Directory of Open Access Journals (Sweden)
Ai-Min Yang
2014-01-01
Full Text Available We use the local fractional series expansion method to solve the Klein-Gordon equations on Cantor sets within the local fractional derivatives. The analytical solutions within the nondifferential terms are discussed. The obtained results show the simplicity and efficiency of the present technique with application to the problems of the liner differential equations on Cantor sets.
Local Fractional Series Expansion Method for Solving Wave and Diffusion Equations on Cantor Sets
Directory of Open Access Journals (Sweden)
Ai-Min Yang
2013-01-01
Full Text Available We proposed a local fractional series expansion method to solve the wave and diffusion equations on Cantor sets. Some examples are given to illustrate the efficiency and accuracy of the proposed method to obtain analytical solutions to differential equations within the local fractional derivatives.
Directory of Open Access Journals (Sweden)
Sun Huan
2016-01-01
Full Text Available In this paper, we use the Laplace transform series expansion method to find the analytical solution for the local fractional heat-transfer equation defined on Cantor sets via local fractional calculus.
Liang, Y.; Gallaher, D. W.; Grant, G.; Lv, Q.
2011-12-01
Change over time, is the central driver of climate change detection. The goal is to diagnose the underlying causes, and make projections into the future. In an effort to optimize this process we have developed the Data Rod model, an object-oriented approach that provides the ability to query grid cell changes and their relationships to neighboring grid cells through time. The time series data is organized in time-centric structures called "data rods." A single data rod can be pictured as the multi-spectral data history at one grid cell: a vertical column of data through time. This resolves the long-standing problem of managing time-series data and opens new possibilities for temporal data analysis. This structure enables rapid time- centric analysis at any grid cell across multiple sensors and satellite platforms. Collections of data rods can be spatially and temporally filtered, statistically analyzed, and aggregated for use with pattern matching algorithms. Likewise, individual image pixels can be extracted to generate multi-spectral imagery at any spatial and temporal location. The Data Rods project has created a series of prototype databases to store and analyze massive datasets containing multi-modality remote sensing data. Using object-oriented technology, this method overcomes the operational limitations of traditional relational databases. To demonstrate the speed and efficiency of time-centric analysis using the Data Rods model, we have developed a sea ice detection algorithm. This application determines the concentration of sea ice in a small spatial region across a long temporal window. If performed using traditional analytical techniques, this task would typically require extensive data downloads and spatial filtering. Using Data Rods databases, the exact spatio-temporal data set is immediately available No extraneous data is downloaded, and all selected data querying occurs transparently on the server side. Moreover, fundamental statistical
Time series clustering in large data sets
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Jiří Fejfar
2011-01-01
Full Text Available The clustering of time series is a widely researched area. There are many methods for dealing with this task. We are actually using the Self-organizing map (SOM with the unsupervised learning algorithm for clustering of time series. After the first experiment (Fejfar, Weinlichová, Šťastný, 2009 it seems that the whole concept of the clustering algorithm is correct but that we have to perform time series clustering on much larger dataset to obtain more accurate results and to find the correlation between configured parameters and results more precisely. The second requirement arose in a need for a well-defined evaluation of results. It seems useful to use sound recordings as instances of time series again. There are many recordings to use in digital libraries, many interesting features and patterns can be found in this area. We are searching for recordings with the similar development of information density in this experiment. It can be used for musical form investigation, cover songs detection and many others applications.The objective of the presented paper is to compare clustering results made with different parameters of feature vectors and the SOM itself. We are describing time series in a simplistic way evaluating standard deviations for separated parts of recordings. The resulting feature vectors are clustered with the SOM in batch training mode with different topologies varying from few neurons to large maps.There are other algorithms discussed, usable for finding similarities between time series and finally conclusions for further research are presented. We also present an overview of the related actual literature and projects.
A Time Series Forecasting Method
Directory of Open Access Journals (Sweden)
Wang Zhao-Yu
2017-01-01
Full Text Available This paper proposes a novel time series forecasting method based on a weighted self-constructing clustering technique. The weighted self-constructing clustering processes all the data patterns incrementally. If a data pattern is not similar enough to an existing cluster, it forms a new cluster of its own. However, if a data pattern is similar enough to an existing cluster, it is removed from the cluster it currently belongs to and added to the most similar cluster. During the clustering process, weights are learned for each cluster. Given a series of time-stamped data up to time t, we divide it into a set of training patterns. By using the weighted self-constructing clustering, the training patterns are grouped into a set of clusters. To estimate the value at time t + 1, we find the k nearest neighbors of the input pattern and use these k neighbors to decide the estimation. Experimental results are shown to demonstrate the effectiveness of the proposed approach.
