasting of hydrological events. Therefore, in this study ARIMA models have been used for forecasting of mean monthly reference crop evapotranspiration by stochastic analysis. The data series of 102 years i.e. 1224 months of Bokaro District were used for analysis and forecasting. Different order of ARIMA model was selected on the basis of autocorrelation function (ACF and partial autocorrelation (PACF of data series. Maximum likelihood method was used for determining the parameters of the models. To see the statistical parameter of model, best fitted model is ARIMA (0, 1, 4 (0, 1, 112.
Energy Technology Data Exchange (ETDEWEB)
Zunino, Luciano, E-mail: lucianoz@ciop.unlp.edu.ar [Centro de Investigaciones Ópticas (CONICET La Plata – CIC), C.C. 3, 1897 Gonnet (Argentina); Departamento de Ciencias Básicas, Facultad de Ingeniería, Universidad Nacional de La Plata (UNLP), 1900 La Plata (Argentina); Olivares, Felipe, E-mail: olivaresfe@gmail.com [Instituto de Física, Pontificia Universidad Católica de Valparaíso (PUCV), 23-40025 Valparaíso (Chile); Scholkmann, Felix, E-mail: Felix.Scholkmann@gmail.com [Research Office for Complex Physical and Biological Systems (ROCoS), Mutschellenstr. 179, 8038 Zurich (Switzerland); Biomedical Optics Research Laboratory, Department of Neonatology, University Hospital Zurich, University of Zurich, 8091 Zurich (Switzerland); Rosso, Osvaldo A., E-mail: oarosso@gmail.com [Instituto de Física, Universidade Federal de Alagoas (UFAL), BR 104 Norte km 97, 57072-970, Maceió, Alagoas (Brazil); Instituto Tecnológico de Buenos Aires (ITBA) and CONICET, C1106ACD, Av. Eduardo Madero 399, Ciudad Autónoma de Buenos Aires (Argentina); Complex Systems Group, Facultad de Ingeniería y Ciencias Aplicadas, Universidad de los Andes, Av. Mons. Álvaro del Portillo 12.455, Las Condes, Santiago (Chile)
2017-06-15
A symbolic encoding scheme, based on the ordinal relation between the amplitude of neighboring values of a given data sequence, should be implemented before estimating the permutation entropy. Consequently, equalities in the analyzed signal, i.e. repeated equal values, deserve special attention and treatment. In this work, we carefully study the effect that the presence of equalities has on permutation entropy estimated values when these ties are symbolized, as it is commonly done, according to their order of appearance. On the one hand, the analysis of computer-generated time series is initially developed to understand the incidence of repeated values on permutation entropy estimations in controlled scenarios. The presence of temporal correlations is erroneously concluded when true pseudorandom time series with low amplitude resolutions are considered. On the other hand, the analysis of real-world data is included to illustrate how the presence of a significant number of equal values can give rise to false conclusions regarding the underlying temporal structures in practical contexts. - Highlights: • Impact of repeated values in a signal when estimating permutation entropy is studied. • Numerical and experimental tests are included for characterizing this limitation. • Non-negligible temporal correlations can be spuriously concluded by repeated values. • Data digitized with low amplitude resolutions could be especially affected. • Analysis with shuffled realizations can help to overcome this limitation.
Shirota, Yukari; Hashimoto, Takako; Fitri Sari, Riri
2018-03-01
It has been very significant to visualize time series big data. In the paper we shall discuss a new analysis method called “statistical shape analysis” or “geometry driven statistics” on time series statistical data in economics. In the paper, we analyse the agriculture, value added and industry, value added (percentage of GDP) changes from 2000 to 2010 in Asia. We handle the data as a set of landmarks on a two-dimensional image to see the deformation using the principal components. The point of the analysis method is the principal components of the given formation which are eigenvectors of its bending energy matrix. The local deformation can be expressed as the set of non-Affine transformations. The transformations give us information about the local differences between in 2000 and in 2010. Because the non-Affine transformation can be decomposed into a set of partial warps, we present the partial warps visually. The statistical shape analysis is widely used in biology but, in economics, no application can be found. In the paper, we investigate its potential to analyse the economic data.
Renal transplant lithiasis: analysis of our series and review of the literature.
Stravodimos, Konstantinos G; Adamis, Stefanos; Tyritzis, Stavros; Georgios, Zavos; Constantinides, Constantinos A
2012-01-01
Renal transplant lithiasis represents a rather uncommon complication. Even rare, it can result in significant morbidity and a devastating loss of renal function if obstruction occurs. We present our experience with graft lithiasis in our series of renal transplantations and review the literature regarding the epidemiology, pathophysiology, and current therapeutic strategies in the management of renal transplant lithiasis. In a retrospective analysis of a consecutive series of 1525 renal transplantations that were performed between January 1983 and March 2007, 7 patients were found to have allograft lithiasis. In five cases, the calculi were localized in the renal unit, and in two cases, in the ureter. A review in the English language was also performed of the Medline and PubMed databases using the keywords renal transplant lithiasis, donor-gifted lithiasis, and urological complications after kidney transplantation. Several retrospective studies regarding the incidence, etiology, as well as predisposing factors for graft lithiasis were reviewed. Data regarding the current therapeutic strategies for graft lithiasis were also evaluated, and outcomes were compared with the results of our series. Most studies report a renal transplant lithiasis incidence of 0.4% to 1%. In our series, incidence of graft lithiasis was 0.46% (n=7). Of the seven patients, three were treated via percutaneous nephrolithotripsy (PCNL); in three patients, shockwave lithotripsy (SWL) was performed; and in a single case, spontaneous passage of a urinary calculus was observed. All patients are currently stone free but still remain under close urologic surveillance. Renal transplant lithiasis requires vigilance, a high index of suspicion, prompt recognition, and management. Treatment protocols should mimic those for solitary kidneys. Minimally invasive techniques are available to remove graft calculi. Long-term follow-up is essential to determine the outcome, as well as to prevent recurrence.
Chen, Wei-Shing
2011-04-01
The aim of the article is to answer the question if the Taiwan unemployment rate dynamics is generated by a non-linear deterministic dynamic process. This paper applies a recurrence plot and recurrence quantification approach based on the analysis of non-stationary hidden transition patterns of the unemployment rate of Taiwan. The case study uses the time series data of the Taiwan’s unemployment rate during the period from 1978/01 to 2010/06. The results show that recurrence techniques are able to identify various phases in the evolution of unemployment transition in Taiwan.
Interpretation of engine cycle-to-cycle variation by chaotic time series analysis
Energy Technology Data Exchange (ETDEWEB)
Daw, C.S.; Kahl, W.K.
1990-01-01
In this paper we summarize preliminary results from applying a new mathematical technique -- chaotic time series analysis (CTSA) -- to cylinder pressure data from a spark-ignition (SI) four-stroke engine fueled with both methanol and iso-octane. Our objective is to look for the presence of deterministic chaos'' dynamics in peak pressure variations and to investigate the potential usefulness of CTSA as a diagnostic tool. Our results suggest that sequential peak cylinder pressures exhibit some characteristic features of deterministic chaos and that CTSA can extract previously unrecognized information from such data. 18 refs., 11 figs., 2 tabs.
Analysis of the gamma spectra of the uranium, actinium, and thorium decay series
International Nuclear Information System (INIS)
Momeni, M.H.
1981-09-01
This report describes the identification of radionuclides in the uranium, actinium, and thorium series by analysis of gamma spectra in the energy range of 40 to 1400 keV. Energies and absolute efficiencies for each gamma line were measured by means of a high-resolution germanium detector and compared with those in the literature. A gamma spectroscopy method, which utilizes an on-line computer for deconvolution of spectra, search and identification of each line, and estimation of activity for each radionuclide, was used to analyze soil and uranium tailings, and ore
Analysis of the development trend of China’s business administration based on time series
Jiang Rui
2016-01-01
On the general direction of the economic system, China is in a crucial period of the establishment of the modern enterprise system and reform of the macroeconomic system, and a lot of high-quality business administration talents are required to make China’s economy be stably developed. This paper carries out time series analysis of the development situation of China’s business administration major: on the whole, the society currently presents an upward trend on the demand for the business adm...
Analysis of archaeological materials through Scanning electron microscopy
International Nuclear Information System (INIS)
Camacho, A.; Tenorio C, D.; Elizalde, S.; Mandujano, C.; Cassiano, G.
2005-01-01
With the purpose to know the uses and the chemical composition of some cultural objects in the pre hispanic epoch this work presents several types of analysis for identifying them by means of the Scanning electron microscopy and its techniques as the Functional analysis of artifacts based on the 'tracks of use' analysis, also the X-ray spectroscopy and the X-ray dispersive energy (EDS) are mentioned, all of them allowing a major approach to the pre hispanic culture in Mexico. (Author)
Time Series Analysis of Onchocerciasis Data from Mexico: A Trend towards Elimination
Pérez-Rodríguez, Miguel A.; Adeleke, Monsuru A.; Orozco-Algarra, María E.; Arrendondo-Jiménez, Juan I.; Guo, Xianwu
2013-01-01
Background In Latin America, there are 13 geographically isolated endemic foci distributed among Mexico, Guatemala, Colombia, Venezuela, Brazil and Ecuador. The communities of the three endemic foci found within Mexico have been receiving ivermectin treatment since 1989. In this study, we predicted the trend of occurrence of cases in Mexico by applying time series analysis to monthly onchocerciasis data reported by the Mexican Secretariat of Health between 1988 and 2011 using the software R. Results A total of 15,584 cases were reported in Mexico from 1988 to 2011. The data of onchocerciasis cases are mainly from the main endemic foci of Chiapas and Oaxaca. The last case in Oaxaca was reported in 1998, but new cases were reported in the Chiapas foci up to 2011. Time series analysis performed for the foci in Mexico showed a decreasing trend of the disease over time. The best-fitted models with the smallest Akaike Information Criterion (AIC) were Auto-Regressive Integrated Moving Average (ARIMA) models, which were used to predict the tendency of onchocerciasis cases for two years ahead. According to the ARIMA models predictions, the cases in very low number (below 1) are expected for the disease between 2012 and 2013 in Chiapas, the last endemic region in Mexico. Conclusion The endemic regions of Mexico evolved from high onchocerciasis-endemic states to the interruption of transmission due to the strategies followed by the MSH, based on treatment with ivermectin. The extremely low level of expected cases as predicted by ARIMA models for the next two years suggest that the onchocerciasis is being eliminated in Mexico. To our knowledge, it is the first study utilizing time series for predicting case dynamics of onchocerciasis, which could be used as a benchmark during monitoring and post-treatment surveillance. PMID:23459370
Use of a Principal Components Analysis for the Generation of Daily Time Series.
Dreveton, Christine; Guillou, Yann
2004-07-01
A new approach for generating daily time series is considered in response to the weather-derivatives market. This approach consists of performing a principal components analysis to create independent variables, the values of which are then generated separately with a random process. Weather derivatives are financial or insurance products that give companies the opportunity to cover themselves against adverse climate conditions. The aim of a generator is to provide a wider range of feasible situations to be used in an assessment of risk. Generation of a temperature time series is required by insurers or bankers for pricing weather options. The provision of conditional probabilities and a good representation of the interannual variance are the main challenges of a generator when used for weather derivatives. The generator was developed according to this new approach using a principal components analysis and was applied to the daily average temperature time series of the Paris-Montsouris station in France. The observed dataset was homogenized and the trend was removed to represent correctly the present climate. The results obtained with the generator show that it represents correctly the interannual variance of the observed climate; this is the main result of the work, because one of the main discrepancies of other generators is their inability to represent accurately the observed interannual climate variance—this discrepancy is not acceptable for an application to weather derivatives. The generator was also tested to calculate conditional probabilities: for example, the knowledge of the aggregated value of heating degree-days in the middle of the heating season allows one to estimate the probability if reaching a threshold at the end of the heating season. This represents the main application of a climate generator for use with weather derivatives.
Online Time Series Analysis of Land Products over Asia Monsoon Region via Giovanni
Shen, Suhung; Leptoukh, Gregory G.; Gerasimov, Irina
2011-01-01
Time series analysis is critical to the study of land cover/land use changes and climate. Time series studies at local-to-regional scales require higher spatial resolution, such as 1km or less, data. MODIS land products of 250m to 1km resolution enable such studies. However, such MODIS land data files are distributed in 10ox10o tiles, due to large data volumes. Conducting a time series study requires downloading all tiles that include the study area for the time period of interest, and mosaicking the tiles spatially. This can be an extremely time-consuming process. In support of the Monsoon Asia Integrated Regional Study (MAIRS) program, NASA GES DISC (Goddard Earth Sciences Data and Information Services Center) has processed MODIS land products at 1 km resolution over the Asia monsoon region (0o-60oN, 60o-150oE) with a common data structure and format. The processed data have been integrated into the Giovanni system (Goddard Interactive Online Visualization ANd aNalysis Infrastructure) that enables users to explore, analyze, and download data over an area and time period of interest easily. Currently, the following regional MODIS land products are available in Giovanni: 8-day 1km land surface temperature and active fire, monthly 1km vegetation index, and yearly 0.05o, 500m land cover types. More data will be added in the near future. By combining atmospheric and oceanic data products in the Giovanni system, it is possible to do further analyses of environmental and climate changes associated with the land, ocean, and atmosphere. This presentation demonstrates exploring land products in the Giovanni system with sample case scenarios.
Imaging hydrated microbial extracellular polymers: Comparative analysis by electron microscopy
Energy Technology Data Exchange (ETDEWEB)
Dohnalkova, A.C.; Marshall, M. J.; Arey, B. W.; Williams, K. H.; Buck, E. C.; Fredrickson, J. K.
2011-01-01
Microbe-mineral and -metal interactions represent a major intersection between the biosphere and geosphere but require high-resolution imaging and analytical tools for investigating microscale associations. Electron microscopy has been used extensively for geomicrobial investigations and although used bona fide, the traditional methods of sample preparation do not preserve the native morphology of microbiological components, especially extracellular polymers. Herein, we present a direct comparative analysis of microbial interactions using conventional electron microscopy approaches of imaging at room temperature and a suite of cryogenic electron microscopy methods providing imaging in the close-to-natural hydrated state. In situ, we observed an irreversible transformation of the hydrated bacterial extracellular polymers during the traditional dehydration-based sample preparation that resulted in their collapse into filamentous structures. Dehydration-induced polymer collapse can lead to inaccurate spatial relationships and hence could subsequently affect conclusions regarding nature of interactions between microbial extracellular polymers and their environment.
BRAND ANALYSIS OF LG ELECTRONICS: A CASE STUDY
Directory of Open Access Journals (Sweden)
Syed Fida Hussain Shah
2013-04-01
Full Text Available LG Electronics is a Korean based global brand in the field of consumer electronics, home appliances and mobile communications. The critical analysis in identifying the steps taken by the LG Electronics in the light of the existing literature review helps us to correlate these steps with the enhanced brand image, brand value and brand positioning. Information is collected from various reports i.e., LG Annual reports; International Magazines from the world of Business and Tech-nology; research literatures and other reputable sources. Innovation & design and constant obsolescence of ICT and IT Products (i.e., mobiles in particular, LG have to stick on R&D, design strategies and innovation and creativity for competing in the global market.
Series: Practical guidance to qualitative research. Part 3: Sampling, data collection and analysis.
Moser, Albine; Korstjens, Irene
2018-12-01
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 (FAQs). This 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 qualitative research papers. The second article focused on context, research questions and designs, and referred to publications for further reading. This third article addresses FAQs about sampling, data collection and analysis. The data collection plan needs to be broadly defined and open at first, and become flexible during data collection. Sampling strategies should be chosen in such a way that they yield rich information and are consistent with the methodological approach used. Data saturation determines sample size and will be different for each study. The most commonly used data collection methods are participant observation, face-to-face in-depth interviews and focus group discussions. Analyses in ethnographic, phenomenological, grounded theory, and content analysis studies yield different narrative findings: a detailed description of a culture, the essence of the lived experience, a theory, and a descriptive summary, respectively. The fourth and final article will focus on trustworthiness and publishing qualitative research.
Disentangling Time-series Spectra with Gaussian Processes: Applications to Radial Velocity Analysis
Energy Technology Data Exchange (ETDEWEB)
Czekala, Ian [Kavli Institute for Particle Astrophysics and Cosmology, Stanford University, Stanford, CA 94305 (United States); Mandel, Kaisey S.; Andrews, Sean M.; Dittmann, Jason A. [Harvard-Smithsonian Center for Astrophysics, 60 Garden Street, Cambridge, MA 02138 (United States); Ghosh, Sujit K. [Department of Statistics, NC State University, 2311 Stinson Drive, Raleigh, NC 27695 (United States); Montet, Benjamin T. [Department of Astronomy and Astrophysics, University of Chicago, 5640 S. Ellis Avenue, Chicago, IL 60637 (United States); Newton, Elisabeth R., E-mail: iczekala@stanford.edu [Massachusetts Institute of Technology, Cambridge, MA 02138 (United States)
2017-05-01
Measurements of radial velocity variations from the spectroscopic monitoring of stars and their companions are essential for a broad swath of astrophysics; these measurements provide access to the fundamental physical properties that dictate all phases of stellar evolution and facilitate the quantitative study of planetary systems. The conversion of those measurements into both constraints on the orbital architecture and individual component spectra can be a serious challenge, however, especially for extreme flux ratio systems and observations with relatively low sensitivity. Gaussian processes define sampling distributions of flexible, continuous functions that are well-motivated for modeling stellar spectra, enabling proficient searches for companion lines in time-series spectra. We introduce a new technique for spectral disentangling, where the posterior distributions of the orbital parameters and intrinsic, rest-frame stellar spectra are explored simultaneously without needing to invoke cross-correlation templates. To demonstrate its potential, this technique is deployed on red-optical time-series spectra of the mid-M-dwarf binary LP661-13. We report orbital parameters with improved precision compared to traditional radial velocity analysis and successfully reconstruct the primary and secondary spectra. We discuss potential applications for other stellar and exoplanet radial velocity techniques and extensions to time-variable spectra. The code used in this analysis is freely available as an open-source Python package.
Harikrishnan, K. P.; Misra, R.; Ambika, G.
2009-09-01
We show that the combined use of correlation dimension (D2) and correlation entropy (K2) as discriminating measures can extract a more accurate information regarding the different types of noise present in a time series data. For this, we make use of an algorithmic approach for computing D2 and K2 proposed by us recently [Harikrishnan KP, Misra R, Ambika G, Kembhavi AK. Physica D 2006;215:137; Harikrishnan KP, Ambika G, Misra R. Mod Phys Lett B 2007;21:129; Harikrishnan KP, Misra R, Ambika G. Pramana - J Phys, in press], which is a modification of the standard Grassberger-Proccacia scheme. While the presence of white noise can be easily identified by computing D2 of data and surrogates, K2 is a better discriminating measure to detect colored noise in the data. Analysis of time series from a real world system involving both white and colored noise is presented as evidence. To our knowledge, this is the first time that such a combined analysis is undertaken on a real world data.
On-line diagnostic techniques for air-operated control valves based on time series analysis
International Nuclear Information System (INIS)
Ito, Kenji; Matsuoka, Yoshinori; Minamikawa, Shigeru; Komatsu, Yasuki; Satoh, Takeshi.
1996-01-01
The objective of this research is to study the feasibility of applying on-line diagnostic techniques based on time series analysis to air-operated control valves - numerous valves of the type which are used in PWR plants. Generally the techniques can detect anomalies by failures in the initial stages for which detection is difficult by conventional surveillance of process parameters measured directly. However, the effectiveness of these techniques depends on the system being diagnosed. The difficulties in applying diagnostic techniques to air-operated control valves seem to come from the reduced sensitivity of their response as compared with hydraulic control systems, as well as the need to identify anomalies in low level signals that fluctuate only slightly but continuously. In this research, simulation tests were performed by setting various kinds of failure modes for a test valve with the same specifications as of a valve actually used in the plants. Actual control signals recorded from an operating plant were then used as input signals for simulation. The results of the tests confirmed the feasibility of applying on-line diagnostic techniques based on time series analysis to air-operated control valves. (author)
Visibility graph analysis of heart rate time series and bio-marker of congestive heart failure
Bhaduri, Anirban; Bhaduri, Susmita; Ghosh, Dipak
2017-09-01
Study of RR interval time series for Congestive Heart Failure had been an area of study with different methods including non-linear methods. In this article the cardiac dynamics of heart beat are explored in the light of complex network analysis, viz. visibility graph method. Heart beat (RR Interval) time series data taken from Physionet database [46, 47] belonging to two groups of subjects, diseased (congestive heart failure) (29 in number) and normal (54 in number) are analyzed with the technique. The overall results show that a quantitative parameter can significantly differentiate between the diseased subjects and the normal subjects as well as different stages of the disease. Further, the data when split into periods of around 1 hour each and analyzed separately, also shows the same consistent differences. This quantitative parameter obtained using the visibility graph analysis thereby can be used as a potential bio-marker as well as a subsequent alarm generation mechanism for predicting the onset of Congestive Heart Failure.
