WorldWideScience

Sample records for series intervention analysis

  1. Dynamic Forecasting Conditional Probability of Bombing Attacks Based on Time-Series and Intervention Analysis.

    Science.gov (United States)

    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.

  2. Using time-series intervention analysis to understand U.S. Medicaid expenditures on antidepressant agents.

    Science.gov (United States)

    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.

  3. Modeling malaria control intervention effect in KwaZulu-Natal, South Africa using intervention time series analysis.

    Science.gov (United States)

    Ebhuoma, Osadolor; Gebreslasie, Michael; Magubane, Lethumusa

    The change of the malaria control intervention policy in South Africa (SA), re-introduction of dichlorodiphenyltrichloroethane (DDT), may be responsible for the low and sustained malaria transmission in KwaZulu-Natal (KZN). We evaluated the effect of the re-introduction of DDT on malaria in KZN and suggested practical ways the province can strengthen her already existing malaria control and elimination efforts, to achieve zero malaria transmission. We obtained confirmed monthly malaria cases in KZN from the malaria control program of KZN from 1998 to 2014. The seasonal autoregressive integrated moving average (SARIMA) intervention time series analysis (ITSA) was employed to model the effect of the re-introduction of DDT on confirmed monthly malaria cases. The result is an abrupt and permanent decline of monthly malaria cases (w 0 =-1174.781, p-value=0.003) following the implementation of the intervention policy. The sustained low malaria cases observed over a long period suggests that the continued usage of DDT did not result in insecticide resistance as earlier anticipated. It may be due to exophagic malaria vectors, which renders the indoor residual spraying not totally effective. Therefore, the feasibility of reducing malaria transmission to zero in KZN requires other reliable and complementary intervention resources to optimize the existing ones. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

  4. Evaluation of the effects of climate and man intervention on ground waters and their dependent ecosystems using time series analysis

    Science.gov (United States)

    Gemitzi, Alexandra; Stefanopoulos, Kyriakos

    2011-06-01

    SummaryGroundwaters and their dependent ecosystems are affected both by the meteorological conditions as well as from human interventions, mainly in the form of groundwater abstractions for irrigation needs. This work aims at investigating the quantitative effects of meteorological conditions and man intervention on groundwater resources and their dependent ecosystems. Various seasonal Auto-Regressive Integrated Moving Average (ARIMA) models with external predictor variables were used in order to model the influence of meteorological conditions and man intervention on the groundwater level time series. Initially, a seasonal ARIMA model that simulates the abstraction time series using as external predictor variable temperature ( T) was prepared. Thereafter, seasonal ARIMA models were developed in order to simulate groundwater level time series in 8 monitoring locations, using the appropriate predictor variables determined for each individual case. The spatial component was introduced through the use of Geographical Information Systems (GIS). Application of the proposed methodology took place in the Neon Sidirochorion alluvial aquifer (Northern Greece), for which a 7-year long time series (i.e., 2003-2010) of piezometric and groundwater abstraction data exists. According to the developed ARIMA models, three distinct groups of groundwater level time series exist; the first one proves to be dependent only on the meteorological parameters, the second group demonstrates a mixed dependence both on meteorological conditions and on human intervention, whereas the third group shows a clear influence from man intervention. Moreover, there is evidence that groundwater abstraction has affected an important protected ecosystem.

  5. Visual time series analysis

    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...

  6. The impact of harm reduction programs and police interventions on the number of syringes collected from public spaces. A time series analysis in Barcelona, 2004-2014.

    Science.gov (United States)

    Espelt, A; Villalbí, J R; Bosque-Prous, M; Parés-Badell, O; Mari-Dell'Olmo, M; Brugal, M T

    2017-12-01

    To estimate the effect of opening two services for people who use drugs and three police interventions on the number of discarded syringes collected from public spaces in Barcelona between 2004 and 2014. We conducted an interrupted time-series analysis of the monthly number of syringes collected from public spaces during this period. The dependent variable was the number of syringes collected per month. The main independent variables were month and five dummy variables (the opening of two facilities with safe consumption rooms, and three police interventions). To examine which interventions affected the number of syringes collected, we performed an interrupted time-series analysis using a quasi-Poisson regression model, obtaining relative risks (RR) and 95% confidence intervals (CIs). The number of syringes collected per month in Barcelona decreased from 13,800 in 2004 to 1655 in 2014 after several interventions. For example, following the closure of an open drug scene in District A of the city, we observed a decreasing trend in the number of syringes collected [RR=0.88 (95% CI: 0.82-0.95)], but an increasing trend in the remaining districts [RR=1.11 (95% CI: 1.05-1.17) and 1.08 (95% CI: 0.99-1.18) for districts B and C, respectively]. Following the opening of a harm reduction facility in District C, we observed an initial increase in the number collected in this district [RR=2.72 (95% CI: 1.57-4.71)] and stabilization of the trend thereafter [RR=0.97 (95% CI: 0.91-1.03)]. The overall number of discarded syringes collected from public spaces has decreased consistently in parallel with a combination of police interventions and the opening of harm reduction facilities. Copyright © 2017 Elsevier B.V. All rights reserved.

  7. Applied time series analysis

    CERN Document Server

    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)""…

  8. Time Series Analysis and Forecasting by Example

    CERN Document Server

    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

  9. 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...

  10. Time series analysis time series analysis methods and applications

    CERN Document Server

    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...

  11. A Course in Time Series Analysis

    CERN Document Server

    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

  12. A time series analysis of the effects of financial incentives and mandatory clinical applications as interventions to improve spontaneous adverse drug reaction reporting by hospital medical staff in China.

    Science.gov (United States)

    Chang, Feng; Xi, Yue; Zhao, Jie; Zhang, Xiaojian; Lu, Yun

    2017-12-01

    Spontaneous reporting of adverse drug reactions (ADRs) in hospitals is often under-reported, which may lead to problems in patient management. This study was aimed to assess the effectiveness of a financial intervention based on a fine and a bonus for improving spontaneous reporting of ADRs by physicians in a hospital setting. This study was conducted at the First Affiliated Hospital of Zhengzhou University (China). Starting in 2009, a bonus of 20 RMB (Chinese currency) was given for each spontaneous ADR report, and a fine of 50 RMB was given for any withheld ADR report. A time series analysis using autoregressive integrated moving average models was performed to assess the changes in the total number of spontaneous ADR reports between the preintervention period (2006-2008) and during the first (2009-2011) and second (2012-2014) intervention periods. The median number of reported ADRs per year increased from 29 (range 27-72) in the preintervention period to 277 (range 199-284) in the first intervention period and to 666 in the second (range 644-691). The monthly number of reported ADRs was stable during the 3 periods: 3.56 ± 3.60/month (95% confidence interval (CI), 2.42-4.75) during the preintervention period, 21 ± 13/month (95% CI, 16.97-25.80) in the first intervention period, and 56 ± 20/month (95% CI, 48.81-62.17) in the second intervention period. A financial incentive and ADR management regulations had a significant effect on the increase of reported ADRs. © 2017 John Wiley & Sons, Ltd.

  13. The foundations of modern time series analysis

    CERN Document Server

    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.

  14. Analysis of series resonant converter with series-parallel connection

    Science.gov (United States)

    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.

  15. 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...

  16. Applied time series analysis and innovative computing

    CERN Document Server

    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.

  17. Time Series Analysis Forecasting and Control

    CERN Document Server

    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

  18. Visibility Graph Based Time Series Analysis.

    Science.gov (United States)

    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.

  19. 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.

  20. Allan deviation analysis of financial return series

    Science.gov (United States)

    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.

  1. Introduction to time series analysis and forecasting

    CERN Document Server

    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.

  2. Entropic Analysis of Electromyography Time Series

    Science.gov (United States)

    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.

  3. Introduction to time series analysis and forecasting

    CERN Document Server

    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

  4. Nonlinear Time Series Analysis via Neural Networks

    Science.gov (United States)

    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.

  5. 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, ...

  6. 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)

  7. 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.

  8. The Statistical Analysis of Time Series

    CERN Document Server

    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

  9. Fourier analysis of time series an introduction

    CERN Document Server

    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

  10. Nonlinear time series analysis with R

    CERN Document Server

    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...

  11. Interrupted time-series analysis: studying trends in neurosurgery.

    Science.gov (United States)

    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.

  12. Time-Series Analysis: A Cautionary Tale

    Science.gov (United States)

    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.

  13. Motivating People To Be Physically Active. Physical Activity Intervention Series.

    Science.gov (United States)

    Marcus, Bess H.; Forsyth, LeighAnn H.

    This book describes proven methods for helping people change from inactive to active living. The behavior change methods are useful for healthy adults as well as individuals with chronic physical and psychological conditions. The book describes intervention programs for individuals and groups and for workplace and community settings. Part 1,…

  14. The impact of national-level interventions to improve hygiene on the incidence of irritant contact dermatitis in healthcare workers: changes in incidence from 1996 to 2012 and interrupted times series analysis.

    Science.gov (United States)

    Stocks, S J; McNamee, R; Turner, S; Carder, M; Agius, R M

    2015-07-01

    Reducing healthcare-associated infections (HCAI) has been a priority in the U.K. over recent decades and this has been reflected in interventions focusing on improving hygiene procedures. To evaluate whether these interventions coincided with an increased incidence of work-related irritant contact dermatitis (ICD) attributed to hand hygiene or/and other hygiene measures in healthcare workers (HCWs). A quasi-experimental (interrupted time series) design was used to compare trends in incidence of ICD in HCWs attributed to hygiene before and after interventions to reduce HCAI with trends in the same periods in control groups (ICD in other workers). Cases of ICD reported to a U.K. surveillance scheme from 1996 to 2012 were analysed. The time periods compared were defined objectively based on the dates of the publication of national evidence-based guidelines, the U.K. Health Act 2006 and the Cleanyourhands campaign. The reported incidence of ICD in HCWs attributed to hygiene has increased steadily from 1996 to 2012 [annual incidence rate ratio (95% confidence interval): hand hygiene only 1.10 (1.07-1.12); all hygiene 1.05 (1.03-1.07)], whereas the incidence in other workers is declining. An increase in incidence of ICD in HCWs attributed to hand hygiene was observed at the beginning of the Cleanyourhands campaign. The increasing incidence of ICD in HCWs combined with the popularity of interventions to reduce HCAI warrants increased efforts towards identifying products and implementing practices posing the least risk of ICD. © 2015 British Association of Dermatologists.

  15. Is mindfulness-based therapy an effective intervention for obsessive-intrusive thoughts: a case series.

    Science.gov (United States)

    Wilkinson-Tough, Megan; Bocci, Laura; Thorne, Kirsty; Herlihy, Jane

    2010-01-01

    Despite the efficacy of cognitive-behavioural interventions in improving the experience of obsessions and compulsions, some people do not benefit from this approach. The present research uses a case series design to establish whether mindfulness-based therapy could benefit those experiencing obsessive-intrusive thoughts by targeting thought-action fusion and thought suppression. Three participants received a relaxation control intervention followed by a six-session mindfulness-based intervention which emphasized daily practice. Following therapy all participants demonstrated reductions in Yale-Brown Obsessive-Compulsive Scale scores to below clinical levels, with two participants maintaining this at follow-up. Qualitative analysis of post-therapy feedback suggested that mindfulness skills such as observation, awareness and acceptance were seen as helpful in managing thought-action fusion and suppression. Despite being limited by small participant numbers, these results suggest that mindfulness may be beneficial to some people experiencing intrusive unwanted thoughts and that further research could establish the possible efficacy of this approach in larger samples. Copyright (c) 2009 John Wiley & Sons, Ltd.

  16. MODIS Time Series to Detect Anthropogenic Interventions and Degradation Processes in Tropical Pasture

    Directory of Open Access Journals (Sweden)

    Daniel Alves Aguiar

    2017-01-01

    Full Text Available The unavoidable diet change in emerging countries, projected for the coming years, will significantly increase the global consumption of animal protein. It is expected that Brazilian livestock production, responsible for close to 15% of global production, be prepared to answer to the increasing demand of beef. Consequently, the evaluation of pasture quality at regional scale is important to inform public policies towards a rational land use strategy directed to improve livestock productivity in the country. Our hypothesis is that MODIS images can be used to evaluate the processes of degradation, restoration and renovation of tropical pastures. To test this hypothesis, two field campaigns were performed covering a route of approximately 40,000 km through nine Brazilian states. To characterize the sampled pastures, biophysical parameters were measured and observations about the pastures, the adopted management and the landscape were collected. Each sampled pasture was evaluated using a time series of MODIS EVI2 images from 2000–2012, according to a new protocol based on seven phenological metrics, 14 Boolean criteria and two numerical criteria. The theoretical basis of this protocol was derived from interviews with producers and livestock experts during a third field campaign. The analysis of the MODIS EVI2 time series provided valuable historical information on the type of intervention and on the biological degradation process of the sampled pastures. Of the 782 pastures sampled, 26.6% experienced some type of intervention, 19.1% were under biological degradation, and 54.3% presented neither intervention nor trend of biomass decrease during the period analyzed.

  17. Intervention analysis of power plant impact on fish populations

    International Nuclear Information System (INIS)

    Madenjian, C.P.

    1984-01-01

    Intervention analysis was applied to 10 yr (years 1973-1982) of field fish abundance data at the D. C. Cook Nuclear Power Plant, southeastern Lake Michigan. Three log-transformed catch series, comprising monthly observations, were examined for each combination of two species (alewife, Alosa pseudoharenga, or yellow perch, Perca flavescens) and gear (trawl or gill net): catch at the plant discharged transect, catch at the reference transect, and the ratio of plant catch to reference catch. Time series separated by age groups were examined. Based on intervention analysis, no change in the abundance of fish populations could be attributed to plant operation. Additionally, a modification of the intervention analysis technique was applied to investigate trends in abundance at both the plant discharge and reference transects. Significant declines were detected for abundance of alewife adults at both of the transects. Results of the trend analysis support the contention that the alewives have undergone a lakewide decrease in abundance during the 1970s

  18. Highly comparative time-series analysis: the empirical structure of time series and their methods.

    Science.gov (United States)

    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.

  19. Time series analysis of temporal networks

    Science.gov (United States)

    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

  20. Improving Teachers' Knowledge of Functional Assessment-Based Interventions: Outcomes of a Professional Development Series

    Science.gov (United States)

    Lane, Kathleen Lynne; Oakes, Wendy Peia; Powers, Lisa; Diebold, Tricia; Germer, Kathryn; Common, Eric A.; Brunsting, Nelson

    2015-01-01

    This paper provides outcomes of a study examining the effectiveness of a year-long professional development training series designed to support in-service educators in learning a systematic approach to functional assessment-based interventions developed by Umbreit and colleagues (2007) that has met with demonstrated success when implemented with…

  1. Nonparametric factor analysis of time series

    OpenAIRE

    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.

  2. DIY Solar Market Analysis Webinar Series: Solar Resource and Technical

    Science.gov (United States)

    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

  3. What marketing scholars should know about time series analysis : time series applications in marketing

    NARCIS (Netherlands)

    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

  4. Time series analysis in the social sciences the fundamentals

    CERN Document Server

    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

  5. Ecological Momentary Assessments and Automated Time Series Analysis to Promote Tailored Health Care : A Proof-of-Principle Study

    NARCIS (Netherlands)

    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,

  6. 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.

  7. Mathematical foundations of time series analysis a concise introduction

    CERN Document Server

    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.

  8. Zoning and workstation analysis in interventional cardiology

    International Nuclear Information System (INIS)

    Degrange, J.P.

    2009-01-01

    As interventional cardiology can induce high doses not only for patients but also for the personnel, the delimitation of regulated areas (or zoning) and workstation analysis (dosimetry) are very important in terms of radioprotection. This paper briefly recalls methods and tools for the different steps to perform zoning and workstation analysis. It outlines the peculiarities of interventional cardiology, presents methods and tools adapted to interventional cardiology, and then discusses the same issues but for workstation analysis. It also outlines specific problems which can be met, and their possible adapted solutions

  9. Time Series Analysis Using Geometric Template Matching.

    Science.gov (United States)

    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.

  10. Time series evaluation of an intervention to increase statin tablet splitting by general practitioners.

    Science.gov (United States)

    Polinski, Jennifer M; Schneeweiss, Sebastian; Maclure, Malcolm; Marshall, Blair; Ramsden, Samuel; Dormuth, Colin

    2011-02-01

    Tablet splitting, in which a higher-dose tablet is split to get 2 doses, reduces patients' drug costs. Statins can be split safely. General practitioners (GPs) may not direct their patients to split statins because of safety concerns or unawareness of costs. Medical chart inserts provide cost-effective education to physicians. The aim of this study was to assess whether providing GPs with statin-splitting chart inserts would increase splitting rates, and to identify predictors of splitting. In 2005 and 2006, we faxed a statin chart insert to British Columbia GPs with a request for a telephone interview. Consenting GPs were mailed 3 statin chart inserts and interviewed by phone (the intervention). In an interrupted time series, we compared monthly rates of statin-splitting prescriptions among intervention and nonintervention GPs before, during, and after the intervention. In multivariate logistic regressions accounting for patient clustering, predictors of splitting included physician and patient demographics and the specific statin prescribed. Of 5051 GPs reached, 282 (6%) agreed to the intervention. Before the intervention, GPs' splitting rate was 2.6%; after intervention, GPs' splitting rate was 7.5%. The rate for the nonintervention GPs was 4.4%. Intervention GPs were 1.68 (95% CI, 1.12-2.53) times more likely to prescribe splitting after the intervention than were nonintervention GPs. Other predictors were a patient's female sex (odds ratio [OR] = 1.26; 95% CI, 1.18-1.34), lower patient income (OR = 1.33; 95% CI, 1.18-1.34), and a lack of drug insurance (OR = 1.89; 95% CI, 1.69-2.04). An inexpensive intervention was effective in producing a sustained increase in GPs' splitting rate during 22 months of observed follow-up. Expanding statin-splitting education to all GPs might reduce prescription costs for many patients and payors. Copyright © 2011 Elsevier HS Journals, Inc. All rights reserved.

  11. 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 ...

  12. Intervention Analysis of Nigeria's Foreign Exchange Rate ...

    African Journals Online (AJOL)

    ADOWIE PERE

    to 2014:12 were used and a number of statistical tools are employed to verify this hypothesis. A useful approach is to ..... Conclusion: We have applied the intervention analysis to model ... Nigerian Journal of Economic and Social studies, Vol.

  13. Stochastic time series analysis of hydrology data for water resources

    Science.gov (United States)

    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.

  14. Case Series of a Knowledge Translation Intervention to Increase Upper Limb Exercise in Stroke Rehabilitation.

    Science.gov (United States)

    Connell, Louise A; McMahon, Naoimh E; Tyson, Sarah F; Watkins, Caroline L; Eng, Janice J

    2016-12-01

    Current approaches to upper limb rehabilitation are not sufficient to drive neural reorganization and maximize recovery after stroke. To address this evidence-practice gap, a knowledge translation intervention using the Behaviour Change Wheel was developed. The intervention involves collaboratively working with stroke therapy teams to change their practice and increase therapy intensity by therapists prescribing supplementary self-directed arm exercise. The purposes of this case series are: (1) to provide an illustrative example of how a research-informed process changed clinical practice and (2) to report on staff members' and patients' perceptions of the utility of the developed intervention. A participatory action research approach was used in 3 stroke rehabilitation units in the United Kingdom. The intervention aimed to change 4 therapist-level behaviors: (1) screening patients for suitability for supplementary self-directed arm exercise, (2) provision of exercises, (3) involving family and caregivers in assisting with exercises, and (4) monitoring and progressing exercises. Data on changes in practice were collected by therapy teams using a bespoke audit tool. Utility of the intervention was explored in qualitative interviews with patients and staff. Components of the intervention were successfully embedded in 2 of the 3 stroke units. At these sites, almost all admitted patients were screened for suitability for supplementary self-directed exercise. Exercises were provided to 77%, 70%, and 88% of suitable patients across the 3 sites. Involving family and caregivers and monitoring and progressing exercises were not performed consistently. This case series is an example of how a rigorous research-informed knowledge translation process resulted in practice change. Research is needed to demonstrate that these changes can translate into increased intensity of upper limb exercise and affect patient outcomes. © 2016 American Physical Therapy Association.

  15. 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

  16. 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)

  17. Tool Wear Monitoring Using Time Series Analysis

    Science.gov (United States)

    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.

  18. Metagenomics meets time series analysis: unraveling microbial community dynamics

    NARCIS (Netherlands)

    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

  19. Law enforcement-applied tourniquets: a case series of life-saving interventions.

    Science.gov (United States)

    Callaway, David W; Robertson, Joshua; Sztajnkrycer, Matthew D

    2015-01-01

    Although the epidemiology of civilian trauma is distinct from that encountered in combat, in both settings, extremity hemorrhage remains a major preventable cause of potential mortality. The current paper describes the largest case series in the literature in which police officers arriving prior to emergency medical services applied commercially available field tourniquets to civilian victims of violent trauma. Although all 3 patients with vascular injury arrived at the receiving emergency department in extremis, they were successfully resuscitated and survived to discharge without major morbidity. While this outcome is likely multifactorial and highlights the exceptional care delivered by the modern trauma system, tourniquet application appears to have kept critically injured patients alive long enough to reach definitive trauma care. No patient had a tourniquet-related complication. This case series suggests that law enforcement officers can effectively identify indications for tourniquets and rapidly apply such life-saving interventions.

  20. AHRQ series on complex intervention systematic reviews-paper 7: PRISMA-CI elaboration and explanation.

    Science.gov (United States)

    Guise, Jeanne-Marie; Butler, Mary; Chang, Christine; Viswanathan, Meera; Pigott, Terri; Tugwell, Peter

    2017-10-01

    Complex interventions are widely used in health care, public health, education, criminology, social work, business, and welfare. They have increasingly become the subject of systematic reviews and are challenging to effectively report. The Complex Interventions Methods Workgroup developed an extension to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses for Complex Interventions (PRISMA-CI). Following the EQUATOR Network guidance for Preferred Reporting Items for Systematic Reviews and Meta-Analysis extensions, this Explanation and Elaboration (EE) document accompanies the PRISMA-CI checklist to promote consistency in reporting of systematic reviews of complex interventions. The EE document explains the meaning and rationale for each unique PRISMA-CI checklist item and provides examples to assist systematic review authors in operationalizing PRISMA-CI guidance. The Complex Interventions Workgroup developed PRISMA-CI as an important start toward increased consistency in reporting of systematic reviews of complex interventions. Because the field is rapidly expanding, the Complex Interventions Methods Workgroup plans to re-evaluate periodically for the need to add increasing specificity and examples as the field matures. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

  1. Topic Time Series Analysis of Microblogs

    Science.gov (United States)

    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

  2. Time Series Factor Analysis with an Application to Measuring Money

    NARCIS (Netherlands)

    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

  3. Time averaging, ageing and delay analysis of financial time series

    Science.gov (United States)

    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.

  4. 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

  5. Time Series Analysis of Insar Data: Methods and Trends

    Science.gov (United States)

    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.

  6. Stochastic Analysis : A Series of Lectures

    CERN Document Server

    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...

  7. Transition Icons for Time-Series Visualization and Exploratory Analysis.

    Science.gov (United States)

    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.

  8. 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.

  9. Multivariate time series analysis with R and financial applications

    CERN Document Server

    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

  10. Elements of nonlinear time series analysis and forecasting

    CERN Document Server

    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...

  11. 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

  12. Cost effective management of duodenal ulcers in Uganda: interventions based on a series of seven cases.

    Science.gov (United States)

    Nzarubara, Gabriel R

    2005-03-01

    Our understanding of the cause and treatment of peptic ulcer disease has changed dramatically over the last couple of decades. It was quite common some years ago to treat chronic ulcers surgically. These days, the operative treatment is restricted to the small proportion of ulcer patients who have complications such as perforation. The author reports seven cases of perforated duodenal ulcers seen in a surgical clinic between 1995 and 2001. Recommendations on the criteria for selecting the appropriate surgical intervention for patients with perforated duodenal ulcer are given. To decide on the appropriate surgical interventions for patients with perforated duodenal ulcer. These are case series of 7 patients who presented with perforated duodenal ulcers without a history of peptic ulcer disease. Seven patients presented with perforated duodenal ulcer 72 hours after perforation in a specialist surgical clinic in Kampala were analyzed. Appropriate management based on these patients is suggested. These patients were initially treated in upcountry clinics for acute gastritis from either alcohol consumption or suspected food poisoning. There was no duodenal ulcer history. As a result, they came to specialist surgical clinic more than 72 hours after perforation. Diagnosis of perforated duodenal ulcer was made and they were operated using the appropriate surgical intervention. Diagnosis of hangovers and acute gastritis from alcoholic consumption or suspected food poisoning should be treated with suspicion because the symptoms and signs may mimic perforated peptic ulcer in "silent" chronic ulcers. The final decision on the appropriate surgical intervention for patients with perforated duodenal ulcer stratifies them into two groups: The previously fit patients who have relatively mild physiological compromise imposed on previously healthy organ system by the perforation can withstand the operative stress of definitive procedure. The Second category includes patients who are

  13. 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

  14. 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.

  15. 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

  16. Handbook of Time Series Analysis Recent Theoretical Developments and Applications

    CERN Document Server

    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

  17. A combined teamwork training and work standardisation intervention in operating theatres: controlled interrupted time series study.