Time domain series system definition and gear set reliability modeling
International Nuclear Information System (INIS)
Xie, Liyang; Wu, Ningxiang; Qian, Wenxue
2016-01-01
Time-dependent multi-configuration is a typical feature for mechanical systems such as gear trains and chain drives. As a series system, a gear train is distinct from a traditional series system, such as a chain, in load transmission path, system-component relationship, system functioning manner, as well as time-dependent system configuration. Firstly, the present paper defines time-domain series system to which the traditional series system reliability model is not adequate. Then, system specific reliability modeling technique is proposed for gear sets, including component (tooth) and subsystem (tooth-pair) load history description, material priori/posterior strength expression, time-dependent and system specific load-strength interference analysis, as well as statistically dependent failure events treatment. Consequently, several system reliability models are developed for gear sets with different tooth numbers in the scenario of tooth root material ultimate tensile strength failure. The application of the models is discussed in the last part, and the differences between the system specific reliability model and the traditional series system reliability model are illustrated by virtue of several numerical examples. - Highlights: • A new type of series system, i.e. time-domain multi-configuration series system is defined, that is of great significance to reliability modeling. • Multi-level statistical analysis based reliability modeling method is presented for gear transmission system. • Several system specific reliability models are established for gear set reliability estimation. • The differences between the traditional series system reliability model and the new model are illustrated.
Efficient Algorithms for Segmentation of Item-Set Time Series
Chundi, Parvathi; Rosenkrantz, Daniel J.
We propose a special type of time series, which we call an item-set time series, to facilitate the temporal analysis of software version histories, email logs, stock market data, etc. In an item-set time series, each observed data value is a set of discrete items. We formalize the concept of an item-set time series and present efficient algorithms for segmenting a given item-set time series. Segmentation of a time series partitions the time series into a sequence of segments where each segment is constructed by combining consecutive time points of the time series. Each segment is associated with an item set that is computed from the item sets of the time points in that segment, using a function which we call a measure function. We then define a concept called the segment difference, which measures the difference between the item set of a segment and the item sets of the time points in that segment. The segment difference values are required to construct an optimal segmentation of the time series. We describe novel and efficient algorithms to compute segment difference values for each of the measure functions described in the paper. We outline a dynamic programming based scheme to construct an optimal segmentation of the given item-set time series. We use the item-set time series segmentation techniques to analyze the temporal content of three different data sets—Enron email, stock market data, and a synthetic data set. The experimental results show that an optimal segmentation of item-set time series data captures much more temporal content than a segmentation constructed based on the number of time points in each segment, without examining the item set data at the time points, and can be used to analyze different types of temporal data.
Highly comparative time-series analysis: the empirical structure of time series and their methods.
Fulcher, Ben D; Little, Max A; Jones, Nick S
2013-06-06
The process of collecting and organizing sets of observations represents a common theme throughout the history of science. However, despite the ubiquity of scientists measuring, recording and analysing the dynamics of different processes, an extensive organization of scientific time-series data and analysis methods has never been performed. Addressing this, annotated collections of over 35 000 real-world and model-generated time series, and over 9000 time-series analysis algorithms are analysed in this work. We introduce reduced representations of both time series, in terms of their properties measured by diverse scientific methods, and of time-series analysis methods, in terms of their behaviour on empirical time series, and use them to organize these interdisciplinary resources. This new approach to comparing across diverse scientific data and methods allows us to organize time-series datasets automatically according to their properties, retrieve alternatives to particular analysis methods developed in other scientific disciplines and automate the selection of useful methods for time-series classification and regression tasks. The broad scientific utility of these tools is demonstrated on datasets of electroencephalograms, self-affine time series, heartbeat intervals, speech signals and others, in each case contributing novel analysis techniques to the existing literature. Highly comparative techniques that compare across an interdisciplinary literature can thus be used to guide more focused research in time-series analysis for applications across the scientific disciplines.
Genealogical series method. Hyperpolar points screen effect
International Nuclear Information System (INIS)
Gorbatov, A.M.