Multifractal analysis of visibility graph-based Ito-related connectivity time series.
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.
International Nuclear Information System (INIS)
Ge Hu; Qing She; Lei Guo
2012-01-01
In this paper, we synthesize three Re(I) complexes of Re(CO) 3 (PPO)Br, Re(CO) 3 (PTO)Br, and Re(CO) 3 (PBI)Br, where PPO=2-phenyl-5-(pyridin-2-yl)-1,3,4-oxadiazole, PTO=2-(pyridin-2-yl)-5-p-tolyl-1,3,4-oxadiazole, PBI=2-(pyridin-2-yl)-1H-benzo[d]imidazole. Their single crystals and photophysical properties are measured and discussed in detail. The correlation between ligand structure and corresponding PL characteristics of Re(I) complex has been investigated. It is found that a ligand with strong electron-donor can efficiently increase both absorption and emissive energy of Re(I) complex. In addition, electron-rich ligand can increase the electron density of the complex and thus enhance the oscillator strength of electronic transition, improving the photoluminescence performance. - Highlights: ► Three novel phosphorescent Re(I) complexes are synthesized. ► Molecular structures, photophysical, and electronic properties are studied. ► Strong electron-donor can increase emissive energy. ► Electron-rich ligand can enhance the oscillator strength of electronic transition.
van der Krieke, Lian; Emerencia, Ando C; Bos, Elisabeth H; Rosmalen, Judith Gm; Riese, Harriëtte; Aiello, Marco; Sytema, Sjoerd; de Jonge, Peter
2015-01-01
BACKGROUND: Health promotion can be tailored by combining ecological momentary assessments (EMA) with time series analysis. This combined method allows for studying the temporal order of dynamic relationships among variables, which may provide concrete indications for intervention. However,
Investigation on Law and Economics Based on Complex Network and Time Series Analysis
Yang, Jian; Qu, Zhao; Chang, Hui
2015-01-01
The research focuses on the cooperative relationship and the strategy tendency among three mutually interactive parties in financing: small enterprises, commercial banks and micro-credit companies. Complex network theory and time series analysis were applied to figure out the quantitative evidence. Moreover, this paper built up a fundamental model describing the particular interaction among them through evolutionary game. Combining the results of data analysis and current situation, it is justifiable to put forward reasonable legislative recommendations for regulations on lending activities among small enterprises, commercial banks and micro-credit companies. The approach in this research provides a framework for constructing mathematical models and applying econometrics and evolutionary game in the issue of corporation financing. PMID:26076460
Agarwal, G. C.; Osafo-Charles, F.; Oneill, W. D.; Gottlieb, G. L.
1982-01-01
Time series analysis is applied to model human operator dynamics in pursuit and compensatory tracking modes. The normalized residual criterion is used as a one-step analytical tool to encompass the processes of identification, estimation, and diagnostic checking. A parameter constraining technique is introduced to develop more reliable models of human operator dynamics. The human operator is adequately modeled by a second order dynamic system both in pursuit and compensatory tracking modes. In comparing the data sampling rates, 100 msec between samples is adequate and is shown to provide better results than 200 msec sampling. The residual power spectrum and eigenvalue analysis show that the human operator is not a generator of periodic characteristics.
Analysis of the Main Factors Influencing Food Production in China Based on Time Series Trend Chart
Institute of Scientific and Technical Information of China (English)
Shuangjin; WANG; Jianying; LI
2014-01-01
Based on the annual sample data on food production in China since the reform and opening up,we select 8 main factors influencing the total food production( growing area,application rate of chemical fertilizer,effective irrigation area,the affected area,total machinery power,food production cost index,food production price index,financial funds for supporting agriculture,farmers and countryside),and put them into categories of material input,resources and environment,and policy factors. Using the factor analysis,we carry out the multi-angle analysis of these typical influencing factors one by one through the time series trend chart. It is found that application rate of chemical fertilizer,the growing area of food crops and drought-affected area become the key factors affecting food production. On this basis,we set forth the corresponding recommendations for improving the comprehensive food production capacity.
Automated preparation of Kepler time series of planet hosts for asteroseismic analysis
DEFF Research Database (Denmark)
Handberg, R.; Lund, M. N.
2014-01-01
. In this paper we present the KASOC Filter, which is used to automatically prepare data from the Kepler/K2 mission for asteroseismic analyses of solar-like planet host stars. The methods are very effective at removing unwanted signals of both instrumental and planetary origins and produce significantly cleaner......One of the tasks of the Kepler Asteroseismic Science Operations Center (KASOC) is to provide asteroseismic analyses on Kepler Objects of Interest (KOIs). However, asteroseismic analysis of planetary host stars presents some unique complications with respect to data preprocessing, compared to pure...... asteroseismic targets. If not accounted for, the presence of planetary transits in the photometric time series often greatly complicates or even hinders these asteroseismic analyses. This drives the need for specialised methods of preprocessing data to make them suitable for asteroseismic analysis...
Time series modeling for analysis and control advanced autopilot and monitoring systems
Ohtsu, Kohei; Kitagawa, Genshiro
2015-01-01
This book presents multivariate time series methods for the analysis and optimal control of feedback systems. Although ships’ autopilot systems are considered through the entire book, the methods set forth in this book can be applied to many other complicated, large, or noisy feedback control systems for which it is difficult to derive a model of the entire system based on theory in that subject area. The basic models used in this method are the multivariate autoregressive model with exogenous variables (ARX) model and the radial bases function net-type coefficients ARX model. The noise contribution analysis can then be performed through the estimated autoregressive (AR) model and various types of autopilot systems can be designed through the state–space representation of the models. The marine autopilot systems addressed in this book include optimal controllers for course-keeping motion, rolling reduction controllers with rudder motion, engine governor controllers, noise adaptive autopilots, route-tracki...
Use of a prototype pulse oximeter for time series analysis of heart rate variability
González, Erika; López, Jehú; Hautefeuille, Mathieu; Velázquez, Víctor; Del Moral, Jésica
2015-05-01
This work presents the development of a low cost pulse oximeter prototype consisting of pulsed red and infrared commercial LEDs and a broad spectral photodetector used to register time series of heart rate and oxygen saturation of blood. This platform, besides providing these values, like any other pulse oximeter, processes the signals to compute a power spectrum analysis of the patient heart rate variability in real time and, additionally, the device allows access to all raw and analyzed data if databases construction is required or another kind of further analysis is desired. Since the prototype is capable of acquiring data for long periods of time, it is suitable for collecting data in real life activities, enabling the development of future wearable applications.
Curceac, S.; Ternynck, C.; Ouarda, T.
2015-12-01
Over the past decades, a substantial amount of research has been conducted to model and forecast climatic variables. In this study, Nonparametric Functional Data Analysis (NPFDA) methods are applied to forecast air temperature and wind speed time series in Abu Dhabi, UAE. The dataset consists of hourly measurements recorded for a period of 29 years, 1982-2010. The novelty of the Functional Data Analysis approach is in expressing the data as curves. In the present work, the focus is on daily forecasting and the functional observations (curves) express the daily measurements of the above mentioned variables. We apply a non-linear regression model with a functional non-parametric kernel estimator. The computation of the estimator is performed using an asymmetrical quadratic kernel function for local weighting based on the bandwidth obtained by a cross validation procedure. The proximities between functional objects are calculated by families of semi-metrics based on derivatives and Functional Principal Component Analysis (FPCA). Additionally, functional conditional mode and functional conditional median estimators are applied and the advantages of combining their results are analysed. A different approach employs a SARIMA model selected according to the minimum Akaike (AIC) and Bayessian (BIC) Information Criteria and based on the residuals of the model. The performance of the models is assessed by calculating error indices such as the root mean square error (RMSE), relative RMSE, BIAS and relative BIAS. The results indicate that the NPFDA models provide more accurate forecasts than the SARIMA models. Key words: Nonparametric functional data analysis, SARIMA, time series forecast, air temperature, wind speed
Differentiation of closely related fungi by electronic nose analysis
DEFF Research Database (Denmark)
Karlshøj, Kristian; Nielsen, Per Væggemose; Larsen, Thomas Ostenfeld
2007-01-01
the electronic nose potentially responded to, volatile metabolites were collected, by diffusive sampling overnight onto tubes containing Tenax TA, between the 7th and 8th day of Incubation.Volatiles were analyzed by gas chromatography coupled to mass spectrometry and the results indicated that mail alcohols...... as well as the noacheese ociated P. expansum have been investigated by electronic nose, GC-MS, and LGMS analysis. The isolates were inoculated on yeast extract sucroseagar in 20-mL headspace flasks and electronicnose analysis was performed daily for a-74period. To assess which volatile metabolites...... by high pressure liquid chromatography, coupled-to a diode array detector and a time of flight mass spectrometer. Several mycotoxins were detected in samples from the specles P.nordicum, P.roqueforti, P.paneum, P.carneum, and P.expansum. Differentiation of closely related mycotoxin producing fungi...
Chloride ingress profiles measured by electron probe micro analysis
DEFF Research Database (Denmark)
Jensen, Ole mejlhede; Coats, Alison M.; Glasser, Fred P.
1996-01-01
Traditional techniques for measuring chloride ingress profiles do not apply well to high performance cement paste systems; the geometric resolution of the traditional measuring techniques is too low. In this paper measurements by Electron Probe Micro Analysis (EPMA) are presented. EPMA is demonst......Traditional techniques for measuring chloride ingress profiles do not apply well to high performance cement paste systems; the geometric resolution of the traditional measuring techniques is too low. In this paper measurements by Electron Probe Micro Analysis (EPMA) are presented. EPMA...... is demonstated to determine chloride ingress in cement paste on a micrometer scale. Potential chloride ingress routes such as cracks or the paste-aggregate interface may also be characterized by EPMA. Copyright (C) 1996 Elsevier Science Ltd...
Technology and Power. A Foucauldian Analysis of Electronic Monitoring Discourses
Anna Vitores; Miquel Domènech
2007-01-01
The article aims to show the importance of FOUCAULT within social studies of science and technology. It also illustrates how a Foucauldian analysis can be useful for studies of science, technology and society focused on power effects. To accomplish these objectives we analyze the emergence of a specific techno-scientific innovation: the electronic monitoring of offenders. We map the discontinuities and discourse dispersions linked to those practices that constitute different materializations ...
2013-12-17
... the comment (or signing the comment for an association, business, labor union, etc.). DOT's complete... design feature: The digital systems architecture for the Airbus Model A350-900 series airplanes is composed of several connected networks. This proposed network architecture is used for a diverse set of...
Forecast models for suicide: Time-series analysis with data from Italy.
Preti, Antonio; Lentini, Gianluca
2016-01-01
The prediction of suicidal behavior is a complex task. To fine-tune targeted preventative interventions, predictive analytics (i.e. forecasting future risk of suicide) is more important than exploratory data analysis (pattern recognition, e.g. detection of seasonality in suicide time series). This study sets out to investigate the accuracy of forecasting models of suicide for men and women. A total of 101 499 male suicides and of 39 681 female suicides - occurred in Italy from 1969 to 2003 - were investigated. In order to apply the forecasting model and test its accuracy, the time series were split into a training set (1969 to 1996; 336 months) and a test set (1997 to 2003; 84 months). The main outcome was the accuracy of forecasting models on the monthly number of suicides. These measures of accuracy were used: mean absolute error; root mean squared error; mean absolute percentage error; mean absolute scaled error. In both male and female suicides a change in the trend pattern was observed, with an increase from 1969 onwards to reach a maximum around 1990 and decrease thereafter. The variances attributable to the seasonal and trend components were, respectively, 24% and 64% in male suicides, and 28% and 41% in female ones. Both annual and seasonal historical trends of monthly data contributed to forecast future trends of suicide with a margin of error around 10%. The finding is clearer in male than in female time series of suicide. The main conclusion of the study is that models taking seasonality into account seem to be able to derive information on deviation from the mean when this occurs as a zenith, but they fail to reproduce it when it occurs as a nadir. Preventative efforts should concentrate on the factors that influence the occurrence of increases above the main trend in both seasonal and cyclic patterns of suicides.
Vacuum Analysis of Scanning Horn of Electron Beam Machine
International Nuclear Information System (INIS)
Suprapto; Sukidi; Sukaryono; Setyo Atmojo; Djasiman
2003-01-01
Vacuum analysis of scanning horn of electron beam machine (EBM) has been carried out. In EBM, electron beam produced by the electron gun is accelerated by the accelerating tube toward the target via scanning horn and window. To avoid the disturbance of electron beam trajectory in side the EBM, it is necessary to evacuate the EBM. In designing and constructing the scanning horn, vacuum analysis must be carried out to find the ultimate vacuum grade based on the analysis as well as on the test resulted by the vacuum pump. The ultimate vacuum grade is important and affecting the electron trajectory from electron gun to the target. The yield of the vacuum analysis show that the load gas to be evacuated were the outgassing, permeation and leakages where each value were 5.96487x10 -6 Torr liter/sec, 6.32083x10 -7 Torr liter/sec, and 1.3116234x10 -4 Torr liter/sec respectively, so that the total gas load was 1.377587x10 -4 Torr liter/sec. The total conductivity according to test result was 15.769 liter/sec, while the effective pumping rate and maximum vacuum obtained by RD 150 pump were 14.269 Torr liter/sec and 9.65x10 -6 Torr respectively, The vacuum steady state indicated by the test result was 3.5x10 -5 Torr. The pressure of 3.5x10 -5 Torr showed by the test is close to the capability of vacuum pump that is 2x10 -5 Torr. The vacuum test indicated a good result and that there was no leakage along the welding joint. In the latter of installation it considered to be has a pressure of 5x10 -6 Torr, because the aluminum gasket will be used to seal the window flanges and will be evacuated by turbomolecular pump with pumping rate of 500 liter/sec and ultimate vacuum of -10 Torr. (author)
Czech Academy of Sciences Publication Activity Database
Reshak, Ali H; Auluck, S.; Kityk, I.
2008-01-01
Roč. 47, č. 7 (2008), s. 5516-5520 ISSN 0021-4922 Institutional research plan: CEZ:AV0Z60870520 Keywords : electronic structure * optical properties Subject RIV: BO - Biophysics Impact factor: 1.309, year: 2008
An Optimized Thermal Analysis of Electronic Unit Used in Aircraft
International Nuclear Information System (INIS)
Shah, A.N.; Mir, F.; Farooq, M.; Farooq, M.
2014-01-01
In a field where change and growth is inevitable, new electronic packaging problems continuously arise. Smaller, but more powerful devices are prone to overheating causing intermittent system failures, corrupted signals and outright system failure. Current study is focused on the analysis of the optimized working of electronic equipment from thermal point of view. In order to achieve the objective, an approach was developed for the thermal analysis of Printed Circuit Board (PCB) including the heat dissipation of its electronic components and then removal of the heat in a sophisticated manner by considering the conduction and convection modes of heat transfer. Mathematical modeling was carried out for a certain problem to address the thermal design, and then a program was developed in MATLAB for the solution of model by using Newton-Raphson method. The proposed unit is to be mounted on an aircraft having suspected thermal characteristics owing to abrupt changes in pressure and temperature as aircraft moves quickly from a lower altitude to higher altitude. In current study, dominant mode of heat transfer was conduction revealing that the major portion of heat transfer takes place by copper cladding and that heat conduction along the length of PCB can be improved enormously by using even thin layer of copper. The results confirmed that temperatures of all the electronic components were within derated values. Meanwhile, it was known that convection also plays a significant role in the reduction of temperatures of the components. The reduction in nodal temperature was in the range of 13 to 42 %. Furthermore, altitude variation from sea level to 15240 m (above sea level) caused the reduction in pressure from 1atm to 0.1095 atm. Consequently, the temperature of the electronic components increased from 73.25 degree C to 83.83 degree C for first node 'a', and from 66.04 degree C to 68.47 degree C for last node 'n' because of the decrease in the convective heat transfer
Quantitative methods for the analysis of electron microscope images
DEFF Research Database (Denmark)
Skands, Peter Ulrik Vallø
1996-01-01
The topic of this thesis is an general introduction to quantitative methods for the analysis of digital microscope images. The images presented are primarily been acquired from Scanning Electron Microscopes (SEM) and interfermeter microscopes (IFM). The topic is approached though several examples...... foundation of the thesis fall in the areas of: 1) Mathematical Morphology; 2) Distance transforms and applications; and 3) Fractal geometry. Image analysis opens in general the possibility of a quantitative and statistical well founded measurement of digital microscope images. Herein lies also the conditions...
Energy Technology Data Exchange (ETDEWEB)
Masrour, R., E-mail: rachidmasrour@hotmail.com [Laboratory of Materials, Processes, Environment and Quality, Cady Ayyed University, National School of Applied Sciences, BP. 63, 46000 Safi (Morocco); LMPHE (URAC 12), Faculty of Science, Mohammed V-Agdal University, Rabat (Morocco); Hlil, E.K. [Institut Néel, CNRS et Université Joseph Fourier, BP 166, F-38042 Grenoble Cedex 9 (France); Hamedoun, M. [Institute of Nanomaterials and Nanotechnologies, MAScIR, Rabat (Morocco); Benyoussef, A. [LMPHE (URAC 12), Faculty of Science, Mohammed V-Agdal University, Rabat (Morocco); Institute of Nanomaterials and Nanotechnologies, MAScIR, Rabat (Morocco); Hassan II Academy of Science and Technology, Rabat (Morocco); Mounkachi, O.; El Moussaoui, H. [Institute of Nanomaterials and Nanotechnologies, MAScIR, Rabat (Morocco)
2014-06-01
Self-consistent ab initio calculations, based on DFT (Density Functional Theory) approach and using FLAPW (Full potential Linear Augmented Plane Wave) method, are performed to investigate both electronic and magnetic properties of the MnSe lattice. Polarized spin and spin–orbit coupling are included in calculations within the framework of the antiferromagnetic state between two adjacent Mn lattices. Magnetic moments considered to lie along (001) axes are computed. Obtained data from ab initio calculations are used as input for the high temperature series expansions (HTSEs) calculations to compute other magnetic parameters. The zero-field high temperature static susceptibility series of the spin −4.28 nearest-neighbor Ising model on face centered cubic (fcc) and lattices is thoroughly analyzed by means of a power series coherent anomaly method (CAM). The exchange interaction between the magnetic atoms and the Néel temperature are deduced using the mean filed and HTSEs theories. - Highlights: • Ab initio calculations are used to investigate both electronic and magnetic properties of the MnSe alloys. • Obtained data from ab initio calculations are used as input for the HTSEs. • The Néel temperature is obtained for MnSe alloys.
Sasmita, Yoga; Darmawan, Gumgum
2017-08-01
This research aims to evaluate the performance of forecasting by Fourier Series Analysis (FSA) and Singular Spectrum Analysis (SSA) which are more explorative and not requiring parametric assumption. Those methods are applied to predicting the volume of motorcycle sales in Indonesia from January 2005 to December 2016 (monthly). Both models are suitable for seasonal and trend component data. Technically, FSA defines time domain as the result of trend and seasonal component in different frequencies which is difficult to identify in the time domain analysis. With the hidden period is 2,918 ≈ 3 and significant model order is 3, FSA model is used to predict testing data. Meanwhile, SSA has two main processes, decomposition and reconstruction. SSA decomposes the time series data into different components. The reconstruction process starts with grouping the decomposition result based on similarity period of each component in trajectory matrix. With the optimum of window length (L = 53) and grouping effect (r = 4), SSA predicting testing data. Forecasting accuracy evaluation is done based on Mean Absolute Percentage Error (MAPE), Mean Absolute Error (MAE) and Root Mean Square Error (RMSE). The result shows that in the next 12 month, SSA has MAPE = 13.54 percent, MAE = 61,168.43 and RMSE = 75,244.92 and FSA has MAPE = 28.19 percent, MAE = 119,718.43 and RMSE = 142,511.17. Therefore, to predict volume of motorcycle sales in the next period should use SSA method which has better performance based on its accuracy.