    Science.gov (United States)

    Morgan, Lauren; Pickering, Sharon P; Hadi, Mohammed; Robertson, Eleanor; New, Steve; Griffin, Damian; Collins, Gary; Rivero-Arias, Oliver; Catchpole, Ken; McCulloch, Peter

    2015-02-01

    Teamwork training and system standardisation have both been proposed to reduce error and harm in surgery. Since the approaches differ markedly, there is potential for synergy between them. Controlled interrupted time series with a 3 month intervention and observation phases before and after. Operating theatres conducting elective orthopaedic surgery in a single hospital system (UK Hospital Trust). Teamwork training based on crew resource management plus training and follow-up support in developing standardised operating procedures. Focus of subsequent standardisation efforts decided by theatre staff. Paired observers watched whole procedures together. We assessed non-technical skills using NOTECHS II, technical performance using glitch rate and compliance with WHO checklist using a simple quality tool. We measured complication and readmission rates and hospital stay using hospital administrative records. Before/after change was compared in the active and control groups using two-way ANOVA and regression models. 1121 patients were operated on before and 1100 after intervention. 44 operations were observed before and 50 afterwards. Non-technical skills (p=0.002) and WHO compliance (pteamwork and system improvement causes marked improvements in team behaviour and WHO performance, but not technical performance or outcome. These findings are consistent with the synergistic hypothesis, but larger controlled studies with a strong implementation strategy are required to test potential outcome effects. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

  18. Twitter-Delivered Behavioral Weight-Loss Interventions: A Pilot Series.

    Science.gov (United States)

    Pagoto, Sherry L; Waring, Molly E; Schneider, Kristin L; Oleski, Jessica L; Olendzki, Effie; Hayes, Rashelle B; Appelhans, Bradley M; Whited, Matthew C; Busch, Andrew M; Lemon, Stephenie C

    2015-10-23

    Lifestyle interventions are efficacious at reducing risk for diabetes and cardiovascular disease but have not had a significant public health impact given high cost and patient and provider burden. Online social networks may reduce the burden of lifestyle interventions to the extent that they displace in-person visits and may enhance opportunities for social support for weight loss. We conducted an iterative series of pilot studies to evaluate the feasibility and acceptability of using online social networks to deliver a lifestyle intervention. In Study 1 (n=10), obese participants with depression received lifestyle counseling via 12 weekly group visits and a private group formed using the online social network, Twitter. Mean weight loss was 2.3 pounds (SD 7.7; range -19.2 to 8.2) or 1.2% (SD 3.6) of baseline weight. A total of 67% (6/9) of participants completing exit interviews found the support of the Twitter group at least somewhat useful. In Study 2 (n=11), participants were not depressed and were required to be regular users of social media. Participants lost, on average, 5.6 pounds (SD 6.3; range -15 to 0) or 3.0% (SD 3.4) of baseline weight, and 100% (9/9) completing exit interviews found the support of the Twitter group at least somewhat useful. To explore the feasibility of eliminating in-person visits, in Study 3 (n=12), we delivered a 12-week lifestyle intervention almost entirely via Twitter by limiting the number of group visits to one, while using the same inclusion criteria as that used in Study 2. Participants lost, on average, 5.4 pounds (SD 6.4; range -14.2 to 3.9) or 3.0% (SD 3.1) of baseline weight, and 90% (9/10) completing exit interviews found the support of the Twitter group at least somewhat useful. Findings revealed that a private Twitter weight-loss group was both feasible and acceptable for many patients, particularly among regular users of social media. Future research should evaluate the efficacy and cost-effectiveness of online

  19. Time series analysis and its applications with R examples

    CERN Document Server

    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...

  20. Multiresolution analysis of Bursa Malaysia KLCI time series

    Science.gov (United States)

    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.

  1. Time Series Analysis of Wheat Futures Reward in China

    Institute of Scientific and Technical Information of China (English)

    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.

  2. 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.

  3. 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

  4. Time series analysis of monthly pulpwood use in the Northeast

    Science.gov (United States)

    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.

  5. Multi-granular trend detection for time-series analysis

    NARCIS (Netherlands)

    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

  6. Time Series Analysis Based on Running Mann Whitney Z Statistics

    Science.gov (United States)

    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-...

  7. 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...

  8. Time Series Analysis of 3D Coordinates Using Nonstochastic Observations

    NARCIS (Netherlands)

    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

  9. Time Series Analysis of 3D Coordinates Using Nonstochastic Observations

    NARCIS (Netherlands)

    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

  10. Identification of human operator performance models utilizing time series analysis

    Science.gov (United States)

    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.

  11. 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 ...

  12. Complexity analysis of the turbulent environmental fluid flow time series

    Science.gov (United States)

    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.

  13. Time series analysis methods and applications for flight data

    CERN Document Server

    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.

  14. Time series analysis of ozone data in Isfahan

    Science.gov (United States)

    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.

  15. Using forecast modelling to evaluate treatment effects in single-group interrupted time series analysis.

    Science.gov (United States)

    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.

  16. 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

  17. Mathematical methods in time series analysis and digital image processing

    CERN Document Server

    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.

  18. Spectral Unmixing Analysis of Time Series Landsat 8 Images

    Science.gov (United States)

    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.

  19. Is Stacking Intervention Components Cost-Effective? An Analysis of the Incredible Years Program

    Science.gov (United States)

    Foster, E. Michael; Olchowski, Allison E.; Webster-Stratton, Carolyn H.

    2007-01-01

    The cost-effectiveness of delivering stacked multiple intervention components for children is compared to implementing single intervention by analyzing the Incredible Years Series program. The result suggests multiple intervention components are more cost-effective than single intervention components.

  20. Notes on economic time series analysis system theoretic perspectives

    CERN Document Server

    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...

  1. Topological data analysis of financial time series: Landscapes of crashes

    Science.gov (United States)

    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.

  2. 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...

  3. Interrupted time series analysis in drug utilization research is increasing: systematic review and recommendations.

    Science.gov (United States)

    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.

  4. Time Series Analysis, Modeling and Applications A Computational Intelligence Perspective

    CERN Document Server

    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...

  5. Recurrence Density Enhanced Complex Networks for Nonlinear Time Series Analysis

    Science.gov (United States)

    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.

  6. Time series analysis for psychological research: examining and forecasting change.

    Science.gov (United States)

    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.

  7. Time series analysis for psychological research: examining and forecasting change

    Science.gov (United States)

    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

  8. 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

  9. 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.

  10. Time series clustering analysis of health-promoting behavior

    Science.gov (United States)

    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.

  11. Time series analysis of gold production in Malaysia

    Science.gov (United States)

    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.

  12. 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.

  13. Pipe-anchor discontinuity analysis utilizing power series solutions, Bessel functions, and Fourier series

    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

  14. 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 δ18O 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.

  15. Remote-Sensing Time Series Analysis, a Vegetation Monitoring Tool

    Science.gov (United States)

    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

  16. Inorganic chemical analysis of environmental materials—A lecture series

    Science.gov (United States)

    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.

  17. 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.

  18. 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.)

  19. Studies in Astronomical Time Series Analysis. VI. Bayesian Block Representations

    Science.gov (United States)

    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.

  20. 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.

  1. Effectiveness of Non-Pharmacological Interventions to Prevent Falls in Older People: A Systematic Overview. The SENATOR Project ONTOP Series

    Science.gov (United States)

    Rimland, Joseph M.; Abraha, Iosief; Dell’Aquila, Giuseppina; Cruz-Jentoft, Alfonso; Soiza, Roy; Gudmusson, Adalsteinn; Petrovic, Mirko; O’Mahony, Denis; Todd, Chris; Cherubini, Antonio

    2016-01-01

    Background Falls are common events in older people, which cause considerable morbidity and mortality. Non-pharmacological interventions are an important approach to prevent falls. There are a large number of systematic reviews of non-pharmacological interventions, whose evidence needs to be synthesized in order to facilitate evidence-based clinical decision making. Objectives To systematically examine reviews and meta-analyses that evaluated non-pharmacological interventions to prevent falls in older adults in the community, care facilities and hospitals. Methods We searched the electronic databases Pubmed, the Cochrane Database of Systematic Reviews, EMBASE, CINAHL, PsycINFO, PEDRO and TRIP from January 2009 to March 2015, for systematic reviews that included at least one comparative study, evaluating any non-pharmacological intervention, to prevent falls amongst older adults. The quality of the reviews was assessed using AMSTAR and ProFaNE taxonomy was used to organize the interventions. Results Fifty-nine systematic reviews were identified which consisted of single, multiple and multifactorial non-pharmacological interventions to prevent falls in older people. The most frequent ProFaNE defined interventions were exercises either alone or combined with other interventions, followed by environment/assistive technology interventions comprising environmental modifications, assistive and protective aids, staff education and vision assessment/correction. Knowledge was the third principle class of interventions as patient education. Exercise and multifactorial interventions were the most effective treatments to reduce falls in older adults, although not all types of exercise were equally effective in all subjects and in all settings. Effective exercise programs combined balance and strength training. Reviews with a higher AMSTAR score were more likely to contain more primary studies, to be updated and to perform meta-analysis. Conclusions The aim of this overview of

  2. A non linear analysis of human gait time series based on multifractal analysis and cross correlations

    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

  3. A non linear analysis of human gait time series based on multifractal analysis and cross correlations

    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.

  4. 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 ...

  5. Statistical analysis and application of quasi experiments to antimicrobial resistance intervention studies.

    Science.gov (United States)

    Shardell, Michelle; Harris, Anthony D; El-Kamary, Samer S; Furuno, Jon P; Miller, Ram R; Perencevich, Eli N

    2007-10-01

    Quasi-experimental study designs are frequently used to assess interventions that aim to limit the emergence of antimicrobial-resistant pathogens. However, previous studies using these designs have often used suboptimal statistical methods, which may result in researchers making spurious conclusions. Methods used to analyze quasi-experimental data include 2-group tests, regression analysis, and time-series analysis, and they all have specific assumptions, data requirements, strengths, and limitations. An example of a hospital-based intervention to reduce methicillin-resistant Staphylococcus aureus infection rates and reduce overall length of stay is used to explore these methods.

  6. Centrality measures in temporal networks with time series analysis

    Science.gov (United States)

    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.

  7. Adult Craniopharyngioma: Case Series, Systematic Review, and Meta-Analysis.

    Science.gov (United States)

    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

  8. Assessing Spontaneous Combustion Instability with Nonlinear Time Series Analysis

    Science.gov (United States)

    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.

  9. The Effectiveness of Cognitive Behavioral Therapy With Mindfulness and an Internet Intervention for Obesity: A Case Series

    Directory of Open Access Journals (Sweden)

    Keizaburo Ogata

    2018-06-01

    Full Text Available It is difficult for obese (body mass index of more than 30 and overweight (body mass index of 25–30 people to reduce and maintain their weight. The aim of this case series was to examine the effectiveness of a new cognitive behavioral therapy (CBT program that combines mindfulness exercises (e.g., the raisin exercise and breathing exercises and an online intervention to prevent dropout and subsequent weight gain in overweight participants. This case series included three participants, for whom previous weight reduction programs had been unsuccessful. All participants completed the program (60-min, group sessions provided weekly for 9 weeks and an 18-month follow-up assessment. Results showed that all participants succeeded in losing weight (loss ranged from 5.30 to 8.88% of their total body weight. Although rebound weight gain is commonly observed in the first year following initial weight loss, the follow-up assessment showed that participants achieved further weight loss during the 18-month follow-up period. These results suggest that a CBT program that comprises mindfulness and an online intervention may be an effective method for weight loss and maintenance, and may prevent dropout in obese and overweight individuals.Trial Registration: This case series was registered at www.umin.ac.jp with identifier UMIN000029664.

  10. Modeling activity patterns of wildlife using time-series analysis.

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    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.

  12. A robust interrupted time series model for analyzing complex health care intervention data

    KAUST Repository

    Cruz, Maricela

    2017-08-29

    Current health policy calls for greater use of evidence-based care delivery services to improve patient quality and safety outcomes. Care delivery is complex, with interacting and interdependent components that challenge traditional statistical analytic techniques, in particular, when modeling a time series of outcomes data that might be

  13. A robust interrupted time series model for analyzing complex health care intervention data

    KAUST Repository

    Cruz, Maricela; Bender, Miriam; Ombao, Hernando

    2017-01-01

    Current health policy calls for greater use of evidence-based care delivery services to improve patient quality and safety outcomes. Care delivery is complex, with interacting and interdependent components that challenge traditional statistical analytic techniques, in particular, when modeling a time series of outcomes data that might be

  14. Time series analysis as input for clinical predictive modeling: modeling cardiac arrest in a pediatric ICU.

    Science.gov (United States)

    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

  15. Trend analysis of time-series data: A novel method for untargeted metabolite discovery

    NARCIS (Netherlands)

    Peters, S.; Janssen, H.-G.; Vivó-Truyols, G.

    2010-01-01

    A new strategy for biomarker discovery is presented that uses time-series metabolomics data. Data sets from samples analysed at different time points after an intervention are searched for compounds that show a meaningful trend following the intervention. Obviously, this requires new data-analytical

  16. Time Series Analysis of the Quasar PKS 1749+096

    Science.gov (United States)

    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.

  17. School Rampage Shootings and Other Youth Disturbances: Early Preventative Interventions. Psychosocial Stress Series

    Science.gov (United States)

    Nader, Kathleen, Ed.

    2012-01-01

    Together, "School Rampage Shootings and Other Youth Disturbances" and its accompanying CD provide a complete toolkit for using early preventative interventions with elementary-school age children. In ten thoughtful, clearly written chapters, both new and experienced practitioners will find a wealth of research- and evidence-based…

  18. 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

  19. A series of studies examining Internet treatment of obesity to inform Internet interventions for substance use and misuse.

    Science.gov (United States)

    Tate, Deborah F

    2011-01-01

    The feasibility and efficacy of Internet treatment programs for overweight and obese people have been demonstrated in a series of randomized trials. Initial studies examined various approaches to Internet behavioral treatment. Other studies have examined delivery of group behavioral counseling using Internet chat rooms, using the Internet for long-term maintenance of weight loss, and enhancing motivation in Internet programs. These interventions have produced weight losses of 4-7 kg over 6 months to 1 year when support via e-mail, automated messages, or chat rooms is provided. Outcomes and lessons learned with application to the treatment of substance use and misuse are provided.

  20. Visualization of Time-Series Sensor Data to Inform the Design of Just-In-Time Adaptive Stress Interventions.

    Science.gov (United States)

    Sharmin, Moushumi; Raij, Andrew; Epstien, David; Nahum-Shani, Inbal; Beck, J Gayle; Vhaduri, Sudip; Preston, Kenzie; Kumar, Santosh

    2015-09-01

    We investigate needs, challenges, and opportunities in visualizing time-series sensor data on stress to inform the design of just-in-time adaptive interventions (JITAIs). We identify seven key challenges: massive volume and variety of data, complexity in identifying stressors, scalability of space, multifaceted relationship between stress and time, a need for representation at multiple granularities, interperson variability, and limited understanding of JITAI design requirements due to its novelty. We propose four new visualizations based on one million minutes of sensor data (n=70). We evaluate our visualizations with stress researchers (n=6) to gain first insights into its usability and usefulness in JITAI design. Our results indicate that spatio-temporal visualizations help identify and explain between- and within-person variability in stress patterns and contextual visualizations enable decisions regarding the timing, content, and modality of intervention. Interestingly, a granular representation is considered informative but noise-prone; an abstract representation is the preferred starting point for designing JITAIs.

  1. An Analysis of Two Dyslexia Interventions

    Science.gov (United States)

    Rauch, A. Lillian Inman

    2017-01-01

    This was a quasi-experimental comparison study conducted in a rural suburban school district in Texas. The primary purpose of this study was to determine whether elementary students with dyslexic tendencies, who received the Tier III, Orton-Gillingham- (O-G) based Take Flight reading intervention being piloted on two campuses, showed statistically…

  2. A manual physical therapy intervention for symptoms of knee osteoarthritis and associated fall risk: A case series of four patients.

    Science.gov (United States)

    Allen, Chris; Sheehan, Riley; Deyle, Gail; Wilken, Jason; Gill, Norman

    2018-02-26

    Patients with knee osteoarthritis (OA) are at an increased risk of falling. Further, the symptoms associated with knee OA are correlated with fall risk. A manual physical therapy (MPT) approach consisting of mobilizing techniques and reinforcing exercise improves the symptoms and functional limitations associated with knee OA. The purpose of this case series is to evaluate an MPT intervention of mobilization techniques and exercise for knee OA on improving symptoms and quantify the secondary benefit of improving stumble recovery. Four patients with symptomatic knee OA and four matched controls completed a fall risk assessment. Following 4 weeks of intervention, patients were reevaluated. Initial Western Ontario and McMaster Universities Arthritis Index (WOMAC) scores indicated notable symptoms and functional limitations in all patients. In addition, all patients displayed elevated fall risk and/or impaired stumble responses. Following 4 weeks of intervention, all patients reported meaningful reductions in all three WOMAC subscales and demonstrated improvements in at least two of the three fall risk measures. We identified potential connections between symptom relief in patients with knee OA, stumble response, and ultimately fall risk. The results suggest that MPT intervention designed to improve the signs and symptoms of knee OA may lead to a secondary benefit of improved gait stability and stumble response.

  3. Interglacial climate dynamics and advanced time series analysis

    Science.gov (United States)

    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

  4. Interventional Pain Management for Sacroiliac Tumors in the Oncologic Population: A Case Series and Paradigm Approach.

    Science.gov (United States)

    Hutson, Nathan; Hung, Joseph C; Puttanniah, Vinay; Lis, Eric; Laufer, Ilya; Gulati, Amitabh

    2017-05-01

    Tumors invading the sacrum and/or ilium often represent incurable metastatic disease, and treatment is targeted toward palliation of symptoms and control of pain. As systemic opioid therapy is frequently inadequate and limited by side effects, a variety of interventional techniques are available to better optimize analgesia. Using six patients as a paradigm for interventional approaches to pain relief, we present a therapeutic algorithm for treating sacroiliac tumor-related pain in the oncologic population. We describe the use of ultrasound-guided proximal sacroiliac joint corticosteroid injection, sacroiliac lateral branch radiofrequency ablation, percutaneous sacroplasty, and implantable neuraxial drug delivery devices to treat malignant sacroiliac pain in six patients. Pre- and postprocedure numerical rating scale (NRS) pain scores, duration of pain relief, and postprocedure pain medication requirements were studied for each patient. Each patient had marked improvement in their pain based on an average postprocedure NRS difference of six points. The average duration of pain relief was eight months. In all cases, opioid requirements decreased after the intervention. Depending on tumor location, burden of disease, and patient preference, patients suffering from metastatic disease to the sacrum may find benefit from use of ultrasound-guided proximal sacroiliac joint corticosteroid injection, sacroiliac lateral branch radiofrequency ablation, percutaneous sacroplasty, dorsal column stimulator leads, and/or implantable neuraxial drug delivery devices. We provide a paradigm for treatment in this patient population. © 2016 American Academy of Pain Medicine. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com

  5. The Prediction of Teacher Turnover Employing Time Series Analysis.

    Science.gov (United States)

    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…

  6. 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.

  7. 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.

  8. 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)

  9. Evaluation of Adherence to Nutritional Intervention Through Trajectory Analysis.

    Science.gov (United States)

    Sevilla-Villanueva, B; Gibert, K; Sanchez-Marre, M; Fito, M; Covas, M I

    2017-05-01

    Classical pre-post intervention studies are often analyzed using traditional statistics. Nevertheless, the nutritional interventions have small effects on the metabolism and traditional statistics are not enough to detect these subtle nutrient effects. Generally, this kind of studies assumes that the participants are adhered to the assigned dietary intervention and directly analyzes its effects over the target parameters. Thus, the evaluation of adherence is generally omitted. Although, sometimes, participants do not effectively adhere to the assigned dietary guidelines. For this reason, the trajectory map is proposed as a visual tool where dietary patterns of individuals can be followed during the intervention and can also be related with nutritional prescriptions. The trajectory analysis is also proposed allowing both analysis: 1) adherence to the intervention and 2) intervention effects. The analysis is made by projecting the differences of the target parameters over the resulting trajectories between states of different time-stamps which might be considered either individually or by groups. The proposal has been applied over a real nutritional study showing that some individuals adhere better than others and some individuals of the control group modify their habits during the intervention. In addition, the intervention effects are different depending on the type of individuals, even some subgroups have opposite response to the same intervention.

  10. 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

  11. A lifestyle intervention program for successfully addressing major cardiometabolic risks in persons with SCI: a three-subject case series.

    Science.gov (United States)

    Bigford, Gregory E; Mendez, Armando J; Betancourt, Luisa; Burns-Drecq, Patricia; Backus, Deborah; Nash, Mark S

    2017-01-01

    This study is a prospective case series analyzing the effects of a comprehensive lifestyle intervention program in three patients with chronic paraplegia having major risks for the cardiometabolic syndrome (CMS). Individuals underwent an intense 6-month program of circuit resistance exercise, nutrition using a Mediterranean diet and behavioral support, followed by a 6-month extension (maintenance) phase involving minimal support. The primary goal was a 7% reduction of body mass. Other outcomes analyzed insulin resistance using the HOMA-IR model, and plasma levels of fasting triglycerides and high-density lipoprotein cholesterol. All participants achieved the goal for 7% reduction of body mass and maintained the loss after the MP. Improvements were observed in 2/3 subjects for HOMA-IR and high-density lipoprotein cholesterol. All participants improved their risk for plasma triglycerides. We conclude, in a three-person case series of persons with chronic paraplegia, a lifestyle intervention program involving circuit resistance training, a calorie-restrictive Mediterranean-style diet and behavioral support, results in clinically significant loss of body mass and effectively reduced component risks for CMS and diabetes. These results were for the most part maintained after a 6-month MP involving minimal supervision.

  12. 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

  13. 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.

  14. 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...

  15. Correlation between detrended fluctuation analysis and the Lempel-Ziv complexity in nonlinear time series analysis

    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

  16. 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

  17. Data imputation analysis for Cosmic Rays time series

    Science.gov (United States)

    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.

  18. 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

  19. Time Series Analysis of Wheat flour Price Shocks in Pakistan: A Case Analysis

    OpenAIRE

    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...

  20. 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.

  1. Analysis of historical series of industrial demand of energy; Analisi delle serie storiche dei consumi energetici dell`industria

    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.

  2. 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

  3. Minimum entropy density method for the time series analysis

    Science.gov (United States)

    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.

  4. Dynamic Factor Analysis of Nonstationary Multivariate Time Series.

    Science.gov (United States)

    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)

  5. Koopman Operator Framework for Time Series Modeling and Analysis

    Science.gov (United States)

    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.

  6. Forecast models for suicide: Time-series analysis with data from Italy.

    Science.gov (United States)

    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.

  7. Multiscale multifractal multiproperty analysis of financial time series based on Rényi entropy

    Science.gov (United States)

    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.

  8. Physical and cognitive task analysis in interventional radiology

    Energy Technology Data Exchange (ETDEWEB)

    Johnson, S [School of Psychology, University of Liverpool, Liverpool (United Kingdom); Healey, A [Royal Liverpool University Hospital, Liverpool (United Kingdom); Evans, J [Royal Liverpool University Hospital, Liverpool (United Kingdom); Murphy, M [Royal Liverpool University Hospital, Liverpool (United Kingdom); Crawshaw, M [Department of Psychology, University of Hull, Hull (United Kingdom); Gould, D [Royal Liverpool University Hospital, Liverpool (United Kingdom)

    2006-01-15

    AIM: To identify, describe and detail the cognitive thought processes, decision-making, and physical actions involved in the preparation and successful performance of core interventional radiology procedures. MATERIALS AND METHODS: Five commonly performed core interventional radiology procedures were selected for cognitive task analysis. Several examples of each procedure being performed by consultant interventional radiologists were videoed. The videos of those procedures, and the steps required for successful outcome, were analysed by a psychologist and an interventional radiologist. Once a skeleton algorithm of the procedures was defined, further refinement was achieved using individual interview techniques with consultant interventional radiologists. Additionally a critique of each iteration of the established algorithm was sought from non-participating independent consultant interventional radiologists. RESULTS: Detailed task descriptions and decision protocols were developed for five interventional radiology procedures (arterial puncture, nephrostomy, venous access, biopsy-using both ultrasound and computed tomography, and percutaneous transhepatic cholangiogram). Identical tasks performed within these procedures were identified and standardized within the protocols. CONCLUSIONS: Complex procedures were broken down and their constituent processes identified. This might be suitable for use as a training protocol to provide a universally acceptable safe practice at the most fundamental level. It is envisaged that data collected in this way can be used as an educational resource for trainees and could provide the basis for a training curriculum in interventional radiology. It will direct trainees towards safe practice of the highest standard. It will also provide performance objectives of a simulator model.

  9. Physical and cognitive task analysis in interventional radiology

    International Nuclear Information System (INIS)

    Johnson, S.; Healey, A.; Evans, J.; Murphy, M.; Crawshaw, M.; Gould, D.

    2006-01-01

    AIM: To identify, describe and detail the cognitive thought processes, decision-making, and physical actions involved in the preparation and successful performance of core interventional radiology procedures. MATERIALS AND METHODS: Five commonly performed core interventional radiology procedures were selected for cognitive task analysis. Several examples of each procedure being performed by consultant interventional radiologists were videoed. The videos of those procedures, and the steps required for successful outcome, were analysed by a psychologist and an interventional radiologist. Once a skeleton algorithm of the procedures was defined, further refinement was achieved using individual interview techniques with consultant interventional radiologists. Additionally a critique of each iteration of the established algorithm was sought from non-participating independent consultant interventional radiologists. RESULTS: Detailed task descriptions and decision protocols were developed for five interventional radiology procedures (arterial puncture, nephrostomy, venous access, biopsy-using both ultrasound and computed tomography, and percutaneous transhepatic cholangiogram). Identical tasks performed within these procedures were identified and standardized within the protocols. CONCLUSIONS: Complex procedures were broken down and their constituent processes identified. This might be suitable for use as a training protocol to provide a universally acceptable safe practice at the most fundamental level. It is envisaged that data collected in this way can be used as an educational resource for trainees and could provide the basis for a training curriculum in interventional radiology. It will direct trainees towards safe practice of the highest standard. It will also provide performance objectives of a simulator model

  10. Guest Editorial: Cultural Analysis as Intervention

    DEFF Research Database (Denmark)

    Jespersen, Astrid Pernille; Petersen, Morten Krogh; Ren, Carina Bregnholm

    2012-01-01

    to a whole new genre of business empiricism – and how to avoid reducing ethnographically-based cultural analysis to a simple matter of methods. What does it entail if we are to more strategically engage with compressed, to-the-point depictions of everyday life? The contributors to this special issue engage......Recently, cultural analyses – especially ethnographic descriptions of everyday-life practices – seem to have found new audiences situated within what Nigel Thrift has termed ‘soft capitalism’ (2006,1997). Ethnography is increasingly perceived by businesses, organizations, and industry as a key...... to producing surplus value due to its ability to gain access to the world of customers, users and citizens; for instance, by uncovering user demands (cf. Cefkin, 2009). This begs the question of what cultural analysis can and ought to do – beyond the scope of acting as a witness for truth and delivering facts...