1991-01-01
The fundamental values of the genealogical series method -the genealogical integrals (sandwiches) have been investigated. The hyperpolar points screen effect has been found. It allows one to calculate the sandwiches for the Fermion systems with large number of particles and to ascertain the validity of the iterated-potential method as well. For the first time the genealogical-series method has been realized numerically for the central spin-independent potential
Methods in Clinical Pharmacology Series
Beaumont, Claire; Young, Graeme C; Cavalier, Tom; Young, Malcolm A
2014-01-01
Human radiolabel studies are traditionally conducted to provide a definitive understanding of the human absorption, distribution, metabolism and excretion (ADME) properties of a drug. However, advances in technology over the past decade have allowed alternative methods to be employed to obtain both clinical ADME and pharmacokinetic (PK) information. These include microdose and microtracer approaches using accelerator mass spectrometry, and the identification and quantification of metabolites in samples from classical human PK studies using technologies suitable for non-radiolabelled drug molecules, namely liquid chromatography-mass spectrometry and nuclear magnetic resonance spectroscopy. These recently developed approaches are described here together with relevant examples primarily from experiences gained in support of drug development projects at GlaxoSmithKline. The advantages of these study designs together with their limitations are described. We also discuss special considerations which should be made for a successful outcome to these new approaches and also to the more traditional human radiolabel study in order to maximize knowledge around the human ADME properties of drug molecules. PMID:25041729
Taylor's series method for solving the nonlinear point kinetics equations
International Nuclear Information System (INIS)
Nahla, Abdallah A.
2011-01-01
Highlights: → Taylor's series method for nonlinear point kinetics equations is applied. → The general order of derivatives are derived for this system. → Stability of Taylor's series method is studied. → Taylor's series method is A-stable for negative reactivity. → Taylor's series method is an accurate computational technique. - Abstract: Taylor's series method for solving the point reactor kinetics equations with multi-group of delayed neutrons in the presence of Newtonian temperature feedback reactivity is applied and programmed by FORTRAN. This system is the couples of the stiff nonlinear ordinary differential equations. This numerical method is based on the different order derivatives of the neutron density, the precursor concentrations of i-group of delayed neutrons and the reactivity. The r th order of derivatives are derived. The stability of Taylor's series method is discussed. Three sets of applications: step, ramp and temperature feedback reactivities are computed. Taylor's series method is an accurate computational technique and stable for negative step, negative ramp and temperature feedback reactivities. This method is useful than the traditional methods for solving the nonlinear point kinetics equations.
A method for summing nonalternating asymptotic series
International Nuclear Information System (INIS)
Kazakov, D.I.
1980-01-01
A method for reconstructing a function from its nonalternating asymptotic series is proposed. It can also be applied when only a limited number of coefficients and their high order asymptotic behaviour are known. The method is illustrated by examples of the ordinary simple integral simulating a functional integral in a theory with degenerate minimum and of the double-well unharmonic oscillator
Directory of Open Access Journals (Sweden)
Zhi-Yong Chen
2014-01-01
Full Text Available From the signal processing point of view, the nondifferentiable data defined on the Cantor sets are investigated in this paper. The local fractional Fourier series is used to process the signals, which are the local fractional continuous functions. Our results can be observed as significant extensions of the previously known results for the Fourier series in the framework of the local fractional calculus. Some examples are given to illustrate the efficiency and implementation of the present method.
Time series analysis time series analysis methods and applications
Rao, Tata Subba; Rao, C R
2012-01-01
The field of statistics not only affects all areas of scientific activity, but also many other matters such as public policy. It is branching rapidly into so many different subjects that a series of handbooks is the only way of comprehensively presenting the various aspects of statistical methodology, applications, and recent developments. The Handbook of Statistics is a series of self-contained reference books. Each volume is devoted to a particular topic in statistics, with Volume 30 dealing with time series. The series is addressed to the entire community of statisticians and scientists in various disciplines who use statistical methodology in their work. At the same time, special emphasis is placed on applications-oriented techniques, with the applied statistician in mind as the primary audience. Comprehensively presents the various aspects of statistical methodology Discusses a wide variety of diverse applications and recent developments Contributors are internationally renowened experts in their respect...
Mathematical methods in time series analysis and digital image processing
Kurths, J; Maass, P; Timmer, J
2008-01-01
The aim of this volume is to bring together research directions in theoretical signal and imaging processing developed rather independently in electrical engineering, theoretical physics, mathematics and the computer sciences. In particular, mathematically justified algorithms and methods, the mathematical analysis of these algorithms, and methods as well as the investigation of connections between methods from time series analysis and image processing are reviewed. An interdisciplinary comparison of these methods, drawing upon common sets of test problems from medicine and geophysical/enviromental sciences, is also addressed. This volume coherently summarizes work carried out in the field of theoretical signal and image processing. It focuses on non-linear and non-parametric models for time series as well as on adaptive methods in image processing.