Lecca, Paola; Mura, Ivan; Re, Angela; Barker, Gary C; Ihekwaba, Adaoha E C
2016-01-01
Chaotic behavior refers to a behavior which, albeit irregular, is generated by an underlying deterministic process. Therefore, a chaotic behavior is potentially controllable. This possibility becomes practically amenable especially when chaos is shown to be low-dimensional, i.e., to be attributable to a small fraction of the total systems components. In this case, indeed, including the major drivers of chaos in a system into the modeling approach allows us to improve predictability of the systems dynamics. Here, we analyzed the numerical simulations of an accurate ordinary differential equation model of the gene network regulating sporulation initiation in Bacillus subtilis to explore whether the non-linearity underlying time series data is due to low-dimensional chaos. Low-dimensional chaos is expectedly common in systems with few degrees of freedom, but rare in systems with many degrees of freedom such as the B. subtilis sporulation network. The estimation of a number of indices, which reflect the chaotic nature of a system, indicates that the dynamics of this network is affected by deterministic chaos. The neat separation between the indices obtained from the time series simulated from the model and those obtained from time series generated by Gaussian white and colored noise confirmed that the B. subtilis sporulation network dynamics is affected by low dimensional chaos rather than by noise. Furthermore, our analysis identifies the principal driver of the networks chaotic dynamics to be sporulation initiation phosphotransferase B (Spo0B). We then analyzed the parameters and the phase space of the system to characterize the instability points of the network dynamics, and, in turn, to identify the ranges of values of Spo0B and of the other drivers of the chaotic dynamics, for which the whole system is highly sensitive to minimal perturbation. In summary, we described an unappreciated source of complexity in the B. subtilis sporulation network by gathering
Analysis of time series for postal shipments in Regional VII East Java Indonesia
Kusrini, DE; Ulama, B. S. S.; Aridinanti, L.
2018-03-01
The change of number delivery goods through PT. Pos Regional VII East Java Indonesia indicates that the trend of increasing and decreasing the delivery of documents and non-documents in PT. Pos Regional VII East Java Indonesia is strongly influenced by conditions outside of PT. Pos Regional VII East Java Indonesia so that the prediction the number of document and non-documents requires a model that can accommodate it. Based on the time series plot monthly data fluctuations occur from 2013-2016 then the model is done using ARIMA or seasonal ARIMA and selected the best model based on the smallest AIC value. The results of data analysis about the number of shipments on each product sent through the Sub-Regional Postal Office VII East Java indicates that there are 5 post offices of 26 post offices entering the territory. The largest number of shipments is available on the PPB (Paket Pos Biasa is regular package shipment/non-document ) and SKH (Surat Kilat Khusus is Special Express Mail/document) products. The time series model generated is largely a Random walk model meaning that the number of shipment in the future is influenced by random effects that are difficult to predict. Some are AR and MA models, except for Express shipment products with Malang post office destination which has seasonal ARIMA model on lag 6 and 12. This means that the number of items in the following month is affected by the number of items in the previous 6 months.
Directory of Open Access Journals (Sweden)
Mohammad Reza
2013-01-01
Full Text Available This paper investigates the relationship between logistics and economic development in Indonesia using time series data on traffic volume and economic growth for the period from 1988 to 2010. Literature reviews were conducted to find the most applicable econometric model. The data of cargo volume that travels through sea, air and rail is used as the logistics index, while GDP is used for the economic index. The time series data was tested using stationarity and co-integration tests. Granger causality tests were employed, and then a proposed logistic model is presented. This study showed that logistics plays an important role in supporting and sustaining economic growth, in a form where the economic growth is the significant demand-pull effect towards logistics. Although the model is developed in the context of Indonesia, the overall statistical analysis can be generalized to other developing economies. Based on the model, this paper presented the importance of sustaining economic development with regards continuously improving the logistics infrastructure.
Sustainability of Italian budgetary policies: a time series analysis (1862-2013
Directory of Open Access Journals (Sweden)
Gordon L. Brady
2017-12-01
Full Text Available In this paper, we analyze the sustainability of Italian public finances using a unique database covering the period 1862-2013. This paper focuses on empirical tests for the sustainability and solvency of fiscal policies. A necessary but not sufficient condition implies that the growth rate of public debt should in the limit be smaller than the asymptotic rate of interest. In addition, the debt-to-GDP ratio must eventually stabilize at a steady-state level. The results of unit root and stationarity tests show that the variables are non-stationary at levels, but stationary in first-differences form, or I(1. However, some breaks in the series emerge, given internal and external crises (wars, oil shocks, regime changes, institutional reforms. Therefore, the empirical analysis is conducted for the entire period, as well as two sub‐periods (1862‐1913 and 1947‐2013. Moreover, anecdotal evidence and visual inspection of the series confirm our results. Furthermore, we conduct tests on cointegration, which evidence that a long-run relationship between public expenditure and revenues is found only for the first sub-period (1862-1913. In essence, the paper’s results reveal that Italy have sustainability problems in the Republican age.
Directory of Open Access Journals (Sweden)
WANG Minhao
2017-08-01
Full Text Available Plate structures with openings are common in many engineering structures. The study of the vibration characteristics of such structures is directly related to the vibration reduction, noise reduction and stability analysis of an overall structure. This paper conducts research into the free vibration characteristics of a thin elastic plate with a rectangular opening parallel to the plate in an arbitrary position. We use the improved Fourier series to represent the displacement tolerance function of the rectangular plate with an opening. We can divide the plate into an eight zone plate to simplify the calculation. We then use linear springs, which are uniformly distributed along the boundary, to simulate the classical boundary conditions and the boundary conditions of the boundaries between the regions. According to the energy functional and variational method, we can obtain the overall energy functional. We can also obtain the generalized eigenvalue matrix equation by studying the extremum of the unknown improved Fourier series expansion coefficients. We can then obtain the natural frequencies and corresponding vibration modes of the rectangular plate with an opening by solving the equation. We then compare the calculated results with the finite element method to verify the accuracy and effectiveness of the method proposed in this paper. Finally, we research the influence of the boundary condition, opening size and opening position on the vibration characteristics of a plate with an opening. This provides a theoretical reference for practical engineering application.
Directory of Open Access Journals (Sweden)
V. Tramutoli
1996-06-01
Full Text Available An autoregressive model was selected to describe geoelectrical time series. An objective technique was subsequently applied to analyze and discriminate values above (below an a priorifixed threshold possibly related to seismic events. A complete check of the model and the main guidelines to estimate the occurrence probability of extreme events are reported. A first application of the proposed technique is discussed through the analysis of the experimental data recorded by an automatic station located in Tito, a small town on the Apennine chain in Southern Italy. This region was hit by the November 1980 Irpinia-Basilicata earthquake and it is one of most active areas of the Mediterranean region. After a preliminary filtering procedure to reduce the influence of external parameters (i.e. the meteo-climatic effects, it was demonstrated that the geoelectrical residual time series are well described by means of a second order autoregressive model. Our findings outline a statistical methodology to evaluate the efficiency of electrical seismic precursors.
Evaluation of the autoregression time-series model for analysis of a noisy signal
International Nuclear Information System (INIS)
Allen, J.W.
1977-01-01
The autoregression (AR) time-series model of a continuous noisy signal was statistically evaluated to determine quantitatively the uncertainties of the model order, the model parameters, and the model's power spectral density (PSD). The result of such a statistical evaluation enables an experimenter to decide whether an AR model can adequately represent a continuous noisy signal and be consistent with the signal's frequency spectrum, and whether it can be used for on-line monitoring. Although evaluations of other types of signals have been reported in the literature, no direct reference has been found to AR model's uncertainties for continuous noisy signals; yet the evaluation is necessary to decide the usefulness of AR models of typical reactor signals (e.g., neutron detector output or thermocouple output) and the potential of AR models for on-line monitoring applications. AR and other time-series models for noisy data representation are being investigated by others since such models require fewer parameters than the traditional PSD model. For this study, the AR model was selected for its simplicity and conduciveness to uncertainty analysis, and controlled laboratory bench signals were used for continuous noisy data. (author)
Economic feasibility of biogas production in swine farms using time series analysis
Directory of Open Access Journals (Sweden)
Felipe Luis Rockenbach
2016-07-01
Full Text Available ABSTRACT: This study aimed to measure the economic feasibility and the time needed to return capital invested for the installation of a swine manure treatment system, these values originated the sale of carbon credits and/or of compensation of electric energy in swine farms, using the Box-Jenkins forecast models. It was found that the use of biogas is a viable option in a large scale with machines that operate daily for 10h or more, being the return period between 70 to 80 months. Time series analysis models are important to anticipate the series under study behavior, providing the swine breeder/investor means to reduce the financial investment risk as well as helping to decrease the production costs. Moreover, this process can be seen as another source of income and enable the breeder to be self-sufficient in the continuous supply of electric energy, which is very valuable nowadays considering that breeders are now increasingly using various technologies.
River catchment rainfall series analysis using additive Holt-Winters method
Puah, Yan Jun; Huang, Yuk Feng; Chua, Kuan Chin; Lee, Teang Shui
2016-03-01
Climate change is receiving more attention from researchers as the frequency of occurrence of severe natural disasters is getting higher. Tropical countries like Malaysia have no distinct four seasons; rainfall has become the popular parameter to assess climate change. Conventional ways that determine rainfall trends can only provide a general result in single direction for the whole study period. In this study, rainfall series were modelled using additive Holt-Winters method to examine the rainfall pattern in Langat River Basin, Malaysia. Nine homogeneous series of more than 25 years data and less than 10% missing data were selected. Goodness of fit of the forecasted models was measured. It was found that seasonal rainfall model forecasts are generally better than the monthly rainfall model forecasts. Three stations in the western region exhibited increasing trend. Rainfall in southern region showed fluctuation. Increasing trends were discovered at stations in the south-eastern region except the seasonal analysis at station 45253. Decreasing trend was found at station 2818110 in the east, while increasing trend was shown at station 44320 that represents the north-eastern region. The accuracies of both rainfall model forecasts were tested using the recorded data of years 2010-2012. Most of the forecasts are acceptable.
Ferrand, Yann; Kelton, Christina M L; Guo, Jeff J; Levy, Martin S; Yu, Yan
2011-03-01
Medicaid programs' spending on antidepressants increased from $159 million in 1991 to $2 billion in 2005. The National Institute for Health Care Management attributed this expenditure growth to increases in drug utilization, entry of newer higher-priced antidepressants, and greater prescription drug insurance coverage. Rising enrollment in Medicaid has also contributed to this expenditure growth. This research examines the impact of specific events, including branded-drug and generic entry, a black box warning, direct-to-consumer advertising (DTCA), and new indication approval, on Medicaid spending on antidepressants. Using quarterly expenditure data for 1991-2005 from the national Medicaid pharmacy claims database maintained by the Centers for Medicare and Medicaid Services, a time-series autoregressive integrated moving average (ARIMA) intervention analysis was performed on 6 specific antidepressant drugs and on overall antidepressant spending. Twenty-nine potentially relevant interventions and their dates of occurrence were identified from the literature. Each was tested for an impact on the time series. Forecasts from the models were compared with a holdout sample of actual expenditure data. Interventions with significant impacts on Medicaid expenditures included the patent expiration of Prozac® (P0.05), implying that the expanding market for antidepressants overwhelmed the effect of generic competition. Copyright © 2011 Elsevier Inc. All rights reserved.
WTF! Taboo Language in TV Series: An Analysis of Professional and Amateur Translation
Directory of Open Access Journals (Sweden)
Micòl Beseghi
2016-02-01
Full Text Available This paper focuses on the topic of censorship associated with the use of strong language and swear words in the translation of contemporary American TV series. In AVT, more specifically in Italian dubbing, the practice of censorship, in the form of suppression or toning down of what might be perceived as offensive, disturbing, too explicit or inconvenient, still remains a problematic issue. By focusing on two recent successful TV series - Girls and Orange is the New Black – which are characterized by the use of strong language (swear words, politically incorrect references and the presence of taboo subjects (homosexuality, sex, drugs, violence – this study will consider the different translation choices applied in dubbing and fansubbing. Previous academic studies have underlined the fact that professional translators tend to remove, more or less consciously, the disturbing elements from the source text, while fansubbers try to adhere as much as possible to the original text, not only in terms of linguistic contents but also in terms of register and style. The results of this analysis seem on the one hand to confirm that there is still not a systematic set of rules that govern the translation of strong language in dubbing, and on the other to indicate that the gap between professional and amateur translation is perhaps becoming less pronounced.
Learning from environmental data: Methods for analysis of forest nutrition time series
Energy Technology Data Exchange (ETDEWEB)
Sulkava, M. (Helsinki Univ. of Technology, Espoo (Finland). Computer and Information Science)
2008-07-01
Data analysis methods play an important role in increasing our knowledge of the environment as the amount of data measured from the environment increases. This thesis fits under the scope of environmental informatics and environmental statistics. They are fields, in which data analysis methods are developed and applied for the analysis of environmental data. The environmental data studied in this thesis are time series of nutrient concentration measurements of pine and spruce needles. In addition, there are data of laboratory quality and related environmental factors, such as the weather and atmospheric depositions. The most important methods used for the analysis of the data are based on the self-organizing map and linear regression models. First, a new clustering algorithm of the self-organizing map is proposed. It is found to provide better results than two other methods for clustering of the self-organizing map. The algorithm is used to divide the nutrient concentration data into clusters, and the result is evaluated by environmental scientists. Based on the clustering, the temporal development of the forest nutrition is modeled and the effect of nitrogen and sulfur deposition on the foliar mineral composition is assessed. Second, regression models are used for studying how much environmental factors and properties of the needles affect the changes in the nutrient concentrations of the needles between their first and second year of existence. The aim is to build understandable models with good prediction capabilities. Sparse regression models are found to outperform more traditional regression models in this task. Third, fusion of laboratory quality data from different sources is performed to estimate the precisions of the analytical methods. Weighted regression models are used to quantify how much the precision of observations can affect the time needed to detect a trend in environmental time series. The results of power analysis show that improving the
Development of analysis software for radiation time-series data with the use of visual studio 2005
International Nuclear Information System (INIS)
Hohara, Sin-ya; Horiguchi, Tetsuo; Ito, Shin
2008-01-01
Time-Series Analysis supplies a new vision that conventional analysis methods such as energy spectroscopy haven't achieved ever. However, application of time-series analysis to radiation measurements needs much effort in software and hardware development. By taking advantage of Visual Studio 2005, we developed an analysis software, 'ListFileConverter', for time-series radiation measurement system called as 'MPA-3'. The software is based on graphical user interface (GUI) architecture that enables us to save a large amount of operation time in the analysis, and moreover to make an easy-access to special file structure of MPA-3 data. In this paper, detailed structure of ListFileConverter is fully explained, and experimental results for counting capability of MPA-3 hardware system and those for neutron measurements with our UTR-KINKI reactor are also given. (author)
Directory of Open Access Journals (Sweden)
Peter Celec
2004-01-01
Full Text Available Cyclic variations of variables are ubiquitous in biomedical science. A number of methods for detecting rhythms have been developed, but they are often difficult to interpret. A simple procedure for detecting cyclic variations in biological time series and quantification of their probability is presented here. Analysis of rhythmic variance (ANORVA is based on the premise that the variance in groups of data from rhythmic variables is low when a time distance of one period exists between the data entries. A detailed stepwise calculation is presented including data entry and preparation, variance calculating, and difference testing. An example for the application of the procedure is provided, and a real dataset of the number of papers published per day in January 2003 using selected keywords is compared to randomized datasets. Randomized datasets show no cyclic variations. The number of papers published daily, however, shows a clear and significant (p<0.03 circaseptan (period of 7 days rhythm, probably of social origin
International Nuclear Information System (INIS)
Schaffner, D. A.; Brown, M. R.; Rock, A. B.
2016-01-01
The frequency spectrum of magnetic fluctuations as measured on the Swarthmore Spheromak Experiment is broadband and exhibits a nearly Kolmogorov 5/3 scaling. It features a steepening region which is indicative of dissipation of magnetic fluctuation energy similar to that observed in fluid and magnetohydrodynamic turbulence systems. Two non-spectrum based time-series analysis techniques are implemented on this data set in order to seek other possible signatures of turbulent dissipation beyond just the steepening of fluctuation spectra. Presented here are results for the flatness, permutation entropy, and statistical complexity, each of which exhibits a particular character at spectral steepening scales which can then be compared to the behavior of the frequency spectrum.
Singular spectrum analysis in nonlinear dynamics, with applications to paleoclimatic time series
Vautard, R.; Ghil, M.
1989-01-01
Two dimensions of a dynamical system given by experimental time series are distinguished. Statistical dimension gives a theoretical upper bound for the minimal number of degrees of freedom required to describe the attractor up to the accuracy of the data, taking into account sampling and noise problems. The dynamical dimension is the intrinsic dimension of the attractor and does not depend on the quality of the data. Singular Spectrum Analysis (SSA) provides estimates of the statistical dimension. SSA also describes the main physical phenomena reflected by the data. It gives adaptive spectral filters associated with the dominant oscillations of the system and clarifies the noise characteristics of the data. SSA is applied to four paleoclimatic records. The principal climatic oscillations and the regime changes in their amplitude are detected. About 10 degrees of freedom are statistically significant in the data. Large noise and insufficient sample length do not allow reliable estimates of the dynamical dimension.
Evaluating disease management program effectiveness: an introduction to time-series analysis.
Linden, Ariel; Adams, John L; Roberts, Nancy
2003-01-01
Currently, the most widely used method in the disease management (DM) industry for evaluating program effectiveness is referred to as the "total population approach." This model is a pretest-posttest design, with the most basic limitation being that without a control group, there may be sources of bias and/or competing extraneous confounding factors that offer a plausible rationale explaining the change from baseline. Furthermore, with the current inclination of DM programs to use financial indicators rather than program-specific utilization indicators as the principal measure of program success, additional biases are introduced that may cloud evaluation results. This paper presents a non-technical introduction to time-series analysis (using disease-specific utilization measures) as an alternative, and more appropriate, approach to evaluating DM program effectiveness than the current total population approach.
Analysis of hohlraum energetics of the SG series and the NIF experiments with energy balance model
Directory of Open Access Journals (Sweden)
Guoli Ren
2017-01-01
Full Text Available The basic energy balance model is applied to analyze the hohlraum energetics data from the Shenguang (SG series laser facilities and the National Ignition Facility (NIF experiments published in the past few years. The analysis shows that the overall hohlraum energetics data are in agreement with the energy balance model within 20% deviation. The 20% deviation might be caused by the diversity in hohlraum parameters, such as material, laser pulse, gas filling density, etc. In addition, the NIF's ignition target designs and our ignition target designs given by simulations are also in accordance with the energy balance model. This work confirms the value of the energy balance model for ignition target design and experimental data assessment, and demonstrates that the NIF energy is enough to achieve ignition if a 1D spherical radiation drive could be created, meanwhile both the laser plasma instabilities and hydrodynamic instabilities could be suppressed.
Event-sequence time series analysis in ground-based gamma-ray astronomy
International Nuclear Information System (INIS)
Barres de Almeida, U.; Chadwick, P.; Daniel, M.; Nolan, S.; McComb, L.
2008-01-01
The recent, extreme episodes of variability detected from Blazars by the leading atmospheric Cerenkov experiments motivate the development and application of specialized statistical techniques that enable the study of this rich data set to its furthest extent. The identification of the shortest variability timescales supported by the data and the actual variability structure observed in the light curves of these sources are some of the fundamental aspects being studied, that answers can bring new developments on the understanding of the physics of these objects and on the mechanisms of production of VHE gamma-rays in the Universe. Some of our efforts in studying the time variability of VHE sources involve the application of dynamic programming algorithms to the problem of detecting change-points in a Poisson sequence. In this particular paper we concentrate on the more primary issue of the applicability of counting statistics to the analysis of time-series on VHE gamma-ray astronomy.
Studies in astronomical time series analysis: Modeling random processes in the time domain
Scargle, J. D.
1979-01-01
Random process models phased in the time domain are used to analyze astrophysical time series data produced by random processes. A moving average (MA) model represents the data as a sequence of pulses occurring randomly in time, with random amplitudes. An autoregressive (AR) model represents the correlations in the process in terms of a linear function of past values. The best AR model is determined from sampled data and transformed to an MA for interpretation. The randomness of the pulse amplitudes is maximized by a FORTRAN algorithm which is relatively stable numerically. Results of test cases are given to study the effects of adding noise and of different distributions for the pulse amplitudes. A preliminary analysis of the optical light curve of the quasar 3C 273 is given.
Xie, Hong-Bo; Dokos, Socrates
2013-01-01
A new method, namely fuzzy central tendency measure (fCTM) analysis, that could enable measurement of the variability of a time series, is presented in this study. Tests on simulated data sets show that fCTM is superior to the conventional central tendency measure (CTM) in several respects, including improved relative consistency and robustness to noise. The proposed fCTM method was applied to electromyograph (EMG) signals recorded during sustained isometric contraction for tracking local muscle fatigue. The results showed that the fCTM increased significantly during the development of muscle fatigue, and it was more sensitive to the fatigue phenomenon than mean frequency (MNF), the most commonly-used muscle fatigue indicator.
Nonlinear Analysis on Cross-Correlation of Financial Time Series by Continuum Percolation System
Niu, Hongli; Wang, Jun
We establish a financial price process by continuum percolation system, in which we attribute price fluctuations to the investors’ attitudes towards the financial market, and consider the clusters in continuum percolation as the investors share the same investment opinion. We investigate the cross-correlations in two return time series, and analyze the multifractal behaviors in this relationship. Further, we study the corresponding behaviors for the real stock indexes of SSE and HSI as well as the liquid stocks pair of SPD and PAB by comparison. To quantify the multifractality in cross-correlation relationship, we employ multifractal detrended cross-correlation analysis method to perform an empirical research for the simulation data and the real markets data.