  11. Modeling Philippine Stock Exchange Composite Index Using Time Series Analysis

    Science.gov (United States)

    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.

  12. 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.

  13. 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.

  14. Dynamical analysis and visualization of tornadoes time series.

    Science.gov (United States)

    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.

  15. Financial time series analysis based on information categorization method

    Science.gov (United States)

    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.

  16. Sleep, School Performance, and a School-Based Intervention among School-Aged Children: A Sleep Series Study in China

    Science.gov (United States)

    Li, Shenghui; Arguelles, Lester; Jiang, Fan; Chen, Wenjuan; Jin, Xingming; Yan, Chonghuai; Tian, Ying; Hong, Xiumei; Qian, Ceng; Zhang, Jun; Wang, Xiaobin; Shen, Xiaoming

    2013-01-01

    Background Sufficient sleep during childhood is essential to ensure a transition into a healthy adulthood. However, chronic sleep loss continues to increase worldwide. In this context, it is imperative to make sleep a high-priority and take action to promote sleep health among children. The present series of studies aimed to shed light on sleep patterns, on the longitudinal association of sleep with school performance, and on practical intervention strategy for Chinese school-aged children. Methods and Findings A serial sleep researches, including a national cross-sectional survey, a prospective cohort study, and a school-based sleep intervention, were conducted in China from November 2005 through December 2009. The national cross-sectional survey was conducted in 8 cities and a random sample of 20,778 children aged 9.0±1.61 years participated in the survey. The five-year prospective cohort study included 612 children aged 6.8±0.31 years. The comparative cross-sectional study (baseline: n = 525, aged 10.80±0.41; post-intervention follow-up: n = 553, aged 10.81±0.33) was undertaken in 6 primary schools in Shanghai. A battery of parent and teacher reported questionnaires were used to collect information on children’s sleep behaviors, school performance, and sociodemographic characteristics. The mean sleep duration was 9.35±0.77 hours. The prevalence of daytime sleepiness was 64.4% (sometimes: 37.50%; frequently: 26.94%). Daytime sleepiness was significantly associated with impaired attention, learning motivation, and particularly, academic achievement. By contrast, short sleep duration only related to impaired academic achievement. After delaying school start time 30 minutes and 60 minutes, respectively, sleep duration correspondingly increased by 15.6 minutes and 22.8 minutes, respectively. Moreover, intervention significantly improved the sleep duration and daytime sleepiness. Conclusions Insufficient sleep and daytime sleepiness commonly existed and

  17. Sleep, school performance, and a school-based intervention among school-aged children: a sleep series study in China.

    Science.gov (United States)

    Li, Shenghui; Arguelles, Lester; Jiang, Fan; Chen, Wenjuan; Jin, Xingming; Yan, Chonghuai; Tian, Ying; Hong, Xiumei; Qian, Ceng; Zhang, Jun; Wang, Xiaobin; Shen, Xiaoming

    2013-01-01

    Sufficient sleep during childhood is essential to ensure a transition into a healthy adulthood. However, chronic sleep loss continues to increase worldwide. In this context, it is imperative to make sleep a high-priority and take action to promote sleep health among children. The present series of studies aimed to shed light on sleep patterns, on the longitudinal association of sleep with school performance, and on practical intervention strategy for Chinese school-aged children. A serial sleep researches, including a national cross-sectional survey, a prospective cohort study, and a school-based sleep intervention, were conducted in China from November 2005 through December 2009. The national cross-sectional survey was conducted in 8 cities and a random sample of 20,778 children aged 9.0±1.61 years participated in the survey. The five-year prospective cohort study included 612 children aged 6.8±0.31 years. The comparative cross-sectional study (baseline: n = 525, aged 10.80±0.41; post-intervention follow-up: n = 553, aged 10.81±0.33) was undertaken in 6 primary schools in Shanghai. A battery of parent and teacher reported questionnaires were used to collect information on children's sleep behaviors, school performance, and sociodemographic characteristics. The mean sleep duration was 9.35±0.77 hours. The prevalence of daytime sleepiness was 64.4% (sometimes: 37.50%; frequently: 26.94%). Daytime sleepiness was significantly associated with impaired attention, learning motivation, and particularly, academic achievement. By contrast, short sleep duration only related to impaired academic achievement. After delaying school start time 30 minutes and 60 minutes, respectively, sleep duration correspondingly increased by 15.6 minutes and 22.8 minutes, respectively. Moreover, intervention significantly improved the sleep duration and daytime sleepiness. Insufficient sleep and daytime sleepiness commonly existed and positively associated with the impairment of

  18. Sleep, school performance, and a school-based intervention among school-aged children: a sleep series study in China.

    Directory of Open Access Journals (Sweden)

    Shenghui Li

    Full Text Available BACKGROUND: Sufficient sleep during childhood is essential to ensure a transition into a healthy adulthood. However, chronic sleep loss continues to increase worldwide. In this context, it is imperative to make sleep a high-priority and take action to promote sleep health among children. The present series of studies aimed to shed light on sleep patterns, on the longitudinal association of sleep with school performance, and on practical intervention strategy for Chinese school-aged children. METHODS AND FINDINGS: A serial sleep researches, including a national cross-sectional survey, a prospective cohort study, and a school-based sleep intervention, were conducted in China from November 2005 through December 2009. The national cross-sectional survey was conducted in 8 cities and a random sample of 20,778 children aged 9.0±1.61 years participated in the survey. The five-year prospective cohort study included 612 children aged 6.8±0.31 years. The comparative cross-sectional study (baseline: n = 525, aged 10.80±0.41; post-intervention follow-up: n = 553, aged 10.81±0.33 was undertaken in 6 primary schools in Shanghai. A battery of parent and teacher reported questionnaires were used to collect information on children's sleep behaviors, school performance, and sociodemographic characteristics. The mean sleep duration was 9.35±0.77 hours. The prevalence of daytime sleepiness was 64.4% (sometimes: 37.50%; frequently: 26.94%. Daytime sleepiness was significantly associated with impaired attention, learning motivation, and particularly, academic achievement. By contrast, short sleep duration only related to impaired academic achievement. After delaying school start time 30 minutes and 60 minutes, respectively, sleep duration correspondingly increased by 15.6 minutes and 22.8 minutes, respectively. Moreover, intervention significantly improved the sleep duration and daytime sleepiness. CONCLUSIONS: Insufficient sleep and daytime sleepiness

  19. Time-Series Analysis of Supergranule Characterstics at Solar Minimum

    Science.gov (United States)

    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.

  20. Evaluating the impact of flexible alcohol trading hours on violence: an interrupted time series analysis.

    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..

  1. Visibility graph analysis on quarterly macroeconomic series of China based on complex network theory

    Science.gov (United States)

    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

  2. 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

  3. 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.

  4. Buildings Energy Efficiency: Interventions Analysis under a Smart Cities Approach

    Directory of Open Access Journals (Sweden)

    Gabriele Battista

    2014-07-01

    Full Text Available Most of the world’s population lives in urban areas and in inefficient buildings under the energy point of view. Starting from these assumptions, there is the need to identify methodologies and innovations able to improve social development and the quality of life of people living in cities. Smart cities can be a viable solution. The methodology traditionally adopted to evaluate building energy efficiency starts from the structure’s energy demands analysis and the demands reduction evaluation. Consequently, the energy savings is assessed through a cascade of interventions. Regarding the building envelope, the first intervention is usually related to the reduction of the thermal transmittance value, but there is also the need to emphasize the building energy savings through other parameters, such as the solar gain factor and dye solar absorbance coefficients. In this contribution, a standard building has been modeled by means of the well-known dynamic software, TRNSYS. This study shows a parametrical analysis through which it is possible to evaluate the effect of each single intervention and, consequently, its influence on the building energy demand. Through this analysis, an intervention chart has been carried out, aiming to assess the intervention efficiency starting from the percentage variation of energy demands.

  5. The Analysis Of Personality Disorder On Two Characters In The Animation Series Black Rock Shooter

    OpenAIRE

    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...

  6. Changing use of surgical antibiotic prophylaxis in Thika Hospital, Kenya: a quality improvement intervention with an interrupted time series design.

    Directory of Open Access Journals (Sweden)

    Alexander M Aiken

    Full Text Available In low-income countries, Surgical Site Infection (SSI is a common form of hospital-acquired infection. Antibiotic prophylaxis is an effective method of preventing these infections, if given immediately before the start of surgery. Although several studies in Africa have compared pre-operative versus post-operative prophylaxis, there are no studies describing the implementation of policies to improve prescribing of surgical antibiotic prophylaxis in African hospitals.We conducted SSI surveillance at a typical Government hospital in Kenya over a 16 month period between August 2010 and December 2011, using standard definitions of SSI and the extent of contamination of surgical wounds. As an intervention, we developed a hospital policy that advised pre-operative antibiotic prophylaxis and discouraged extended post-operative antibiotics use. We measured process, outcome and balancing effects of this intervention in using an interrupted time series design.From a starting point of near-exclusive post-operative antibiotic use, after policy introduction in February 2011 there was rapid adoption of the use of pre-operative antibiotic prophylaxis (60% of operations at 1 week; 98% at 6 weeks and a substantial decrease in the use of post-operative antibiotics (40% of operations at 1 week; 10% at 6 weeks in Clean and Clean-Contaminated surgery. There was no immediate step-change in risk of SSI, but overall, there appeared to be a moderate reduction in the risk of superficial SSI across all levels of wound contamination. There were marked reductions in the costs associated with antibiotic use, the number of intravenous injections performed and nursing time spent administering these.Implementation of a locally developed policy regarding surgical antibiotic prophylaxis is an achievable quality improvement target for hospitals in low-income countries, and can lead to substantial benefits for individual patients and the institution.

  7. Changing use of surgical antibiotic prophylaxis in Thika Hospital, Kenya: a quality improvement intervention with an interrupted time series design.

    Science.gov (United States)

    Aiken, Alexander M; Wanyoro, Anthony K; Mwangi, Jonah; Juma, Francis; Mugoya, Isaac K; Scott, J Anthony G

    2013-01-01

    In low-income countries, Surgical Site Infection (SSI) is a common form of hospital-acquired infection. Antibiotic prophylaxis is an effective method of preventing these infections, if given immediately before the start of surgery. Although several studies in Africa have compared pre-operative versus post-operative prophylaxis, there are no studies describing the implementation of policies to improve prescribing of surgical antibiotic prophylaxis in African hospitals. We conducted SSI surveillance at a typical Government hospital in Kenya over a 16 month period between August 2010 and December 2011, using standard definitions of SSI and the extent of contamination of surgical wounds. As an intervention, we developed a hospital policy that advised pre-operative antibiotic prophylaxis and discouraged extended post-operative antibiotics use. We measured process, outcome and balancing effects of this intervention in using an interrupted time series design. From a starting point of near-exclusive post-operative antibiotic use, after policy introduction in February 2011 there was rapid adoption of the use of pre-operative antibiotic prophylaxis (60% of operations at 1 week; 98% at 6 weeks) and a substantial decrease in the use of post-operative antibiotics (40% of operations at 1 week; 10% at 6 weeks) in Clean and Clean-Contaminated surgery. There was no immediate step-change in risk of SSI, but overall, there appeared to be a moderate reduction in the risk of superficial SSI across all levels of wound contamination. There were marked reductions in the costs associated with antibiotic use, the number of intravenous injections performed and nursing time spent administering these. Implementation of a locally developed policy regarding surgical antibiotic prophylaxis is an achievable quality improvement target for hospitals in low-income countries, and can lead to substantial benefits for individual patients and the institution.

  8. 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

  9. 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

  10. Biological time series analysis using a context free language: applicability to pulsatile hormone data.

    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.

  11. Time Series in Education: The Analysis of Daily Attendance in Two High Schools

    Science.gov (United States)

    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),…

  12. Mapping air temperature using time series analysis of LST : The SINTESI approach

    NARCIS (Netherlands)

    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

  13. 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, ...

  14. Taxation in Public Education. Analysis and Bibliography Series, No. 12.

    Science.gov (United States)

    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…

  15. End-of-Life Care Interventions: An Economic Analysis.

    Science.gov (United States)

    Pham, B; Krahn, M

    2014-01-01

    The annual cost of providing care for patients in their last year of life is estimated to account for approximately 9% of the Ontario health care budget. Access to integrated, comprehensive support and pain/symptom management appears to be inadequate and inequitable. To evaluate the cost-effectiveness of end-of-life (EoL) care interventions included in the EoL care mega-analysis. Multiple sources were used, including systematic reviews, linked health administration databases, survey data, planning documents, expert input, and additional literature searches. We conducted a literature review of cost-effectiveness studies to inform the primary economic analysis. We conducted the primary economic analysis and budget impact analysis for an Ontario cohort of decedents and their families and included interventions pertaining to team-based models of care, patient care planning discussions, educational interventions for patients and caregivers, and supportive interventions for informal caregivers. The time horizon was the last year of life. Costs were in 2013 Canadian dollars. Effectiveness measures included days at home, percentage dying at home, and quality-adjusted life-days. We developed a Markov model; model inputs were obtained from a cohort of Ontario decedents assembled from Institute for Clinical Evaluative Sciences databases and published literature. In-home palliative team care was cost-effective; it increased the chance of dying at home by 10%, increased the average number of days at home (6 days) and quality-adjusted life-days (0.5 days), and it reduced costs by approximately $4,400 per patient. Expanding in-home palliative team care to those currently not receiving such services (approximately 45,000 per year, at an annual cost of $76-108 million) is likely to improve quality of life, reduce the use of acute care resources, and save $191-$385 million in health care costs. Results for the other interventions were uncertain. The cost-effectiveness analysis was

  16. Time-series panel analysis (TSPA): multivariate modeling of temporal associations in psychotherapy process.

    Science.gov (United States)

    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.

  17. RECONSTRUCTION OF PRECIPITATION SERIES AND ANALYSIS OF CLIMATE CHANGE OVER PAST 500 YEARS IN NORTHERN CHINA

    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.

  18. The Timeseries Toolbox - A Web Application to Enable Accessible, Reproducible Time Series Analysis

    Science.gov (United States)

    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.

  19. Financial time series analysis based on effective phase transfer entropy

    Science.gov (United States)

    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.

  20. Stock price forecasting based on time series analysis

    Science.gov (United States)

    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.

  1. 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.

  2. A unified nonlinear stochastic time series analysis for climate science.

    Science.gov (United States)

    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.

  3. Methodology Series Module 6: Systematic Reviews and Meta-analysis.

    Science.gov (United States)

    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.

  4. Nonpharmacological interventions to treat physical frailty and sarcopenia in older patients: a systematic overview – the SENATOR Project ONTOP Series

    Directory of Open Access Journals (Sweden)

    Lozano-Montoya I

    2017-04-01

    Full Text Available Isabel Lozano-Montoya,1,* Andrea Correa-Pérez,1,* Iosief Abraha,2 Roy L Soiza,3 Antonio Cherubini,2 Denis O’Mahony,4 Alfonso J Cruz-Jentoft1 1Servicio de Geriatría, Hospital Universitario Ramón y Cajal (IRYCIS, Madrid, Spain; 2Geriatrics and Geriatric Emergency Care, Italian National Research Center on Aging (IRCCS-INRCA, Ancona, Italy; 3Department of Medicine for the Elderly, National Health Service Grampian, Aberdeen, UK; 4Department of Medicine, University College Cork, Cork, Ireland *These authors contributed equally to this work Background: Physical frailty (PF and sarcopenia are predictors of negative health outcomes such as falls, disability, hospitalization, and death. Some systematic reviews (SRs have been published on different nonpharmacological treatments of frailty and sarcopenia using heterogeneous definitions of them. Objective: To critically appraise the evidence from SRs of the primary studies on nonpharmacological interventions to treat PF (defined by Fried’s frailty phenotype and sarcopenia (defined by the EWGSOP in older patients. Design: Overview of SRs and meta-analysis of comparative studies. Data sources: PubMed, Cochrane Database of Systematic Reviews, EMBASE, and CINAHL were searched in October 2015. Eligibility criteria for selecting studies: SRs that included at least one comparative study evaluating any nonpharmacological intervention to treat PF or sarcopenia in older patients in any health care setting. Any primary study described in these SRs with experimental design was included. Data extraction and management: Two reviewers independently screened titles, abstracts, and full-texts of articles. Quality assessment was carried out by using criteria from the Cochrane Collaboration and the GRADE working group. Results: Ten SRs with 5 primary studies satisfied the inclusion criteria. The most frequent interventions in the included studies were physical exercise (4 and nutritional supplementation (2. Muscle

  5. A novel water quality data analysis framework based on time-series data mining.

    Science.gov (United States)

    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.

  6. Time series analysis of diverse extreme phenomena: universal features

    Science.gov (United States)

    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.

  7. Real analysis series, functions of several variables, and applications

    CERN Document Server

    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...

  8. Personal identity narratives of therapeutic songwriting participants following Spinal Cord Injury: A case series analysis.

    Science.gov (United States)

    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.

  9. Analysis of engineering cycles thermodynamics and fluid mechanics series

    CERN Document Server

    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

  10. Intervention analysis of introduction of rotavirus vaccine on hospital admissions rates due to acute diarrhea

    Directory of Open Access Journals (Sweden)

    Maria de Lourdes Teixeira Masukawa

    2014-10-01

    Full Text Available The aim of this study is to investigate the impact of rotavirus vaccine on hospitalization rates for acute diarrhea in children younger than 5 years old after the introduction of the vaccine in 2006. A descriptive analytical observational study was carried out of the hospitalization rates occurred between 2000 and 2011 in 22 Regional Health Centers of Paraná State, Brazil. The effect of the vaccine was assessed by applying the SARIMA/Box-Jenkins time series methodology of intervention analysis, which allows verifying the slopes of the series are different after the introduction of the vaccine and estimating the magnitude of these effects for children younger than five years of age, by age group, for each region center. It was verified a statistically significant reduction by center/month on hospitalization rates for children 1 year old and younger, with averages of 47% and 58%, respectively, in December 2011.

  11. Time series analysis of aerobic bacterial flora during Miso fermentation.

    Science.gov (United States)

    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.

  12. Increasing compliance with low tidal volume ventilation in the ICU with two nudge-based interventions: evaluation through intervention time-series analyses.

    Science.gov (United States)

    Bourdeaux, Christopher P; Thomas, Matthew Jc; Gould, Timothy H; Malhotra, Gaurav; Jarvstad, Andreas; Jones, Timothy; Gilchrist, Iain D

    2016-05-26

    Low tidal volume (TVe) ventilation improves outcomes for ventilated patients, and the majority of clinicians state they implement it. Unfortunately, most patients never receive low TVes. 'Nudges' influence decision-making with subtle cognitive mechanisms and are effective in many contexts. There have been few studies examining their impact on clinical decision-making. We investigated the impact of 2 interventions designed using principles from behavioural science on the deployment of low TVe ventilation in the intensive care unit (ICU). University Hospitals Bristol, a tertiary, mixed medical and surgical ICU with 20 beds, admitting over 1300 patients per year. Data were collected from 2144 consecutive patients receiving controlled mechanical ventilation for more than 1 hour between October 2010 and September 2014. Patients on controlled mechanical ventilation for more than 20 hours were included in the final analysis. (1) Default ventilator settings were adjusted to comply with low TVe targets from the initiation of ventilation unless actively changed by a clinician. (2) A large dashboard was deployed displaying TVes in the format mL/kg ideal body weight (IBW) with alerts when TVes were excessive. TVe in mL/kg IBW. TVe was significantly lower in the defaults group. In the dashboard intervention, TVe fell more quickly and by a greater amount after a TVe of 8 mL/kg IBW was breached when compared with controls. This effect improved in each subsequent year for 3 years. This study has demonstrated that adjustment of default ventilator settings and a dashboard with alerts for excessive TVe can significantly influence clinical decision-making. This offers a promising strategy to improve compliance with low TVe ventilation, and suggests that using insights from behavioural science has potential to improve the translation of evidence into practice. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please

  13. 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...

  14. Functional analysis-based interventions for challenging behaviour in dementia.

    Science.gov (United States)

    Moniz Cook, Esme D; Swift, Katie; James, Ian; Malouf, Reem; De Vugt, Marjolein; Verhey, Frans

    2012-02-15

    Functional analysis (FA) for the management of challenging behaviour is a promising behavioural intervention that involves exploring the meaning or purpose of an individual's behaviour. It extends the 'ABC' approach of behavioural analysis, to overcome the restriction of having to derive a single explanatory hypothesis for the person's behaviour. It is seen as a first line alternative to traditional pharmacological management for agitation and aggression. FA typically requires the therapist to develop and evaluate hypotheses-driven strategies that aid family and staff caregivers to reduce or resolve a person's distress and its associated behavioural manifestations. To assess the effects of functional analysis-based interventions for people with dementia (and their caregivers) living in their own home or in other settings. We searched ALOIS: the Cochrane Dementia and Cognitive Improvement Group's Specialized Register on 3 March 2011 using the terms: FA, behaviour (intervention, management, modification), BPSD, psychosocial and Dementia. Randomised controlled trials (RCTs) with reported behavioural outcomes that could be associated with functional analysis for the management of challenging behaviour in dementia. Four reviewers selected trials for inclusion. Two reviewers worked independently to extract data and assess trial quality, including bias. Meta-analyses for reported incidence, frequency, severity of care recipient challenging behaviour and mood (primary outcomes) and caregiver reaction, burden and mood were performed. Details of adverse effects were noted. Eighteen trials are included in the review. The majority were in family care settings. For fourteen studies, FA was just one aspect of a broad multi-component programme of care. Assessing the effect of FA was compromised by ill-defined protocols for the duration of component parts of these programmes (i.e. frequency of the intervention or actual time spent). Therefore, establishing the real effect of the

  15. 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

  16. Implementation and impact of an audit and feedback antimicrobial stewardship intervention in the orthopaedics department of a tertiary-care hospital: a controlled interrupted time series study.

    Science.gov (United States)

    Tavares, Margarida; Carvalho, Ana Cláudia; Almeida, José Pedro; Andrade, Paulo; São-Simão, Ricardo; Soares, Pedro; Alves, Carlos; Pinto, Rui; Fontanet, Arnaud; Watier, Laurence

    2018-06-01

    A prospective audit and feedback antimicrobial stewardship intervention conducted in the Orthopaedics Department of a university hospital in Portugal was evaluated by comparing an interrupted time series in the intervention group with a non-intervention (control) group. Monthly antibiotic use (except cefazolin) was measured as the World Health Organization's Anatomical Therapeutic Chemical defined daily doses (ATC-DDD) from January 2012 to September 2016, excluding the 6-month phase of intervention implementation starting on 1 January 2015. Compared with the control group, the intervention group had a monthly decrease in the use of fluoroquinolones by 2.3 DDD/1000 patient-days [95% confidence interval (CI) -3.97 to -0.63]. An increase in the use of penicillins by 103.3 DDD/1000 patient-days (95% CI 47.42 to 159.10) was associated with intervention implementation, followed by a decrease during the intervention period (slope = -5.2, 95% CI -8.56 to -1.82). In the challenging scenario of treatment of osteoarticular and prosthetic joint infections, an audit and feedback intervention reduced antibiotic exposure and spectrum. Copyright © 2018 Elsevier B.V. and International Society of Chemotherapy. All rights reserved.

  17. Multifractal detrended cross-correlation analysis on gold, crude oil and foreign exchange rate time series

    Science.gov (United States)

    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.

  18. 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.

  19. Meta-Analysis of Workplace Physical Activity Interventions

    Science.gov (United States)

    Conn, Vicki S.; Hafdahl, Adam R.; Cooper, Pamela S.; Brown, Lori M.; Lusk, Sally L.

    2009-01-01

    Context Most adults do not achieve adequate physical activity. Despite the potential benefits of worksite health promotion, no previous comprehensive meta-analysis has summarized health and physical activity behavior outcomes from these programs. This comprehensive meta-analysis integrated the extant wide range of worksite physical activity intervention research. Evidence acquisition Extensive searching located published and unpublished intervention studies reported from 1969 through 2007. Results were coded from primary studies. Random-effects meta-analytic procedures, including moderator analyses, were completed in 2008. Evidence synthesis Effects on most variables were substantially heterogeneous because diverse studies were included. Standardized mean difference (d) effect sizes were synthesized across approximately 38,231 subjects. Significantly positive effects were observed for physical activity behavior (0.21), fitness (0.57), lipids (0.13), anthropometric measures (0.08), work attendance (0.19), and job stress (0.33). The significant effect size for diabetes risk (0.98) is more tentative given small sample sizes. Significant heterogeneity documents intervention effects varied across studies. The mean effect size for fitness corresponds to a difference between treatment minus control subjects' means on V02max of 3.5 mL/kg/min; for lipids, −0.2 on total cholesterol:HDL; and for diabetes risk, −12.6 mg/dL on fasting glucose. Conclusions These findings document that some workplace physical activity interventions can improve both health and important worksite outcomes. Effects were variable for most outcomes, reflecting the diversity of primary studies. Future primary research should compare interventions to confirm causal relationships and further explore heterogeneity. PMID:19765506

  20. 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.

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

    Science.gov (United States)

    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.

  2. 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.

  3. Financing Human Development for Sectorial Growth: A Time Series Analysis

    Directory of Open Access Journals (Sweden)

    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.