Palmprint Verification Using Time Series Method
Directory of Open Access Journals (Sweden)
A. A. Ketut Agung Cahyawan Wiranatha
2013-11-01
Full Text Available The use of biometrics as an automatic recognition system is growing rapidly in solving security problems, palmprint is one of biometric system which often used. This paper used two steps in center of mass moment method for region of interest (ROI segmentation and apply the time series method combined with block window method as feature representation. Normalized Euclidean Distance is used to measure the similarity degrees of two feature vectors of palmprint. System testing is done using 500 samples palms, with 4 samples as the reference image and the 6 samples as test images. Experiment results show that this system can achieve a high performance with success rate about 97.33% (FNMR=1.67%, FMR=1.00 %, T=0.036.
Methods of solving sequence and series problems
Grigorieva, Ellina
2016-01-01
This book aims to dispel the mystery and fear experienced by students surrounding sequences, series, convergence, and their applications. The author, an accomplished female mathematician, achieves this by taking a problem solving approach, starting with fascinating problems and solving them step by step with clear explanations and illuminating diagrams. The reader will find the problems interesting, unusual, and fun, yet solved with the rigor expected in a competition. Some problems are taken directly from mathematics competitions, with the name and year of the exam provided for reference. Proof techniques are emphasized, with a variety of methods presented. The text aims to expand the mind of the reader by often presenting multiple ways to attack the same problem, as well as drawing connections with different fields of mathematics. Intuitive and visual arguments are presented alongside technical proofs to provide a well-rounded methodology. With nearly 300 problems including hints, answers, and solutions,Met...
Methods for summing general Kapteyn series
Energy Technology Data Exchange (ETDEWEB)
Tautz, R C [Zentrum fuer Astronomie und Astrophysik, Technische Universitaet Berlin, Hardenbergstrasse 36, D-10623 Berlin (Germany); Lerche, I [Institut fuer Geowissenschaften, Naturwissenschaftliche Fakultaet III, Martin-Luther-Universitaet Halle, D-06099 Halle (Germany); Dominici, D, E-mail: rct@gmx.eu, E-mail: lercheian@yahoo.com, E-mail: dominicd@newpaltz.edu [Department of Mathematics, State University of New York at New Paltz, 1 Hawk Dr, New Paltz, NY 12561-2443 (United States)
2011-09-23
The general features and characteristics of Kapteyn series, which are a special type of series involving the Bessel function, are investigated. For many applications in physics, astrophysics and mathematics, it is crucial to have closed-form expressions in order to determine their functional structure and parametric behavior. The closed-form expressions of Kapteyn series have mostly been limited to special cases, even though there are often similarities in the approaches used to reduce the series to analytically tractable forms. The goal of this paper is to review the previous work in the area and to show that Kapteyn series can be expressed as trigonometric or gamma function series, which can be evaluated in a closed form for specific parameters. Two examples with a similar structure are given, showing the complexity of Kapteyn series. (paper)
Standard setting: Comparison of two methods
Directory of Open Access Journals (Sweden)
Oyebode Femi
2006-09-01
Full Text Available Abstract Background The outcome of assessments is determined by the standard-setting method used. There is a wide range of standard – setting methods and the two used most extensively in undergraduate medical education in the UK are the norm-reference and the criterion-reference methods. The aims of the study were to compare these two standard-setting methods for a multiple-choice question examination and to estimate the test-retest and inter-rater reliability of the modified Angoff method. Methods The norm – reference method of standard -setting (mean minus 1 SD was applied to the 'raw' scores of 78 4th-year medical students on a multiple-choice examination (MCQ. Two panels of raters also set the standard using the modified Angoff method for the same multiple-choice question paper on two occasions (6 months apart. We compared the pass/fail rates derived from the norm reference and the Angoff methods and also assessed the test-retest and inter-rater reliability of the modified Angoff method. Results The pass rate with the norm-reference method was 85% (66/78 and that by the Angoff method was 100% (78 out of 78. The percentage agreement between Angoff method and norm-reference was 78% (95% CI 69% – 87%. The modified Angoff method had an inter-rater reliability of 0.81 – 0.82 and a test-retest reliability of 0.59–0.74. Conclusion There were significant differences in the outcomes of these two standard-setting methods, as shown by the difference in the proportion of candidates that passed and failed the assessment. The modified Angoff method was found to have good inter-rater reliability and moderate test-retest reliability.
Standard setting: comparison of two methods.