Analysis of the development trend of China’s business administration based on time series
Directory of Open Access Journals (Sweden)
Jiang Rui
2016-01-01
Full Text Available On the general direction of the economic system, China is in a crucial period of the establishment of the modern enterprise system and reform of the macroeconomic system, and a lot of high-quality business administration talents are required to make China’s economy be stably developed. This paper carries out time series analysis of the development situation of China’s business administration major: on the whole, the society currently presents an upward trend on the demand for the business administration talents. With the gradually increasing demand for the business administration talents, various colleges and universities also set up the business administration major to train a large number of administration talents, thus leading to an upward trend for the academic focus on business administration.
Series: Practical guidance to qualitative research. Part 3: Sampling, data collection and analysis
Moser, Albine; Korstjens, Irene
2018-01-01
Abstract 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 (FAQs). This 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 qualitative research papers. The second article focused on context, research questions and designs, and referred to publications for further reading. This third article addresses FAQs about sampling, data collection and analysis. The data collection plan needs to be broadly defined and open at first, and become flexible during data collection. Sampling strategies should be chosen in such a way that they yield rich information and are consistent with the methodological approach used. Data saturation determines sample size and will be different for each study. The most commonly used data collection methods are participant observation, face-to-face in-depth interviews and focus group discussions. Analyses in ethnographic, phenomenological, grounded theory, and content analysis studies yield different narrative findings: a detailed description of a culture, the essence of the lived experience, a theory, and a descriptive summary, respectively. The fourth and final article will focus on trustworthiness and publishing qualitative research. PMID:29199486
International Nuclear Information System (INIS)
Brar, Gurinder Singh; Hari, Yogeshwar; Williams, Dennis K.
2013-01-01
Pressure Vessel Code, Section VIII, Division 2 and ASME STS-1. -- Highlights: • Fourier series is used to predict the load carrying capacity of cylindrical vessel. • Reliability approach used for analysis as against the deterministic approach. • Cylindrical pressure vessel is subjected to axial end load and external pressure. • Axisymmetric and asymmetric analysis carried out for imperfect pressure vessels. • Results are compared to the recommendations laid out in ASME B and PV Code
Energy Technology Data Exchange (ETDEWEB)
Masrour, R., E-mail: rachidmasrour@hotmail.com [Laboratory of Materials, Processes, Environment and Quality, Cady Ayyed University, National School of Applied Sciences, 63 46000, Safi (Morocco); LMPHE (URAC 12), Faculty of Science, Mohammed V-Agdal University, Rabat (Morocco); Hlil, E.K. [Institut Néel, CNRS et Université Joseph Fourier, BP 166, F-38042 Grenoble cedex 9 (France); Hamedoun, M. [Institute of Nanomaterials and Nanotechnologies, MAScIR, Rabat (Morocco); Benyoussef, A. [LMPHE (URAC 12), Faculty of Science, Mohammed V-Agdal University, Rabat (Morocco); Institute of Nanomaterials and Nanotechnologies, MAScIR, Rabat (Morocco); Hassan II Academy of Science and Technology, Rabat (Morocco); Mounkachi, O.; El Moussaoui, H. [Institute of Nanomaterials and Nanotechnologies, MAScIR, Rabat (Morocco)
2015-03-15
Self-consistent ab initio calculations, based on density functional theory (DFT) approach and using a full potential linear augmented plane wave (FLAPW) method, are performed to investigate both electronic and magnetic properties of the Fe{sub 3}O{sub 4}. Polarized spin and spin–orbit coupling are included in calculations within the framework of the antiferromagnetic state between two adjacent Fe plans. Magnetic moment considered to lie along (010) axes are computed. Obtained data from ab initio calculations are used as input for the high temperature series expansions (HTSEs) calculations to compute other magnetic parameters. The exchange interactions between the magnetic atoms Fe–Fe in Fe{sub 3}O{sub 4} are given using the mean field theory. The high temperature series expansions (HTSEs) of the magnetic susceptibility of with the magnetic moments, m{sub Fe} in Fe{sub 3}O{sub 4} is given up to seventh order series in (1/k{sub B}T). The Néel temperature T{sub N} is obtained by HTSEs of the magnetic susceptibility series combined with the Padé approximant method. The critical exponent γ associated with the magnetic susceptibility is deduced as well. - Highlights: • Ab initio calculations, based on DFT approach and FLAPW are used to study the electronic properties of Fe{sub 3}O{sub 4}. • Magnetic moments of Fe{sub 1} and Fe{sub 2} are estimated to −/+3.44 µ{sub B}. • HTSE method is used to calculate the Néel temperature of Fe{sub 3}O{sub 4}.
Longitudinal Jitter Analysis of a Linear Accelerator Electron Gun
Directory of Open Access Journals (Sweden)
MingShan Liu
2016-11-01
Full Text Available We present measurements and analysis of the longitudinal timing jitter of a Beijing Electron Positron Collider (BEPCII linear accelerator electron gun. We simulated the longitudinal jitter effect of the gun using PARMELA to evaluate beam performance, including: beam profile, average energy, energy spread, and XY emittances. The maximum percentage difference of the beam parameters is calculated to be 100%, 13.27%, 42.24% and 65.01%, 86.81%, respectively. Due to this, the bunching efficiency is reduced to 54%. However, the longitudinal phase difference of the reference particle was 9.89°. The simulation results are in agreement with tests and are helpful to optimize the beam parameters by tuning the trigger timing of the gun during the bunching process.
Electron bunchlength measurement from analysis of fluctuations in spontaneous emission
International Nuclear Information System (INIS)
Catravas, P.; Leemans, W.P.; Wurtele, J.S.; Zolotorev, M.S.; Babzien, M.; Ben-Zvi, I.; Segalov, Z.; Wang, X.; Yakimenko, V.
1999-01-01
A statistical analysis of fluctuations in the spontaneous emission of a single bunch of electrons is shown to provide a new bunchlength diagnostic. This concept, originally proposed by Zolotorev and Stupakov [1], is based on the fact that shot noise from a finite bunch has a correlation length defined by the bunchlength, and therefore has a spiky spectrum. Single shot spectra of wiggler spontaneous emission have been measured at 632 nm from 44 MeV single electron bunches of 1 - 5 ps. The scaling of the spectral fluctuations with frequency resolution and the scaling of the spectral intensity distribution with bunchlength are studied. Bunchlength was extracted in a single shot measurement. Agreement was obtained between the experiment and a theoretical model, and with independent time integrated measurements. copyright 1999 American Institute of Physics
Nonlinear Analysis of Time Series in Genome-Wide Linkage Disequilibrium Data
Hernández-Lemus, Enrique; Estrada-Gil, Jesús K.; Silva-Zolezzi, Irma; Fernández-López, J. Carlos; Hidalgo-Miranda, Alfredo; Jiménez-Sánchez, Gerardo
2008-02-01
The statistical study of large scale genomic data has turned out to be a very important tool in population genetics. Quantitative methods are essential to understand and implement association studies in the biomedical and health sciences. Nevertheless, the characterization of recently admixed populations has been an elusive problem due to the presence of a number of complex phenomena. For example, linkage disequilibrium structures are thought to be more complex than their non-recently admixed population counterparts, presenting the so-called ancestry blocks, admixed regions that are not yet smoothed by the effect of genetic recombination. In order to distinguish characteristic features for various populations we have implemented several methods, some of them borrowed or adapted from the analysis of nonlinear time series in statistical physics and quantitative physiology. We calculate the main fractal dimensions (Kolmogorov's capacity, information dimension and correlation dimension, usually named, D0, D1 and D2). We also have made detrended fluctuation analysis and information based similarity index calculations for the probability distribution of correlations of linkage disequilibrium coefficient of six recently admixed (mestizo) populations within the Mexican Genome Diversity Project [1] and for the non-recently admixed populations in the International HapMap Project [2]. Nonlinear correlations showed up as a consequence of internal structure within the haplotype distributions. The analysis of these correlations as well as the scope and limitations of these procedures within the biomedical sciences are discussed.
Energy Technology Data Exchange (ETDEWEB)
Martinez-Luna, R. J.; Vega, J. M. de la; Vilches, M.; Guirado, D.; Zamora, L. I.; Lallena, A. M.
2011-07-01
Using the techniques of statistical process control (SPC) keeps track of the variable that controls the stability of the spectrum of electron beam accelerators in clinical use. In this process, applied since 1995, we obtained a high number of false alarms. Our work shows that this unexpected behavior appears to treat the variable of interest as a normal random variable, independent and identically distributed (iid), when in fact the observations of this variable are positively correlated with each other. (Author)
Gualandi, Adriano; Serpelloni, Enrico; Elina Belardinelli, Maria; Bonafede, Maurizio; Pezzo, Giuseppe; Tolomei, Cristiano
2015-04-01
A critical point in the analysis of ground displacement time series, as those measured by modern space geodetic techniques (primarly continuous GPS/GNSS and InSAR) is the development of data driven methods that allow to discern and characterize the different sources that generate the observed displacements. A widely used multivariate statistical technique is the Principal Component Analysis (PCA), which allows to reduce the dimensionality of the data space maintaining most of the variance of the dataset explained. It reproduces the original data using a limited number of Principal Components, but it also shows some deficiencies, since PCA does not perform well in finding the solution to the so-called Blind Source Separation (BSS) problem. The recovering and separation of the different sources that generate the observed ground deformation is a fundamental task in order to provide a physical meaning to the possible different sources. PCA fails in the BSS problem since it looks for a new Euclidean space where the projected data are uncorrelated. Usually, the uncorrelation condition is not strong enough and it has been proven that the BSS problem can be tackled imposing on the components to be independent. The Independent Component Analysis (ICA) is, in fact, another popular technique adopted to approach this problem, and it can be used in all those fields where PCA is also applied. An ICA approach enables us to explain the displacement time series imposing a fewer number of constraints on the model, and to reveal anomalies in the data such as transient deformation signals. However, the independence condition is not easy to impose, and it is often necessary to introduce some approximations. To work around this problem, we use a variational bayesian ICA (vbICA) method, which models the probability density function (pdf) of each source signal using a mix of Gaussian distributions. This technique allows for more flexibility in the description of the pdf of the sources
Angeler, David G; Viedma, Olga; Moreno, José M
2009-11-01
Time lag analysis (TLA) is a distance-based approach used to study temporal dynamics of ecological communities by measuring community dissimilarity over increasing time lags. Despite its increased use in recent years, its performance in comparison with other more direct methods (i.e., canonical ordination) has not been evaluated. This study fills this gap using extensive simulations and real data sets from experimental temporary ponds (true zooplankton communities) and landscape studies (landscape categories as pseudo-communities) that differ in community structure and anthropogenic stress history. Modeling time with a principal coordinate of neighborhood matrices (PCNM) approach, the canonical ordination technique (redundancy analysis; RDA) consistently outperformed the other statistical tests (i.e., TLAs, Mantel test, and RDA based on linear time trends) using all real data. In addition, the RDA-PCNM revealed different patterns of temporal change, and the strength of each individual time pattern, in terms of adjusted variance explained, could be evaluated, It also identified species contributions to these patterns of temporal change. This additional information is not provided by distance-based methods. The simulation study revealed better Type I error properties of the canonical ordination techniques compared with the distance-based approaches when no deterministic component of change was imposed on the communities. The simulation also revealed that strong emphasis on uniform deterministic change and low variability at other temporal scales is needed to result in decreased statistical power of the RDA-PCNM approach relative to the other methods. Based on the statistical performance of and information content provided by RDA-PCNM models, this technique serves ecologists as a powerful tool for modeling temporal change of ecological (pseudo-) communities.
Time Series Analysis OF SAR Image Fractal Maps: The Somma-Vesuvio Volcanic Complex Case Study
Pepe, Antonio; De Luca, Claudio; Di Martino, Gerardo; Iodice, Antonio; Manzo, Mariarosaria; Pepe, Susi; Riccio, Daniele; Ruello, Giuseppe; Sansosti, Eugenio; Zinno, Ivana
2016-04-01
The fractal dimension is a significant geophysical parameter describing natural surfaces representing the distribution of the roughness over different spatial scale; in case of volcanic structures, it has been related to the specific nature of materials and to the effects of active geodynamic processes. In this work, we present the analysis of the temporal behavior of the fractal dimension estimates generated from multi-pass SAR images relevant to the Somma-Vesuvio volcanic complex (South Italy). To this aim, we consider a Cosmo-SkyMed data-set of 42 stripmap images acquired from ascending orbits between October 2009 and December 2012. Starting from these images, we generate a three-dimensional stack composed by the corresponding fractal maps (ordered according to the acquisition dates), after a proper co-registration. The time-series of the pixel-by-pixel estimated fractal dimension values show that, over invariant natural areas, the fractal dimension values do not reveal significant changes; on the contrary, over urban areas, it correctly assumes values outside the natural surfaces fractality range and show strong fluctuations. As a final result of our analysis, we generate a fractal map that includes only the areas where the fractal dimension is considered reliable and stable (i.e., whose standard deviation computed over the time series is reasonably small). The so-obtained fractal dimension map is then used to identify areas that are homogeneous from a fractal viewpoint. Indeed, the analysis of this map reveals the presence of two distinctive landscape units corresponding to the Mt. Vesuvio and Gran Cono. The comparison with the (simplified) geological map clearly shows the presence in these two areas of volcanic products of different age. The presented fractal dimension map analysis demonstrates the ability to get a figure about the evolution degree of the monitored volcanic edifice and can be profitably extended in the future to other volcanic systems with
Hewett, Thomas T.
There are a number of areas in psychology where an electronic spreadsheet simulator can be used to study and explore functional relationships among a number of parameters. For example, when dealing with sensation, perception, and pattern recognition, it is sometimes desirable for students to understand both the basic neurophysiology and the…
Schwartz, Stanley F.
This publication introduces electronic document imaging systems and provides guidance for local governments in New York in deciding whether such systems should be adopted for their own records and information management purposes. It advises local governments on how to develop plans for using such technology by discussing its advantages and…
2013-11-18
... Boeing Company applied for a change to Type Certificate No. T00001SE Rev. 30 dated June 6, 2012 for... integration may result in security vulnerabilities from intentional or unintentional corruption of data and... material did not anticipate this type of system architecture or electronic access to aircraft systems...
Interrupted time-series analysis of regulations to reduce paracetamol (acetaminophen poisoning.
Directory of Open Access Journals (Sweden)
Oliver W Morgan
2007-04-01
Full Text Available Paracetamol (acetaminophen poisoning is the leading cause of acute liver failure in Great Britain and the United States. Successful interventions to reduced harm from paracetamol poisoning are needed. To achieve this, the government of the United Kingdom introduced legislation in 1998 limiting the pack size of paracetamol sold in shops. Several studies have reported recent decreases in fatal poisonings involving paracetamol. We use interrupted time-series analysis to evaluate whether the recent fall in the number of paracetamol deaths is different to trends in fatal poisoning involving aspirin, paracetamol compounds, antidepressants, or nondrug poisoning suicide.We calculated directly age-standardised mortality rates for paracetamol poisoning in England and Wales from 1993 to 2004. We used an ordinary least-squares regression model divided into pre- and postintervention segments at 1999. The model included a term for autocorrelation within the time series. We tested for changes in the level and slope between the pre- and postintervention segments. To assess whether observed changes in the time series were unique to paracetamol, we compared against poisoning deaths involving compound paracetamol (not covered by the regulations, aspirin, antidepressants, and nonpoisoning suicide deaths. We did this comparison by calculating a ratio of each comparison series with paracetamol and applying a segmented regression model to the ratios. No change in the ratio level or slope indicated no difference compared to the control series. There were about 2,200 deaths involving paracetamol. The age-standardised mortality rate rose from 8.1 per million in 1993 to 8.8 per million in 1997, subsequently falling to about 5.3 per million in 2004. After the regulations were introduced, deaths dropped by 2.69 per million (p = 0.003. Trends in the age-standardised mortality rate for paracetamol compounds, aspirin, and antidepressants were broadly similar to paracetamol
SRD 100 Database for Simulation of Electron Spectra for Surface Analysis (SESSA)Database for Simulation of Electron Spectra for Surface Analysis (SESSA) (PC database for purchase) This database has been designed to facilitate quantitative interpretation of Auger-electron and X-ray photoelectron spectra and to improve the accuracy of quantitation in routine analysis. The database contains all physical data needed to perform quantitative interpretation of an electron spectrum for a thin-film specimen of given composition. A simulation module provides an estimate of peak intensities as well as the energy and angular distributions of the emitted electron flux.
Biniek, Laure; Chochos, Christos L; Hadziioannou, Georges; Leclerc, Nicolas; Lévêque, Patrick; Heiser, Thomas
2010-04-06
A series of donor-acceptor alternated conjugated copolymers, composed of thiophene, bithiophene, thieno[3,2-b]thiophene, and 2,1,3-benzothiadiazole units and differing from each other by the nature and the number of 3-alkylthiophene in the backbone, have been synthesized by Stille cross-coupling polymerization. The material's optical and electrochemical properties, in solution and in thin films, have been investigated using UV-Visible absorption and cyclic voltammetry. Bulk heterojunction solar cells using blends of the newly synthesized copolymers, as electron donor, and C60-PCBM or C70-PCBM, as electron transporting material, have been elaborated. A maximum power conversion efficiency of 1.8% is achieved with a 1:4 PPBzT(2) -C12:C70-PCBM weight ratio. Copyright © 2010 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Analysis of Seasonal Signal in GPS Short-Baseline Time Series
Wang, Kaihua; Jiang, Weiping; Chen, Hua; An, Xiangdong; Zhou, Xiaohui; Yuan, Peng; Chen, Qusen
2018-04-01
Proper modeling of seasonal signals and their quantitative analysis are of interest in geoscience applications, which are based on position time series of permanent GPS stations. Seasonal signals in GPS short-baseline (paper, to better understand the seasonal signal in GPS short-baseline time series, we adopted and processed six different short-baselines with data span that varies from 2 to 14 years and baseline length that varies from 6 to 1100 m. To avoid seasonal signals that are overwhelmed by noise, each of the station pairs is chosen with significant differences in their height (> 5 m) or type of the monument. For comparison, we also processed an approximately zero baseline with a distance of pass-filtered (BP) noise is valid for approximately 40% of the baseline components, and another 20% of the components can be best modeled by a combination of the first-order Gauss-Markov (FOGM) process plus white noise (WN). The TEM displacements are then modeled by considering the monument height of the building structure beneath the GPS antenna. The median contributions of TEM to the annual amplitude in the vertical direction are 84% and 46% with and without additional parts of the monument, respectively. Obvious annual signals with amplitude > 0.4 mm in the horizontal direction are observed in five short-baselines, and the amplitudes exceed 1 mm in four of them. These horizontal seasonal signals are likely related to the propagation of daily/sub-daily TEM displacement or other signals related to the site environment. Mismodeling of the tropospheric delay may also introduce spurious seasonal signals with annual amplitudes of 5 and 2 mm, respectively, for two short-baselines with elevation differences greater than 100 m. The results suggest that the monument height of the additional part of a typical GPS station should be considered when estimating the TEM displacement and that the tropospheric delay should be modeled cautiously, especially with station pairs with
DynPeak: An Algorithm for Pulse Detection and Frequency Analysis in Hormonal Time Series
Vidal, Alexandre; Zhang, Qinghua; Médigue, Claire; Fabre, Stéphane; Clément, Frédérique
2012-01-01
The endocrine control of the reproductive function is often studied from the analysis of luteinizing hormone (LH) pulsatile secretion by the pituitary gland. Whereas measurements in the cavernous sinus cumulate anatomical and technical difficulties, LH levels can be easily assessed from jugular blood. However, plasma levels result from a convolution process due to clearance effects when LH enters the general circulation. Simultaneous measurements comparing LH levels in the cavernous sinus and jugular blood have revealed clear differences in the pulse shape, the amplitude and the baseline. Besides, experimental sampling occurs at a relatively low frequency (typically every 10 min) with respect to LH highest frequency release (one pulse per hour) and the resulting LH measurements are noised by both experimental and assay errors. As a result, the pattern of plasma LH may be not so clearly pulsatile. Yet, reliable information on the InterPulse Intervals (IPI) is a prerequisite to study precisely the steroid feedback exerted on the pituitary level. Hence, there is a real need for robust IPI detection algorithms. In this article, we present an algorithm for the monitoring of LH pulse frequency, basing ourselves both on the available endocrinological knowledge on LH pulse (shape and duration with respect to the frequency regime) and synthetic LH data generated by a simple model. We make use of synthetic data to make clear some basic notions underlying our algorithmic choices. We focus on explaining how the process of sampling affects drastically the original pattern of secretion, and especially the amplitude of the detectable pulses. We then describe the algorithm in details and perform it on different sets of both synthetic and experimental LH time series. We further comment on how to diagnose possible outliers from the series of IPIs which is the main output of the algorithm. PMID:22802933
Kastner, Monika; Sawka, Anna M; Hamid, Jemila; Chen, Maggie; Thorpe, Kevin; Chignell, Mark; Ewusie, Joycelyne; Marquez, Christine; Newton, David; Straus, Sharon E
2014-09-25
Osteoporosis affects over 200 million people worldwide at a high cost to healthcare systems, yet gaps in management still exist. In response, we developed a multi-component osteoporosis knowledge translation (Op-KT) tool involving a patient-initiated risk assessment questionnaire (RAQ), which generates individualized best practice recommendations for physicians and customized education for patients at the point of care. The objective of this study was to evaluate the effectiveness of the Op-KT tool for appropriate disease management by physicians. The Op-KT tool was evaluated using an interrupted time series design. This involved multiple assessments of the outcomes 12 months before (baseline) and 12 months after tool implementation (52 data points in total). Inclusion criteria were family physicians and their patients at risk for osteoporosis (women aged ≥ 50 years, men aged ≥ 65 years). Primary outcomes were the initiation of appropriate osteoporosis screening and treatment. Analyses included segmented linear regression modeling and analysis of variance. The Op-KT tool was implemented in three family practices in Ontario, Canada representing 5 family physicians with 2840 age eligible patients (mean age 67 years; 76% women). Time series regression models showed an overall increase from baseline in the initiation of screening (3.4%; P management addressed by their physician. Study limitations included the inherent susceptibility of our design compared with a randomized trial. The multicomponent Op-KT tool significantly increased osteoporosis investigations in three family practices, and highlights its potential to facilitate patient self-management. Next steps include wider implementation and evaluation of the tool in primary care.