  4. Spatially adaptive mixture modeling for analysis of FMRI time series.

    Science.gov (United States)

    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

  5. Simultaneous determination of radionuclides separable into natural decay series by use of time-interval analysis

    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.)

  6. 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)

  7. Bioelectric signal classification using a recurrent probabilistic neural network with time-series discriminant component analysis.

    Science.gov (United States)

    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.

  8. 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.)

  9. Effects of Interventions Based in Behavior Analysis on Motor Skill Acquisition: A Meta-Analysis

    Science.gov (United States)

    Alstot, Andrew E.; Kang, Minsoo; Alstot, Crystal D.

    2013-01-01

    Techniques based in applied behavior analysis (ABA) have been shown to be useful across a variety of settings to improve numerous behaviors. Specifically within physical activity settings, several studies have examined the effect of interventions based in ABA on a variety of motor skills, but the overall effects of these interventions are unknown.…

  10. 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)

  11. An Interactive Analysis of Hyperboles in a British TV Series: Implications For EFL Classes

    Science.gov (United States)

    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…

  12. Transition of chaotic motion to a limit cycle by intervention of economic policy: an empirical analysis in agriculture.

    Science.gov (United States)

    Sakai, Kenshi; Managi, Shunsuke; Vitanov, Nikolay K; Demura, Katsuhiko

    2007-04-01

    This paper investigates the transition of dynamics observed in an actual real agricultural economic dataset. Lyapunov spectrum analysis is conducted on the data to distinguish deterministic chaos and the limit cycle. Chaotic and periodic oscillation were identified before and after the second oil crisis, respectively. The statitonarity of the time series is investigated using recurrence plots. This shows that government intervention might reduce market instability by removing a chaotic market's long-term unpredictability.

  13. Meta-analysis of workplace physical activity interventions.

    Science.gov (United States)

    Conn, Vicki S; Hafdahl, Adam R; Cooper, Pamela S; Brown, Lori M; Lusk, Sally L

    2009-10-01

    Most adults do not achieve adequate physical activity levels. Despite the potential benefits of worksite health promotion, no previous comprehensive meta-analysis has summarized health and physical activity behavior outcomes from such programs. This comprehensive meta-analysis integrated the extant wide range of worksite physical activity intervention research. Extensive searching located published and unpublished intervention studies reported from 1969 through 2007. Results were coded from primary studies. Random-effects meta-analytic procedures, including moderator analyses, were completed in 2008. Effects on most variables were substantially heterogeneous because diverse studies were included. Standardized mean difference (d) effect sizes were synthesized across approximately 38,231 subjects. Significantly positive effects were observed for physical activity behavior (0.21); fitness (0.57); lipids (0.13); anthropometric measures (0.08); work attendance (0.19); and job stress (0.33). The significant effect size for diabetes risk (0.98) is less robust given small sample sizes. The mean effect size for fitness corresponds to a difference between treatment minus control subjects' means on VO2max of 3.5 mL/kg/min; for lipids, -0.2 on the ratio of total cholesterol to high-density lipoprotein; and for diabetes risk, -12.6 mg/dL on fasting glucose. These findings document that some workplace physical activity interventions can improve both health and important worksite outcomes. Effects were variable for most outcomes, reflecting the diversity of primary studies. Future primary research should compare interventions to confirm causal relationships and further explore heterogeneity.

  14. Economic analysis of an internet-based depression prevention intervention.

    Science.gov (United States)

    Ruby, Alexander; Marko-Holguin, Monika; Fogel, Joshua; Van Voorhees, Benjamin W

    2013-09-01

    -based interventions like CATCH-IT appears economically viable in the context of an Accountable Care Organization. Furthermore, while the cost of implementing an effective safety protocol is proportionally high for this intervention, CATCH-IT is still significantly cheaper to implement than current treatment options. Limitations of this research included diminished participation in follow-up surveys assessing willingness-to-pay. IMPLICATIONS FOR HEALTH CARE PROVISION AND USE AND HEALTH POLICIES: This research emphasizes that preventive interventions have the potential to be cheaper to implement than treatment protocols, even before taking into account lost productivity due to illness. Research such as this business application analysis of the CATCH-IT program highlights the importance of supporting preventive medical interventions as the healthcare system already does for treatment interventions. This research is the first to analyze the economic costs of an Internet-based intervention. Further research into the costs and outcomes of such interventions is certainly warranted before they are widely adopted. Furthermore, more research regarding the safety of Internet-based programs will likely need to be conducted before they are broadly accepted.

  15. A Markovian Entropy Measure for the Analysis of Calcium Activity Time Series.

    Science.gov (United States)

    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.

  16. 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.

  17. 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%.

  18. Trend analysis and change point detection of annual and seasonal temperature series in Peninsular Malaysia

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    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

  20. Contradiction analysis: towards a dialectical approach in ergonomics field interventions

    Directory of Open Access Journals (Sweden)

    Dimitris Nathanael

    2015-03-01

    Full Text Available The present paper is a methodological contribution to the ergonomics field intervention process. It proposes a perspective on work analysis based on the dialectics notion of contradictions. Contradiction analysis is proposed as being complementary to more established work decomposition methods. The aim of including such an analysis is to frame various heterogeneous determinants of a work activity in practical terms, swiftly and in a manner that preserves its multifaceted unity and essence. Such framing is of particular value when considering alternative design solutions because it provides a practical means for anticipating the effects and side effects of proposed changes. The proposed method is inspired by two theoretical constructs: (i contradiction, as used in Cultural Historical Activity Theory, and (ii regulation, as developed and used by the francophone tradition of the ergonomics of activity. Two brief examples of its use are presented, and its usefulness, possible pitfalls and need for further developments are discussed.

  1. 100 classic papers of interventional radiology: A citation analysis.

    Science.gov (United States)

    Crockett, Matthew T; Browne, Ronan Fj; MacMahon, Peter J; Lawler, Leo

    2015-04-28

    To define the 100 citation classic papers of interventional radiology. Using the database of Journal Citation Reports the 40 highest impact factor radiology journals were chosen. From these journals the 100 most cited interventional radiology papers were chosen and analysed. The top paper received 2497 citations and the 100(th) paper 200 citations. The average number of citations was 320. Dates of publication ranged from 1953 - 2005. Most papers originated in the United States (n = 67) followed by Italy (n = 20) and France (n = 10). Harvard University (n = 18) and Osped Civile (n = 11) were the most prolific institutions. Ten journals produced all of the top 100 papers with "Radiology" and "AJR" making up the majority. SN Goldberg and T Livraghi were the most prolific authors. Nearly two thirds of the papers (n = 61) were published after 1990. This analysis identifies many of the landmark interventional radiology papers and provides a fascinating insight into the changing discourse within the field. It also identifies topics, authors and institutions which have impacted greatly on the specialty.

  2. 100 classic papers of interventional radiology: A citation analysis

    Science.gov (United States)

    Crockett, Matthew T; Browne, Ronan FJ; MacMahon, Peter J; Lawler, Leo

    2015-01-01

    AIM: To define the 100 citation classic papers of interventional radiology. METHODS: Using the database of Journal Citation Reports the 40 highest impact factor radiology journals were chosen. From these journals the 100 most cited interventional radiology papers were chosen and analysed. RESULTS: The top paper received 2497 citations and the 100th paper 200 citations. The average number of citations was 320. Dates of publication ranged from 1953 - 2005. Most papers originated in the United States (n = 67) followed by Italy (n = 20) and France (n = 10). Harvard University (n = 18) and Osped Civile (n = 11) were the most prolific institutions. Ten journals produced all of the top 100 papers with “Radiology” and “AJR” making up the majority. SN Goldberg and T Livraghi were the most prolific authors. Nearly two thirds of the papers (n = 61) were published after 1990. CONCLUSION: This analysis identifies many of the landmark interventional radiology papers and provides a fascinating insight into the changing discourse within the field. It also identifies topics, authors and institutions which have impacted greatly on the specialty. PMID:25918585

  3. Ultrasonic image analysis and image-guided interventions.

    Science.gov (United States)

    Noble, J Alison; Navab, Nassir; Becher, H

    2011-08-06

    The fields of medical image analysis and computer-aided interventions deal with reducing the large volume of digital images (X-ray, computed tomography, magnetic resonance imaging (MRI), positron emission tomography and ultrasound (US)) to more meaningful clinical information using software algorithms. US is a core imaging modality employed in these areas, both in its own right and used in conjunction with the other imaging modalities. It is receiving increased interest owing to the recent introduction of three-dimensional US, significant improvements in US image quality, and better understanding of how to design algorithms which exploit the unique strengths and properties of this real-time imaging modality. This article reviews the current state of art in US image analysis and its application in image-guided interventions. The article concludes by giving a perspective from clinical cardiology which is one of the most advanced areas of clinical application of US image analysis and describing some probable future trends in this important area of ultrasonic imaging research.

  4. Phase synchronization based minimum spanning trees for analysis of financial time series with nonlinear correlations

    Science.gov (United States)

    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

  5. The Benefits of Peer Review and a Multisemester Capstone Writing Series on Inquiry and Analysis Skills in an Undergraduate Thesis.

    Science.gov (United States)

    Weaver, K F; Morales, V; Nelson, M; Weaver, P F; Toledo, A; Godde, K

    2016-01-01

    This study examines the relationship between the introduction of a four-course writing-intensive capstone series and improvement in inquiry and analysis skills of biology senior undergraduates. To measure the impact of the multicourse write-to-learn and peer-review pedagogy on student performance, we used a modified Valid Assessment of Learning in Undergraduate Education rubric for Inquiry and Analysis and Written Communication to score senior research theses from 2006 to 2008 (pretreatment) and 2009 to 2013 (intervention). A Fisher-Freeman-Halton test and a two-sample Student's t test were used to evaluate individual rubric dimensions and composite rubric scores, respectively, and a randomized complete block design analysis of variance was carried out on composite scores to examine the impact of the intervention across ethnicity, legacy (e.g., first-generation status), and research laboratory. The results show an increase in student performance in rubric scoring categories most closely associated with science literacy and critical-thinking skills, in addition to gains in students' writing abilities. © 2016 K. F. Weaver et al. CBE—Life Sciences Education © 2016 The American Society for Cell Biology. This article is distributed by The American Society for Cell Biology under license from the author(s). It is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).

  6. AHRQ series on complex intervention systematic reviews-paper 6: PRISMA-CI extension statement and checklist.

    Science.gov (United States)

    Guise, Jeanne-Marie; Butler, Mary E; Chang, Christine; Viswanathan, Meera; Pigott, Terri; Tugwell, Peter

    2017-10-01

    Complex interventions are widely used in health systems, public health, education, and communities and are increasingly the subject of systematic reviews. Oversimplification and inconsistencies in reporting about complex interventions can limit the usability of review findings. Although guidance exists to ensure that reports of individual studies and systematic reviews adhere to accepted scientific standards, their design-specific focus leaves important reporting gaps relative to complex interventions in health care. This paper provides a stand-alone extension to the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) reporting tool for complex interventions-PRISMA-CI-to help authors, publishers, and readers understand and apply to systematic reviews of complex interventions. PRISMA-CI development followed the Enhancing the QUAlity and Transparency Of health Research Network guidance for extensions and focused on adding or modifying only essential items that are truly unique to complex interventions and are not covered by broader interpretation of current PRISMA guidance. PRISMA-CI provides an important structure and guidance for systematic reviews and meta-analyses for the highly prevalent and dynamic field of complex interventions. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

  7. Toward mHealth Brief Contact Interventions in Suicide Prevention: Case Series From the Suicide Intervention Assisted by Messages (SIAM) Randomized Controlled Trial.

    Science.gov (United States)

    Berrouiguet, Sofian; Larsen, Mark Erik; Mesmeur, Catherine; Gravey, Michel; Billot, Romain; Walter, Michel; Lemey, Christophe; Lenca, Philippe

    2018-01-10

    Research indicates that maintaining contact either via letter or postcard with at-risk adults following discharge from care services after a suicide attempt (SA) can reduce reattempt risk. Pilot studies have demonstrated that interventions using mobile health (mHealth) technologies are feasible in a suicide prevention setting. The aim of this study was to report three cases of patients recruited in the Suicide Intervention Assisted by Messages (SIAM) study to describe how a mobile intervention may influence follow-up. SIAM is a 2-year, multicenter randomized controlled trial conducted by the Brest University Hospital, France. Participants in the intervention group receive SIAM text messages 48 hours after discharge, then at day 8 and day 15, and months 1, 2, 3, 4, 5, and 6. The study includes participants aged 18 years or older, who have attended a participating hospital for an SA, and have been discharged from the emergency department (ED) or a psychiatric unit (PU) for a stay of less than 7 days. Eligible participants are randomized between the SIAM intervention messages and a control group. In this study, we present three cases from the ongoing SIAM study that demonstrate the capability of a mobile-based brief contact intervention for triggering patient-initiated contact with a crisis support team at various time points throughout the mobile-based follow-up period. Out of the 244 patients recruited in the SIAM randomized controlled trial, three cases were selected to illustrate the impact of mHealth on suicide risk management. Participants initiated contact with the emergency crisis support service after receiving text messages up to 6 months following discharge from the hospital. Contact was initiated immediately following receipt of a text message or up to 6 days following a message. This text message-based brief contact intervention has demonstrated the potential to reconnect suicidal individuals with crisis support services while they are experiencing

  8. Comparative efficacy of interventions to promote hand hygiene in hospital: systematic review and network meta-analysis

    Science.gov (United States)

    Hongsuwan, Maliwan; Limmathurotsakul, Direk; Lubell, Yoel; Lee, Andie S; Harbarth, Stephan; Day, Nicholas P J; Graves, Nicholas; Cooper, Ben S

    2015-01-01

    Objective To evaluate the relative efficacy of the World Health Organization 2005 campaign (WHO-5) and other interventions to promote hand hygiene among healthcare workers in hospital settings and to summarize associated information on use of resources. Design Systematic review and network meta-analysis. Data sources Medline, Embase, CINAHL, NHS Economic Evaluation Database, NHS Centre for Reviews and Dissemination, Cochrane Library, and the EPOC register (December 2009 to February 2014); studies selected by the same search terms in previous systematic reviews (1980-2009). Review methods Included studies were randomised controlled trials, non-randomised trials, controlled before-after trials, and interrupted time series studies implementing an intervention to improve compliance with hand hygiene among healthcare workers in hospital settings and measuring compliance or appropriate proxies that met predefined quality inclusion criteria. When studies had not used appropriate analytical methods, primary data were re-analysed. Random effects and network meta-analyses were performed on studies reporting directly observed compliance with hand hygiene when they were considered sufficiently homogeneous with regard to interventions and participants. Information on resources required for interventions was extracted and graded into three levels. Results Of 3639 studies retrieved, 41 met the inclusion criteria (six randomised controlled trials, 32 interrupted time series, one non-randomised trial, and two controlled before-after studies). Meta-analysis of two randomised controlled trials showed the addition of goal setting to WHO-5 was associated with improved compliance (pooled odds ratio 1.35, 95% confidence interval 1.04 to 1.76; I2=81%). Of 22 pairwise comparisons from interrupted time series, 18 showed stepwise increases in compliance with hand hygiene, and all but four showed a trend for increasing compliance after the intervention. Network meta-analysis indicated

  9. Time Series Data Analysis of Wireless Sensor Network Measurements of Temperature.

    Science.gov (United States)

    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.

  10. Multi-complexity ensemble measures for gait time series analysis: application to diagnostics, monitoring and biometrics.

    Science.gov (United States)

    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.

  11. Bibliometric analysis of interventions with batterers in Spain

    Directory of Open Access Journals (Sweden)

    Victoria A. Ferrer Perez

    2015-01-01

    Full Text Available This study analyse the evolution and characteristics of scientific production on intervention programmes with gender violence perpetrators performed in Spain. The standard bibliometric indicators were applied to 148 studies identified. The greatest productivity is focused between 2008 and 2010 and the largest number of records corresponds to articles in specialised scientific journals. As far as authorship is concerned, an analysis of the number of studies per person indicates that the results obtained are only initially consistent with Lotka’s Law, that is, there are a majority of not very productive authors and a minority who publish frequently, but the data do not fit this law. An analysis of collaboration between authors enables us to determine the existence of one “Social Circle” or “Invisible College”, at least. Most of the records analysed focus on the description of one or several intervention programmes with men who abuse their partner. Results show that there are progressively more evidence based studies on batterers and their treatment.

  12. Harmonic Analysis of a Nonstationary Series of Temperature Paleoreconstruction for the Central Part of Greenland

    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.

  13. Properties of Asymmetric Detrended Fluctuation Analysis in the time series of RR intervals

    Science.gov (United States)

    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.

  14. 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

  15. Statistical attribution analysis of the nonstationarity of the annual runoff series of the Weihe River.

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    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.

  17. A Filtering of Incomplete GNSS Position Time Series with Probabilistic Principal Component Analysis

    Science.gov (United States)

    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.

  18. A Recurrent Probabilistic Neural Network with Dimensionality Reduction Based on Time-series Discriminant Component Analysis.

    Science.gov (United States)

    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.

  19. Regression and regression analysis time series prediction modeling on climate data of quetta, pakistan

    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)

  20. Bayesian near-boundary analysis in basic macroeconomic time series models

    NARCIS (Netherlands)

    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

  1. A Comparison of Missing-Data Procedures for Arima Time-Series Analysis

    Science.gov (United States)

    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…

  2. Using trajectory sensitivity analysis to find suitable locations of series compensators for improving rotor angle stability

    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...

  3. Detrended partial cross-correlation analysis of two nonstationary time series influenced by common external forces

    Science.gov (United States)

    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.

  4. Operation States Analysis of the Series-Parallel resonant Converter Working Above Resonance Frequency

    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.

  5. AAMFT Master Series Tapes: An Analysis of the Inclusion of Feminist Principles into Family Therapy Practice.

    Science.gov (United States)

    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…

  6. Dynamic factor analysis in the frequency domain: causal modeling of multivariate psychophysiological time series

    NARCIS (Netherlands)

    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

  7. Harmonic analysis of dense time series of landsat imagery for modeling change in forest conditions

    Science.gov (United States)

    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...

  8. Economic Conditions and the Divorce Rate: A Time-Series Analysis of the Postwar United States.

    Science.gov (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.…

  9. 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.

  10. The effect of stricter licensing on road traffic injury events involving 15 to 17-year-old moped drivers in Sweden: A time series intervention study.

    Science.gov (United States)

    Bonander, Carl; Andersson, Ragnar; Nilson, Finn

    2015-10-01

    This study aimed to evaluate and quantify the effect of the introduction of the AM driving license on non-fatal moped-related injuries in Sweden. With the introduction of the new license category in October 2009, prospective moped drivers are now required to pass a mandatory theory test following a practical and theoretical course. In addition, obtaining a license to operate a moped is now considerably more costly. Time series intervention analysis on monthly aggregated injury data (1st Jan 2007-31st Dec 2013) was performed using generalized additive models for location, shape and scale (GAMLSS) to quantify the effect size on injury events involving teenage (15-17 years) moped drivers, while controlling for trend and seasonality. Exposure was adjusted for by using the number of registered mopeds in traffic as a proxy. The introduction of AM license was associated with a 41% reduction in the rate of injury events involving 15-year-old moped drivers (IRR 0.59 [95% CI: 0.48-0.72]), and a 39% and 36% decrease in those involving 16-year-old (IRR 0.61 [95% CI: 0.48-0.79]) and 17-year-old drivers (IRR 0.64 [95% CI: 0.46-0.90]), respectively. The effect in the 15-year-old stratum was decreased roughly by half after adjusting for exposure, but remained significant, and the corresponding estimates in the other age groups did not change noticeably. This study provides quasi-experimental evidence of an effect on non-fatal moped-related injuries as a result of stricter licensing rules. Only part of the effect could be explained by a reduction in the number of mopeds in traffic, indicating that other mechanisms must be studied to fully understand the cause of the reduction in injuries. Copyright © 2015 Elsevier Ltd. All rights reserved.

  11. Unified functional network and nonlinear time series analysis for complex systems science: The pyunicorn package

    Science.gov (United States)

    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].

  12. Independent component analysis: A new possibility for analysing series of electron energy loss spectra

    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

  13. Analysis of occupational doses in interventional radiology and cardiology installations

    International Nuclear Information System (INIS)

    Vano, E.; Gonzalez, L.; Ten, J.I.; Guibelalde, E.; Fernandez, J.M.

    1997-01-01

    The relationship between patient dose (PD) and occupational dose (OD) is not easily predictable in interventional radiology installations due to a large number of factors which can modify the occupational risk (OR). In the present work an analysis is made of the four main aspects which influence OR, namely, x-ray beam used, radiation protection (RP) tools available (aprons, thyroid protectors, gloves, screens, etc) and their regular use, type and number of procedures performed (diagnostic or therapeutic, complexity level, etc), and RP training level of the specialists. High filtration x-ray beams can entail a decrease of 20% in OD. A regular use of ceiling mounted faceplates can involve dose savings up to 65%. Mean values of dose per procedure for interventional radiologists are something greater (about 15%) than those recorded for cardiologists, except for the dosimeters placed on left forearm and shoulder. The ratio between OD and PD range around 100 μSv/1,000 cGy.cm 2 . The influence of the staff RP training level on OD is difficult to assess. In the IC Service from the Madrid San Carlos University Hospital (SCUH), PD have been reduced in above 30% and OD in a factor of 3, after running some training programmes. (author)

  14. Analysis of Foreign Exchange Interventions by Intervention Agent with an Artificial Market Approach

    Science.gov (United States)

    Matsui, Hiroki; Tojo, Satoshi

    We propose a multi-agent system which learns intervention policies and evaluates the effect of interventions in an artificial foreign exchange market. Izumi et al. had presented a system called AGEDASI TOF to simulate artificial market, together with a support system for the government to decide foreign exchange policies. However, the system needed to fix the amount of governmental intervention prior to the simulation, and was not realistic. In addition, the interventions in the system did not affect supply and demand of currencies; thus we could not discuss the effect of intervention correctly. First, we improve the system so as to make much of the weights of influential factors. Thereafter, we introduce an intervention agent that has the role of the central bank to stabilize the market. We could show that the agent learned the effective intervention policies through the reinforcement learning, and that the exchange rate converged to a certain extent in the expected range. We could also estimate the amount of intervention, showing the efficacy of signaling. In this model, in order to investigate the aliasing of the perception of the intervention agent, we introduced a pseudo-agent who was supposed to be able to observe all the behaviors of dealer agents; with this super-agent, we discussed the adequate granularity for a market state description.

  15. Time Series Imputation via L1 Norm-Based Singular Spectrum Analysis

    Science.gov (United States)

    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.

  16. Analysis of Land Subsidence Monitoring in Mining Area with Time-Series Insar Technology

    Science.gov (United States)

    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.

  17. Housefly population density correlates with shigellosis among children in Mirzapur, Bangladesh: a time series analysis.

    Directory of Open Access Journals (Sweden)

    Tamer H Farag

    Full Text Available BACKGROUND: Shigella infections are a public health problem in developing and transitional countries because of high transmissibility, severity of clinical disease, widespread antibiotic resistance and lack of a licensed vaccine. Whereas Shigellae are known to be transmitted primarily by direct fecal-oral contact and less commonly by contaminated food and water, the role of the housefly Musca domestica as a mechanical vector of transmission is less appreciated. We sought to assess the contribution of houseflies to Shigella-associated moderate-to-severe diarrhea (MSD among children less than five years old in Mirzapur, Bangladesh, a site where shigellosis is hyperendemic, and to model the potential impact of a housefly control intervention. METHODS: Stool samples from 843 children presenting to Kumudini Hospital during 2009-2010 with new episodes of MSD (diarrhea accompanied by dehydration, dysentery or hospitalization were analyzed. Housefly density was measured twice weekly in six randomly selected sentinel households. Poisson time series regression was performed and autoregression-adjusted attributable fractions (AFs were calculated using the Bruzzi method, with standard errors via jackknife procedure. FINDINGS: Dramatic springtime peaks in housefly density in 2009 and 2010 were followed one to two months later by peaks of Shigella-associated MSD among toddlers and pre-school children. Poisson time series regression showed that housefly density was associated with Shigella cases at three lags (six weeks (Incidence Rate Ratio = 1.39 [95% CI: 1.23 to 1.58] for each log increase in fly count, an association that was not confounded by ambient air temperature. Autocorrelation-adjusted AF calculations showed that a housefly control intervention could have prevented approximately 37% of the Shigella cases over the study period. INTERPRETATION: Houseflies may play an important role in the seasonal transmission of Shigella in some developing

  18. Meta- and statistical analysis of single-case intervention research data: quantitative gifts and a wish list.

    Science.gov (United States)

    Kratochwill, Thomas R; Levin, Joel R

    2014-04-01

    In this commentary, we add to the spirit of the articles appearing in the special series devoted to meta- and statistical analysis of single-case intervention-design data. Following a brief discussion of historical factors leading to our initial involvement in statistical analysis of such data, we discuss: (a) the value added by including statistical-analysis recommendations in the What Works Clearinghouse Standards for single-case intervention designs; (b) the importance of visual analysis in single-case intervention research, along with the distinctive role that could be played by single-case effect-size measures; and (c) the elevated internal validity and statistical-conclusion validity afforded by the incorporation of various forms of randomization into basic single-case design structures. For the future, we envision more widespread application of quantitative analyses, as critical adjuncts to visual analysis, in both primary single-case intervention research studies and literature reviews in the behavioral, educational, and health sciences. Copyright © 2014 Society for the Study of School Psychology. Published by Elsevier Ltd. All rights reserved.

  19. Sensitivity analysis of machine-learning models of hydrologic time series

    Science.gov (United States)

    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.

  20. Application of the Allan Variance to Time Series Analysis in Astrometry and Geodesy: A Review.

    Science.gov (United States)

    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.

  1. Social network analysis of character interaction in the Stargate and Star Trek television series

    Science.gov (United States)

    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.

  2. Principal components and iterative regression analysis of geophysical series: Application to Sunspot number (1750 2004)

    Science.gov (United States)

    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.