George, Sanju; Haque, M Sayeed; Oyebode, Femi
2006-09-14
The outcome of assessments is determined by the standard-setting method used. There is a wide range of standard-setting methods and the two used most extensively in undergraduate medical education in the UK are the norm-reference and the criterion-reference methods. The aims of the study were to compare these two standard-setting methods for a multiple-choice question examination and to estimate the test-retest and inter-rater reliability of the modified Angoff method. The norm-reference method of standard-setting (mean minus 1 SD) was applied to the 'raw' scores of 78 4th-year medical students on a multiple-choice examination (MCQ). Two panels of raters also set the standard using the modified Angoff method for the same multiple-choice question paper on two occasions (6 months apart). We compared the pass/fail rates derived from the norm reference and the Angoff methods and also assessed the test-retest and inter-rater reliability of the modified Angoff method. The pass rate with the norm-reference method was 85% (66/78) and that by the Angoff method was 100% (78 out of 78). The percentage agreement between Angoff method and norm-reference was 78% (95% CI 69% - 87%). The modified Angoff method had an inter-rater reliability of 0.81-0.82 and a test-retest reliability of 0.59-0.74. There were significant differences in the outcomes of these two standard-setting methods, as shown by the difference in the proportion of candidates that passed and failed the assessment. The modified Angoff method was found to have good inter-rater reliability and moderate test-retest reliability.
Jumps in GNSS coordinates time series, a simple and fast methodology to clean the data sets
Bruni, Sara; Zerbini, Susanna; Raicich, Fabio; Errico, Maddalena; Santi, Efisio
2014-05-01
GNSS coordinate time series often suffer from the presence of undesired offsets of different nature which may impair the reliable estimation of the long-period trend and that should be corrected in the original data sets. Examples of such discontinuities are those originated by earthquakes, monumentation problems, replacement/maintenance of the station equipment, change of the reference system and by a number of unforeseen events. We have developed an automated and fast data inspection procedure for estimating the time of occurrence and the magnitude of the jumps and for correcting the time series accordingly. These processing characteristics are important because many time series are now spanning almost two decades, and dense GNSS networks are becoming a reality. The procedure has been developed and tailored to GNSS data sets starting from the Sequential T-test Analysis of Regime Shifts (STARS) originally conceived by Rodionov (Geophys. Res. Lett., 31, L09204, 2004) in the context of climatic studies. This technique does not make any a priori assumption on the time of occurrence and on the magnitude of the discontinuities. A jump is detected and its magnitude estimated when, over two consecutive time windows of the same length, the mean value exhibits a statistically significant change. Three user-defined parameters are required: the cut-off length, L, representing the minimum time interval between two consecutive discontinuities, the significance level, p, of the exploited two-tailed Student t-test, and the Huber parameter, H, used to compute a weighted mean over the L-day intervals. The method has been tested on GPS coordinates time series of stations located in the southeastern Po Plain, in Italy. The series span more than 15 years and are affected by offsets of different nature. The methodology has proven to be effective, as confirmed by the comparison between the corrected GPS time series and those obtained by other co-located observation techniques such as
On sets of convergence and divergence of multiple orthogonal series
International Nuclear Information System (INIS)
D'yachenko, M I; Kazaryan, K S
2002-01-01
Multiple Fourier series with respect to uniformly bounded orthonormal systems (ONSs) are studied. The following results are obtained. Theorem 1. Let Φ={φ n (x)} n=1 ∞ be a complete orthonormal system on [0,1] that is uniformly bounded by M on this interval, assume that m≥2, and let Φ(m)={φ n (x)} nelement ofN m , where φ n (n)=φ n 1 (x 1 )...φ n m (x m ). Then there exists a function f(x) element of L([0,1] m ) cubically diverges on some measurable subset H of [0,1] m with μ m (H)≥1-(1-1/M 2 ) m . Theorem 3. For M>1 and an integer m≥2 let E be an arbitrary measurable subset of [0,1] such that μ(E)=1-1/M 2 . Then there exists a complete orthonormal system Φ on [0,1] uniformly bounded by M there such that the multiple Fourier series of each function f(x) element of L([0,1] m ) with respect to the product system Φ(m) cubically converges to f(x) a.e. on E m . Definitive results in this direction are established also for incomplete uniformly bounded ONSs
The "Set Map" Method of Navigation.