Ramseyer, Fabian; Kupper, Zeno; Caspar, Franz; Znoj, Hansjörg; Tschacher, Wolfgang
2014-10-01
Processes occurring in the course of psychotherapy are characterized by the simple fact that they unfold in time and that the multiple factors engaged in change processes vary highly between individuals (idiographic phenomena). Previous research, however, has neglected the temporal perspective by its traditional focus on static phenomena, which were mainly assessed at the group level (nomothetic phenomena). To support a temporal approach, the authors introduce time-series panel analysis (TSPA), a statistical methodology explicitly focusing on the quantification of temporal, session-to-session aspects of change in psychotherapy. TSPA-models are initially built at the level of individuals and are subsequently aggregated at the group level, thus allowing the exploration of prototypical models. TSPA is based on vector auto-regression (VAR), an extension of univariate auto-regression models to multivariate time-series data. The application of TSPA is demonstrated in a sample of 87 outpatient psychotherapy patients who were monitored by postsession questionnaires. Prototypical mechanisms of change were derived from the aggregation of individual multivariate models of psychotherapy process. In a 2nd step, the associations between mechanisms of change (TSPA) and pre- to postsymptom change were explored. TSPA allowed a prototypical process pattern to be identified, where patient's alliance and self-efficacy were linked by a temporal feedback-loop. Furthermore, therapist's stability over time in both mastery and clarification interventions was positively associated with better outcomes. TSPA is a statistical tool that sheds new light on temporal mechanisms of change. Through this approach, clinicians may gain insight into prototypical patterns of change in psychotherapy. PsycINFO Database Record (c) 2014 APA, all rights reserved.
Hybrid analysis for indicating patients with breast cancer using temperature time series.
Silva, Lincoln F; Santos, Alair Augusto S M D; Bravo, Renato S; Silva, Aristófanes C; Muchaluat-Saade, Débora C; Conci, Aura
2016-07-01
Breast cancer is the most common cancer among women worldwide. Diagnosis and treatment in early stages increase cure chances. The temperature of cancerous tissue is generally higher than that of healthy surrounding tissues, making thermography an option to be considered in screening strategies of this cancer type. This paper proposes a hybrid methodology for analyzing dynamic infrared thermography in order to indicate patients with risk of breast cancer, using unsupervised and supervised machine learning techniques, which characterizes the methodology as hybrid. The dynamic infrared thermography monitors or quantitatively measures temperature changes on the examined surface, after a thermal stress. In the dynamic infrared thermography execution, a sequence of breast thermograms is generated. In the proposed methodology, this sequence is processed and analyzed by several techniques. First, the region of the breasts is segmented and the thermograms of the sequence are registered. Then, temperature time series are built and the k-means algorithm is applied on these series using various values of k. Clustering formed by k-means algorithm, for each k value, is evaluated using clustering validation indices, generating values treated as features in the classification model construction step. A data mining tool was used to solve the combined algorithm selection and hyperparameter optimization (CASH) problem in classification tasks. Besides the classification algorithm recommended by the data mining tool, classifiers based on Bayesian networks, neural networks, decision rules and decision tree were executed on the data set used for evaluation. Test results support that the proposed analysis methodology is able to indicate patients with breast cancer. Among 39 tested classification algorithms, K-Star and Bayes Net presented 100% classification accuracy. Furthermore, among the Bayes Net, multi-layer perceptron, decision table and random forest classification algorithms, an
Principal component analysis of MSBAS DInSAR time series from Campi Flegrei, Italy
Tiampo, Kristy F.; González, Pablo J.; Samsonov, Sergey; Fernández, Jose; Camacho, Antonio
2017-09-01
Because of its proximity to the city of Naples and with a population of nearly 1 million people within its caldera, Campi Flegrei is one of the highest risk volcanic areas in the world. Since the last major eruption in 1538, the caldera has undergone frequent episodes of ground subsidence and uplift accompanied by seismic activity that has been interpreted as the result of a stationary, deeper source below the caldera that feeds shallower eruptions. However, the location and depth of the deeper source is not well-characterized and its relationship to current activity is poorly understood. Recently, a significant increase in the uplift rate has occurred, resulting in almost 13 cm of uplift by 2013 (De Martino et al., 2014; Samsonov et al., 2014b; Di Vito et al., 2016). Here we apply a principal component decomposition to high resolution time series from the region produced by the advanced Multidimensional SBAS DInSAR technique in order to better delineate both the deeper source and the recent shallow activity. We analyzed both a period of substantial subsidence (1993-1999) and a second of significant uplift (2007-2013) and inverted the associated vertical surface displacement for the most likely source models. Results suggest that the underlying dynamics of the caldera changed in the late 1990s, from one in which the primary signal arises from a shallow deflating source above a deeper, expanding source to one dominated by a shallow inflating source. In general, the shallow source lies between 2700 and 3400 m below the caldera while the deeper source lies at 7600 m or more in depth. The combination of principal component analysis with high resolution MSBAS time series data allows for these new insights and confirms the applicability of both to areas at risk from dynamic natural hazards.
Linden, Ariel
2018-05-11
Interrupted time series analysis (ITSA) is an evaluation methodology in which a single treatment unit's outcome is studied serially over time and the intervention is expected to "interrupt" the level and/or trend of that outcome. ITSA is commonly evaluated using methods which may produce biased results if model assumptions are violated. In this paper, treatment effects are alternatively assessed by using forecasting methods to closely fit the preintervention observations and then forecast the post-intervention trend. A treatment effect may be inferred if the actual post-intervention observations diverge from the forecasts by some specified amount. The forecasting approach is demonstrated using the effect of California's Proposition 99 for reducing cigarette sales. Three forecast models are fit to the preintervention series-linear regression (REG), Holt-Winters (HW) non-seasonal smoothing, and autoregressive moving average (ARIMA)-and forecasts are generated into the post-intervention period. The actual observations are then compared with the forecasts to assess intervention effects. The preintervention data were fit best by HW, followed closely by ARIMA. REG fit the data poorly. The actual post-intervention observations were above the forecasts in HW and ARIMA, suggesting no intervention effect, but below the forecasts in the REG (suggesting a treatment effect), thereby raising doubts about any definitive conclusion of a treatment effect. In a single-group ITSA, treatment effects are likely to be biased if the model is misspecified. Therefore, evaluators should consider using forecast models to accurately fit the preintervention data and generate plausible counterfactual forecasts, thereby improving causal inference of treatment effects in single-group ITSA studies. © 2018 John Wiley & Sons, Ltd.
International Nuclear Information System (INIS)
Wang, H Y; Li, Z Y; Gao, Z H; Wu, J J; Sun, B; Li, C L
2014-01-01
Land condition assessment is a basic prerequisite for finding the degradation of a territory, which might lead to desertification under climatic and human pressures. The temporal change in vegetation productivity is a key indicator of land degradation. In this paper, taking the Otindag Sandy Land as a case, the mean normalized difference vegetation index (NDVI a ), net primary production (NPP) and vegetation rain use efficiency (RUE) dynamic trends during 2001–2010 were analysed. The Mann-Kendall test and the Correlation Analysis method were used and their sensitivities to land degradation were evaluated. The results showed that the three vegetation indicators (NDVI a , NPP and RUE) showed a downward trend with the two methods in the past 10 years and the land was degraded. For the analysis of the three vegetation indicators (NDVI a , NPP and RUE), it indicated a decreasing trend in 62.57%, 74.16% and 88.56% of the study area according to the Mann-Kendall test and in 57.85%, 68.38% and 85.29% according to the correlation analysis method. However, the change trends were not significant, the significant trends at the 95% confidence level only accounted for a small proportion. Analysis of NDVI a , NPP and RUE series showed a significant decreasing trend in 9.21%, 4.81% and 6.51% with the Mann-Kendall test. The NPP change trends showed obvious positive link with the precipitation in the study area. While the effect of the inter-annual variation of the precipitation for RUE was small, the vegetation RUE can provide valuable insights into the status of land condition and had best sensitivity to land degradation
Technology and Power. A Foucauldian Analysis of Electronic Monitoring Discourses
Directory of Open Access Journals (Sweden)
Anna Vitores
2007-05-01
Full Text Available The article aims to show the importance of FOUCAULT within social studies of science and technology. It also illustrates how a Foucauldian analysis can be useful for studies of science, technology and society focused on power effects. To accomplish these objectives we analyze the emergence of a specific techno-scientific innovation: the electronic monitoring of offenders. We map the discontinuities and discourse dispersions linked to those practices that constitute different materializations of this electronic device. Because we start from questions concerning power technologies, rather than simply analyzing the ideologies and knowledges that legitimate electronic monitoring and its technical reliability, we attend to the assemblage of discourses, rhetorics, vocabularies, techniques and procedures by which knowledge is intertwined and joins with the exercise of power. In this way, we show how one of FOUCAULT's technologies of power—disciplinary technology—is articulated, nourished and contradicted by other emergent logics drawing on new forms of regulation and social control. URN: urn:nbn:de:0114-fqs070225
Quantification of multielement-multilayer-samples in electron probe analysis
International Nuclear Information System (INIS)
Pfeiffer, A.
1995-03-01
The following dissertation presents the theoretical basis of analytical correction models and Monte Carlo simulations in the field of electron probe microanalysis to describe the excitation conditions of x-rays in a multilayer-multielement-sample. In this connection analyzing programs have been developed to make a quantitative investigation of heterogeneous samples possible. In the work the mathematical methods and formulas, which are mainly based on empirical and semiempirical findings, are described and their validity is discussed in detail. Especially the improvements of the 'multiple reflections'-model by August are compared with the Φ(ρz)-models by Pouchou, Merlet and Bastin. The calculations of depth distribution functions for characteristics and continuous fluorescence excitation result in a consistent and completeΦ(ρz)-model. This allows to analyze layered structures in great detail. Because of the increasing importance in electron probe microanalysis and as a reference method a Monte Carlo model is described. With this model electron trajectories and excitation conditions in arbitrary two dimensional geometries can be calculated. The validity of the analytical model is proven with a comprehensive comparison of results of new calculations to published data. To show an application of the programs and models in routine use in the industrial research and development, a quantitative analysis of a Co/Si system is made. In the conclusion of this dissertation some reflections upon investigations, which are based on this work and which should be made in future are outlined. (author)
Testing Homeopathy in Mouse Emotional Response Models: Pooled Data Analysis of Two Series of Studies
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Paolo Bellavite
2012-01-01
Full Text Available Two previous investigations were performed to assess the activity of Gelsemium sempervirens (Gelsemium s. in mice, using emotional response models. These two series are pooled and analysed here. Gelsemium s. in various homeopathic centesimal dilutions/dynamizations (4C, 5C, 7C, 9C, and 30C, a placebo (solvent vehicle, and the reference drugs diazepam (1 mg/kg body weight or buspirone (5 mg/kg body weight were delivered intraperitoneally to groups of albino CD1 mice, and their effects on animal behaviour were assessed by the light-dark (LD choice test and the open-field (OF exploration test. Up to 14 separate replications were carried out in fully blind and randomised conditions. Pooled analysis demonstrated highly significant effects of Gelsemium s. 5C, 7C, and 30C on the OF parameter “time spent in central area” and of Gelsemium s. 5C, 9C, and 30C on the LD parameters “time spent in lit area” and “number of light-dark transitions,” without any sedative action or adverse effects on locomotion. This pooled data analysis confirms and reinforces the evidence that Gelsemium s. regulates emotional responses and behaviour of laboratory mice in a nonlinear fashion with dilution/dynamization.
Spectral analysis of time series of events: effect of respiration on heart rate in neonates
International Nuclear Information System (INIS)
Van Drongelen, Wim; Williams, Amber L; Lasky, Robert E
2009-01-01
Certain types of biomedical processes such as the heart rate generator can be considered as signals that are sampled by the occurring events, i.e. QRS complexes. This sampling property generates problems for the evaluation of spectral parameters of such signals. First, the irregular occurrence of heart beats creates an unevenly sampled data set which must either be pre-processed (e.g. by using trace binning or interpolation) prior to spectral analysis, or analyzed with specialized methods (e.g. Lomb's algorithm). Second, the average occurrence of events determines the Nyquist limit for the sampled time series. Here we evaluate different types of spectral analysis of recordings of neonatal heart rate. Coupling between respiration and heart rate and the detection of heart rate itself are emphasized. We examine both standard and data adaptive frequency bands of heart rate signals generated by models of coupled oscillators and recorded data sets from neonates. We find that an important spectral artifact occurs due to a mirror effect around the Nyquist limit of half the average heart rate. Further we conclude that the presence of respiratory coupling can only be detected under low noise conditions and if a data-adaptive respiratory band is used
Variability of African Farming Systems from Phenological Analysis of NDVI Time Series
Vrieling, Anton; deBeurs, K. M.; Brown, Molly E.
2011-01-01
Food security exists when people have access to sufficient, safe and nutritious food at all times to meet their dietary needs. The natural resource base is one of the many factors affecting food security. Its variability and decline creates problems for local food production. In this study we characterize for sub-Saharan Africa vegetation phenology and assess variability and trends of phenological indicators based on NDVI time series from 1982 to 2006. We focus on cumulated NDVI over the season (cumNDVI) which is a proxy for net primary productivity. Results are aggregated at the level of major farming systems, while determining also spatial variability within farming systems. High temporal variability of cumNDVI occurs in semiarid and subhumid regions. The results show a large area of positive cumNDVI trends between Senegal and South Sudan. These correspond to positive CRU rainfall trends found and relate to recovery after the 1980's droughts. We find significant negative cumNDVI trends near the south-coast of West Africa (Guinea coast) and in Tanzania. For each farming system, causes of change and variability are discussed based on available literature (Appendix A). Although food security comprises more than the local natural resource base, our results can perform an input for food security analysis by identifying zones of high variability or downward trends. Farming systems are found to be a useful level of analysis. Diversity and trends found within farming system boundaries underline that farming systems are dynamic.
Time series analysis of ambient air concentrations in Alexandria and Nile delta region, Egypt
International Nuclear Information System (INIS)
EI Raev, M.; Shalaby, E.A.; Ghatass, Z.F.; Marey, H.S.
2007-01-01
Data collected from the Air Monitoring Network of Alexandria and Delta (EEAA/EIMP-program), were analyzed. Emphasis is given to indicator pollutants PM 10 , NO 2 , SO 2 , O 3 and CO. Two sites have been selected in Alexandria (IGSR and Shohada) and three sites in Delta region (Kafr Elzyat, Mansoura and Mahalla) for analysis of three years from 2000-2002. Box -Jenkins modeling has been used mainly for forecasting and assessing relative importance of various parameters or pollutants. Results showed that, the autoregressive (AR) order for all series ranged from 0-2 except NO 2 at Mansoura site. Also the moving average order ranged from 0-2 except CO at IGSR site. Nitrogen dioxide and Ozone at IGSR site have the same ARIMA model which is (0, 1, and 2). Cross correlation analysis has revealed important information on the dynamics, chemistry and interpretation of ambient pollution. Cross-correlation functions of SO 2 and PM 10 at IGSR sites suggest that, sulfur dioxide has been adsorbed on the surface of particulates which has an alkaline nature. This enhances the oxidation of sulfur dioxide to sulfate, which results in low levels of SO 2 in spite of the presence of sources
Statistical Analysis of fMRI Time-Series: A Critical Review of the GLM Approach
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Martin M Monti
2011-03-01
Full Text Available Functional Magnetic Resonance Imaging (fMRI is one of the most widely used tools to study the neural underpinnings of human cognition. Standard analysis of fMRI data relies on a General Linear Model (GLM approach to separate stimulus induced signals from noise. Crucially, this approach relies on a number of assumptions about the data which, for inferences to be valid, must be met. The current paper reviews the GLM approach to analysis of fMRI time-series, focusing in particular on the degree to which such data abides by the assumptions of the GLM framework, and on the methods that have been developed to correct for any violation of those assumptions. Rather than biasing estimates of effect size, the major consequence of non-conformity to the assumptions is to introduce bias into estimates of the variance, thus affecting test statistics, power and false positive rates. Furthermore, this bias can have pervasive effects on both individual subject and group-level statistics, potentially yielding qualitatively different results across replications, especially after the thresholding procedures commonly used for inference-making.
A Time Series Analysis Using R for Understanding Car Sales On The Romanian Market
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Mihaela Cornelia Sandu
2015-09-01
Full Text Available The size of the Romanian automobile industry is relative small compared to the main car producers in Europe and the world, but an analysis of its structure and dynamic appears to be most relevant given the strong linkages with the main macroeconomic indicators and important microeconomic variables at the level of the household.The paper presents a time series analysis for car sales in Romania, in the period 2007-2014, focusing on the sales dynamic of the national main producer– Dacia Pitesti. The aim of the investigation is twofold: to test the impact of macroeconomic variables on this important and underexplored segment of the economy and to emphasize potential differences between the factors influencing the buying decision for domestic versus foreign cars (observed in three regimes: new, registered and reenrolled. While the major influence of the global economic crisis cannot be ignored for the analyzed interval, we believe that it may also help to illustrate the real behaviors of individuals by setting the line between the immediate period after the crisis as treatment under scarcity conditions and the re-installment of normality towards the second half of the time interval. The results are confirming the general findings of the literature for the main indicators but they not entirely consistent with the rational economic models, especially with regard to the nature of the investigated goods (the cars – normal or positional.
Scott, John W; Nyinawankusi, Jeanne D'Arc; Enumah, Samuel; Maine, Rebecca; Uwitonze, Eric; Hu, Yihan; Kabagema, Ignace; Byiringiro, Jean Claude; Riviello, Robert; Jayaraman, Sudha
2017-07-01
Injury is a major cause of premature death and disability in East Africa, and high-quality pre-hospital care is essential for optimal trauma outcomes. The Rwandan pre-hospital emergency care service (SAMU) uses an electronic database to evaluate and optimize pre-hospital care through a continuous quality improvement programme (CQIP), beginning March 2014. The SAMU database was used to assess pre-hospital quality metrics including supplementary oxygen for hypoxia (O2), intravenous fluids for hypotension (IVF), cervical collar placement for head injuries (c-collar), and either splinting (splint) or administration of pain medications (pain) for long bone fractures. Targets of >90% were set for each metric and daily team meetings and monthly feedback sessions were implemented to address opportunities for improvement. These five pre-hospital quality metrics were assessed monthly before and after implementation of the CQIP. Met and unmet needs for O2, IVF, and c-collar were combined into a summative monthly SAMU Trauma Quality Scores (STQ score). An interrupted time series linear regression model compared the STQ score during 14 months before the CQIP implementation to the first 14 months after. During the 29-month study period 3,822 patients met study criteria. 1,028 patients needed one or more of the five studied interventions during the study period. All five endpoints had a significant increase between the pre-CQI and post-CQI periods (pRwanda. This programme may be used as an example for additional efforts engaging frontline staff with real-time data feedback in order to rapidly translate data collection efforts into improved care for the injured in a resource-limited setting. Copyright © 2017 Elsevier Ltd. All rights reserved.