  3. 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.

  4. 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.

  5. Parameter trajectory analysis to identify treatment effects of pharmacological interventions.

    Directory of Open Access Journals (Sweden)

    Christian A Tiemann

    Full Text Available The field of medical systems biology aims to advance understanding of molecular mechanisms that drive disease progression and to translate this knowledge into therapies to effectively treat diseases. A challenging task is the investigation of long-term effects of a (pharmacological treatment, to establish its applicability and to identify potential side effects. We present a new modeling approach, called Analysis of Dynamic Adaptations in Parameter Trajectories (ADAPT, to analyze the long-term effects of a pharmacological intervention. A concept of time-dependent evolution of model parameters is introduced to study the dynamics of molecular adaptations. The progression of these adaptations is predicted by identifying necessary dynamic changes in the model parameters to describe the transition between experimental data obtained during different stages of the treatment. The trajectories provide insight in the affected underlying biological systems and identify the molecular events that should be studied in more detail to unravel the mechanistic basis of treatment outcome. Modulating effects caused by interactions with the proteome and transcriptome levels, which are often less well understood, can be captured by the time-dependent descriptions of the parameters. ADAPT was employed to identify metabolic adaptations induced upon pharmacological activation of the liver X receptor (LXR, a potential drug target to treat or prevent atherosclerosis. The trajectories were investigated to study the cascade of adaptations. This provided a counter-intuitive insight concerning the function of scavenger receptor class B1 (SR-B1, a receptor that facilitates the hepatic uptake of cholesterol. Although activation of LXR promotes cholesterol efflux and -excretion, our computational analysis showed that the hepatic capacity to clear cholesterol was reduced upon prolonged treatment. This prediction was confirmed experimentally by immunoblotting measurements of SR-B1

  6. Prostatic Artery Embolization After Failed Urological Interventions for Benign Prostatic Obstruction: A Case Series of Three Patients

    Energy Technology Data Exchange (ETDEWEB)

    Bhatia, Shivank S., E-mail: sbhatia1@med.miami.edu; Dalal, Ravi, E-mail: rdalal@med.miami.edu [University of Miami – Miller School of Medicine, Department of Radiology (United States); Gomez, Christopher, E-mail: Cgomez7@med.miami.edu [University of Miami – Miller School of Medicine, Department of Urology (United States); Narayanan, Govindarajan, E-mail: gnarayanan@med.miami.edu [University of Miami – Miller School of Medicine, Department of Radiology (United States)

    2016-08-15

    Benign prostate obstruction with associated lower urinary tract symptoms is a common diagnosis with multiple minimally invasive treatment options available. Herein, the authors describe three patients who failed prior different urological interventions who underwent prostate artery embolization with a subsequent improvement in symptoms. The positive response suggests that embolization may be an effective treatment alternative in this subset of patients.

  7. Case Series.

    Science.gov (United States)

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

    2017-01-01

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

  8. Interventions for central serous chorioretinopathy: a network meta-analysis

    Science.gov (United States)

    Salehi, Mahsa; Wenick, Adam S; Law, Hua Andrew; Evans, Jennifer R; Gehlbach, Peter

    2016-01-01

    Background Central serous chorioretinopathy (CSC) is characterized by serous detachment of the neural retina with dysfunction of the choroid and retinal pigment epithelium (RPE). The effects on the retina are usually self limited, although some people are left with irreversible vision loss due to progressive and permanent photoreceptor damage or RPE atrophy. There have been a variety of interventions used in CSC, including, but not limited to, laser treatment, photodynamic therapy (PDT), and intravitreal injection of anti-vascular endothelial growth factor (anti-VEGF) agents. However, it is not known whether these or other treatments offer significant advantages over observation or other interventions. At present there is no evidence-based consensus on the management of CSC. Due in large part to the propensity for CSC to resolve spontaneously or to follow a waxing and waning course, the most common initial approach to treatment is observation. It remains unclear whether this is the best approach with regard to safety and efficacy. Objectives To compare the relative effectiveness of interventions for central serous chorioretinopathy. Search methods We searched CENTRAL (which contains the Cochrane Eyes and Vision Trials Register) (2015, Issue 9), Ovid MEDLINE, Ovid MEDLINE In-Process and Other Non-Indexed Citations, Ovid MEDLINE Daily, Ovid OLDMEDLINE (January 1946 to February 2014), EMBASE (January 1980 to October 2015), the ISRCTN registry (www.isrctn.com/editAdvancedSearch), ClinicalTrials.gov (www.clinicaltrials.gov) and the World Health Organization (WHO) International Clinical Trials Registry Platform (ICTRP) (www.who.int/ictrp/search/en). We did not use any date or language restrictions in the electronic searches for trials. We last searched the electronic databases on 5 October 2015. Selection criteria Randomized controlled trials (RCTs) that compared any intervention for CSC with any other intervention for CSC or control. Data collection and analysis Two

  9. 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.

  10. Statistical tools for analysis and modeling of cosmic populations and astronomical time series: CUDAHM and TSE

    Science.gov (United States)

    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.

  11. A systematic review of case-series studies on the effectiveness of interventions to reduce polypharmacy and its adverse consequences in the elderly.

    Directory of Open Access Journals (Sweden)

    Maria Benedetta Michelazzo

    2017-03-01

    Full Text Available Background. Aging is frequently accompanied by chronic diseases; as a consequence, older people are often exposed to polypharmacy that has been associated with negative health-consequences. The aim of this study is to conduct a systematic review of the literature reporting on the effectiveness of different approaches to reduce polypharmacy in the elderly. Methods. We conducted a comprehensive literature search of MEDLINE, Scopus and ISI Web of Knowledge databases. Eligible studies were case-series reporting outcomes of interventions aimed at reducing polypharmacy and its consequences in the elderly. A quality appraisal of the studies included was performed. Results. Nineteen studies were included, of which six conducted in community setting, seven in hospital setting, and six in nursing homes. Seventeen of them were judged as moderate quality, and two of them as poor quality. The majority of the interventions were carried out by pharmacists, alone (35% or with other professionals (40%. Interventions consisted in pharmacotherapy reviews based on various tools and software; in some cases educational interventions were performed for review-performers and patients. Studies conducted in community-setting provided also a feedback to primary care physician. The outcomes included five categories: therapy’s characteristics (e.g. number of drugs, appropriate prescriptions, quality of life, health-related outcomes, costs, healthcare services’ utilization. Therapy-related outcomes were those more affected by all types of interventions. Conclusion. Interventions aimed at reviewing patients’ therapy are effective in optimizing the use of drugs, and could be considered also  in improving quality of life, healthcare costs, services’ utilization, and health-related outcomes.

  12. Efficacy of behavioural interventions for transport behaviour change: systematic review, meta-analysis and intervention coding.

    Science.gov (United States)

    Arnott, Bronia; Rehackova, Lucia; Errington, Linda; Sniehotta, Falko F; Roberts, Jennifer; Araujo-Soares, Vera

    2014-11-28

    Reducing reliance on motorised transport and increasing use of more physically active modes of travel may offer an opportunity to address physical inactivity. This review evaluates the evidence for the effects of behavioural interventions to reduce car use for journeys made by adults and codes intervention development and content. The review follows the procedure stated in the registration protocol published in the PROSPERO database (registration number CRD42011001797). Controlled studies evaluating behavioural interventions to reduce car use compared with no interventions or alternative interventions on outcome measures of transport behaviours taken in adult participants are included in this review. Searches were conducted on all records in Applied Social Sciences Index and Abstracts (ASSIA), Ovid Embase, Ovid Medline, Ovid PsycInfo, Scopus, Sociological Abstracts, Transportation Research Information Service (TRIS), Transportation Research International Documentation (TRID), and Web of Science databases. Peer reviewed publications in English language meeting the inclusion criteria are eligible. Methodological quality is assessed using the Cochrane Risk of Bias Tool. Interventions are categorised in terms of behavioural frameworks, theories and techniques. 15 full text articles are included, representing 13 unique studies, with 4895 participants and 27 intervention arms. Risk of bias across the review is appraised as considerable due to the unclear methodological quality of individual studies. Heterogeneity of included studies is considerable. Meta-analyses reveal no significant effect on reduction of frequency of car use or on increasing the proportion of journeys by alternative, more active modes of transport. There is insufficient data relating to alternative outcomes such as distance and duration which may have important health implications. Interventions were top-down but could not be described as theory-based. Intervention efficacy was associated with the use

  13. 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.

  14. Pacing: a concept analysis of the chronic pain intervention.

    Science.gov (United States)

    Jamieson-Lega, Kathryn; Berry, Robyn; Brown, Cary A

    2013-01-01

    The intervention of pacing is regularly recommended for chronic pain patients. However, pacing is poorly defined and appears to be interpreted in varying, potentially contradictory manners within the field of chronic pain. This conceptual lack of clarity has implications for effective service delivery and for researchers' ability to conduct rigorous study. An examination of the background literature demonstrates that while pacing is often one part of a multidisciplinary pain management program, outcome research is hindered by a lack of a clear and shared definition of this currently ill-defined construct. To conduct a formal concept analysis of the term 'pacing'. A standardized concept analysis process (including literature scoping to identify all uses of the concept, analysis to determine defining attributes of the concept and identification of model, borderline and contrary cases) was used to determine what the concept of pacing does and does not represent within the current evidence base. A conceptual model including the core attributes of action, time, balance, learning and self-management emerged. From these attributes, an evidence-based definition for pacing was composed and distributed to stakeholders for review. After consideration of stakeholder feedback, the emergent definition of pacing was finalized as follows: "Pacing is an active self-management strategy whereby individuals learn to balance time spent on activity and rest for the purpose of achieving increased function and participation in meaningful activities". The findings of the present concept analysis will help to standardize the use and definition of the term pacing across disciplines for the purposes of both pain management and research.

  15. Adventures in Modern Time Series Analysis: From the Sun to the Crab Nebula and Beyond

    Science.gov (United States)

    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.

  16. Flood Frequency Analysis For Partial Duration Series In Ganjiang River Basin

    Science.gov (United States)

    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.

  17. Identifying Effective Components of Child Maltreatment Interventions: A Meta-analysis.

    Science.gov (United States)

    van der Put, Claudia E; Assink, Mark; Gubbels, Jeanne; Boekhout van Solinge, Noëlle F

    2018-06-01

    There is a lack of knowledge about specific components that make interventions effective in preventing or reducing child maltreatment. The aim of the present meta-analysis was to increase this knowledge by summarizing findings on effects of interventions for child maltreatment and by examining potential moderators of this effect, such as intervention components and study characteristics. Identifying effective components is essential for developing or improving child maltreatment interventions. A literature search yielded 121 independent studies (N = 39,044) examining the effects of interventions for preventing or reducing child maltreatment. From these studies, 352 effect sizes were extracted. The overall effect size was significant and small in magnitude for both preventive interventions (d = 0.26, p child maltreatment. For preventive interventions, larger effect sizes were found for short-term interventions (0-6 months), interventions focusing on increasing self-confidence of parents, and interventions delivered by professionals only. Further, effect sizes of preventive interventions increased as follow-up duration increased, which may indicate a sleeper effect of preventive interventions. For curative interventions, larger effect sizes were found for interventions focusing on improving parenting skills and interventions providing social and/or emotional support. Interventions can be effective in preventing or reducing child maltreatment. Theoretical and practical implications are discussed.

  18. 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

  19. 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)

  20. A Time Series Analysis to Asymmetric Marketing Competition Within a Market Structure

    OpenAIRE

    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...

  1. Time series analysis in road safety research uisng state space methods

    OpenAIRE

    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...

  2. Time Series Modeling of Army Mission Command Communication Networks: An Event-Driven Analysis

    Science.gov (United States)

    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

  3. 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.

  4. The Fourier decomposition method for nonlinear and non-stationary time series analysis.

    Science.gov (United States)

    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.

  5. The physiology analysis system: an integrated approach for warehousing, management and analysis of time-series physiology data.

    Science.gov (United States)

    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.

  6. Trend Estimation and Regression Analysis in Climatological Time Series: An Application of Structural Time Series Models and the Kalman Filter.

    Science.gov (United States)

    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

  7. Early detection of metabolic and energy disorders by thermal time series stochastic complexity analysis

    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.

  8. Early detection of metabolic and energy disorders by thermal time series stochastic complexity analysis

    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

  9. Time series analysis of infrared satellite data for detecting thermal anomalies: a hybrid approach

    Science.gov (United States)

    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.

  10. Spatial analysis of precipitation time series over the Upper Indus Basin

    Science.gov (United States)

    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.

  11. Spectral analysis of uneven time series of geological variables; Analisis espectral de series temporales de variables geologicas con muestreo irregular

    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)

  12. Cost-Effectiveness Analysis in Practice: Interventions to Improve High School Completion

    Science.gov (United States)

    Hollands, Fiona; Bowden, A. Brooks; Belfield, Clive; Levin, Henry M.; Cheng, Henan; Shand, Robert; Pan, Yilin; Hanisch-Cerda, Barbara

    2014-01-01

    In this article, we perform cost-effectiveness analysis on interventions that improve the rate of high school completion. Using the What Works Clearinghouse to select effective interventions, we calculate cost-effectiveness ratios for five youth interventions. We document wide variation in cost-effectiveness ratios between programs and between…

  13. Studies in astronomical time series analysis. I - Modeling random processes in the time domain

    Science.gov (United States)

    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.

  14. 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)

  15. On the Impact of a Quadratic Acceleration Term in the Analysis of Position Time Series

    Science.gov (United States)

    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

  16. Memory training interventions for older adults: a meta-analysis.

    Science.gov (United States)

    Gross, Alden L; Parisi, Jeanine M; Spira, Adam P; Kueider, Alexandra M; Ko, Jean Y; Saczynski, Jane S; Samus, Quincy M; Rebok, George W

    2012-01-01

    A systematic review and meta-analysis of memory training research was conducted to characterize the effect of memory strategies on memory performance among cognitively intact, community-dwelling older adults, and to identify characteristics of individuals and of programs associated with improved memory. The review identified 402 publications, of which 35 studies met criteria for inclusion. The overall effect size estimate, representing the mean standardized difference in pre-post change between memory-trained and control groups, was 0.31 standard deviations (SD; 95% confidence interval (CI): 0.22, 0.39). The pre-post training effect for memory-trained interventions was 0.43 SD (95% CI: 0.29, 0.57) and the practice effect for control groups was 0.06 SD (95% CI: 0.05, 0.16). Among 10 distinct memory strategies identified in studies, meta-analytic methods revealed that training multiple strategies was associated with larger training gains (p=0.04), although this association did not reach statistical significance after adjusting for multiple comparisons. Treatment gains among memory-trained individuals were not better after training in any particular strategy, or by the average age of participants, session length, or type of control condition. These findings can inform the design of future memory training programs for older adults.

  17. Interventional Effects for Mediation Analysis with Multiple Mediators.

    Science.gov (United States)

    Vansteelandt, Stijn; Daniel, Rhian M

    2017-03-01

    The mediation formula for the identification of natural (in)direct effects has facilitated mediation analyses that better respect the nature of the data, with greater consideration of the need for confounding control. The default assumptions on which it relies are strong, however. In particular, they are known to be violated when confounders of the mediator-outcome association are affected by the exposure. This complicates extensions of counterfactual-based mediation analysis to settings that involve repeatedly measured mediators, or multiple correlated mediators. VanderWeele, Vansteelandt, and Robins introduced so-called interventional (in)direct effects. These can be identified under much weaker conditions than natural (in)direct effects, but have the drawback of not adding up to the total effect. In this article, we adapt their proposal to achieve an exact decomposition of the total effect, and extend it to the multiple mediator setting. Interestingly, the proposed effects capture the path-specific effects of an exposure on an outcome that are mediated by distinct mediators, even when-as often-the structural dependence between the multiple mediators is unknown, for instance, when the direction of the causal effects between the mediators is unknown, or there may be unmeasured common causes of the mediators.

  18. Development of indicators of vegetation recovery based on time series analysis of SPOT Vegetation data

    Science.gov (United States)

    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.

  19. Comparative performance analysis of shunt and series passive filter for LED lamp

    Science.gov (United States)

    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%.

  20. Work-related accidents among the Iranian population: a time series analysis, 2000-2011.

    Science.gov (United States)

    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.

  1. Work-related accidents among the Iranian population: a time series analysis, 2000–2011

    Science.gov (United States)

    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

  2. Cost Analysis of Early Psychosocial Intervention in Alzheimer's Disease

    DEFF Research Database (Denmark)

    Søgaard, R.; Sørensen, J.; Waldorff, F.B.

    2014-01-01

    BACKGROUND/AIM: To investigate the impact of early psychosocial intervention aimed at patients with Alzheimer's disease (AD) and their caregivers on resource use and costs from a societal perspective. METHODS: Dyads of patients and their primary caregiver were randomised to intervention (n = 163...

  3. HIV and dyadic intervention: an interdependence and communal coping analysis

    NARCIS (Netherlands)

    Montgomery, C.M.; Watts, C.; Pool, R.

    2012-01-01

    Background The most common form of HIV transmission in sub-Saharan Africa is heterosexual sex between two partners. While most HIV prevention interventions are aimed at the individual, there is mounting evidence of the feasibility, acceptability, and efficacy of dyadic interventions. However, the

  4. Intensive Intervention Practice Guide: School-Based Functional Analysis

    Science.gov (United States)

    Pennington, Brittany; Pokorski, Elizabeth A.; Kumm, Skip; Sterrett, Brittany I.

    2017-01-01

    The National Center for Leadership in Intensive Intervention (NCLII), a consortium funded by the Office of Special Education Programs (OSEP), prepares special education leaders to become experts in research on intensive intervention for students with disabilities who have persistent and severe academic (e.g., reading and math) and behavioral…

  5. Parent-Implemented Communication Intervention: Sequential Analysis of Triadic Relationships

    Science.gov (United States)

    Brown, Jennifer A.; Woods, Juliann J.

    2016-01-01

    Collaboration with parents and caregivers to support young children's communication development is an important component to early intervention services. Coaching parents to implement communication support strategies is increasingly common in parent-implemented interventions, but few studies examine the process as well as the outcomes. We explored…

  6. 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

  7. A Cost Analysis of School-Based Lifestyle Interventions.

    Science.gov (United States)

    Oosterhoff, Marije; Bosma, Hans; van Schayck, Onno C P; Joore, Manuela A

    2018-05-31

    A uniform approach for costing school-based lifestyle interventions is currently lacking. The objective of this study was to develop a template for costing primary school-based lifestyle interventions and apply this to the costing of the "Healthy Primary School of the Future" (HPSF) and the "Physical Activity School" (PAS), which aim to improve physical activity and dietary behaviors. Cost-effectiveness studies were reviewed to identify the cost items. Societal costs were reflected by summing up the education, household and leisure, labor and social security, and health perspectives. Cost inputs for HPSF and PAS were obtained for the first year after implementation. In a scenario analysis, the costs were explored for a hypothetical steady state. From a societal perspective, the per child costs were €2.7/$3.3 (HPSF) and €- 0.3/$- 0.4 (PAS) per day during the first year after implementation, and €1.0/$1.2 and €- 1.3/$- 1.6 in a steady state, respectively (2016 prices). The highest costs were incurred by the education perspective (first year: €8.7/$10.6 (HPSF) and €4.0/$4.9 (PAS); steady state: €6.1/$7.4 (HPSF) and €2.1/$2.6 (PAS)), whereas most of the cost offsets were received by the household and leisure perspective (first year: €- 6.0/$- 7.3 (HPSF) and €- 4.4/$- 5.4 (PAS); steady state: €- 5.0/$- 6.1 (HPSF) and €- 3.4/$- 4.1 (PAS)). The template proved helpful for costing HPSF and PAS from various stakeholder perspectives. The costs for the education sector were fully (PAS) and almost fully (HPSF) compensated by the savings within the household sector. Whether the additional costs of HPSF over PAS represent value for money will depend on their relative effectiveness.

  8. Detrended fluctuation analysis based on higher-order moments of financial time series

    Science.gov (United States)

    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.

  9. 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.

  10. 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.

  11. 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.

  12. 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)

  13. Causality as a Rigorous Notion and Quantitative Causality Analysis with Time Series

    Science.gov (United States)

    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

  14. Phase correction and error estimation in InSAR time series analysis

    Science.gov (United States)

    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

  15. Humanitarian Interventions: Western Imperialism or a Responsibility to Protect?--An Analysis of the Humanitarian Interventions in Darfur

    Science.gov (United States)

    Damboeck, Johanna

    2012-01-01

    Purpose: The aim of this article is to provide an analysis of the features that have shaped the state's decision-making process in the United Nations, with regard to the humanitarian intervention in Darfur from 2003 onwards. Design/methodology/approach: The methodological approach to the study is a review of political statement papers grounded in…

  16. Cost-Effectiveness Analysis Comparing Pre-Diagnosis Autism Spectrum Disorder (ASD)-Targeted Intervention with Ontario's Autism Intervention Program

    Science.gov (United States)

    Penner, Melanie; Rayar, Meera; Bashir, Naazish; Roberts, S. Wendy; Hancock-Howard, Rebecca L.; Coyte, Peter C.

    2015-01-01

    Novel management strategies for autism spectrum disorder (ASD) propose providing interventions before diagnosis. We performed a cost-effectiveness analysis comparing the costs and dependency-free life years (DFLYs) generated by pre-diagnosis intensive Early Start Denver Model (ESDM-I); pre-diagnosis parent-delivered ESDM (ESDM-PD); and the Ontario…

  17. Multidimensional scaling analysis of financial time series based on modified cross-sample entropy methods

    Science.gov (United States)

    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.

  18. Radial artery pulse waveform analysis based on curve fitting using discrete Fourier series.

    Science.gov (United States)

    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.

  19. Analysis of cyclical behavior in time series of stock market returns

    Science.gov (United States)

    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.

  20. 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)

  1. 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.

  2. A prospective interrupted time series study of interventions to improve the quality, rating, framing and structure of goal-setting in community-based brain injury rehabilitation.

    Science.gov (United States)

    Hassett, Leanne; Simpson, Grahame; Cotter, Rachel; Whiting, Diane; Hodgkinson, Adeline; Martin, Diane

    2015-04-01

    To investigate whether the introduction of an electronic goals system followed by staff training improved the quality, rating, framing and structure of goals written by a community-based brain injury rehabilitation team. Interrupted time series design. Two interventions were introduced six months apart. The first intervention comprised the introduction of an electronic goals system. The second intervention comprised a staff goal training workshop. An audit protocol was devised to evaluate the goals. A random selection of goal statements from the 12 months prior to the interventions (Time 1 baseline) were compared with all goal statements written after the introduction of the electronic goals system (Time 2) and staff training (Time 3). All goals were de-identified for client and time-period, and randomly ordered. A total of 745 goals (Time 1 n = 242; Time 2 n = 283; Time 3 n = 220) were evaluated. Compared with baseline, the introduction of the electronic goals system alone significantly increased goal rating, framing and structure (χ(2) tests 144.7, 18.9, 48.1, respectively, p goal quality, which was only a trend at Time 2, was statistically significant at Time 3 (χ(2) 15.0, p ≤ 001). The training also led to a further significant increase in the framing and structuring of goals over the electronic goals system (χ(2) 11.5, 12.5, respectively, p ≤ 0.001). An electronic goals system combined with staff training improved the quality, rating, framing and structure of goal statements. © The Author(s) 2014.

  3. Simple and complicated rectal diverticula: endoscopic analysis of a case series from Brazil

    Directory of Open Access Journals (Sweden)

    Guilherme Lang Motta

    2012-09-01

    Full Text Available INTRODUCTION: Diverticular disease of the colon is a very common condition, present in most of the elderly population. However, the occurrence of rectal diverticula is extremely unusual. It is typically an incidental finding at colonoscopy. OBJECTIVE: Describe epidemiological, clinical, surgical and endoscopic characteristics of a case series of rectal diverticula in Brazil. METHODS: Four patients with rectal diverticula were analyzed in terms of symptomatology, associated conditions and colonoscopy findings. Endoscopic findings were discussed individually. RESULTS: The prevalence of rectal diverticula at our endoscopy unit was 0.15% of all colonoscopies, affecting 0.74% of patients with colonic diverticulosis. The endoscopic analysis showed the diverticulum ostium with mean size of 2.3 cm, depth of 2.8 cm and anal margin distance of 6.8 cm. Colonoscopy also demonstrated simple rectal diverticulum in all patients. Diverticula were located in the anterior, right lateral and posterior walls of the rectum. One patient developed diverticulitis as complication and underwent to diverticulectomy. CONCLUSIONS: Rectal diverticulum is an incidental finding at colonoscopy and associated with diverticulosis. Its rarity and specific colonoscopic characteristics make it a unique entity. Asymptomatic in most cases, it rarely needs intervention. Surgery is reserved for complicated cases.INTRODUÇÃO: Diverticulose é uma condição muito comum, presente em grande parte da população idosa. Divertículo retal, entretanto, é condição rara. Geralmente é um achado incidental em colonoscopias. OBJETIVO: Descrever as características epidemiológicas, clínicas, cirúrgicas e, especialmente, endoscópicas de uma série de casos de divertículos retais no Brasil. MÉTODOS: Quatro pacientes com divertículos retais são analisados em relação a sintomatologia, condições associadas e colonoscopias. Os achados endoscópicos são discutidos especificamente

  4. Association of Attorney Advertising and FDA Action with Prescription Claims: A Time Series Segmented Regression Analysis.