Tippett, Julian
1998-01-01
Explains the "set map" method of using the baseplate compass to solve walkers' navigational needs as opposed to the 1-2-3 method for taking a bearing. The map, with the compass permanently clipped to it, is rotated to the position in which its features have the same orientation as their counterparts on the ground. Includes directions and…
HOMPRA Europe - A gridded precipitation data set from European homogenized time series
Rustemeier, Elke; Kapala, Alice; Meyer-Christoffer, Anja; Finger, Peter; Schneider, Udo; Venema, Victor; Ziese, Markus; Simmer, Clemens; Becker, Andreas
2017-04-01
Reliable monitoring data are essential for robust analyses of climate variability and, in particular, long-term trends. In this regard, a gridded, homogenized data set of monthly precipitation totals - HOMPRA Europe (HOMogenized PRecipitation Analysis of European in-situ data)- is presented. The data base consists of 5373 homogenized monthly time series, a carefully selected subset held by the Global Precipitation Climatology Centre (GPCC). The chosen series cover the period 1951-2005 and contain less than 10% missing values. Due to the large number of data, an automatic algorithm had to be developed for the homogenization of these precipitation series. In principal, the algorithm is based on three steps: * Selection of overlapping station networks in the same precipitation regime, based on rank correlation and Ward's method of minimal variance. Since the underlying time series should be as homogeneous as possible, the station selection is carried out by deterministic first derivation in order to reduce artificial influences. * The natural variability and trends were temporally removed by means of highly correlated neighboring time series to detect artificial break-points in the annual totals. This ensures that only artificial changes can be detected. The method is based on the algorithm of Caussinus and Mestre (2004). * In the last step, the detected breaks are corrected monthly by means of a multiple linear regression (Mestre, 2003). Due to the automation of the homogenization, the validation of the algorithm is essential. Therefore, the method was tested on artificial data sets. Additionally the sensitivity of the method was tested by varying the neighborhood series. If available in digitized form, the station history was also used to search for systematic errors in the jump detection. Finally, the actual HOMPRA Europe product is produced by interpolation of the homogenized series onto a 1° grid using one of the interpolation schems operationally at GPCC
Advantages and limitations of the SETS method
International Nuclear Information System (INIS)
Mahaffy, J.H.
1983-01-01
The stability-enchancing two-step (SETS) method has been used successfully in the Transient Reactor Analysis Code (TRAC) for several years. The method consists of a basic semi-implicit step combined with a stabilizer step that, taken together, eliminate the material Courant stability limit associated with standard semi-implicit numerical methods. This approach toward stability requires significantly fewer computational operations than a fully implicit method, but currently maintains the first-order accuracy in space and time of its semi-implicit predecessors
A method for generating high resolution satellite image time series
Guo, Tao
2014-10-01
There is an increasing demand for satellite remote sensing data with both high spatial and temporal resolution in many applications. But it still is a challenge to simultaneously improve spatial resolution and temporal frequency due to the technical limits of current satellite observation systems. To this end, much R&D efforts have been ongoing for years and lead to some successes roughly in two aspects, one includes super resolution, pan-sharpen etc. methods which can effectively enhance the spatial resolution and generate good visual effects, but hardly preserve spectral signatures and result in inadequate analytical value, on the other hand, time interpolation is a straight forward method to increase temporal frequency, however it increase little informative contents in fact. In this paper we presented a novel method to simulate high resolution time series data by combing low resolution time series data and a very small number of high resolution data only. Our method starts with a pair of high and low resolution data set, and then a spatial registration is done by introducing LDA model to map high and low resolution pixels correspondingly. Afterwards, temporal change information is captured through a comparison of low resolution time series data, and then projected onto the high resolution data plane and assigned to each high resolution pixel according to the predefined temporal change patterns of each type of ground objects. Finally the simulated high resolution data is generated. A preliminary experiment shows that our method can simulate a high resolution data with a reasonable accuracy. The contribution of our method is to enable timely monitoring of temporal changes through analysis of time sequence of low resolution images only, and usage of costly high resolution data can be reduces as much as possible, and it presents a highly effective way to build up an economically operational monitoring solution for agriculture, forest, land use investigation
Transformation-cost time-series method for analyzing irregularly sampled data.
Ozken, Ibrahim; Eroglu, Deniz; Stemler, Thomas; Marwan, Norbert; Bagci, G Baris; Kurths, Jürgen
2015-06-01
Irregular sampling of data sets is one of the challenges often encountered in time-series analysis, since traditional methods cannot be applied and the frequently used interpolation approach can corrupt the data and bias the subsequence analysis. Here we present the TrAnsformation-Cost Time-Series (TACTS) method, which allows us to analyze irregularly sampled data sets without degenerating the quality of the data set. Instead of using interpolation we consider time-series segments and determine how close they are to each other by determining the cost needed to transform one segment into the following one. Using a limited set of operations-with associated costs-to transform the time series segments, we determine a new time series, that is our transformation-cost time series. This cost time series is regularly sampled and can be analyzed using standard methods. While our main interest is the analysis of paleoclimate data, we develop our method using numerical examples like the logistic map and the Rössler oscillator. The numerical data allows us to test the stability of our method against noise and for different irregular samplings. In addition we provide guidance on how to choose the associated costs based on the time series at hand. The usefulness of the TACTS method is demonstrated using speleothem data from the Secret Cave in Borneo that is a good proxy for paleoclimatic variability in the monsoon activity around the maritime continent.