International Nuclear Information System (INIS)
Martinez-Luna, R. J.; Vega, J. M. de la; Vilches, M.; Guirado, D.; Zamora, L. I.; Lallena, A. M.
2011-01-01
Using the techniques of statistical process control (SPC) keeps track of the variable that controls the stability of the spectrum of electron beam accelerators in clinical use. In this process, applied since 1995, we obtained a high number of false alarms. Our work shows that this unexpected behavior appears to treat the variable of interest as a normal random variable, independent and identically distributed (iid), when in fact the observations of this variable are positively correlated with each other. (Author)
African Journals Online (AJOL)
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Key words: Case report, case series, concept analysis, research design. African Health Sciences 2012; (4): 557 - 562 http://dx.doi.org/10.4314/ahs.v12i4.25. PO Box 17666 .... According to the latest version of the Dictionary of. Epidemiology ...
Trend analysis using non-stationary time series clustering based on the finite element method
Gorji Sefidmazgi, M.; Sayemuzzaman, M.; Homaifar, A.; Jha, M. K.; Liess, S.
2014-01-01
In order to analyze low-frequency variability of climate, it is useful to model the climatic time series with multiple linear trends and locate the times of significant changes. In this paper, we have used non-stationary time series clustering to find change points in the trends. Clustering in a multi-dimensional non-stationary time series is challenging, since the problem is mathematically ill-posed. Clustering based on the finite element method (FEM) is one of the methods ...
Energy Technology Data Exchange (ETDEWEB)
Ferrer Polo, J.; Ardiles Lopez, K. L. (CEDEX, Ministerio de Obras Publicas, Transportes y Medio ambiente, Madrid (Spain))
1994-01-01
Work on the statistical modelling of maximum daily rainfalls is presented, with a view to estimating the quantiles for different return periods. An index flood approach has been adopted in which the local quantiles are a result of rescaling a regional law using the mean of each series of values, that is utilized as a local scale factor. The annual maximum series have been taken from 1.545 meteorological stations over a 30 year period, and these have been classified into 26 regions defined according to meteorological criteria, the homogeneity of wich has been checked by means of a statistical analysis of the coefficients of variation of the samples,using the. An estimation has been made of the parameters for the following four distribution models: Two Component Extreme Value (TCEV); General Extreme Value (GEV); Log-Pearson III (LP3); and SQRT-Exponential Type Distribution of Maximum. The analysis of the quantiles obtained reveals slight differences in the results thus detracting from the importance of the model selection. The last of the above-mentioned distribution has been finally chosen, on the basis of the following: it is defined with fewer parameters it is the only that was proposed specifically for the analysis of daily rainfall maximums; it yields more conservative results than the traditional Gumbel distribution for the high return periods; and it is capable of providing a good description of the main sampling statistics concerning the right-hand tail of the distribution, a fact that has been checked with Montecarlo's simulation techniques. The choice of a distribution model with only two parameters has led to the selection of the regional coefficient of variation as the only determining parameter for the regional quantiles. This has permitted the elimination of the quantiles discontinuity of the classical regional approach, thus smoothing the values of that coefficient by means of an isoline plan on a national scale.
Benvenuti, C.; Cosso, R.; Genest, J.; Hauer, M.; Lacarrère, D.; Rijllart, A.; Saban, R.
1996-08-01
A computer-controlled surface analysis instrument, incorporating static Auger electron spectroscopy, scanning Auger mapping, and secondary electron imaging, has been designed and built at CERN to study and characterize the inner surface of superconducting radio-frequency cavities to be installed in the Large Electron Positron collider. A detailed description of the instrument, including the analytical head, the control system, and the vacuum system is presented. Some recent results obtained from the cavities provide examples of the instrument's capabilities.
International Nuclear Information System (INIS)
Kirk, B.L.
1985-12-01
The ITS (Integrated Tiger Series) Monte Carlo code package developed at Sandia National Laboratories and distributed as CCC-467/ITS by the Radiation Shielding Information Center (RSIC) at Oak Ridge National Laboratory (ORNL) consists of eight codes - the standard codes, TIGER, CYLTRAN, ACCEPT; the P-codes, TIGERP, CYLTRANP, ACCEPTP; and the M-codes ACCEPTM, CYLTRANM. The codes have been adapted to run on the IBM 3081, VAX 11/780, CDC-7600, and Cray 1 with the use of the update emulator UPEML. This manual should serve as a guide to a user running the codes on IBM computers having 370 architecture. The cases listed were tested on the IBM 3033, under the MVS operating system using the VS Fortran Level 1.3.1 compiler
Low temperature x-ray analysis and electron microscopy of a new family of superconducting materials
International Nuclear Information System (INIS)
Ossipyan, Yu.A.; Borodin, V.A.; Goncharov, V.A.; Kondakov, S.F.; Khasanov, S.S.; Chernyshova, L.M.; Shekhtman, V.S.; Shmyt'ko, I.M.; Stchegolev, N.F.
1987-01-01
Recent findings in the field of high temperature superconductivity require that structural aspects of the behavior of this class of materials be investigated in detail in a wide temperature interval. A series of superconducting ceramics on the base of lanthanum and yttrium oxides (La/sub 2-x/Sr/sub x/CuO 4 ; x = 0, 2 and YBaCuO) have been obtained in the solid state Physics Institute of the Academy of Sciences of the USSR. This paper presents the results of the analysis of powder and sintered materials, using X-ray diffractometers (DRON), scanning electron microscope and special devices, enabling the investigations to be carried out within 4.2 K - 573 K
Kim, J.; Park, M.; Baik, H. S.; Choi, Y.
2016-12-01
At the present time, arguments continue regarding the migration speeds of Martian dune fields and their correlation with atmospheric circulation. However, precisely measuring the spatial translation of Martian dunes has rarely conducted only a very few times Therefore, we developed a generic procedure to precisely measure the migration of dune fields with recently introduced 25-cm resolution High Resolution Imaging Science Experimen (HIRISE) employing a high-accuracy photogrammetric processor and sub-pixel image correlator. The processor was designed to trace estimated dune migration, albeit slight, over the Martian surface by 1) the introduction of very high resolution ortho images and stereo analysis based on hierarchical geodetic control for better initial point settings; 2) positioning error removal throughout the sensor model refinement with a non-rigorous bundle block adjustment, which makes possible the co-alignment of all images in a time series; and 3) improved sub-pixel co-registration algorithms using optical flow with a refinement stage conducted on a pyramidal grid processor and a blunder classifier. Moreover, volumetric changes of Martian dunes were additionally traced by means of stereo analysis and photoclinometry. The established algorithms have been tested using high-resolution HIRISE images over a large number of Martian dune fields covering whole Mars Global Dune Database. Migrations over well-known crater dune fields appeared to be almost static for the considerable temporal periods and were weakly correlated with wind directions estimated by the Mars Climate Database (Millour et al. 2015). Only over a few Martian dune fields, such as Kaiser crater, meaningful migration speeds (>1m/year) compared to phtotogrammetric error residual have been measured. Currently a technical improved processor to compensate error residual using time series observation is under developing and expected to produce the long term migration speed over Martian dune
[Time-series analysis on effect of air pollution on stroke mortality in Tianjin, China].
Wang, De-zheng; Gu, Qing; Jiang, Guo-hong; Yang, De-yi; Zhang, Hui; Song, Gui-de; Zhang, Ying
2012-12-01
To investigate the effect of air pollution on stroke mortality in Tianjin, China, and to provide basis for stroke control and prevention. Total data of mortality surveillance were collected by Tianjin Centers for Disease Control and Prevention. Meteorological data and atmospheric pollution data were from Tianjin Meteorological Bureau and Tianjin Environmental Monitoring Center, respectively. Generalized additive Poisson regression model was used in time-series analysis on the relationship between air pollution and stroke mortality in Tianjin. Single-pollutant analysis and multi-pollutant analysis were performed after adjustment for confounding factors such as meteorological factors, long-term trend of death, "days of the week" effect and population. The crude death rates of stroke in Tianjin were from 136.67 in 2001 to 160.01/100000 in 2009, with an escalating trend (P = 0.000), while the standardized mortality ratios of stroke in Tianjin were from 138.36 to 99.14/100000, with a declining trend (P = 0.000). An increase of 10 µg/m³ in daily average concentrations of atmospheric SO₂, NO₂ and PM₁₀ led to 1.0105 (95%CI: 1.0060 ∼ 1.0153), 1.0197 (95%CI: 1.0149 ∼ 1.0246) and 1.0064 (95%CI: 1.0052 ∼ 1.0077), respectively, in relative risks of stroke mortality. SO₂ effect peaked after 1-day exposure, while NO₂ and PM₁₀ effects did within 1 day. Air pollution in Tianjin may increase the risk of stroke mortality in the population and induce acute onset of stroke. It is necessary to carry out air pollution control and allocate health resources rationally to reduce the hazard of stroke mortality.
ENTREPRENEURIAL ACTIVITY IN ROMANIA – A TIME SERIES CLUSTERING ANALYSIS AT THE NUTS3 LEVEL
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Sipos-Gug Sebastian
2013-07-01
Full Text Available Entrepreneurship is an active field of research, having known a major increase in interest and publication levels in the last years (Landström et al., 2012. Within this field recently there has been an increasing interest in understanding why some regions seem to have a significantly higher entrepreneurship activity compared to others. In line with this research field, we would like to investigate the differences in entrepreneurial activity among the Romanian counties (NUTS 3 regions. While the classical research paradigm in this field is to conduct a temporally stationary analysis, we choose to use a time series clustering analysis to better understanding the dynamics of entrepreneurial activity between counties. Our analysis showed that if we use the total number of new privately owned companies that are founded each year in the last decade (2002-2012 we can distinguish between 5 clusters, one with high total entrepreneurial activity (18 counties, one with above average activity (8 counties, two clusters with average and slightly below average activity (total of 18 counties and one cluster with low and declining activity (2 counties. If we are interested in the entrepreneurial activity rate, that is the number of new privately owned companies founded each year adjusted by the population of the respective county, we obtain 4 clusters, one with a very high entrepreneurial rate (1 county, one with average rate (10 counties, and two clusters with below average entrepreneurial rate (total of 31 counties. In conclusion, our research shows that Romania is far from being a homogeneous geographical area in respect to entrepreneurial activity. Depending on what we are interested in, it can be divided in 5 or 4 clusters of counties, which behave differently as a function of time. Further research should be focused on explaining these regional differences, on studying the high performance clusters and trying to improve the low performing ones.
EDITORIAL: Electron Microscopy and Analysis Group Conference 2011 (EMAG 2011)
Moebus, Guenter; Walther, Thomas; Brydson, Rik; Ozkaya, Dogan; MacLaren, Ian; Donnelly, Steve; Nellist, Pete; Li, Ziyou; Baker, Richard; Chiu, YuLung
2012-07-01
The biennial EMAG conference has established a strong reputation as a key event for the national and international electron microscopy community. In 2011 the meeting was held at The University of Birmingham, and I must first take this opportunity of thanking Birmingham for hosting the conference and for the excellent support we received from the local organisers. As a committee, we are delighted to see that enthusiasm for the EMAG conference series continues to be strong. We received more than 160 submitted abstracts, and 157 delegates attended the meeting. The scientific programme organiser, Ian MacLaren, put together an exciting programme. Plenary lectures were presented by Professor Knut Urban, Dr Frances Ross and Dr Richard Henderson. There were a further 10 invited speakers, from the UK, Continental Europe, Australia, the USA and Japan. The quality of the contributed oral and poster presentations was also very high. EMAG is keen to encourage student participation, and a winner and two runners-up were presented with prizes for the best oral and poster presentations from a student. I am always struck by the scientific quality of the oral and poster contributions and the vibrant discussions that occur both in the formal sessions and in the exhibition space at EMAG. I am convinced that a crucial part of maintaining that scientific quality is the opportunity that is offered of having a paper fully reviewed by two internationally selected referees and published in the Journal of Physics: Conference Series. For many students, this is the first fully reviewed paper they publish. I hope that you, like me, will be struck by the scientific quality of the 87 papers that follow, and that you will find them interesting and informative. Finally I must thank the platinum sponsors for their support of the meeting. These were Gatan, Zeiss, FEI, JEOL and Hitachi. I must also thank the European Microscopy Society for their generous sponsorship and support for the travel costs of
ITS Version 3.0: The Integrated TIGER Series of coupled electron/photon Monte Carlo transport codes
International Nuclear Information System (INIS)
Halbleib, J.A.; Kensek, R.P.; Valdez, G.D.; Mehlhorn, T.A.; Seltzer, S.M.; Berger, M.J.
1993-01-01
ITS is a powerful and user-friendly software package permitting state-of-the-art Monte Carlo solution of linear time-independent coupled electron/photon radiation transport problems, with or without the presence of macroscopic electric and magnetic fields. It combines operational simplicity and physical accuracy in order to provide experimentalists and theorists alike with a method for the routine but rigorous solution of sophisticated radiation transport problems. Flexibility of construction permits tailoring of the codes to specific applications and extension of code capabilities to more complex applications through simple update procedures
ITS Version 3.0: The Integrated TIGER Series of coupled electron/photon Monte Carlo transport codes
Energy Technology Data Exchange (ETDEWEB)
Halbleib, J.A.; Kensek, R.P.; Valdez, G.D.; Mehlhorn, T.A. [Sandia National Labs., Albuquerque, NM (United States); Seltzer, S.M.; Berger, M.J. [National Inst. of Standards and Technology, Gaithersburg, MD (United States). Ionizing Radiation Div.
1993-06-01
ITS is a powerful and user-friendly software package permitting state-of-the-art Monte Carlo solution of linear time-independent coupled electron/photon radiation transport problems, with or without the presence of macroscopic electric and magnetic fields. It combines operational simplicity and physical accuracy in order to provide experimentalists and theorists alike with a method for the routine but rigorous solution of sophisticated radiation transport problems. Flexibility of construction permits tailoring of the codes to specific applications and extension of code capabilities to more complex applications through simple update procedures.
Trend analysis using non-stationary time series clustering based on the finite element method
Gorji Sefidmazgi, M.; Sayemuzzaman, M.; Homaifar, A.; Jha, M. K.; Liess, S.
2014-05-01
In order to analyze low-frequency variability of climate, it is useful to model the climatic time series with multiple linear trends and locate the times of significant changes. In this paper, we have used non-stationary time series clustering to find change points in the trends. Clustering in a multi-dimensional non-stationary time series is challenging, since the problem is mathematically ill-posed. Clustering based on the finite element method (FEM) is one of the methods that can analyze multidimensional time series. One important attribute of this method is that it is not dependent on any statistical assumption and does not need local stationarity in the time series. In this paper, it is shown how the FEM-clustering method can be used to locate change points in the trend of temperature time series from in situ observations. This method is applied to the temperature time series of North Carolina (NC) and the results represent region-specific climate variability despite higher frequency harmonics in climatic time series. Next, we investigated the relationship between the climatic indices with the clusters/trends detected based on this clustering method. It appears that the natural variability of climate change in NC during 1950-2009 can be explained mostly by AMO and solar activity.
Risk assessment of environmentally influenced airway diseases based on time-series analysis.
Herbarth, O
1995-09-01
Threshold values are of prime importance in providing a sound basis for public health decisions. A key issue is determining threshold or maximum exposure values for pollutants and assessing their potential health risks. Environmental epidemiology could be instrumental in assessing these levels, especially since the assessment of ambient exposures involves relatively low concentrations of pollutants. This paper presents a statistical method that allows the determination of threshold values as well as the assessment of the associated risk using a retrospective, longitudinal study design with a prospective follow-up. Morbidity data were analyzed using the Fourier method, a time-series analysis that is based on the assumption of a high temporal resolution of the data. This method eliminates time-dependent responses like temporal inhomogeneity and pseudocorrelation. The frequency of calls for respiratory distress conditions to the regional Mobile Medical Emergency Service (MMES) in the city of Leipzig were investigated. The entire population of Leipzig served as a pool for data collection. In addition to the collection of morbidity data, air pollution measurements were taken every 30 min for the entire study period using sulfur dioxide as the regional indicator variable. This approach allowed the calculation of a dose-response curve for respiratory diseases and air pollution indices in children and adults. Significantly higher morbidities were observed above a 24-hr mean value of 0.6 mg SO2/m3 air for children and 0.8 mg SO2/m3 for adults.(ABSTRACT TRUNCATED AT 250 WORDS)
Directory of Open Access Journals (Sweden)
Jie You
2015-01-01
Full Text Available OBJECTIVES: To investigate an unusual outbreak of tetrodotoxin poisoning in Leizhou, southeast China, a case series analysis was conducted to identify the source of illness. METHODS: A total of 22 individuals experienced symptoms of poisoning, including tongue numbness, dizziness, nausea and limb numbness and weakness. Two toxic species, Amoya caninus and Yongeichthys nebulosus, were morphologically identified from the batches of gobies consumed by the patients. Tetrodotoxin levels in the blood and Goby fish samples were detected using liquid chromatography-tandem mass spectrometry. RESULTS: The tetrodotoxin levels in the remaining cooked Goby fish were determined to be 2090.12 µg/kg. For Amoya caninus, the toxicity levels were 1858.29 µg/kg in the muscle and 1997.19 µg/kg in the viscera and for Yongeichthys nebulosus, they were 2783.00 µg/kg in the muscle and 2966.21 µg/kg in the viscera. CONCLUSION: This outbreak demonstrates an underestimation of the risk of Goby fish poisoning. Furthermore, the relationships among the toxic species, climates and marine algae present should be clarified in the future.
Amigó, José M; Hirata, Yoshito; Aihara, Kazuyuki
2017-08-01
In a previous paper, the authors studied the limits of probabilistic prediction in nonlinear time series analysis in a perfect model scenario, i.e., in the ideal case that the uncertainty of an otherwise deterministic model is due to only the finite precision of the observations. The model consisted of the symbolic dynamics of a measure-preserving transformation with respect to a finite partition of the state space, and the quality of the predictions was measured by the so-called ignorance score, which is a conditional entropy. In practice, though, partitions are dispensed with by considering numerical and experimental data to be continuous, which prompts us to trade off in this paper the Shannon entropy for the differential entropy. Despite technical differences, we show that the core of the previous results also hold in this extended scenario for sufficiently high precision. The corresponding imperfect model scenario will be revisited too because it is relevant for the applications. The theoretical part and its application to probabilistic forecasting are illustrated with numerical simulations and a new prediction algorithm.
A Long-Term Prediction Model of Beijing Haze Episodes Using Time Series Analysis
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Xiaoping Yang
2016-01-01
Full Text Available The rapid industrial development has led to the intermittent outbreak of pm2.5 or haze in developing countries, which has brought about great environmental issues, especially in big cities such as Beijing and New Delhi. We investigated the factors and mechanisms of haze change and present a long-term prediction model of Beijing haze episodes using time series analysis. We construct a dynamic structural measurement model of daily haze increment and reduce the model to a vector autoregressive model. Typical case studies on 886 continuous days indicate that our model performs very well on next day’s Air Quality Index (AQI prediction, and in severely polluted cases (AQI ≥ 300 the accuracy rate of AQI prediction even reaches up to 87.8%. The experiment of one-week prediction shows that our model has excellent sensitivity when a sudden haze burst or dissipation happens, which results in good long-term stability on the accuracy of the next 3–7 days’ AQI prediction.
Mapping Mountain Pine Beetle Mortality through Growth Trend Analysis of Time-Series Landsat Data
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Lu Liang
2014-06-01
Full Text Available Disturbances are key processes in the carbon cycle of forests and other ecosystems. In recent decades, mountain pine beetle (MPB; Dendroctonus ponderosae outbreaks have become more frequent and extensive in western North America. Remote sensing has the ability to fill the data gaps of long-term infestation monitoring, but the elimination of observational noise and attributing changes quantitatively are two main challenges in its effective application. Here, we present a forest growth trend analysis method that integrates Landsat temporal trajectories and decision tree techniques to derive annual forest disturbance maps over an 11-year period. The temporal trajectory component successfully captures the disturbance events as represented by spectral segments, whereas decision tree modeling efficiently recognizes and attributes events based upon the characteristics of the segments. Validated against a point set sampled across a gradient of MPB mortality, 86.74% to 94.00% overall accuracy was achieved with small variability in accuracy among years. In contrast, the overall accuracies of single-date classifications ranged from 37.20% to 75.20% and only become comparable with our approach when the training sample size was increased at least four-fold. This demonstrates that the advantages of this time series work flow exist in its small training sample size requirement. The easily understandable, interpretable and modifiable characteristics of our approach suggest that it could be applicable to other ecoregions.