    Science.gov (United States)

    Tippett, Elizabeth C; Chen, Brian K

    2015-12-01

    Attorneys sponsor television advertisements that include repeated warnings about adverse drug events to solicit consumers for lawsuits against drug manufacturers. The relationship between such advertising, safety actions by the US Food and Drug Administration (FDA), and healthcare use is unknown. To investigate the relationship between attorney advertising, FDA actions, and prescription drug claims. The study examined total users per month and prescription rates for seven drugs with substantial attorney advertising volume and FDA or other safety interventions during 2009. Segmented regression analysis was used to detect pre-intervention trends, post-intervention level changes, and changes in post-intervention trends relative to the pre-intervention trends in the use of these seven drugs, using advertising volume, media hits, and the number of Medicare enrollees as covariates. Data for these variables were obtained from the Center for Medicare and Medicaid Services, Kantar Media, and LexisNexis. Several types of safety actions were associated with reductions in drug users and/or prescription rates, particularly for fentanyl, varenicline, and paroxetine. In most cases, attorney advertising volume rose in conjunction with major safety actions. Attorney advertising volume was positively correlated with prescription rates in five of seven drugs, likely because advertising volume began rising before safety actions, when prescription rates were still increasing. On the other hand, attorney advertising had mixed associations with the number of users per month. Regulatory and safety actions likely reduced the number of users and/or prescription rates for some drugs. Attorneys may have strategically chosen to begin advertising adverse drug events prior to major safety actions, but we found little evidence that attorney advertising reduced drug use. Further research is needed to better understand how consumers and physicians respond to attorney advertising.

  5. Characterization of Land Transitions Patterns from Multivariate Time Series Using Seasonal Trend Analysis and Principal Component Analysis

    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.

  6. Stepping Stones and Creating Futures intervention: shortened interrupted time series evaluation of a behavioural and structural health promotion and violence prevention intervention for young people in informal settlements in Durban, South Africa.

    Science.gov (United States)

    Jewkes, Rachel; Gibbs, Andrew; Jama-Shai, Nwabisa; Willan, Samantha; Misselhorn, Alison; Mushinga, Mildred; Washington, Laura; Mbatha, Nompumelelo; Skiweyiya, Yandisa

    2014-12-29

    Gender-based violence and HIV are highly prevalent in the harsh environment of informal settlements and reducing violence here is very challenging. The group intervention Stepping Stones has been shown to reduce men's perpetration of violence in more rural areas, but violence experienced by women in the study was not affected. Economic empowerment interventions with gender training can protect older women from violence, but microloan interventions have proved challenging with young women. We investigated whether combining a broad economic empowerment intervention and Stepping Stones could impact on violence among young men and women. The intervention, Creating Futures, was developed as a new generation of economic empowerment intervention, which enabled livelihood strengthening though helping participants find work or set up a business, and did not give cash or make loans. We piloted Stepping Stones with Creating Futures in two informal settlements of Durban with 232 out of school youth, mostly aged 18-30 and evaluated with a shortened interrupted time series of two baseline surveys and at 28 and 58 weeks post-baseline. 94/110 men and 111/122 women completed the last assessment, 85.5% and 90.2% respectively of those enrolled. To determine trend, we built random effects regression models with each individual as the cluster for each variable, and measured the slope of the line across the time points. Men's mean earnings in the past month increased by 247% from R411 (~$40) to R1015 (~$102, and women's by 278% R 174 (~$17) to R 484 (about $48) (trend test, p < 0.0001). There was a significant reduction in women's experience of the combined measure of physical and/or sexual IPV in the prior three months from 30.3% to 18.9% (p = 0.037). This was not seen for men. However both men and women scored significantly better on gender attitudes and men significantly reduced their controlling practices in their relationship. The prevalence of moderate or severe depression

  7. Forecasting malaria cases using climatic factors in delhi, India: a time series analysis.

    Science.gov (United States)

    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.

  8. Capturing Context-Related Change in Emotional Dynamics via Fixed Moderated Time Series Analysis.

    Science.gov (United States)

    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.

  9. Non-linear time series analysis on flow instability of natural circulation under rolling motion condition

    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

  10. Seasonal and annual precipitation time series trend analysis in North Carolina, United States

    Science.gov (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

  11. A Meta-Analysis of Treatment Interventions for Internet Addiction Among Korean Adolescents.

    Science.gov (United States)

    Chun, JongSerl; Shim, HaiSun; Kim, Soyoun

    2017-04-01

    This study comprehensively examined the effects of treatment interventions for Internet addiction among adolescents in South Korea through a meta-analysis. We analyzed 70 domestic master's theses and journal articles that reported on controlled studies and involved pre- and post-test analyses in the design. The dates of these publications fall between 2000 and 2015. The total effect size, calculated by random-effect analysis (g), revealed that interventions for the treatment of Internet addiction were effective (ES = 1.838). Meta-ANOVAs revealed differences between groups based on a theoretical model, intervention group size, and intervention duration. Integrative therapy produced larger effect sizes (ES = 2.794) compared to other treatment models such as cognitive behavioral therapy and reality therapy. Effect sizes for interventions, including nine to 12 people (ES = 2.178), were larger than those of interventions including more or fewer participants. Finally, treatment interventions that lasted 8 or more weeks revealed larger effect sizes (ES = 2.294) compared to shorter interventions. The study findings suggest directions for the development and effective operation of future Internet addiction interventions among Korean adolescents. Increasing the effectiveness of these interventions requires an integrative theoretical model, an intervention group size of nine to 12 participants, and a long-term intervention.

  12. 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

  13. 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.

  14. Frequency Analysis of Modis Ndvi Time Series for Determining Hotspot of Land Degradation in Mongolia

    Science.gov (United States)

    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.

  15. Wet tropospheric delays forecast based on Vienna Mapping Function time series analysis

    Science.gov (United States)

    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.

  16. 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.

  17. Permutation entropy based time series analysis: Equalities in the input signal can lead to false conclusions

    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.

  18. Visualization of time series statistical data by shape analysis (GDP ratio changes among Asia countries)

    Science.gov (United States)

    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.

  19. Renal transplant lithiasis: analysis of our series and review of the literature.

    Science.gov (United States)

    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.

  20. Use of recurrence plot and recurrence quantification analysis in Taiwan unemployment rate time series

    Science.gov (United States)

    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.

  1. 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.

  2. 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

  3. Analysis of the development trend of China’s business administration based on time series

    OpenAIRE

    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...

  4. Meta-Analysis of Parent-Mediated Interventions for Young Children with Autism Spectrum Disorder

    Science.gov (United States)

    Nevill, Rose E.; Lecavalier, Luc; Stratis, Elizabeth A.

    2018-01-01

    A number of studies of parent-mediated interventions in autism spectrum disorder have been published in the last 15 years. We reviewed 19 randomized clinical trials of parent-mediated interventions for children with autism spectrum disorder between the ages of 1 and 6 years and conducted a meta-analysis on their efficacy. Meta-analysis outcomes…

  5. Effect of a population-level performance dashboard intervention on maternal-newborn outcomes: an interrupted time series study.

    Science.gov (United States)

    Weiss, Deborah; Dunn, Sandra I; Sprague, Ann E; Fell, Deshayne B; Grimshaw, Jeremy M; Darling, Elizabeth; Graham, Ian D; Harrold, JoAnn; Smith, Graeme N; Peterson, Wendy E; Reszel, Jessica; Lanes, Andrea; Walker, Mark C; Taljaard, Monica

    2018-06-01

    To assess the effect of the Maternal Newborn Dashboard on six key clinical performance indicators in the province of Ontario, Canada. Interrupted time series using population-based data from the provincial birth registry covering a 3-year period before implementation of the Dashboard and 2.5 years after implementation (November 2009 through March 2015). All hospitals in the province of Ontario providing maternal-newborn care (n=94). A hospital-based online audit and feedback programme. Rates of the six performance indicators included in the Dashboard. 2.5 years after implementation, the audit and feedback programme was associated with statistically significant absolute decreases in the rates of episiotomy (decrease of 1.5 per 100 women, 95% CI 0.64 to 2.39), induction for postdates in women who were less than 41 weeks at delivery (decrease of 11.7 per 100 women, 95% CI 7.4 to 16.0), repeat caesarean delivery in low-risk women performed before 39 weeks (decrease of 10.4 per 100 women, 95% CI 9.3 to 11.5) and an absolute increase in the rate of appropriately timed group B streptococcus screening (increase of 2.8 per 100, 95% CI 2.2 to 3.5). The audit and feedback programme did not significantly affect the rates of unsatisfactory newborn screening blood samples or formula supplementation at discharge. No statistically significant effects were observed for the two internal control outcomes or the four external control indicators-in fact, two external control indicators (episiotomy and postdates induction) worsened relative to before implementation. An electronic audit and feedback programme implemented in maternal-newborn hospitals was associated with clinically relevant practice improvements at the provincial level in the majority of targeted indicators. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

  6. The effect of the late 2000s financial crisis on suicides in Spain: an interrupted time-series analysis.

    Science.gov (United States)

    Lopez Bernal, James A; Gasparrini, Antonio; Artundo, Carlos M; McKee, Martin

    2013-10-01

    The current financial crisis is having a major impact on European economies, especially that of Spain. Past evidence suggests that adverse macro-economic conditions exacerbate mental illness, but evidence from the current crisis is limited. This study analyses the association between the financial crisis and suicide rates in Spain. An interrupted time-series analysis of national suicides data between 2005 and 2010 was used to establish whether there has been any deviation in the underlying trend in suicide rates associated with the financial crisis. Segmented regression with a seasonally adjusted quasi-Poisson model was used for the analysis. Stratified analyses were performed to establish whether the effect of the crisis on suicides varied by region, sex and age group. The mean monthly suicide rate in Spain during the study period was 0.61 per 100 000 with an underlying trend of a 0.3% decrease per month. We found an 8.0% increase in the suicide rate above this underlying trend since the financial crisis (95% CI: 1.009-1.156; P = 0.03); this was robust to sensitivity analysis. A control analysis showed no change in deaths from accidental falls associated with the crisis. Stratified analyses suggested that the association between the crisis and suicide rates is greatest in the Mediterranean and Northern areas, in males and amongst those of working age. The financial crisis in Spain has been associated with a relative increase in suicides. Males and those of working age may be at particular risk of suicide associated with the crisis and may benefit from targeted interventions.

  7. Time Series Analysis of Onchocerciasis Data from Mexico: A Trend towards Elimination

    Science.gov (United States)

    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

  8. Use of a Principal Components Analysis for the Generation of Daily Time Series.

    Science.gov (United States)

    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.

  9. Online Time Series Analysis of Land Products over Asia Monsoon Region via Giovanni

    Science.gov (United States)

    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.

  10. Behavioural interventions for urinary incontinence in community-dwelling seniors: an evidence-based analysis.

    Science.gov (United States)

    2008-01-01

    In early August 2007, the Medical Advisory Secretariat began work on the Aging in the Community project, an evidence-based review of the literature surrounding healthy aging in the community. The Health System Strategy Division at the Ministry of Health and Long-Term Care subsequently asked the secretariat to provide an evidentiary platform for the ministry's newly released Aging at Home Strategy.After a broad literature review and consultation with experts, the secretariat identified 4 key areas that strongly predict an elderly person's transition from independent community living to a long-term care home. Evidence-based analyses have been prepared for each of these 4 areas: falls and fall-related injuries, urinary incontinence, dementia, and social isolation. For the first area, falls and fall-related injuries, an economic model is described in a separate report.Please visit the Medical Advisory Secretariat Web site, http://www.health.gov.on.ca/english/providers/program/mas/mas_about.html, to review these titles within the Aging in the Community series.AGING IN THE COMMUNITY: Summary of Evidence-Based AnalysesPrevention of Falls and Fall-Related Injuries in Community-Dwelling Seniors: An Evidence-Based AnalysisBehavioural Interventions for Urinary Incontinence in Community-Dwelling Seniors: An Evidence-Based AnalysisCaregiver- and Patient-Directed Interventions for Dementia: An Evidence-Based AnalysisSocial Isolation in Community-Dwelling Seniors: An Evidence-Based AnalysisThe Falls/Fractures Economic Model in Ontario Residents Aged 65 Years and Over (FEMOR) OBJECTIVE: To assess the effectiveness of behavioural interventions for the treatment and management of urinary incontinence (UI) in community-dwelling seniors. TARGET POPULATION AND CONDITION Urinary incontinence defined as "the complaint of any involuntary leakage of urine" was identified as 1 of the key predictors in a senior's transition from independent community living to admission to a long-term care

  11. Impact of STROBE statement publication on quality of observational study reporting: interrupted time series versus before-after analysis.

    Directory of Open Access Journals (Sweden)

    Sylvie Bastuji-Garin

    Full Text Available In uncontrolled before-after studies, CONSORT was shown to improve the reporting of randomised trials. Before-after studies ignore underlying secular trends and may overestimate the impact of interventions. Our aim was to assess the impact of the 2007 STROBE statement publication on the quality of observational study reporting, using both uncontrolled before-after analyses and interrupted time series.For this quasi-experimental study, original articles reporting cohort, case-control, and cross-sectional studies published between 2004 and 2010 in the four dermatological journals having the highest 5-year impact factors (≥ 4 were selected. We compared the proportions of STROBE items (STROBE score adequately reported in each article during three periods, two pre STROBE period (2004-2005 and 2006-2007 and one post STROBE period (2008-2010. Segmented regression analysis of interrupted time series was also performed.Of the 456 included articles, 187 (41% reported cohort studies, 166 (36.4% cross-sectional studies, and 103 (22.6% case-control studies. The median STROBE score was 57% (range, 18%-98%. Before-after analysis evidenced significant STROBE score increases between the two pre-STROBE periods and between the earliest pre-STROBE period and the post-STROBE period (median score2004-05 48% versus median score2008-10 58%, p<0.001 but not between the immediate pre-STROBE period and the post-STROBE period (median score2006-07 58% versus median score2008-10 58%, p = 0.42. In the pre STROBE period, the six-monthly mean STROBE score increased significantly, by 1.19% per six-month period (absolute increase 95%CI, 0.26% to 2.11%, p = 0.016. By segmented analysis, no significant changes in STROBE score trends occurred (-0.40%; 95%CI, -2.20 to 1.41; p = 0.64 in the post STROBE statement publication.The quality of reports increased over time but was not affected by STROBE. Our findings raise concerns about the relevance of uncontrolled before

  12. Measuring Quality Improvement in Acute Ischemic Stroke Care: Interrupted Time Series Analysis of Door-to-Needle Time

    Directory of Open Access Journals (Sweden)

    Anne Margreet van Dishoeck

    2014-06-01

    Full Text Available Background: In patients with acute ischemic stroke, early treatment with recombinant tissue plasminogen activator (rtPA improves functional outcome by effectively reducing disability and dependency. Timely thrombolysis, within 1 h, is a vital aspect of acute stroke treatment, and is reflected in the widely used performance indicator ‘door-to-needle time' (DNT. DNT measures the time from the moment the patient enters the emergency department until he/she receives intravenous rtPA. The purpose of the study was to measure quality improvement from the first implementation of thrombolysis in stroke patients in a university hospital in the Netherlands. We further aimed to identify specific interventions that affect DNT. Methods: We included all patients with acute ischemic stroke consecutively admitted to a large university hospital in the Netherlands between January 2006 and December 2012, and focused on those treated with thrombolytic therapy on admission. Data were collected routinely for research purposes and internal quality measurement (the Erasmus Stroke Study. We used a retrospective interrupted time series design to study the trend in DNT, analyzed by means of segmented regression. Results: Between January 2006 and December 2012, 1,703 patients with ischemic stroke were admitted and 262 (17% were treated with rtPA. Patients treated with thrombolysis were on average 63 years old at the time of the stroke and 52% were male. Mean age (p = 0.58 and sex distribution (p = 0.98 did not change over the years. The proportion treated with thrombolysis increased from 5% in 2006 to 22% in 2012. In 2006, none of the patients were treated within 1 h. In 2012, this had increased to 81%. In a logistic regression analysis, this trend was significant (OR 1.6 per year, CI 1.4-1.8. The median DNT was reduced from 75 min in 2006 to 45 min in 2012 (p Conclusion and Implications: The DNT steadily improved from the first implementation of thrombolysis. Specific

  13. Series: Practical guidance to qualitative research. Part 3: Sampling, data collection and analysis.

    Science.gov (United States)

    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.

  14. 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.

  15. Combined use of correlation dimension and entropy as discriminating measures for time series analysis

    Science.gov (United States)

    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.

  16. 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)

  17. Visibility graph analysis of heart rate time series and bio-marker of congestive heart failure

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    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.

  19. Impact of pharmaceutical policy interventions on utilization of antipsychotic medicines in Finland and Portugal in times of economic recession: interrupted time series analyses.

    Science.gov (United States)

    Leopold, Christine; Zhang, Fang; Mantel-Teeuwisse, Aukje K; Vogler, Sabine; Valkova, Silvia; Ross-Degnan, Dennis; Wagner, Anita K

    2014-07-25

    To analyze the impacts of pharmaceutical sector policies implemented to contain country spending during the economic recession--a reference price system in Finland and a mix of policies including changes in reimbursement rates, a generic promotion campaign and discounts granted to the public payer in Portugal - on utilization of, as a proxy for access to, antipsychotic medicines. We obtained monthly IMS Health sales data in standard units of antipsychotic medicines in Portugal and Finland for the period January 2007 to December 2011. We used an interrupted time series design to estimate changes in overall use and generic market shares by comparing pre-policy and post-policy levels and trends. Both countries' policy approaches were associated with slight, likely unintended, decreases in overall use of antipsychotic medicines and with increases in generic market shares of major antipsychotic products. In Finland, quetiapine and risperidone generic market shares increased substantially (estimates one year post-policy compared to before, quetiapine: 6.80% [3.92%, 9.68%]; risperidone: 11.13% [6.79%, 15.48%]. The policy interventions in Portugal resulted in a substantially increased generic market share for amisulpride (estimate one year post-policy compared to before: 22.95% [21.01%, 24.90%]; generic risperidone already dominated the market prior to the policy interventions. Different policy approaches to contain pharmaceutical expenditures in times of the economic recession in Finland and Portugal had intended--increased use of generics--and likely unintended--slightly decreased overall sales, possibly consistent with decreased access to needed medicines--impacts. These findings highlight the importance of monitoring and evaluating the effects of pharmaceutical policy interventions on use of medicines and health outcomes.

  20. Investigation on Law and Economics Based on Complex Network and Time Series Analysis

    Science.gov (United States)

    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

  1. Modeling of human operator dynamics in simple manual control utilizing time series analysis. [tracking (position)

    Science.gov (United States)

    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.

  2. 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.

  3. 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...

  4. Time series modeling for analysis and control advanced autopilot and monitoring systems

    CERN Document Server

    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...

  5. Use of a prototype pulse oximeter for time series analysis of heart rate variability

    Science.gov (United States)

    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.

  6. Physical activity interventions differentially affect exercise task and barrier self-efficacy: A meta-analysis

    Science.gov (United States)

    Higgins, Torrance J.; Middleton, Kathryn R.; Winner, Larry; Janelle, Christopher M.; Middleton, Kathryn R.

    2014-01-01

    Objective Researchers have yet to establish how interventions to increase physical activity influence specific self-efficacy beliefs. The current study sought to quantify the effect of interventions to increase physical activity among healthy adults on exercise task (EXSE) and barrier self-efficacy (BSE) via meta-analysis. Intervention characteristics associated with self-efficacy and physical activity changes were also identified. Methods A systematic database search and manual searches through reference lists of related publications were conducted for articles on randomized, controlled physical activity interventions. Published intervention studies reporting changes in physical activity behavior and either EXSE or BSE in healthy adults were eligible for inclusion. Results Of the 1,080 studies identified, 20 were included in the meta-analyses. Interventions had a significant effect of g = 0.208, 95% confidence interval (CI) [0.027, 0.388], p physical activity. Moderator analyses indicated shorter interventions that did not include structured exercise sessions effectively increased EXSE and physical activity, whereas long interventions improved BSE. Interventions that did not provide support increased BSE and physical activity levels. Further, interventions that did not require the use of daily exercise logs improved EXSE and physical activity behavior. Conclusion Interventions designed to increase physical activity differentially influenced EXSE and BSE. EXSE appeared to play a more significant role during exercise adoption, whereas BSE was involved in the maintenance of exercise behavior. Recommendations are offered for the design of future interventions. PMID:23957904

  7. Short-term forecasting of meteorological time series using Nonparametric Functional Data Analysis (NPFDA)

    Science.gov (United States)

    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

  8. Methotrexate therapy for chronic noninfectious uveitis: analysis of a case series of 160 patients.

    Science.gov (United States)

    Samson, C M; Waheed, N; Baltatzis, S; Foster, C S

    2001-06-01

    To evaluate the outcomes of patients with chronic noninfectious uveitis unresponsive to conventional antiinflammatory therapy who were treated with methotrexate. Retrospective noncomparative interventional case series. All patients with chronic noninfectious uveitis treated with methotrexate at a single institution from 1985 to 1999. Charts of patients seen on the Ocular Immunology & Uveitis Service at the Massachusetts Eye & Ear Infirmary were reviewed. Patients with chronic uveitis of noninfectious origin treated with methotrexate were included in the study. Control of inflammation, steroid-sparing effect, visual acuity, adverse reactions. A total of 160 patients met the inclusion criteria. Control of inflammation was achieved in 76.2% of patients. Steroid-sparing effect was achieved in 56% of patients. Visual acuity was maintained or improved in 90% of patients. Side effects requiring discontinuation of medication occurred in 18% of patients. Potentially serious adverse reactions occurred in only 8.1% of patients. There was neither long-term morbidity nor mortality caused by methotrexate. Methotrexate is effective in the treatment of chronic noninfectious uveitis that fails to respond to conventional steroid treatment. It is an effective steroid-sparing immunomodulator, is a safe medication, and is well tolerated.

  9. A meta-analysis of cognitive intervention, parent management training, and psychopharmacological intervention in the treatment of conduct disorder

    OpenAIRE

    Anderson, David W.

    1996-01-01

    Conduct disorder in children and adolescents has developed into a very costly problem with severe negative consequences to individuals, families, and communities. A void exists in the literature in that no summaries have been found which compare the effectiveness of the leading treatment modalities for conduct disorder. The purpose of this study is to conduct a meta-analysis comparing three psychotherapeutic interventions for the treatment of conduct disorders in c...

  10. Analysis of the impact of alternative enterprise interventions on ...

    African Journals Online (AJOL)

    interventions of the REP have impacted rural livelihoods and poverty. The ... African Review of Economics and Finance | ISSN 2042-1478 | Volume 8 | Issue 2 ... with failures of governments' urban-biased public policies and ill-designed ... practices, focusing on agricultural production activities alone cannot engender.

  11. Meta-Analysis of Psychological Assessment as a Therapeutic Intervention

    Science.gov (United States)

    Poston, John M.; Hanson, William E.

    2010-01-01

    This study entails the use of meta-analytic techniques to calculate and analyze 18 independent and 52 nonindependent effect sizes across 17 published studies of psychological assessment as a therapeutic intervention. In this sample of studies, which involves 1,496 participants, a significant overall Cohen's d effect size of 0.423 (95% CI [0.321,…

  12. Using Brief Experimental Analysis to Intensify Tier 3 Reading Interventions

    Science.gov (United States)

    Coolong-Chaffin, Melissa; Wagner, Dana

    2015-01-01

    As implementation of multi-tiered systems of support becomes common practice across the nation, practitioners continue to need strategies for intensifying interventions and supports for the subset of students who fail to make adequate progress despite strong programs at Tiers 1 and 2. Experts recommend making several changes to the structure and…

  13. How can interventions increase motivation for physical activity? A systematic review and meta-analysis

    OpenAIRE

    Crutzen, Rik; Nurmi, Johanna; Beattie, Marguerite; Dombrowski, Stephan; Knittle, Keegan; Hankonen, Nelli

    2018-01-01

    Motivation is a proximal determinant of behavior in many psychological theories, and increasing motivation is central to most behavior change interventions. This systematic review and meta-analysis sought to fill a gap in the literature by identifying features of behavior change interventions associated with favorable changes in three prominent motivational constructs: intention, stage of change and autonomous motivation. A systematic literature search identified 88 intervention studies (N = ...

  14. Accuracy evaluation of Fourier series analysis and singular spectrum analysis for predicting the volume of motorcycle sales in Indonesia

    Science.gov (United States)

    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.

  15. Time Series Analysis of the Bacillus subtilis Sporulation Network Reveals Low Dimensional Chaotic Dynamics.

    Science.gov (United States)

    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

  16. HIV/STI prevention interventions: A systematic review and meta-analysis

    Directory of Open Access Journals (Sweden)

    Globerman Jason

    2017-12-01

    Full Text Available Behavioral interventions can prevent the transmission of HIV and sexually transmitted infections. This systematic review and meta-analysis assesses the effectiveness and quality of available evidence of HIV prevention interventions for people living with HIV in high-income settings. Searches were conducted in MEDLINE, EMBASE, PsycINFO, and CDC Compendium of Effective Interventions. Interventions published between January, 1998 and September, 2015 were included. Quality of evidence was assessed using the Grading of Recommendations Assessment, Development and Evaluation (GRADE. Forty-six articles and 63 datasets involving 14,096 individuals met inclusion criteria. Included articles were grouped by intervention type, comparison group and outcome. Few of these had high or moderate quality of evidence and statistically significant effects. One intervention type, group-level health education interventions, were effective in reducing HIV/STI incidence when compared to attention controls. A second intervention type, comprehensive risk counseling and services, was effective in reducing sexual risk behaviors when compared to both active and attention controls. All other intervention types showed no statistically significant effect or had low or very low quality of evidence. Given that the majority of interventions produced low or very low quality of evidence, researchers should commit to rigorous evaluation and high quality reporting of HIV intervention studies.