Transformation-cost time-series method for analyzing irregularly sampled data
Ozken, Ibrahim; Eroglu, Deniz; Stemler, Thomas; Marwan, Norbert; Bagci, G. Baris; Kurths, Jürgen
2015-06-01
Irregular sampling of data sets is one of the challenges often encountered in time-series analysis, since traditional methods cannot be applied and the frequently used interpolation approach can corrupt the data and bias the subsequence analysis. Here we present the TrAnsformation-Cost Time-Series (TACTS) method, which allows us to analyze irregularly sampled data sets without degenerating the quality of the data set. Instead of using interpolation we consider time-series segments and determine how close they are to each other by determining the cost needed to transform one segment into the following one. Using a limited set of operations—with associated costs—to transform the time series segments, we determine a new time series, that is our transformation-cost time series. This cost time series is regularly sampled and can be analyzed using standard methods. While our main interest is the analysis of paleoclimate data, we develop our method using numerical examples like the logistic map and the Rössler oscillator. The numerical data allows us to test the stability of our method against noise and for different irregular samplings. In addition we provide guidance on how to choose the associated costs based on the time series at hand. The usefulness of the TACTS method is demonstrated using speleothem data from the Secret Cave in Borneo that is a good proxy for paleoclimatic variability in the monsoon activity around the maritime continent.
Method for calculating annual energy efficiency improvement of TV sets
International Nuclear Information System (INIS)
Varman, M.; Mahlia, T.M.I.; Masjuki, H.H.
2006-01-01
The popularization of 24 h pay-TV, interactive video games, web-TV, VCD and DVD are poised to have a large impact on overall TV electricity consumption in the Malaysia. Following this increased consumption, energy efficiency standard present a highly effective measure for decreasing electricity consumption in the residential sector. The main problem in setting energy efficiency standard is identifying annual efficiency improvement, due to the lack of time series statistical data available in developing countries. This study attempts to present a method of calculating annual energy efficiency improvement for TV set, which can be used for implementing energy efficiency standard for TV sets in Malaysia and other developing countries. Although the presented result is only an approximation, definitely it is one of the ways of accomplishing energy standard. Furthermore, the method can be used for other appliances without any major modification
Method for calculating annual energy efficiency improvement of TV sets
Energy Technology Data Exchange (ETDEWEB)
Varman, M. [Department of Mechanical Engineering, University of Malaya, Lembah Pantai, 50603 Kuala Lumpur (Malaysia); Mahlia, T.M.I. [Department of Mechanical Engineering, University of Malaya, Lembah Pantai, 50603 Kuala Lumpur (Malaysia)]. E-mail: indra@um.edu.my; Masjuki, H.H. [Department of Mechanical Engineering, University of Malaya, Lembah Pantai, 50603 Kuala Lumpur (Malaysia)
2006-10-15
The popularization of 24 h pay-TV, interactive video games, web-TV, VCD and DVD are poised to have a large impact on overall TV electricity consumption in the Malaysia. Following this increased consumption, energy efficiency standard present a highly effective measure for decreasing electricity consumption in the residential sector. The main problem in setting energy efficiency standard is identifying annual efficiency improvement, due to the lack of time series statistical data available in developing countries. This study attempts to present a method of calculating annual energy efficiency improvement for TV set, which can be used for implementing energy efficiency standard for TV sets in Malaysia and other developing countries. Although the presented result is only an approximation, definitely it is one of the ways of accomplishing energy standard. Furthermore, the method can be used for other appliances without any major modification.
WANG, D.; Wang, Y.; Zeng, X.
2017-12-01
Accurate, fast forecasting of hydro-meteorological time series is presently a major challenge in drought and flood mitigation. This paper proposes a hybrid approach, Wavelet De-noising (WD) and Rank-Set Pair Analysis (RSPA), that takes full advantage of a combination of the two approaches to improve forecasts of hydro-meteorological time series. WD allows decomposition and reconstruction of a time series by the wavelet transform, and hence separation of the noise from the original series. RSPA, a more reliable and efficient version of Set Pair Analysis, is integrated with WD to form the hybrid WD-RSPA approach. Two types of hydro-meteorological data sets with different characteristics and different levels of human influences at some representative stations are used to illustrate the WD-RSPA approach. The approach is also compared to three other generic methods: the conventional Auto Regressive Integrated Moving Average (ARIMA) method, Artificial Neural Networks (ANNs) (BP-error Back Propagation, MLP-Multilayer Perceptron and RBF-Radial Basis Function), and RSPA alone. Nine error metrics are used to evaluate the model performance. The results show that WD-RSPA is accurate, feasible, and effective. In particular, WD-RSPA is found to be the best among the various generic methods compared in this paper, even when the extreme events are included within a time series.