Roddy, Chantal; Rickard, Nikki; Tamplin, Jeanette; Baker, Felicity Anne
2018-07-01
Spinal Cord Injury (SCI) patients face unique identity challenges associated with physical limitations, higher comorbid depression, increased suicidality and reduced subjective well-being. Post-injury identity is often unaddressed in subacute rehabilitation environments where critical physical and functional rehabilitation goals are prioritized. Therapeutic songwriting has demonstrated prior efficacy in promoting healthy adjustment and as a means of expression for post-injury narratives. The current study sought to examine the identity narratives of therapeutic songwriting participants. Case-series analysis of the individual identity trajectories of eight individuals. Subacute rehabilitation facility, Victoria, Australia. Eight individuals with an SCI; 7 males and 1 female. Six-week therapeutic songwriting intervention facilitated by a music therapist to promote identity rehabilitation. Identity, subjective well-being and distress, emotional state. Three participants demonstrated positive trajectories and a further three showed negative trajectories; remaining participants were ambiguous in their response. Injury severity differentiated those with positive trajectories from those with negative trajectories, with greater injury severity apparent for those showing negative trends. Self-concept also improved more in those with positive trajectories. Core demographic variables did not however meaningfully predict the direction of change in core identity or wellbeing indices. Identity-focused songwriting holds promise as a means of promoting healthy identity reintegration. Further research on benefits for those with less severe spinal injuries is warranted.
Milojevic, Ai; Armstrong, Ben; Wilkinson, Paul
2017-10-01
There is emerging evidence that people affected by flooding suffer adverse impacts on their mental well-being, mostly based on self-reports. We examined prescription records for drugs used in the management of common mental disorder among primary care practices located in the vicinity of recent large flood events in England, 2011-2014. A controlled interrupted time series analysis was conducted of the number of prescribing items for antidepressant drugs in the year before and after the flood onset. Pre-post changes were compared by distance of the practice from the inundated boundaries among 930 practices located within 10 km of a flood. After control for deprivation and population density, there was an increase of 0.59% (95% CI 0.24 to 0.94) prescriptions in the postflood year among practices located within 1 km of a flood over and above the change observed in the furthest distance band. The increase was greater in more deprived areas. This study suggests an increase in prescribed antidepressant drugs in the year after flooding in primary care practices close to recent major floods in England. The degree to which the increase is actually concentrated in those flooded can only be determined by more detailed linkage studies. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.
Comparison on the Analysis on PM10 Data based on Average and Extreme Series
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Mohd Amin Nor Azrita
2018-01-01
Full Text Available The main concern in environmental issue is on extreme phenomena (catastrophic instead of common events. However, most statistical approaches are concerned primarily with the centre of a distribution or on the average value rather than the tail of the distribution which contains the extreme observations. The concept of extreme value theory affords attention to the tails of distribution where standard models are proved unreliable to analyse extreme series. High level of particulate matter (PM10 is a common environmental problem which causes various impacts to human health and material damages. If the main concern is on extreme events, then extreme value analysis provides the best result with significant evidence. The monthly average and monthly maxima PM10 data for Perlis from 2003 to 2014 were analysed. Forecasting for average data is made by Holt-Winters method while return level determine the predicted value of extreme events that occur on average once in a certain period. The forecasting from January 2015 to December 2016 for average data found that the highest forecasted value is 58.18 (standard deviation 18.45 on February 2016 while return level achieved 253.76 units for 24 months (2015-2016 return periods.
ANALYSIS OF TIME SERIES FOR THE CURRENCY PAIR CROATIAN KUNA / EURO
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Marko Martinović
2017-01-01
Full Text Available The domestic currency Croatian kuna (HRK was introduced in May 1995. To date, the Croatian National Bank (HNB, as a regulator and formulator of monetary policy in Croatia has operated a policy of stable exchange rate, typically referenced to the formal currency of the European Union euro (EUR. From the date of introduction of the euro 01/01/1999 until 01/01/2016 the value of the currency pair HRK / EUR changed in value by only 4.25% (HNB. Although the value of the Croatian kuna is relatively stable, there are some fluctuations on an annual level (e.g. in the last few years because of the global crisis as well as on periodic levels within a year. The aim of this paper is to show the movement of the value of the currency pair since the beginning of 2002 to the present day (the time curve, analyze the correctness, trends and periodicity (seasonal behavior, if any exist.The research will be done using the method of Time Series Analysis, assuming that the external (global economy and internal factors (economic policy remain similar or the same. According to the results, further assessment of price developments in the period followed will be made by using the obtained predicative models. In the event that the curve contains the component of periodicity, the observed patterns will be studied further.
Forecasting Container Throughput at the Doraleh Port in Djibouti through Time Series Analysis
Mohamed Ismael, Hawa; Vandyck, George Kobina
The Doraleh Container Terminal (DCT) located in Djibouti has been noted as the most technologically advanced container terminal on the African continent. DCT's strategic location at the crossroads of the main shipping lanes connecting Asia, Africa and Europe put it in a unique position to provide important shipping services to vessels plying that route. This paper aims to forecast container throughput through the Doraleh Container Port in Djibouti by Time Series Analysis. A selection of univariate forecasting models has been used, namely Triple Exponential Smoothing Model, Grey Model and Linear Regression Model. By utilizing the above three models and their combination, the forecast of container throughput through the Doraleh port was realized. A comparison of the different forecasting results of the three models, in addition to the combination forecast is then undertaken, based on commonly used evaluation criteria Mean Absolute Deviation (MAD) and Mean Absolute Percentage Error (MAPE). The study found that the Linear Regression forecasting Model was the best prediction method for forecasting the container throughput, since its forecast error was the least. Based on the regression model, a ten (10) year forecast for container throughput at DCT has been made.
Accuracy analysis of measurements on a stable power-law distributed series of events
International Nuclear Information System (INIS)
Matthews, J O; Hopcraft, K I; Jakeman, E; Siviour, G B
2006-01-01
We investigate how finite measurement time limits the accuracy with which the parameters of a stably distributed random series of events can be determined. The model process is generated by timing the emigration of individuals from a population that is subject to deaths and a particular choice of multiple immigration events. This leads to a scale-free discrete random process where customary measures, such as mean value and variance, do not exist. However, converting the number of events occurring in fixed time intervals to a 1-bit 'clipped' process allows the construction of well-behaved statistics that still retain vestiges of the original power-law and fluctuation properties. These statistics include the clipped mean and correlation function, from measurements of which both the power-law index of the distribution of events and the time constant of its fluctuations can be deduced. We report here a theoretical analysis of the accuracy of measurements of the mean of the clipped process. This indicates that, for a fixed experiment time, the error on measurements of the sample mean is minimized by an optimum choice of the number of samples. It is shown furthermore that this choice is sensitive to the power-law index and that the approach to Poisson statistics is dominated by rare events or 'outliers'. Our results are supported by numerical simulation
A population based time series analysis of asthma hospitalisations in Ontario, Canada: 1988 to 2000
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Upshur Ross EG
2001-08-01
Full Text Available Abstract Background Asthma is a common yet incompletely understood health problem associated with a high morbidity burden. A wide variety of seasonally variable environmental stimuli such as viruses and air pollution are believed to influence asthma morbidity. This study set out to examine the seasonal patterns of asthma hospitalisations in relation to age and gender for the province of Ontario over a period of 12 years. Methods A retrospective, population-based study design was used to assess temporal patterns in hospitalisations for asthma from April 1, 1988 to March 31, 2000. Approximately 14 million residents of Ontario eligible for universal healthcare coverage during this time were included for analysis. Time series analyses were conducted on monthly aggregations of hospitalisations. Results There is strong evidence of an autumn peak and summer trough seasonal pattern occurring every year over the 12-year period (Fisher-Kappa (FK = 23.93, p > 0.01; Bartlett Kolmogorov Smirnov (BKS = 0.459, p Conclusions A clear and consistent seasonal pattern was observed in this study for asthma hospitalisations. These findings have important implications for the development of effective management and prevention strategies.
Absolute high-resolution Se+ photoionization cross-section measurements with Rydberg-series analysis
International Nuclear Information System (INIS)
Esteves, D. A.; Bilodeau, R. C.; Sterling, N. C.; Phaneuf, R. A.; Kilcoyne, A. L. D.; Red, E. C.; Aguilar, A.
2011-01-01
Absolute single photoionization cross-section measurements for Se + ions were performed at the Advanced Light Source (ALS) at Lawrence Berkeley National Laboratory using the photo-ion merged-beams technique. Measurements were made at a photon energy resolution of 5.5 meV from 17.75 to 21.85 eV spanning the 4s 2 4p 3 4 S 3/2 o ground-state ionization threshold and the 2 P 3/2 o , 2 P 1/2 o , 2 D 5/2 o , and 2 D 3/2 o metastable state thresholds. Extensive analysis of the complex resonant structure in this region identified numerous Rydberg series of resonances and obtained the Se 2+ 4s 2 4p 23 P 2 and 4s 2 4p 21 S 0 state energies. In addition, particular attention was given to removing significant effects in the measurements due to a small percentage of higher-order undulator radiation.
Time series analysis of the developed financial markets' integration using visibility graphs
Zhuang, Enyu; Small, Michael; Feng, Gang
2014-09-01
A time series representing the developed financial markets' segmentation from 1973 to 2012 is studied. The time series reveals an obvious market integration trend. To further uncover the features of this time series, we divide it into seven windows and generate seven visibility graphs. The measuring capabilities of the visibility graphs provide means to quantitatively analyze the original time series. It is found that the important historical incidents that influenced market integration coincide with variations in the measured graphical node degree. Through the measure of neighborhood span, the frequencies of the historical incidents are disclosed. Moreover, it is also found that large "cycles" and significant noise in the time series are linked to large and small communities in the generated visibility graphs. For large cycles, how historical incidents significantly affected market integration is distinguished by density and compactness of the corresponding communities.
Reliability Analysis of the CERN Radiation Monitoring Electronic System CROME
AUTHOR|(CDS)2126870
For the new in-house developed CERN Radiation Monitoring Electronic System (CROME) a reliability analysis is necessary to ensure compliance with the statu-tory requirements regarding the Safety Integrity Level. The required Safety Integrity Level by IEC 60532 standard is SIL 2 (for the Safety Integrated Functions Measurement, Alarm Triggering and Interlock Triggering). The ﬁrst step of the reliability analysis was a system and functional analysis which served as basis for the implementation of the CROME system in the software “Iso-graph”. In the “Prediction” module of Isograph the failure rates of all components were calculated. Failure rates for passive components were calculated by the Military Standard 217 and failure rates for active components were obtained from lifetime tests by the manufacturers. The FMEA was carried out together with the board designers and implemented in the “FMECA” module of Isograph. The FMEA served as basis for the Fault Tree Analysis and the detection of weak points...
Reliability analysis of grid connected small wind turbine power electronics
International Nuclear Information System (INIS)
Arifujjaman, Md.; Iqbal, M.T.; Quaicoe, J.E.
2009-01-01
Grid connection of small permanent magnet generator (PMG) based wind turbines requires a power conditioning system comprising a bridge rectifier, a dc-dc converter and a grid-tie inverter. This work presents a reliability analysis and an identification of the least reliable component of the power conditioning system of such grid connection arrangements. Reliability of the configuration is analyzed for the worst case scenario of maximum conversion losses at a particular wind speed. The analysis reveals that the reliability of the power conditioning system of such PMG based wind turbines is fairly low and it reduces to 84% of initial value within one year. The investigation is further enhanced by identifying the least reliable component within the power conditioning system and found that the inverter has the dominant effect on the system reliability, while the dc-dc converter has the least significant effect. The reliability analysis demonstrates that a permanent magnet generator based wind energy conversion system is not the best option from the point of view of power conditioning system reliability. The analysis also reveals that new research is required to determine a robust power electronics configuration for small wind turbine conversion systems.
Determinants of Egyptian Banking Sector Profitability: Time-Series Analysis from 2004-2014
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Heba Youssef Hashem
2016-06-01
Full Text Available Purpose - The purpose of this paper is to examine the determinants of banking sector profitability in Egypt to shed light on the most influential variables that have a significant impact on the performance of this vital sector. Design/methodology/approach - The analysis includes a time series model of quarterly data from 2004 to 2014. The model utilizes Cointegration technique to investigate the long-run relationship between the return on equity as a proxy for bank profitability and several bank-specific variables including liquidity, capital adequacy, and percentage of non-performing loans. In addition, Vector Error Correction Model (VECM is utilized to explore the short-run dynamics of the model and the speed of adjustment to reach the long-run equilibrium. Findings - The main findings of this work show that banking sector profitability is inversely related to capital adequacy, the percentage of loan provisions and the ratio of deposits to total assets. On the other hand, it is positively related to the size of the banking sector which implies that the banking sector exhibits economies of scale. Research limitations/implications - The implications of this work is that it helps reveal the major factors affecting bank performance in the short-run and long-run, and hence provide bank managers and monetary policy makers with beneficial insights on how to enhance bank performance. Since the banking sector represents one of the main engines of financing investment, enhancing the efficiency of this sector would contribute to economic growth and prosperity Originality/value - The Vector error correction model showed that about 4% of the disequilibrium is corrected each quarter to reach the long run equilibrium. In addition, all bank specific variables were found to affect profitability in the long-run only. This study would serve as a base that further work on Egyptian banking sector profitability can build on by incorporating more variables in the
Temporal trend of carpal tunnel release surgery: a population-based time series analysis.
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Naif Fnais
Full Text Available BACKGROUND: Carpal tunnel release (CTR is among the most common hand surgeries, although little is known about its pattern. In this study, we aimed to investigate temporal trends, age and gender variation and current practice patterns in CTR surgeries. METHODS: We conducted a population-based time series analysis among over 13 million residents of Ontario, who underwent operative management for carpal tunnel syndrome (CTS from April 1, 1992 to March 31, 2010 using administrative claims data. RESULTS: The primary analysis revealed a fairly stable procedure rate of approximately 10 patients per 10,000 population per year receiving CTRs without any significant, consistent temporal trend (p = 0.94. Secondary analyses revealed different trends in procedure rates according to age. The annual procedure rate among those age >75 years increased from 22 per 10,000 population at the beginning of the study period to over 26 patients per 10,000 population (p<0.01 by the end of the study period. CTR surgical procedures were approximately two-fold more common among females relative to males (64.9% vs. 35.1 respectively; p<0.01. Lastly, CTR procedures are increasingly being conducted in the outpatient setting while procedures in the inpatient setting have been declining steadily - the proportion of procedures performed in the outpatient setting increased from 13% to over 30% by 2010 (p<0.01. CONCLUSION: Overall, CTR surgical-procedures are conducted at a rate of approximately 10 patients per 10,000 population annually with significant variation with respect to age and gender. CTR surgical procedures in ambulatory-care facilities may soon outpace procedure rates in the in-hospital setting.
Directory of Open Access Journals (Sweden)
David K Humphreys
Full Text Available On November 24(th 2005, the Government of England and Wales removed regulatory restrictions on the times at which licensed premises could sell alcohol. This study tests availability theory by treating the implementation of Licensing Act (2003 as a natural experiment in alcohol policy.An interrupted time series design was employed to estimate the Act's immediate and delayed impact on violence in the City of Manchester (Population 464,200. We collected police recorded rates of violence, robbery, and total crime between the 1st of February 2004 and the 31st of December 2007. Events were aggregated by week, yielding a total of 204 observations (95 pre-, and 109 post-intervention. Secondary analysis examined changes in daily patterns of violence. Pre- and post-intervention events were separated into four three-hour segments 18∶00-20∶59, 21∶00-23.59, 00∶00-02∶59, 03∶00-05∶59.Analysis found no evidence that the Licensing Act (2003 affected the overall volume of violence. However, analyses of night-time violence found a gradual and permanent shift of weekend violence into later parts of the night. The results estimated an initial increase of 27.5% between 03∶00 to 06∶00 (ω = 0.2433, 95% CI = 0.06, 0.42, which increased to 36% by the end of the study period (δ = -0.897, 95% CI = -1.02, -0.77.This study found no evidence that a national policy increasing the physical availability of alcohol affected the overall volume of violence. There was, however, evidence suggesting that the policy may be associated with changes to patterns of violence in the early morning (3 a.m. to 6 a.m..
Savage, Ruth L; Tatley, Michael V
2018-05-01
We undertook an analysis of all the reports to the New Zealand Centre for Adverse Reactions Monitoring of a roxithromycin/warfarin interaction after two recent reports described intense rapid warfarin potentiation. The interaction was first published in 1995. Cytochrome P450 3A4 inhibition has been the proposed mechanism but has limited biologic plausibility. There are suggestions that the clinical significance of the interaction may be increased by severe illness, polypharmacy, renal dysfunction, older age and increased warfarin sensitivity. To investigate the potentiating effect of warfarin on roxithromycin in this New Zealand case series, the reports were reviewed to identify patients at risk, compare the reporting pattern with published Australian data and evaluate the appropriateness of current prescribing advice. Thirty patient reports were identified. The age range was 23-88 years, mean 66.8, median 73.0 (standard deviation 17.7) and the international normalised ratios after roxithromycin commencement ranged from 3.6 to 16.7 (mean 7.6, median 7.6, standard deviation 3.6). For eight patients with measurements on day 3, international normalised ratios were 4.3-16.7 (mean 10.4, median 8.8, standard deviation 4.4). Four patients had serious haemorrhage. Indications for roxithromycin were a range of respiratory tract infections. Anticoagulation was stable for most patients prior to acute infection. Serious infection occurred in 54.5% (12 of 22 patients with information). Polypharmacy (five or more medicines daily) was used by 36.7% of patients long term, increasing acutely to 83.3%, including additional potentially interacting medicines. Warfarin daily dose (1.5-13.0 mg, mean 4.4, median 4.0, standard deviation 2.2) was moderate to low. Pre-roxithromycin international normalised ratio values ranged from 1.4 to 3.7, mean and median 2.5, standard deviation 0.5. A high proportion of interactions were observed between warfarin and roxithromycin compared with other
Forensic analysis of online marketing for electronic nicotine delivery systems.
Cobb, Nathan K; Brookover, Jody; Cobb, Caroline O
2015-03-01
Electronic nicotine delivery systems (ENDS) are growing in awareness and use in the USA. They are currently unregulated as the Food and Drug Administration has yet to assert jurisdiction under its tobacco authority over these products, and a US Court of Appeals held they cannot be regulated as drugs/delivery devices if they are not marketed for a therapeutic purpose. Observation of the current online marketplace suggests ENDS, like some nutraceutical products, are being promoted using affiliate marketing techniques using claims concerning purported health benefits. This study performed a forensic analysis to characterise the relationships between online ENDS affiliate advertisements and ENDS sellers, and evaluated descriptive content on advertisements and websites to inform future policy and regulatory efforts. A purposive sampling strategy was used to identify three forms of ENDS advertising. Web proxy software recorded identifiable objects and their ties to each other. Network analysis of these ties followed, as well as analysis of descriptive content on advertisements and websites identified. The forensic analysis included four ENDS advertisements, two linked affiliate websites, and two linked seller websites, and demonstrated a multilevel relationship between advertisements and sellers with multiple layers of redirection. Descriptive analysis indicated that advertisements and affiliates, but not linked sellers, included smoking cessation claims. Results suggest that ENDS sellers may be trying to distance marketing efforts containing unsubstantiated claims from sales. A separate descriptive analysis of 20 ENDS seller web pages indicated that the use of affiliate marketing by sellers may be widespread. These findings support increased monitoring and regulation of ENDS marketing to prevent deceptive marketing tactics and ensure consumer safety. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please
Klinker, Markus; Marante, Carlos; Argenti, Luca; González-Vázquez, Jesús; Martín, Fernando
2018-02-15
Direct measurement of autoionization lifetimes by using time-resolved experimental techniques is a promising approach when energy-resolved spectroscopic methods do not work. Attosecond time-resolved experiments have recently provided the first quantitative determination of autoionization lifetimes of the lowest members of the well-known Hopfield series of resonances in N 2 . In this work, we have used the recently developed XCHEM approach to study photoionization of the N 2 molecule in the vicinity of these resonances. The XCHEM approach allows us to describe electron correlation in the molecular electronic continuum at a level similar to that provided by multireference configuration interaction methods in bound state calculations, a necessary condition to accurately describe autoionization, shakeup, and interchannel couplings occurring in this range of photon energies. Our results show that electron correlation leading to interchannel mixing is the main factor that determines the magnitude and shape of the N 2 photoionization cross sections, as well as the lifetimes of the Hopfield resonances. At variance with recent speculations, nonadiabatic effects do not seem to play a significant role. These conclusions are supported by the very good agreement between the calculated cross sections and those determined in synchrotron radiation and attosecond experiments.