  17. Physical activity interventions differentially affect exercise task and barrier self-efficacy: a meta-analysis.

    Science.gov (United States)

    Higgins, Torrance J; Middleton, Kathryn R; Winner, Larry; Janelle, Christopher M

    2014-08-01

    Researchers have yet to establish how interventions to increase physical activity influence specific self-efficacy beliefs. The current study sought to quantify the effect of interventions to increase physical activity among healthy adults on exercise task (EXSE) and barrier self-efficacy (BSE) via meta-analysis. Intervention characteristics associated with self-efficacy and physical activity changes were also identified. A systematic database search and manual searches through reference lists of related publications were conducted for articles on randomized, controlled physical activity interventions. Published intervention studies reporting changes in physical activity behavior and either EXSE or BSE in healthy adults were eligible for inclusion. Of the 1,080 studies identified, 20 were included in the meta-analyses. Interventions had a significant effect of g = 0.208, 95% confidence interval (CI) [0.027, 0.388], p exercise sessions effectively increased EXSE and physical activity, whereas long interventions improved BSE. Interventions that did not provide support increased BSE and physical activity levels. Further, interventions that did not require the use of daily exercise logs improved EXSE and physical activity behavior. Interventions designed to increase physical activity differentially influenced EXSE and BSE. EXSE appeared to play a more significant role during exercise adoption, whereas BSE was involved in the maintenance of exercise behavior. Recommendations are offered for the design of future interventions.

  18. Analysis of time series for postal shipments in Regional VII East Java Indonesia

    Science.gov (United States)

    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.

  19. The Relationship between Logistics and Economic Development in Indonesia: Analysis of Time Series Data

    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.

  20. 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.

  1. Free vibration characteristics analysis of rectangular plate with rectangular opening based on Fourier series method

    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.

  2. Parametric time series analysis of geoelectrical signals: an application to earthquake forecasting in Southern Italy

    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.

  3. 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)

  4. 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.

  5. River catchment rainfall series analysis using additive Holt-Winters method

    Science.gov (United States)

    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.

  6. 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.

  7. 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

  8. Analysis of interventional therapy for progressing stage gastric cancer

    International Nuclear Information System (INIS)

    Zhu Mingde; Zhang Zijing; Ji Hongsheng; Ge Chenlin; Hao Gang; Wei Kongming; Yuan Yuhou; Zhao Xiuping

    2008-01-01

    Objective: To investigate the interventional therapy and its curative effect for progressing stage gastric cancer. Methods: two hundred and twelve patients with progressing stage gastric cancer were treated with arterial perfusion and arterial embolization. Gastric cardia cancer was treated through the left gastric artery and the left inferior phrenic artery or splenic artery. Cancers of lesser and greater gastric curvature was treated either through the left and right gastric arteries or common hepatic artery or through gastroduodenal artery, right gastroomental artery or splenic artery. Gastric antrum cancers were perfused through gastroduodenal artery or after the middle segmental embolization of right gastroomental artery. Results: One hundred and ninety three cases undergone interventional management were followed up. The CR + PR of gastric cardia cancer was 53.13%; gastric body cancer 44.44%; gastric antrum cancer 10%; recurrent cancer and remnant gastric cancer 0. There was no significant difference in outcome between gastric cardia cancer and gastric body cancer (P>0.05) but significant differences were shown both between gastric cardia cancer and gastric antrum cancer, and between gastric body cancer and gastric antrum cancer (P<0.05), with 1 year and 2 years survival rates of 81% and 56% respectively. Conclusion: The interventional therapeutic effect of progressing stage gastric cancers is different due to the different sites of the lesions in the gastric tissue. The curative effect of gastric cardia cancer and gastric body cancer is better than that of gastric antrum cancer, recurrent cancer and remnant gastric cancer. (authors)

  9. Game-based digital interventions for depression therapy: a systematic review and meta-analysis.

    Science.gov (United States)

    Li, Jinhui; Theng, Yin-Leng; Foo, Schubert

    2014-08-01

    The aim of this study was to review the existing literature on game-based digital interventions for depression systematically and examine their effectiveness through a meta-analysis of randomized controlled trials (RCTs). Database searching was conducted using specific search terms and inclusion criteria. A standard meta-analysis was also conducted of available RCT studies with a random effects model. The standard mean difference (Cohen's d) was used to calculate the effect size of each study. Nineteen studies were included in the review, and 10 RCTs (eight studies) were included in the meta-analysis. Four types of game interventions-psycho-education and training, virtual reality exposure therapy, exercising, and entertainment-were identified, with various types of support delivered and populations targeted. The meta-analysis revealed a moderate effect size of the game interventions for depression therapy at posttreatment (d=-0.47 [95% CI -0.69 to -0.24]). A subgroup analysis showed that interventions based on psycho-education and training had a smaller effect than those based on the other forms, and that self-help interventions yielded better outcomes than supported interventions. A higher effect was achieved when a waiting list was used as the control. The review and meta-analysis support the effectiveness of game-based digital interventions for depression. More large-scale, high-quality RCT studies with sufficient long-term data for treatment evaluation are needed.

  10. Selection and Evaluation of Media for Behavioral Health Interventions Employing Critical Media Analysis.

    Science.gov (United States)

    Wilson, Patrick A; Cherenack, Emily M; Jadwin-Cakmak, Laura; Harper, Gary W

    2018-01-01

    Although a growing number of psychosocial health promotion interventions use the critical analysis of media to facilitate behavior change, no specific guidelines exist to assist researchers and practitioners in the selection and evaluation of culturally relevant media stimuli for intervention development. Mobilizing Our Voices for Empowerment is a critical consciousness-based health enhancement intervention for HIV-positive Black young gay/bisexual men that employs the critical analysis of popular media. In the process of developing and testing this intervention, feedback on media stimuli was collected from youth advisory board members (n = 8), focus group participants (n = 19), intervention participants (n = 40), and intervention facilitators (n = 6). A thematic analysis of qualitative data resulted in the identification of four key attributes of media stimuli and participants' responses to media stimuli that are important to consider when selecting and evaluating media stimuli for use in behavioral health interventions employing the critical analysis of media: comprehension, relevance, emotionality, and action. These four attributes are defined and presented as a framework for evaluating media, and adaptable tools are provided based on this framework to guide researchers and practitioners in the selection and evaluation of media for similar interventions.

  11. Innovative Technology-Based Interventions for Autism Spectrum Disorders: A Meta-Analysis

    Science.gov (United States)

    Grynszpan, Ouriel; Weiss, Patrice L.; Perez-Diaz, Fernando; Gal, Eynat

    2014-01-01

    This article reports the results of a meta-analysis of technology-based intervention studies for children with autism spectrum disorders. We conducted a systematic review of research that used a pre-post design to assess innovative technology interventions, including computer programs, virtual reality, and robotics. The selected studies provided…

  12. Impact of a Family Empowerment Intervention on Delinquent Behavior: A Latent Growth Model Analysis.

    Science.gov (United States)

    Dembo, Richard; Schmeidler, James; Wothke, Werner

    2003-01-01

    Analysis indicated that reported frequency of involvement in delinquency declined more over time for families receiving Family Empowerment Intervention (FEI) as opposed to those receiving Extended Services Intervention (ESI). Results provide support for the impact of FEI services on reported frequency of delinquent behavior over a 36-month…

  13. Do Instructional Interventions Influence College Students' Critical Thinking Skills? A Meta-Analysis

    Science.gov (United States)

    Niu, Lian; Behar-Horenstein, Linda S.; Garvan, Cyndi W.

    2013-01-01

    Promoting students' critical thinking skills is an important task of higher education. Colleges and universities have designed various instructional interventions to enhance students' critical thinking skills. Empirical studies have yielded inconsistent results in terms of the effects of such interventions. This meta-analysis presents a synthesis…

  14. Effectiveness of E-self-help interventions for curbing adult problem drinking: A meta-analysis.

    NARCIS (Netherlands)

    Riper, H.; Spek, V.; Boon, B.; Conijn, B.; Kramer, J.; Martin-Abello, K.; Smit, H.F.E.

    2011-01-01

    Background: Self-help interventions without professional contact to curb adult problem drinking in the community are increasingly being delivered via the Internet. Objective: The objective of this meta-analysis was to assess the overall effectiveness of these eHealth interventions. Methods: In all,

  15. Identifying effective components of child maltreatment interventions: A meta-analysis

    NARCIS (Netherlands)

    van der Put, C.E.; Assink, M.; Gubbels, J.; Boekhout van Solinge, N.F.

    There is a lack of knowledge about specific components that make interventions effective in preventing or reducing child maltreatment. The aim of the present meta-analysis was to increase this knowledge by summarizing findings on effects of interventions for child maltreatment and by examining

  16. Functional Technology for Individuals with Intellectual Disabilities: Meta-Analysis of Mobile Device-Based Interventions

    Science.gov (United States)

    Kim, Jemma; Kimm, Christina H.

    2017-01-01

    This study employs a meta-analysis of single-subject design research to investigate the efficacy of mobile device-based interventions for individuals with intellectual disabilities (ID) and to further examine possible variables that may moderate the intervention outcomes. A total of 23 studies, 78 participants, and 140 observed cases that met the…

  17. 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)

  18. Analysis of rhythmic variance - ANORVA. A new simple method for detecting rhythms in biological time series

    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

  19. Possible signatures of dissipation from time-series analysis techniques using a turbulent laboratory magnetohydrodynamic plasma

    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.

  20. Singular spectrum analysis in nonlinear dynamics, with applications to paleoclimatic time series

    Science.gov (United States)

    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.

  1. Evaluating disease management program effectiveness: an introduction to time-series analysis.

    Science.gov (United States)

    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.

  2. 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.

  3. 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.

  4. Studies in astronomical time series analysis: Modeling random processes in the time domain

    Science.gov (United States)

    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.

  5. Fuzzy central tendency measure for time series variability analysis with application to fatigue electromyography signals.

    Science.gov (United States)

    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.

  6. Nonlinear Analysis on Cross-Correlation of Financial Time Series by Continuum Percolation System

    Science.gov (United States)

    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.

  7. 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.

  8. Time Series Analysis of the Microbiota of Children Suffering From Acute Infectious Diarrhea and Their Recovery After Treatment

    Directory of Open Access Journals (Sweden)

    Ener C. Dinleyici

    2018-06-01

    Full Text Available Gut microbiota is closely related to acute infectious diarrhea, one of the leading causes of mortality and morbidity in children worldwide. Understanding the dynamics of the recovery from this disease is of clinical interest. This work aims to correlate the dynamics of gut microbiota with the evolution of children who were suffering from acute infectious diarrhea caused by a rotavirus, and their recovery after the administration of a probiotic, Saccharomyces boulardii CNCM I-745. The experiment involved 10 children with acute infectious diarrhea caused by a rotavirus, and six healthy children, all aged between 3 and 4 years. The children who suffered the rotavirus infection received S. boulardii CNCM I-745 twice daily for the first 5 days of the experiment. Fecal samples were collected from each participant at 0, 3, 5, 10, and 30 days after probiotic administration. Microbial composition was characterized by 16S rRNA gene sequencing. Alpha and beta diversity were calculated, along with dynamical analysis based on Taylor's law to assess the temporal stability of the microbiota. All children infected with the rotavirus stopped having diarrhea at day 3 after the intervention. We observed low alpha diversities in the first 5 days (p-value < 0.05, Wilcoxon test, larger at 10 and 30 days after probiotic treatment. Canonical correspondence analysis (CCA showed differences in the gut microbiota of healthy children and of those who suffered from acute diarrhea in the first days (p-value < 0.05, ADONIS test, but not in the last days of the experiment. Temporal variability was larger in children infected with the rotavirus than in healthy ones. In particular, Gammaproteobacteria class was found to be abundant in children with acute diarrhea. We identified the microbiota transition from a diseased state to a healthy one with time, whose characterization may lead to relevant clinical data. This work highlights the importance of using time series for the

  9. Protective Effect of Dual-Strain Probiotics in Preterm Infants: A Multi-Center Time Series Analysis

    Science.gov (United States)

    Schwab, Frank; Garten, Lars; Geffers, Christine; Gastmeier, Petra; Piening, Brar

    2016-01-01

    Objective To determine the effect of dual-strain probiotics on the development of necrotizing enterocolitis (NEC), mortality and nosocomial bloodstream infections (BSI) in preterm infants in German neonatal intensive care units (NICUs). Design A multi-center interrupted time series analysis. Setting 44 German NICUs with routine use of dual-strain probiotics on neonatal ward level. Patients Preterm infants documented by NEO-KISS, the German surveillance system for nosocomial infections in preterm infants with birth weights below 1,500 g, between 2004 and 2014. Intervention Routine use of dual-strain probiotics containing Lactobacillus acidophilus and Bifidobacterium spp. (Infloran) on the neonatal ward level. Main outcome measures Incidences of NEC, overall mortality, mortality following NEC and nosocomial BSI. Results Data from 10,890 preterm infants in 44 neonatal wards was included in this study. Incidences of NEC and BSI were 2.5% (n = 274) and 15.0%, (n = 1631), respectively. Mortality rate was 6.1% (n = 665). The use of dual-strain probiotics significantly reduced the risk of NEC (HR = 0.48; 95% CI = 0.38–0.62), overall mortality (HR = 0.60, 95% CI = 0.44–0.83), mortality after NEC (HR = 0.51, 95% CI = 0.26–0.999) and nosocomial BSI (HR = 0.89, 95% CI = 0.81–0.98). These effects were even more pronounced in the subgroup analysis of preterm infants with birth weights below 1,000 g. Conclusion In order to reduce NEC and mortality in preterm infants, it is advisable to add routine prophylaxis with dual-strain probiotics to clinical practice in neonatal wards. PMID:27332554

  10. Cost-Effectiveness Analysis Comparing Pre-diagnosis Autism Spectrum Disorder (ASD)-Targeted Intervention with Ontario's Autism Intervention Program.

    Science.gov (United States)

    Penner, Melanie; Rayar, Meera; Bashir, Naazish; Roberts, S Wendy; Hancock-Howard, Rebecca L; Coyte, Peter C

    2015-09-01

    Novel management strategies for autism spectrum disorder (ASD) propose providing interventions before diagnosis. We performed a cost-effectiveness analysis comparing the costs and dependency-free life years (DFLYs) generated by pre-diagnosis intensive Early Start Denver Model (ESDM-I); pre-diagnosis parent-delivered ESDM (ESDM-PD); and the Ontario Status Quo (SQ). The analyses took government and societal perspectives to age 65. We assigned probabilities of Independent, Semi-dependent or Dependent living based on projected IQ. Costs per person (in Canadian dollars) were ascribed to each living setting. From a government perspective, the ESDM-PD produced an additional 0.17 DFLYs for $8600 less than SQ. From a societal perspective, the ESDM-I produced an additional 0.53 DFLYs for $45,000 less than SQ. Pre-diagnosis interventions targeting ASD symptoms warrant further investigation.

  11. Series: Practical guidance to qualitative research. Part 3: Sampling, data collection and analysis

    Science.gov (United States)

    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

  12. Endovascular Versus Open Surgical Intervention in Patients with Takayasu's Arteritis: A Meta-analysis.

    Science.gov (United States)

    Jung, Jae Hyun; Lee, Young Ho; Song, Gwan Gyu; Jeong, Han Saem; Kim, Jae-Hoon; Choi, Sung Jae

    2018-06-01

    Although medical treatment has advanced, surgical treatment is needed to control symptoms of Takayasu's arteritis (TA), such as angina, stroke, hypertension, or claudication. Endovascular or open surgical intervention is performed; however, there are few comparative studies on these methods. This meta-analysis and systematic review aimed to examine the outcome of surgical treatment of TA. A meta-analysis comparing outcomes of endovascular and open surgical intervention was performed using MEDLINE and Embase. This meta-analysis included only observational studies, and the evidence level was low to moderate. Data were pooled and analysed using a fixed or random effects model with the I 2 statistic. The included studies involved a total of 770 patients and 1363 lesions, with 389 patients treated endovascularly and 420 treated by surgical revascularization. Restenosis was more common with endovascular than open surgical intervention (odds ratio [OR] 5.18, 95% confidence interval [CI] 2.78-9.62; p open surgical intervention patients in the coronary artery, supra-aortic branches, and renal artery. In both the active and inactive stages, restenosis was more common in those treated endovascularly than in those treated by open surgery. However, stroke occurred less often with endovascular intervention than with open surgical intervention (OR 0.33, 95% CI 0.12-0.90; p = .003). Mortality and complications other than stroke and mortality did not differ between endovascular and open surgical intervention. This meta-analysis has shown a lower risk of restenosis with open surgical intervention than with endovascular intervention. Stroke was generally more common with open surgical intervention than with endovascular intervention. However, there were differences according to the location of the lesion, and the risk of stroke in open surgery is higher when the supra-aortic branches are involved rather than the renal arteries. Copyright © 2018 European Society for Vascular

  13. Fourier series analysis of a cylindrical pressure vessel subjected to axial end load and external pressure

    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

  14. Nonlinear Analysis of Time Series in Genome-Wide Linkage Disequilibrium Data

    Science.gov (United States)

    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.

  15. Improving prehospital trauma care in Rwanda through continuous quality improvement: an interrupted time series analysis.

    Science.gov (United States)

    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.

  16. HIV and dyadic intervention: an interdependence and communal coping analysis.

    Directory of Open Access Journals (Sweden)

    Catherine M Montgomery

    Full Text Available The most common form of HIV transmission in sub-Saharan Africa is heterosexual sex between two partners. While most HIV prevention interventions are aimed at the individual, there is mounting evidence of the feasibility, acceptability, and efficacy of dyadic interventions. However, the mechanisms through which dyadic-level interventions achieve success remain little explored. We address this gap by using Lewis et al's interdependence model of couple communal coping and behaviour change to analyse data from partners participating in an HIV prevention trial in Uganda and Zambia.We conducted a comparative qualitative study using in-depth interviews. Thirty-three interviews were conducted in total; ten with couples and twenty-three with staff members at the two sites. The Ugandan site recruited a sero-discordant couple cohort and the Zambian site recruited women alone. Spouses' transformation of motivation is strong where couples are recruited and both partners stand to gain considerably by participating in the research; it is weaker where this is not the case. As such, coping mechanisms differ in the two sites; among sero-discordant couples in Uganda, communal coping is evidenced through joint consent to participate, regular couple counselling and workshops, sharing of HIV test results, and strong spousal support for adherence and retention. By contrast, coping at the Zambian site is predominantly left to the individual woman and occurs against a backdrop of mutual mistrust and male disenfranchisement. We discuss these findings in light of practical and ethical considerations of recruiting couples to HIV research.We argue for the need to consider the broader context within which behaviour change occurs and propose that future dyadic research be situated within the framework of the 'risk environment'.

  17. Characterization of Ground Displacement Sources from Variational Bayesian Independent Component Analysis of Space Geodetic Time Series

    Science.gov (United States)

    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

  18. Intervention of hydrogen analysis laboratory for radioactive materials study

    International Nuclear Information System (INIS)

    Bruno, N.; Vinces, H.; Figueroa, S.

    1996-01-01

    The objective of the practice was the measurement of the hydrogen concentration on structural material from the Central Nuclear Atucha I (CNA-I) cooling channels using a LECO gas analyser. Original samples were previously separated into fractions at the Laboratiorio para Ensayos de Post-Irradiacion (LAPEP), Centro Atomico Ezeiza. The practice and the preliminary conditions of the laboratory and equipment to reduce the occupational dose for personnel and the work area contamination are described in this paper. In addition to the training activity for workers, the radiological control performed during the intervention and procedure followed to decontaminate LECO and the laboratory are summarized here. (authors)

  19. Statistical performance and information content of time lag analysis and redundancy analysis in time series modeling.

    Science.gov (United States)

    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.

  20. Time Series Analysis OF SAR Image Fractal Maps: The Somma-Vesuvio Volcanic Complex Case Study

    Science.gov (United States)

    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

  1. Examination of an antecedent communication intervention to reduce tangibly maintained challenging behavior: A controlled analog analysis

    NARCIS (Netherlands)

    O'Reilly, M.F.; Fragale, C.; Gainey, S.; Kang, S.Y.; Koch, H.; Shubert, J.; El Zein, F.; Longino, D.; Chung, M.; Xu, Z.W.; White, P.J.; Lang, R.B.; Davis, T.; Rispoli, M.; Lancioni, G.E.; Didden, H.C.M.; Healy, O.; Kagohara, D.; Meer, L. van der; Sigafoos, J.

    2012-01-01

    We examined the influence of an antecedent communication intervention on challenging behavior for three students with developmental disorders. Students were taught to request tangible items that were identified as reinforcers for challenging behavior in a prior functional analysis. individual

  2. Health coaching interventions for persons with chronic conditions: a systematic review and meta-analysis protocol.

    Science.gov (United States)

    Boehmer, Kasey R; Barakat, Suzette; Ahn, Sangwoo; Prokop, Larry J; Erwin, Patricia J; Murad, M Hassan

    2016-09-01

    Chronic conditions are increasingly more common and negatively impact quality of life, disability, morbidity, and mortality. Health coaching has emerged as a possible intervention to help individuals with chronic conditions adopt health supportive behaviors that improve both quality of life and health outcomes. We planned a systematic review and meta-analysis of the contemporary health coaching literature published in the last decade to evaluate the effect of health coaching on clinically important, disease-specific, functional, and behavioral outcomes. We will include randomized controlled trials or quasi-experimental studies that compared health coaching to alternative interventions or usual care. To enable adoption of effective interventions, we aim to explore how the effect of intervention is modified by the intervention components, delivering personnel (i.e., health professionals vs trained lay or peer persons), dose, frequency, and setting. Analysis of intervention outcomes will be reported and classified using an existing theoretical framework, the Theory of Patient Capacity, to identify the areas of patients' capacity to access and use healthcare and enact self-care where coaching may be an effective intervention. This systematic review and meta-analysis will identify and synthesize evidence to inform the practice of health coaching by providing evidence on components and characteristics of the intervention essential for success in individuals with chronic health conditions. PROSPERO CRD42016039730.

  3. Interrupted Time Series Versus Statistical Process Control in Quality Improvement Projects.

    Science.gov (United States)

    Andersson Hagiwara, Magnus; Andersson Gäre, Boel; Elg, Mattias

    2016-01-01

    To measure the effect of quality improvement interventions, it is appropriate to use analysis methods that measure data over time. Examples of such methods include statistical process control analysis and interrupted time series with segmented regression analysis. This article compares the use of statistical process control analysis and interrupted time series with segmented regression analysis for evaluating the longitudinal effects of quality improvement interventions, using an example study on an evaluation of a computerized decision support system.

  4. Options for the deduction of target and intervention values for radon precursors of the 238U- and 232Th-series in soils

    International Nuclear Information System (INIS)

    Stoop, P.; Lembrechts, J.

    1993-04-01

    Radiation protection policy in the Netherlands applies to human activities in which ionizing radiation presents a hazard, not to naturally occurring sources of radiation. The risk levels (maximum permissible risk and negligible risk) apply to sources of radiation that cause an additional risk. Translation of these levels into practical environmental quality objectives therefore implies that both the extent and the origin of the risk are determined. The distinction between the natural and the additional radiation dose is of particular interest. In this report various possibilities are described for measuring, explaining and predicting the naturally occurring concentrations of the precursors of the element radon in the two radioactive decay series starting with 238 U and 232 Th. Several methods are given that may be used to derive environmental quality objectives for the soil with respect to these radionuclides. These environmental quality objectives are an important basis for among other things the soil sanitation policy. The nature of the radionuclides considered may have consequences for the choice of sanitation techniques. Because possible sources and cases of soil pollution may have important consequences for the Dutch policy on soil sanitation, a short overview is given of data published on these subjects. The foundation and the control of intervention levels requires insight in the relative importance of pollution pathways. As a result, pathways have been given ample attention. 9 figs., 17 tabs., 66 refs

  5. Evaluation of Internet-Based Interventions on Waist Circumference Reduction: A Meta-Analysis.

    Science.gov (United States)

    Seo, Dong-Chul; Niu, Jingjing

    2015-07-21

    Internet-based interventions are more cost-effective than conventional interventions and can provide immediate, easy-to-access, and individually tailored support for behavior change. Waist circumference is a strong predictor of an increased risk for a host of diseases, such as hypertension, diabetes, and dyslipidemia, independent of body mass index. To date, no study has examined the effect of Internet-based lifestyle interventions on waist circumference change. This study aimed to systematically review the effect of Internet-based interventions on waist circumference change among adults. This meta-analysis reviewed randomized controlled trials (N=31 trials and 8442 participants) that used the Internet as a main intervention approach and reported changes in waist circumference. Internet-based interventions showed a significant reduction in waist circumference (mean change -2.99 cm, 95% CI -3.68 to -2.30, I(2)=93.3%) and significantly better effects on waist circumference loss (mean loss 2.38 cm, 95% CI 1.61-3.25, I(2)=97.2%) than minimal interventions such as information-only groups. Meta-regression results showed that baseline waist circumference, gender, and the presence of social support in the intervention were significantly associated with waist circumference reduction. Internet-based interventions have a significant and promising effect on waist circumference change. Incorporating social support into an Internet-based intervention appears to be useful in reducing waist circumference. Considerable heterogeneity exists among the effects of Internet-based interventions. The design of an intervention may have a significant impact on the effectiveness of the intervention.

  6. Thankful for the little things: A meta-analysis of gratitude interventions.

    Science.gov (United States)

    Davis, Don E; Choe, Elise; Meyers, Joel; Wade, Nathaniel; Varjas, Kristen; Gifford, Allison; Quinn, Amy; Hook, Joshua N; Van Tongeren, Daryl R; Griffin, Brandon J; Worthington, Everett L

    2016-01-01

    A recent qualitative review by Wood, Froh, and Geraghty (2010) cast doubt on the efficacy of gratitude interventions, suggesting the need to carefully attend to the quality of comparison groups. Accordingly, in a series of meta-analyses, we evaluate the efficacy of gratitude interventions (ks = 4-18; Ns = 395-1,755) relative to a measurement-only control or an alternative-activity condition across 3 outcomes (i.e., gratitude, anxiety, psychological well-being). Gratitude interventions outperformed a measurement-only control on measures of psychological well-being (d = .31, 95% confidence interval [CI = .04, .58]; k = 5) but not gratitude (d = .20; 95% CI [-.04, .44]; k = 4). Gratitude interventions outperformed an alternative-activity condition on measures of gratitude (d = .46, 95% CI [.27, .64]; k = 15) and psychological well-being (d = .17, 95% CI [.09, .24]; k = 20) but not anxiety (d = .11, 95% CI [-.08, .31]; k = 5). More-detailed subdivision was possible on studies with outcomes assessing psychological well-being. Among these, gratitude interventions outperformed an activity-matched comparison (d = .14; 95% CI [.01, .27]; k = 18). Gratitude interventions performed as well as, but not better than, a psychologically active comparison (d = -.03, 95% CI [-.13, .07]; k = 9). On the basis of these findings, we summarize the current state of the literature and make suggestions for future applied research on gratitude. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

  7. Analysis of Seasonal Signal in GPS Short-Baseline Time Series

    Science.gov (United States)

    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

  8. Therapeutic intervention for internalized stigma of severe mental illness: A systematic review and meta-analysis.

    Science.gov (United States)

    Tsang, Hector W H; Ching, S C; Tang, K H; Lam, H T; Law, Peggy Y Y; Wan, C N

    2016-05-01

    Internalized stigma can lead to pervasive negative effects among people with severe mental illness (SMI). Although prevalence of internalized stigma is high, there is a dearth of interventions and meanwhile a lack of evidence as to their effectiveness. This study aims at unraveling the existence of different therapeutic interventions and the effectiveness internalized stigma reduction in people with SMI via a systematic review and meta-analysis. Five electronic databases were searched. Studies were included if they (1) involved community or hospital based interventions on internalized stigma, (2) included participants who were given a diagnosis of SMI>50%, and (3) were empirical and quantitative in nature. Fourteen articles were selected for extensive review and five for meta-analysis. Nine studies showed significant decrease in internalized stigma and two showed sustainable effects. Meta-analysis showed that there was a small to moderate significant effect in therapeutic interventions (SMD=-0.43; p=0.003). Among the intervention elements, four studies suggested a favorable effect of psychoeducation. Meta-analysis showed that there was small to moderate significant effect (SMD=-0.40; p=0.001). Most internalized stigma reduction programs appear to be effective. This systematic review cannot make any recommendation on which intervention is more effective although psychoeducation seems most promising. More Randomized Controlled Trials (RCT) on particular intervention components using standard outcome measures are recommended in future studies. Copyright © 2016. Published by Elsevier B.V.

  9. DynPeak: An Algorithm for Pulse Detection and Frequency Analysis in Hormonal Time Series

    Science.gov (United States)

    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

  10. A knowledge translation tool improved osteoporosis disease management in primary care: an interrupted time series analysis.

    Science.gov (United States)

    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.

  11. Hybrid analysis for indicating patients with breast cancer using temperature time series.

    Science.gov (United States)

    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

  12. Principal component analysis of MSBAS DInSAR time series from Campi Flegrei, Italy

    Science.gov (United States)

    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.

  13. Assessment of land degradation using time series trend analysis of vegetation indictors in Otindag Sandy land

    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

  14. Testing Homeopathy in Mouse Emotional Response Models: Pooled Data Analysis of Two Series of Studies

    Directory of Open Access Journals (Sweden)

    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.

  15. 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

  16. Variability of African Farming Systems from Phenological Analysis of NDVI Time Series

    Science.gov (United States)

    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.

  17. 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

  18. Statistical Analysis of fMRI Time-Series: A Critical Review of the GLM Approach

    Directory of Open Access Journals (Sweden)

    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.

  19. A Time Series Analysis Using R for Understanding Car Sales On The Romanian Market

    Directory of Open Access Journals (Sweden)

    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.

  20. Segmented regression analysis of interrupted time series data to assess outcomes of a South American road traffic alcohol policy change.

    Science.gov (United States)

    Nistal-Nuño, Beatriz

    2017-09-01

    In Chile, a new law introduced in March 2012 decreased the legal blood alcohol concentration (BAC) limit for driving while impaired from 1 to 0.8 g/l and the legal BAC limit for driving under the influence of alcohol from 0.5 to 0.3 g/l. The goal is to assess the impact of this new law on mortality and morbidity outcomes in Chile. A review of national databases in Chile was conducted from January 2003 to December 2014. Segmented regression analysis of interrupted time series was used for analyzing the data. In a series of multivariable linear regression models, the change in intercept and slope in the monthly incidence rate of traffic deaths and injuries and association with alcohol per 100,000 inhabitants was estimated from pre-intervention to postintervention, while controlling for secular changes. In nested regression models, potential confounding seasonal effects were accounted for. All analyses were performed at a two-sided significance level of 0.05. Immediate level drops in all the monthly rates were observed after the law from the end of the prelaw period in the majority of models and in all the de-seasonalized models, although statistical significance was reached only in the model for injures related to alcohol. After the law, the estimated monthly rate dropped abruptly by -0.869 for injuries related to alcohol and by -0.859 adjusting for seasonality (P < 0.001). Regarding the postlaw long-term trends, it was evidenced a steeper decreasing trend after the law in the models for deaths related to alcohol, although these differences were not statistically significant. A strong evidence of a reduction in traffic injuries related to alcohol was found following the law in Chile. Although insufficient evidence was found of a statistically significant effect for the beneficial effects seen on deaths and overall injuries, potential clinically important effects cannot be ruled out. Copyright © 2017 The Royal Society for Public Health. Published by Elsevier Ltd

  1. Error perspective and consequences evaluation of the professional intervention in physical education: a content analysis

    Directory of Open Access Journals (Sweden)

    Jeane Barcelos Soriano

    2007-12-01

    and generate an increasing search for better professional education and responsibility for tasks specifi c to the area, as well as a concern with the ethical factors of professional intervention in physical education. The purpose of this study was to understand how physical education professionals describe and interpret the consequences of their professional intervention, based on the error perspective. Information was obtained by means of a semi-structure interview, conducted with 11 professionals who were not part of the school system, and who had 7 – 25 years of professional education. The data treatment followed the characteristics of the content analysis, establishing later the analysis categories, namely: 1 Academic Education and Professional Identity, which includes the characteristics and circumstances of professional education, identity and culture and 2 Professional intervention and Accreditation, which includes aspects connected to professional legitimacy and the accreditation process. This study allowed us to consider that, while Physical Education professionals are concerned with the quality of the services offered in the area, they do not clearly defi ne what constitutes a professional error in the area, and neither do they evaluate the consequences of their professional intervention based on this perspective.

  2. case series

    African Journals Online (AJOL)

    Administrator

    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 ...

  3. Efficacy of computer technology-based HIV prevention interventions: a meta-analysis.

    Science.gov (United States)

    Noar, Seth M; Black, Hulda G; Pierce, Larson B

    2009-01-02

    To conduct a meta-analysis of computer technology-based HIV prevention behavioral interventions aimed at increasing condom use among a variety of at-risk populations. Systematic review and meta-analysis of existing published and unpublished studies testing computer-based interventions. Meta-analytic techniques were used to compute and aggregate effect sizes for 12 randomized controlled trials that met inclusion criteria. Variables that had the potential to moderate intervention efficacy were also tested. The overall mean weighted effect size for condom use was d = 0.259 (95% confidence interval = 0.201, 0.317; Z = 8.74, P partners, and incident sexually transmitted diseases. In addition, interventions were significantly more efficacious when they were directed at men or women (versus mixed sex groups), utilized individualized tailoring, used a Stages of Change model, and had more intervention sessions. Computer technology-based HIV prevention interventions have similar efficacy to more traditional human-delivered interventions. Given their low cost to deliver, ability to customize intervention content, and flexible dissemination channels, they hold much promise for the future of HIV prevention.

  4. Comparative Cost Analysis of Four Interventions to Prevent HIV Transmission in Bandung, Indonesia

    Directory of Open Access Journals (Sweden)

    Eveline J.M. Verstraaten

    2017-11-01

    Full Text Available Background: the costs of HIV/AIDS interventions in Indonesia are largely unknown. Knowing these costs is an important input for policy makers in the decision-making of setting priorities among HIV/AIDS interventions. The aim of this analysis is to determine the costs of four HIV/AIDS interventions in Bandung, Indonesia in 2015, to inform the local AIDS commission. Methods: data on utilization and costs of the different interventions were collected in a sexual transmitted infections (STI-clinic and the KPA, the local HIV/AIDS commission, for the period of January 2015-December 2015. The costs were estimated from a societal perspective, using a micro-costing approach. Results: the total annualized costs for condom distribution, mobile voluntary counselling and testing (VCT, religious based information, communication, and education (IEC and STI services equalled US$56,926, US$2,985, US$1,963 and US$5,865, respectively. Conclusion: this analysis has provided cost estimates of four different HIV/AIDS interventions in Bandung, Indonesia. Additionally, it has estimated the costs of scaling up these interventions. Together, this provides important information for policy makers vis-à-vis the implementation of these interventions. However, an evaluation of the effectiveness of these interventions is needed to estimate the cost-effectiveness.

  5. Qualitative analysis of an educational intervention with HIV-discordant heterosexual Latino couples.

    Science.gov (United States)

    Pérez-Jiménez, David; Orengo-Aguayo, Rosaura E

    2011-12-01

    This qualitative analysis elucidates the potential elements of the intervention that may be effective in terms of a) increasing knowledge about HIV/ AIDS in the members of this population; b) increasing the use of male condoms and the practice of mutual masturbation; and c) changing opinions toward male condom use and mutual masturbation. Five heterosexual HIV-discordant couples participated in the adapted intervention, which consisted of four three-hour-long sessions. One month after the intervention, we conducted a qualitative semi-structured interview with every participant to evaluate issues related to the process and content of the activities comprising the intervention, the impact of the intervention, logistics, and recruitment and retention as well as to make a more general evaluation. The information was submitted to qualitative content analysis. After the intervention, participants reported having better attitudes regarding safer sex, particularly in terms of condom use. A reason given by the participants to feel more positive toward condom use and mutual masturbation was that these practices could prevent the infection of the HIV-negative partner. This study provides important evidence of an intervention that promises to be efficacious in preventing some high-risk sexual behaviors among Latino HIV-discordant heterosexual couples. The evidence presented seems to suggest that an intervention that includes basic relevant information about HIV/AIDS, that explains the benefits of condom use and other safer sex options, and that provides effective negotiation and communication strategies could significantly reduce HIV transmission among these couples.

  6. Impact of diurnal temperature range on mortality in a high plateau area in southwest China: A time series analysis.

    Science.gov (United States)

    Ding, Zan; Guo, Pi; Xie, Fang; Chu, Huifang; Li, Kun; Pu, Jingbo; Pang, Shaojie; Dong, Hongli; Liu, Yahui; Pi, Fuhua; Zhang, Qingying

    2015-09-01

    Diurnal temperature range (DTR) is an important meteorological indicator that reflects weather stability and is associated with global climate change and urbanization. Previous studies have explored the effect of DTR on human health in coastal cities with small daily temperature variations, but we have little evidence for high plateau regions where large DTRs usually occur. Using daily mortality data (2007-2013), we conducted a time-series analysis to assess the effect of DTR on daily mortality in Yuxi, a high plateau city in southwest China. Poisson regression with distributed lag non-linear model was used to estimate DTR effects on daily mortality, controlling for daily mean temperature, relative humidity, sunshine duration, wind speed, atmospheric pressure, day of the week, and seasonal and long-term trends. The cumulative effects of DTR were J-shaped curves for non-accidental, cardiorespiratory and cardiovascular mortality, with a U-shaped curve for respiratory mortality. Risk assessments showed strong monotonic increases in mortality starting at a DTR of approximately 16 °C. The relative risk of non-accidental morality with extreme high DTR at lag 0 and 0-21 days was 1.03 (95% confidence interval: 0.95-1.11) and 1.33 (0.94-1.89), respectively. The risk of mortality with extreme high DTR was greater for males and age <75 years than females and age ≥75 years. The effect of DTR on mortality was non-linear, with high DTR associated with increased mortality. A DTR of 16 °C may be a cut-off point for mortality prognosis and has implications for developing intervention strategies to address high DTR exposure. Copyright © 2015 Elsevier B.V. All rights reserved.

  7. Trend analysis using non-stationary time series clustering based on the finite element method

    OpenAIRE

    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 ...

  8. Statistical analysis of yearly series of maximum daily rainfall in Spain. Analisis estadistico de las series anuales de maximas lluvias diarias en Espaa

    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.

  9. Systematic review and meta-analysis of music interventions in hypertension treatment: a quest for answers.

    Science.gov (United States)

    Kühlmann, Anne Y R; Etnel, Jonathan R G; Roos-Hesselink, Jolien W; Jeekel, Johannes; Bogers, Ad J J C; Takkenberg, Johanna J M

    2016-04-19

    Adverse effects, treatment resistance and high costs associated with pharmacological treatment of hypertension have led to growing interest in non-pharmacological complementary therapies such as music interventions. This meta-analysis aims to provide an overview of reported evidence on the efficacy of music interventions in the treatment of hypertension. A systematic literature search was conducted for publications on the effect of music interventions on blood pressure in adult hypertensive subjects published between January 1990-June 2014. Randomized controlled trials with a follow-up duration ≥28 days were included. Blood pressure measures were pooled using inverse variance weighting. Of the 1689 abstracts reviewed, 10 randomized controlled trials were included. Random-effects pooling of the music intervention groups showed a trend toward a decrease in mean systolic blood pressure (SBP) from 144 mmHg(95 % CI:137-152) to 134 mmHg(95 % CI:124-144), and in mean diastolic blood pressure (DBP) from 84 mmHg(95 % CI:78-89) to 78 mmHg(95 % CI:73-84). Fixed-effect analysis of a subgroup of 3 trials with valid control groups showed a significant decrease in pooled mean SBP and DBP in both intervention and control groups. A comparison between music intervention groups and control groups was not possible due to unavailable measures of dispersion. This systematic review and meta-analysis revealed a trend towards a decrease in blood pressure in hypertensive patients who received music interventions, but failed to establish a cause-effect relationship between music interventions and blood pressure reduction. Considering the potential value of this safe, low-cost intervention, well-designed, high quality and sufficiently powered randomized studies assessing the efficacy of music interventions in the treatment of hypertension are warranted.

  10. Interventions to reduce stress in university students: a review and meta-analysis.

    Science.gov (United States)

    Regehr, Cheryl; Glancy, Dylan; Pitts, Annabel

    2013-05-15

    Recent research has revealed concerning rates of anxiety and depression among university students. Nevertheless, only a small percentage of these students receive treatment from university health services. Universities are thus challenged with instituting preventative programs that address student stress and reduce resultant anxiety and depression. A systematic review of the literature and meta-analysis was conducted to examine the effectiveness of interventions aimed at reducing stress in university students. Studies were eligible for inclusion if the assignment of study participants to experimental or control groups was by random allocation or parallel cohort design. Retrieved studies represented a variety of intervention approaches with students in a broad range of programs and disciplines. Twenty-four studies, involving 1431 students were included in the meta-analysis. Cognitive, behavioral and mindfulness interventions were associated with decreased symptoms of anxiety. Secondary outcomes included lower levels of depression and cortisol. Included studies were limited to those published in peer reviewed journals. These studies over-represent interventions with female students in Western countries. Studies on some types of interventions such as psycho-educational and arts based interventions did not have sufficient data for inclusion in the meta-analysis. This review provides evidence that cognitive, behavioral, and mindfulness interventions are effective in reducing stress in university students. Universities are encouraged to make such programs widely available to students. In addition however, future work should focus on developing stress reduction programs that attract male students and address their needs. Copyright © 2012 Elsevier B.V. All rights reserved.

  11. The investigation of Martian dune fields using very high resolution photogrammetric measurements and time series analysis

    Science.gov (United States)

    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

  12. [Time-series analysis on effect of air pollution on stroke mortality in Tianjin, China].

    Science.gov (United States)

    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.

  13. 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.

  14. A cost-effectiveness threshold analysis of a multidisciplinary structured educational intervention in pediatric asthma.

    Science.gov (United States)

    Rodriguez-Martinez, Carlos E; Sossa-Briceño, Monica P; Castro-Rodriguez, Jose A

    2018-05-01

    Asthma educational interventions have been shown to improve several clinically and economically important outcomes. However, these interventions are costly in themselves and could lead to even higher disease costs. A cost-effectiveness threshold analysis would be helpful in determining the threshold value of the cost of educational interventions, leading to these interventions being cost-effective. The aim of the present study was to perform a cost-effectiveness threshold analysis to determine the level at which the cost of a pediatric asthma educational intervention would be cost-effective and cost-saving. A Markov-type model was developed in order to estimate costs and health outcomes of a simulated cohort of pediatric patients with persistent asthma treated over a 12-month period. Effectiveness parameters were obtained from a single uncontrolled before-and-after study performed with Colombian asthmatic children. Cost data were obtained from official databases provided by the Colombian Ministry of Health. The main outcome was the variable "quality-adjusted life-years" (QALYs). A deterministic threshold sensitivity analysis showed that the asthma educational intervention will be cost-saving to the health system if its cost is under US$513.20. Additionally, the analysis showed that the cost of the intervention would have to be below US$967.40 in order to be cost-effective. This study identified the level at which the cost of a pediatric asthma educational intervention will be cost-effective and cost-saving for the health system in Colombia. Our findings could be a useful aid for decision makers in efficiently allocating limited resources when planning asthma educational interventions for pediatric patients.

  15. Trend analysis using non-stationary time series clustering based on the finite element method

    Science.gov (United States)

    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.

  16. Risk assessment of environmentally influenced airway diseases based on time-series analysis.

    Science.gov (United States)

    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)

  17. Tetrodotoxin poisoning caused by Goby fish consumption in southeast China: a retrospective case series analysis

    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.

  18. On the limits of probabilistic forecasting in nonlinear time series analysis II: Differential entropy.

    Science.gov (United States)

    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.

  19. A Long-Term Prediction Model of Beijing Haze Episodes Using Time Series Analysis

    Directory of Open Access Journals (Sweden)

    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.

  20. 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.

  1. Mental health impacts of flooding: a controlled interrupted time series analysis of prescribing data in England.

    Science.gov (United States)

    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.

  2. 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.

  3. 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.

  4. Forecasting Container Throughput at the Doraleh Port in Djibouti through Time Series Analysis

    Science.gov (United States)

    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.

  5. 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

  6. 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.

  7. 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.

  8. Time series analysis of the developed financial markets' integration using visibility graphs

    Science.gov (United States)

    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.

  9. A Cost-Effectiveness Analysis of Early Literacy Interventions

    Science.gov (United States)

    Simon, Jessica

    2011-01-01

    Success in early literacy activities is associated with improved educational outcomes, including reduced dropout risk, in-grade retention, and special education referrals. When considering programs that will work for a particular school and context; cost-effectiveness analysis may provide useful information for decision makers. The study…

  10. Advancing School-Based Interventions through Economic Analysis

    Science.gov (United States)

    Olsson, Tina M.; Ferrer-Wreder, Laura; Eninger, Lilianne

    2014-01-01

    Commentators interested in school-based prevention programs point to the importance of economic issues for the future of prevention efforts. Many of the processes and aims of prevention science are dependent upon prevention resources. Although economic analysis is an essential tool for assessing resource use, the attention given economic analysis…

  11. Using qualitative comparative analysis in a systematic review of a complex intervention.

    Science.gov (United States)

    Kahwati, Leila; Jacobs, Sara; Kane, Heather; Lewis, Megan; Viswanathan, Meera; Golin, Carol E

    2016-05-04

    Systematic reviews evaluating complex interventions often encounter substantial clinical heterogeneity in intervention components and implementation features making synthesis challenging. Qualitative comparative analysis (QCA) is a non-probabilistic method that uses mathematical set theory to study complex phenomena; it has been proposed as a potential method to complement traditional evidence synthesis in reviews of complex interventions to identify key intervention components or implementation features that might explain effectiveness or ineffectiveness. The objective of this study was to describe our approach in detail and examine the suitability of using QCA within the context of a systematic review. We used data from a completed systematic review of behavioral interventions to improve medication adherence to conduct two substantive analyses using QCA. The first analysis sought to identify combinations of nine behavior change techniques/components (BCTs) found among effective interventions, and the second analysis sought to identify combinations of five implementation features (e.g., agent, target, mode, time span, exposure) found among effective interventions. For each substantive analysis, we reframed the review's research questions to be designed for use with QCA, calibrated sets (i.e., transformed raw data into data used in analysis), and identified the necessary and/or sufficient combinations of BCTs and implementation features found in effective interventions. Our application of QCA for each substantive analysis is described in detail. We extended the original review findings by identifying seven combinations of BCTs and four combinations of implementation features that were sufficient for improving adherence. We found reasonable alignment between several systematic review steps and processes used in QCA except that typical approaches to study abstraction for some intervention components and features did not support a robust calibration for QCA. QCA was

  12. Healthcare provider-led interventions to support medication adherence following ACS: a meta-analysis.

    Science.gov (United States)

    Crawshaw, Jacob; Auyeung, Vivian; Ashworth, Lucy; Norton, Sam; Weinman, John

    2017-01-01

    We conducted a systematic review and meta-analysis to determine the effectiveness of healthcare provider-led (HCPs) interventions to support medication adherence in patients with acute coronary syndrome (ACS). A systematic search of Cochrane Library, Medline, EMBASE, PsycINFO, Web of Science, IPA, CINAHL, ASSIA, OpenGrey, EthOS, WorldCat and PQDT was undertaken. Interventions were deemed eligible if they included adult ACS patients, were HCP-led, measured medication adherence and randomised participants to parallel groups. Intervention content was coded using the Behaviour Change Technique (BCT) Taxonomy and data were pooled for analysis using random-effects models. Our search identified 8870 records, of which 27 were eligible (23 primary studies). A meta-analysis (n=9735) revealed HCP-led interventions increased the odds of medication adherence by 54% compared to control interventions (k=23, OR 1.54, 95% CI 1.26 to 1.88, I 2 =57.5%). After removing outliers, there was a 41% increase in the odds of medication adherence with moderate heterogeneity (k=21, OR 1.41, 95% CI 1.21 to 1.65, I 2 =35.3%). Interventions that included phone contact yielded (k=12, OR 1.63, 95% CI 1.25 to 2.12, I 2 =32.0%) a larger effect compared to those delivered exclusively in person. A total of 32/93 BCTs were identified across interventions (mean=4.7, SD=2.2) with 'information about health consequences' (BCT 5.1) (19/23) the most common. HCP-led interventions for ACS patients appear to have a small positive impact on medication adherence. While we were able to identify BCTs among interventions, data were insufficient to determine the impact of particular BCTs on study effectiveness. CRD42016037706.

  13. 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

  14. 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.

  15. The Critical Analysis of the Intervention Basis and Evolution in Agriculture

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    Włodzimierz Rembisz

    2010-12-01

    Full Text Available The principles and evolution of intervention in agriculture are critically analyzed from the perspective of the economics and economic of agriculture theories. The allocation and returns aspects of economics are used as references in the analysis. The assumptions and outcomes of a triple factors production function, first aspect, are usually used as a justification for intervention support. That type of production function explains, as is believed, the lover possibilities of labor productivity growth in agriculture compared to non- farm labor employment. That affects, as assumed, income disparities between farm and non-farm labor. The analysis also disputes the politically, institutionally and administratively based justifications for the intervention. The evolution of intervention measures from price support towards direct payments and subsequently more market, are subject of review as well.

  16. Case Series Analysis of New Zealand Reports of Rapid Intense Potentiation of Warfarin by Roxithromycin.

    Science.gov (United States)

    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

  17. State intervention causing inefficiency: an empirical analysis of the Norwegian Continental Shelf

    International Nuclear Information System (INIS)

    Kashani, Hossein A.

    2005-01-01

    State intervention in the Norwegian Continental Shelf started with the establishment of Statoil as the medium of state ownership over the found petroleum and as a tool to monitor oil companies' procurement behaviour. This paper tests the extent to which the state intervention created inefficiencies in the Norwegian Continental Shelf (NCS) activities, as measured by data envelopment analysis, stochastic frontier analysis, Malmquist Indices, and standard regression analysis. Our results confirm such inefficiencies. Accordingly, the results provide an important insight into NCS production techniques and, more generally, into governments' abilities to influence private sector behaviour through contracts and tendering

  18. Dietary interventions to prevent and manage diabetes in worksite settings: a meta-analysis

    OpenAIRE

    Shrestha, Archana; Karmacharya, Biraj Man; Khudyakov, Polyna; Weber, Mary Beth; Spiegelman, Donna

    2017-01-01

    Objectives: The translation of lifestyle intervention to improve glucose tolerance into the workplace has been rare. The objective of this meta-analysis is to summarize the evidence for the effectiveness of dietary interventions in worksite settings on lowering blood sugar levels. Methods: We searched for studies in PubMed, Embase, Econlit, Ovid, Cochrane, Web of Science, and Cumulative Index to Nursing and Allied Health Literature. Search terms were as follows: (1) Exposure-based: nutrition/...

  19. Applied behavior analysis as intervention for autism: definition, features and philosophical concepts

    Directory of Open Access Journals (Sweden)

    Síglia Pimentel Höher Camargo

    2013-11-01

    Full Text Available Autism spectrum disorder (ASD is a lifelong pervasive developmental disorder with no known causes and cure. However, educational and behavioral interventions with a foundation in applied behavior analysis (ABA have been shown to improve a variety of skill areas such as communication, social, academic, and adaptive behaviors of individuals with ASD. The goal of this work is to present the definition, features and philosophical concepts that underlie ABA and make this science an effective intervention method for people with autism.

  20. EFFICACY OF PHYSIOTHERAPY INTERVENTIONS LATE AFTER STROKE: A META-ANALYSIS

    OpenAIRE

    Ferrarello , Francesco; Baccini , Marco; Rinaldi , Lucio Antonio; Cavallini , Maria Chiara; Mossello , Enrico; Masotti , Giulio; Marchionni , Niccolò; Di Bari , Mauro

    2010-01-01

    Abstract Objective. Physiotherapy is usually provided only in the first few months after stroke, while its effectiveness and appropriateness in the chronic phase are uncertain. We conducted a systematic review and meta-analysis of randomized clinical trials (RCT) to evaluate the efficacy of physiotherapy interventions on motor and functional outcomes late after stroke. Methods. We searched published studies where participants were randomized to an active physiotherapy intervention,...