Energy Technology Data Exchange (ETDEWEB)
Han, Deming; Hao, Fengqi [School of Life Science and Technology, Changchun University of Science and Technology, Changchun 130022 (China); Tian, Jian [Clean Energy Technology Laboratory, Changchun University of Science and Technology, Changchun 130022 (China); Pang, Chunying; Li, Jingmei [School of Life Science and Technology, Changchun University of Science and Technology, Changchun 130022 (China); Zhao, Lihui, E-mail: zhaolihui@yahoo.com [School of Life Science and Technology, Changchun University of Science and Technology, Changchun 130022 (China); Zhang, Gang [State Key Laboratory of Theoretical and Computational Chemistry, Institute of Theoretical Chemistry, Jilin University, Changchun 130023 (China)
2015-03-15
The geometry structures, electronic structures, absorption and phosphorescent properties of a series of iridium(III) complexes with the different N-substitution cyclometalating ligand and the same benzyldiphenylphosphine auxiliary ligand have been theoretically investigated by using the density functional theory method. The lowest energy absorption wavelengths are located at 378 nm for A, 430 nm for B, 411 nm for C, 436 nm for D, and 394 nm for E. The introduction of N atom substitution at 1-, 2-, 3-, and 4-positions on the pyridyl moiety of complex A leads to an obvious redshifted absorption. The lowest energy emissions for complexes A–E are localized at 450, 409, 438, 483, and 429 nm, respectively, simulated in CH{sub 2}Cl{sub 2} medium at M052X level. Ionization potential and electron affinity have been calculated to evaluate the injection abilities of holes and electrons into these complexes. For complex C, the calculated results showed that it can possibly possess the larger radiative decay rate (k{sub r}) value than those of other four complexes. It is anticipated that the theoretical studies can provide valuable information for designing new phosphorescent metal complexes of organic light-emitting diodes. - Highlights: • Five Ir(III) complexes have been theoretically investigated. • The effect of N-substitution cyclometalating ligand has been studied. • The complex C possibly possesses the largest radiative decay rate value.
International Nuclear Information System (INIS)
Cousens, D.R.; French, D.H.; Ramsden, A.R.
1989-01-01
The limited contrast range of conventional black and white imaging does not enable full use to be made of the dynamic range of the video signal obtained from a scanning electron microscope or microprobe. The use of false colour substantially increases the information that can be derived from such images enabling relationships to be displayed that cannot be observed in black and white. This capability is now used extensively in combination with quantitative electron microprobe analysis as a research tool for ore characterization and host rocks studies related to minerals exploration in the CSIRO Div.sion of Exploration Geoscience. Thus the CAMEBAX scanning electron microprobe has been modified to allow digital images acquisition and software (IMAGE) developed which allows false colour backscatter electron (BSE) images to be obtained during the course of routine electron microprobe analysis. 1 fig
Energy Technology Data Exchange (ETDEWEB)
Vigdorovich, V.N.; Dzhuraev, T.D.
1985-03-01
Analogs and prototypes of the compounds supplementing the system of isoelectron isonuclear series of holovalent tetraelectron compounds by Gorunova are revealed. The investigation of all series of tetraelectron ovalenthol compounds allows one to supplement the variety of known series used for regular tracing and forecasting of compound properties (series of cation and anion substitutions by isonuclear series of the A/sup 4/B/sup 4/, A/sup 3/B/sup 5/, A/sup 1/B/sup 7/ type and others compounds. The above series for medium ordinal numbers anti Z equal 10, 14, 18, 23 and 36 permit to illustrate the possibility of existence of such analogs or series, for example for the compounds of the type A/sup 3/-- B/sup 5/:AlN-BP or Z=1(f AlP-ScN-BV (for Z=14), ScP-AlV (for Z=18), GaP-AlAs-YN-BNb (for Z=23) and YAs-GaNb-InV-ScSb-LaP-AlPr (for Z=36).
International Nuclear Information System (INIS)
Vigdorovich, V.N.; Dzhuraev, T.D.
1985-01-01
Analogs and prototypes of the compounds supplementing the system of isoelectron isonuclear series of holovalent tetraelectron compounds by Gorunova are revealed. The investigation of all series of tetraelectron ovalenthol compounds allows one to supplement the variety of known series used for regular tracing and forecasting of compound properties (series of cation and anion substitutions by isonuclear series of the A 4 B 4 , A 3 B 5 , A 1 B 7 type and others compounds. The above series for medium ordinal numbers anti Z equal 10, 14, 18, 23 and 36 permit to illustrate the possibility of existence of such analogs or series, for example for the compounds of the type A 3 -- B 5 :AlN-BP or Z=1(f AlP-ScN-BV (for Z=14), ScP-AlV (for Z=18), GaP-AlAs-YN-BNb ( for Z=23) and YAs-GaNb-InV-ScSb-LaP-AlPr (for Z=36)
Electron probe analysis of biological fluids: Possibilities and limitations
International Nuclear Information System (INIS)
Roinel, N.
1984-01-01
Physical methods of investigation have become essential to investigations at the cellular or subcellular level. Nuclear magnetic resonance is the most recent and striking example, since it is not only a tool for fundamental physicists and organic chemists, but also an extraordinary powerful imaging tool for physicians. The absorption properties of X rays were used immediately after their discovery to image the bones of skeletons. Later, X rays were also found to be extremely efficient in the measurement of the elemental content of microvolumes irradiated by electron probes. The electron probe analyzer (EPA) was immediately adopted by numerous laboratories of metallurgy, geology, and mineral sciences. In the last fifteen years, since the use of this instrument was suggested for liquid analysis, and a preparative technique was developed, the EPA has been used by an increasing number of biological laboratories for measuring the concentrations of the elements contained in subnanoliter volumes of biological fluids. The so-called microdroplet technique has become a routine laboratory method, the only one able to measure the concentrations of an unlimited number of elements in a single 0.1-nl sample. This explains its use in fields as various as renal, reproductive, digestive, and plant physiology, zoology, etc. Several review papers discuss these applications. The possibilities and limitations of the technique are discussed below
Analysis of series resistance effects on forward I - V and C - V characteristics of mis type diodes
International Nuclear Information System (INIS)
Altindal, S.; Tekeli, Z.; Karadeniz, S.; Tugluoglu, N.; Ercan, I.
2002-01-01
In order to determine the series resistance R s , we have followed Lie et al., Cheung et al. and Kang et al., from the plot of I vs dV/dLn(I) which was linear curve over a wide range of current values at each temperature. The values of Rs were obtained from the slope of the linear parts of the curves and then the series resistance at each temperature has been evaluated at Ln(I) vs (V-IR s ) curves. The curves are linear over a wide range of voltage. The most reliable values of ideality factor n and reverse saturation current Is were then determined. In addition to role of series resistance on the C-V and G-V characteristics of diode have been investigated. Both C-V and G-V measurements show that the measured capacitance and conductance seriously varies with applied bias and frequency due to presence of R s . The density of interface states, barrier height and series resistance from the forward bias I-V characteristics using this method agrees very well with that obtained from the capacitance technique. It is clear that ignoring the series resistance (device with high series resistance) can lead to significant errors in the analysis of the I-V-T, C-V-f and G-V-f characteristics
Analysis of three amphibian populations with quarter-century long time-series.
Meyer, A H; Schimidt, B R; Grossenbacher, K
1998-01-01
Amphibians are in decline in many parts of the world. Long tme-series of amphibian populations are necessary to distinguish declines from the often strong fluctuations observed in natural populations. Time-series may also help to understand the causes of these declines. We analysed 23-28-year long time-series of the frog Rana temporaria. Only one of the three studied populations showed a negative trend which was probably caused by the introduction of fish. Two populations appeared to be densi...
Directory of Open Access Journals (Sweden)
Philip Stearns
2011-06-01
Full Text Available Photo essay. A collection of Images produced by intentionally corrupting the circuitry of a Kodak DC280 2 MP digitalcamera. By rewiring the electronics of a digital camera, glitched images are produced in a manner that parallels chemically processing unexposed film or photographic paper to produce photographic images without exposure to light. The DCP Series of Digital Images are direct visualizations of data generated by a digital camera as it takes a picture. Electronic processes associated with the normal operations of the camera, which are usually taken for granted, are revealed through an act of intervention. The camera is turned insideout through complexes of shortcircuits, selected by the artist, transforming the camera from a picture taking device to a data capturing device that renders raw data (electronic signals as images. In essence, these images are snapshots of electronic signals dancing through the camera's circuits, manually rerouted, written directly to the onboard memory device. Rather than seeing images of the world through a lens, we catch a glimpse of what the camera sees when it is forced to peer inside its own mind.
LINGUISTIC FEATURES ANALYSIS OF THE ENGLISH ELECTRONIC COMMERCE WEBSITES
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Siti Nurani
2014-06-01
Full Text Available This research aims at identifying linguistic features used in the English electronic commerce websites used in correlation with the field, tenor and mode of discourse as parts of Systemic Functional Linguistics (SFL approach. Findings have shown that in the field of discourse, the linguistic features are largely appeared in the experiential domain analysis which shows that all terms of registers function as technical terms, of which the two major forms of nouns and verbs were the most frequent categories among other kinds of technical terms. The goal orientation is considered to be as a long term and the social activity is exchange. In the tenor of discourse, the linguistic features are highly appeared in the social distance analysis which shows that the social distance between participants is considered minimal. The agentive role is said to be equal and the social role is considered as non-hierarchic. In the mode of discourse, the linguistic features are excessively occurred in the language role analysis which exists equally of both constitutive and ancillary. The channel is in graphic mode. The medium is in written with a visual contact as its device.
Xia, Li C; Steele, Joshua A; Cram, Jacob A; Cardon, Zoe G; Simmons, Sheri L; Vallino, Joseph J; Fuhrman, Jed A; Sun, Fengzhu
2011-01-01
The increasing availability of time series microbial community data from metagenomics and other molecular biological studies has enabled the analysis of large-scale microbial co-occurrence and association networks. Among the many analytical techniques available, the Local Similarity Analysis (LSA) method is unique in that it captures local and potentially time-delayed co-occurrence and association patterns in time series data that cannot otherwise be identified by ordinary correlation analysis. However LSA, as originally developed, does not consider time series data with replicates, which hinders the full exploitation of available information. With replicates, it is possible to understand the variability of local similarity (LS) score and to obtain its confidence interval. We extended our LSA technique to time series data with replicates and termed it extended LSA, or eLSA. Simulations showed the capability of eLSA to capture subinterval and time-delayed associations. We implemented the eLSA technique into an easy-to-use analytic software package. The software pipeline integrates data normalization, statistical correlation calculation, statistical significance evaluation, and association network construction steps. We applied the eLSA technique to microbial community and gene expression datasets, where unique time-dependent associations were identified. The extended LSA analysis technique was demonstrated to reveal statistically significant local and potentially time-delayed association patterns in replicated time series data beyond that of ordinary correlation analysis. These statistically significant associations can provide insights to the real dynamics of biological systems. The newly designed eLSA software efficiently streamlines the analysis and is freely available from the eLSA homepage, which can be accessed at http://meta.usc.edu/softs/lsa.
Mathematics for electronic technology
Howson, D P
1975-01-01
Mathematics for Electronic Technology is a nine-chapter book that begins with the elucidation of the introductory concepts related to use of mathematics in electronic engineering, including differentiation, integration, partial differentiation, infinite series, vectors, vector algebra, and surface, volume and line integrals. Subsequent chapters explore the determinants, differential equations, matrix analysis, complex variable, topography, graph theory, and numerical analysis used in this field. The use of Fourier method for harmonic analysis and the Laplace transform is also described. The ma
WANG, D.; Wang, Y.; Zeng, X.
2017-12-01
Accurate, fast forecasting of hydro-meteorological time series is presently a major challenge in drought and flood mitigation. This paper proposes a hybrid approach, Wavelet De-noising (WD) and Rank-Set Pair Analysis (RSPA), that takes full advantage of a combination of the two approaches to improve forecasts of hydro-meteorological time series. WD allows decomposition and reconstruction of a time series by the wavelet transform, and hence separation of the noise from the original series. RSPA, a more reliable and efficient version of Set Pair Analysis, is integrated with WD to form the hybrid WD-RSPA approach. Two types of hydro-meteorological data sets with different characteristics and different levels of human influences at some representative stations are used to illustrate the WD-RSPA approach. The approach is also compared to three other generic methods: the conventional Auto Regressive Integrated Moving Average (ARIMA) method, Artificial Neural Networks (ANNs) (BP-error Back Propagation, MLP-Multilayer Perceptron and RBF-Radial Basis Function), and RSPA alone. Nine error metrics are used to evaluate the model performance. The results show that WD-RSPA is accurate, feasible, and effective. In particular, WD-RSPA is found to be the best among the various generic methods compared in this paper, even when the extreme events are included within a time series.
Mills, T
2012-01-01
This book develops the major themes of time series analysis from its formal beginnings in the early part of the 20th century to the present day through the research of six distinguished British statisticians, all of whose work is characterised by the British traits of pragmatism and the desire to solve practical problems of importance.
Menenti, M.; Azzali, S.; Verhoef, W.; Van Swol, R.
1993-01-01
Examples are presented of applications of a fast Fourier transform algorithm to analyze time series of images of Normalized Difference Vegetation Index values. The results obtained for a case study on Zambia indicated that differences in vegetation development among map units of an existing agroclimatic map were not significant, while reliable differences were observed among the map units obtained using the Fourier analysis.
D.E. Allen (David); M.J. McAleer (Michael); A.K. Singh (Abhay)
2016-01-01
textabstractThis paper features an analysis of the relationship between the DOW JONES Industrial Average Index (DJIA) and a sentiment news series using daily data obtained from the Thomson Reuters News Analytics (TRNA)1 provided by SIRCA (The Securities Industry Research Centre of the Asia Pacic).
Durbin, J.; Koopman, S.J.M.
1998-01-01
The analysis of non-Gaussian time series using state space models is considered from both classical and Bayesian perspectives. The treatment in both cases is based on simulation using importance sampling and antithetic variables; Monte Carlo Markov chain methods are not employed. Non-Gaussian
Directory of Open Access Journals (Sweden)
Caponnetto Pasquale
2011-12-01
Full Text Available Abstract Introduction Smoking cessation programs are useful in helping smokers to quit, but smoking is a very difficult addiction to break and the need for novel and effective approaches to smoking cessation interventions is unquestionable. The E-cigarette is a battery-powered electronic nicotine delivery device that may help smokers to remain abstinent during their quit attempt. We report for the first time objective measures of smoking cessation in smokers who experimented with the E-cigarette. Case presentation Three Caucasian smokers (two men aged 47 and 65 years and one woman aged 38 years with a documented history of recurring relapses were able to quit and to remain abstinent for at least six months after taking up an E-cigarette. Conclusions This is the first time that objective measures of smoking cessation are reported for smokers who quit successfully after using an E-cigarette. This was accomplished in smokers who repeatedly failed in previous attempts with professional smoking cessation assistance using the usual nicotine dependence treatments and smoking cessation counselling.
Energy Technology Data Exchange (ETDEWEB)
Bufaiçal, L., E-mail: lbufaical@ufg.br [Instituto de Física, Universidade Federal de Goiás, 74001-970 Goiânia, GO (Brazil); Adriano, C. [Instituto de Física “Gleb Wataghin”, UNICAMP, 13083-859 Campinas, SP (Brazil); Lora-Serrano, R. [Instituto de Física, Universidade Federal de Uberlândia, 38400-902 Uberlândia, MG (Brazil); Duque, J.G.S. [Núcleo de Física, Universidade Federal de Sergipe, Campus Itabaiana, 49500-000 Itabaiana, SE (Brazil); Mendonça-Ferreira, L. [Centro de Ciências Naturais e Humanas, Universidade Federal do ABC, 09210-170 Santo André, SP (Brazil); Rojas-Ayala, C.; Baggio-Saitovitch, E.; Bittar, E.M. [Centro Brasileiro de Pesquisas Físicas, 22290-180 Rio de Janeiro, RJ (Brazil); Pagliuso, P.G. [Instituto de Física “Gleb Wataghin”, UNICAMP, 13083-859 Campinas, SP (Brazil)
2014-04-01
Polycrystalline samples of the series of double perovskites Sr{sub 2−x}La{sub x}FeIrO{sub 6} were synthesized. Their structural, electronic and magnetic properties were investigated by X-ray powder diffraction, Mössbauer spectroscopy, magnetic susceptibility, heat capacity and electrical resistivity experiments. The compounds crystallize in a monoclinic structure and were fitted in space group P2{sub 1}/n, with a significant degree of Fe/Ir cationic disorder. As in Ca{sub 2−x}La{sub x}FeIrO{sub 6} the Sr-based system seems to evolve from an antiferromagnetic ground state for the end members (x=0.0 and x=2.0) to a ferrimagnetic order in the intermediate regions (x∼1). Since Mössbauer spectra indicate that Fe valence remains 3+ with doping, this tendency of change in the nature of the microscopic interaction could be attributed to Ir valence changes, induced by La{sup 3+} electrical doping. Upon comparing both Ca and Sr series, Sr{sub 2−x}La{sub x}FeIrO{sub 6} is more structurally homogenous and presents higher magnetization and transition temperatures. Magnetic susceptibility measurements at high temperatures on Sr{sub 1.2}La{sub 0.8}FeIrO{sub 6} indicate a very high ferrimagnetic Curie temperature T{sub C}∼700K. For the Sr{sub 2}FeIrO{sub 6} compound, electrical resistivity experiments under applied pressure suggest that this material might be a Mott insulator. - Graphical abstract: The Weiss constant as a function of La doping for the (Ca,Sr){sub 2−x}La{sub x}FeIrO{sub 6} series, indicating changes in Fe–Ir magnetic coupling on both families. - Highlights: • The double perovskite series (Ca,Sr){sub 2−x}La{sub x}FeIrO{sub 6} were synthesized. • Changes in the Fe-Ir magnetic coupling due to La doping on both series. • Evidence of high T{sub C} on Sr{sub 1.2}La{sub 0.8}FeIrO{sub 6}. • Indication of Mott insulator behavior on Sr{sub 2}FeIrO{sub 6}.
An econometric time-series analysis of global CO2 concentrations and emissions
International Nuclear Information System (INIS)
Cohen, B.C.; Labys, W.C.; Eliste, P.
2001-01-01
This paper extends previous work on the econometric modelling of CO 2 concentrations and emissions. The importance of such work rests in the fact that models of the Cohen-Labys variety represent the only alternative to scientific or physical models of CO 2 accumulations whose parameters are inferred rather than estimated. The stimulation for this study derives from the recent discovery of oscillations and cycles in the net biospheric flux of CO 2 . A variety of time series tests is thus used to search for the presence of normality, stationarity, cyclicality and stochastic processes in global CO 2 emissions and concentrations series. Given the evidence for cyclicality of a short-run nature in the spectra of these series, both structural time series and error correction model are applied to confirm the frequency and amplitude of these cycles. Our results suggest new possibilities for determining equilibrium levels of CO 2 concentrations and subsequently revising stabilization policies. (Author)
Cointegration and Error Correction Modelling in Time-Series Analysis: A Brief Introduction
Directory of Open Access Journals (Sweden)
Helmut Thome
2015-07-01
Full Text Available Criminological research is often based on time-series data showing some type of trend movement. Trending time-series may correlate strongly even in cases where no causal relationship exists (spurious causality. To avoid this problem researchers often apply some technique of detrending their data, such as by differencing the series. This approach, however, may bring up another problem: that of spurious non-causality. Both problems can, in principle, be avoided if the series under investigation are “difference-stationary” (if the trend movements are stochastic and “cointegrated” (if the stochastically changing trendmovements in different variables correspond to each other. The article gives a brief introduction to key instruments and interpretative tools applied in cointegration modelling.
Energy Technology Data Exchange (ETDEWEB)
Bordenave-Montesquieu, A.; Moretto-Capelle, P.; Gonzalez, A.; Benhenni, M. (Toulouse-3 Univ., 31 (France)); Bachau, H.; Sanchez, I. (Bordeaux-1 Univ., 33 - Talence (France). Lab. des Collisions Atomiques)
1994-09-28
A high resolution electron spectrometry of the (3lnl') Ryberg series populated in N[sup 7+] + He and Ne[sup 10+] + He collisions at 10 q keV, 10[sup o] allows us to observe, for the first time by this method, two post-collisional effects. First, it is found with nitrogen ions that, when n increases from n = 4 to 9, the L-distribution peaks more and more on the high angular momentum states. This is qualitatively understood as a Stark deformation of the Rydberg orbit by the Coulomb field of the receding ion. Also, in the n range where the double capture process populates symmetrical 4l4l' states (n>9), an enhancement of the intensities of the 3lnl' Rydberg lines is observed for both collisonal systems. This is thought to be a signature of the so-called auto transfer to Rydberg states effect. The transfer of population from the 3l4l' to the 3lnl' states is found to be favoured against a direct autoionization of these 4l4l' states into the n = 2 continuum. These experimental findings together with preliminary spectroscopic calculations concerning the configuration interaction of the Ne[sup 8+] (4l4l') states with the Ne[sup 8+](3lnl') Rydberg series are also discussed within the context of the electron stabilization which follows a double capture. (Author).