Identification of Dynamic Loads Based on Second-Order Taylor-Series Expansion Method
Li, Xiaowang; Deng, Zhongmin
2016-01-01
A new method based on the second-order Taylor-series expansion is presented to identify the structural dynamic loads in the time domain. This algorithm expresses the response vectors as Taylor-series approximation and then a series of formulas are deduced. As a result, an explicit discrete equation which associates system response, system characteristic, and input excitation together is set up. In a multi-input-multi-output (MIMO) numerical simulation study, sinusoidal excitation and white no...
A novel weight determination method for time series data aggregation
Xu, Paiheng; Zhang, Rong; Deng, Yong
2017-09-01
Aggregation in time series is of great importance in time series smoothing, predicting and other time series analysis process, which makes it crucial to address the weights in times series correctly and reasonably. In this paper, a novel method to obtain the weights in time series is proposed, in which we adopt induced ordered weighted aggregation (IOWA) operator and visibility graph averaging (VGA) operator and linearly combine the weights separately generated by the two operator. The IOWA operator is introduced to the weight determination of time series, through which the time decay factor is taken into consideration. The VGA operator is able to generate weights with respect to the degree distribution in the visibility graph constructed from the corresponding time series, which reflects the relative importance of vertices in time series. The proposed method is applied to two practical datasets to illustrate its merits. The aggregation of Construction Cost Index (CCI) demonstrates the ability of proposed method to smooth time series, while the aggregation of The Taiwan Stock Exchange Capitalization Weighted Stock Index (TAIEX) illustrate how proposed method maintain the variation tendency of original data.
A Parsimonious Bootstrap Method to Model Natural Inflow Energy Series
Directory of Open Access Journals (Sweden)
Fernando Luiz Cyrino Oliveira
2014-01-01
Full Text Available The Brazilian energy generation and transmission system is quite peculiar in its dimension and characteristics. As such, it can be considered unique in the world. It is a high dimension hydrothermal system with huge participation of hydro plants. Such strong dependency on hydrological regimes implies uncertainties related to the energetic planning, requiring adequate modeling of the hydrological time series. This is carried out via stochastic simulations of monthly inflow series using the family of Periodic Autoregressive models, PAR(p, one for each period (month of the year. In this paper it is shown the problems in fitting these models by the current system, particularly the identification of the autoregressive order “p” and the corresponding parameter estimation. It is followed by a proposal of a new approach to set both the model order and the parameters estimation of the PAR(p models, using a nonparametric computational technique, known as Bootstrap. This technique allows the estimation of reliable confidence intervals for the model parameters. The obtained results using the Parsimonious Bootstrap Method of Moments (PBMOM produced not only more parsimonious model orders but also adherent stochastic scenarios and, in the long range, lead to a better use of water resources in the energy operation planning.
Krieger, Ulrich K.; Siegrist, Franziska; Marcolli, Claudia; Emanuelsson, Eva U.; Gøbel, Freya M.; Bilde, Merete; Marsh, Aleksandra; Reid, Jonathan P.; Huisman, Andrew J.; Riipinen, Ilona; Hyttinen, Noora; Myllys, Nanna; Kurtén, Theo; Bannan, Thomas; Percival, Carl J.; Topping, David
2018-01-01
To predict atmospheric partitioning of organic compounds between gas and aerosol particle phase based on explicit models for gas phase chemistry, saturation vapor pressures of the compounds need to be estimated. Estimation methods based on functional group contributions require training sets of compounds with well-established saturation vapor pressures. However, vapor pressures of semivolatile and low-volatility organic molecules at atmospheric temperatures reported in the literature often differ by several orders of magnitude between measurement techniques. These discrepancies exceed the stated uncertainty of each technique which is generally reported to be smaller than a factor of 2. At present, there is no general reference technique for measuring saturation vapor pressures of atmospherically relevant compounds with low vapor pressures at atmospheric temperatures. To address this problem, we measured vapor pressures with different techniques over a wide temperature range for intercomparison and to establish a reliable training set. We determined saturation vapor pressures for the homologous series of polyethylene glycols (H - (O - CH2 - CH2)n - OH) for n = 3 to n = 8 ranging in vapor pressure at 298 K from 10-7 to 5×10-2 Pa and compare them with quantum chemistry calculations. Such a homologous series provides a reference set that covers several orders of magnitude in saturation vapor pressure, allowing a critical assessment of the lower limits of detection of vapor pressures for the different techniques as well as permitting the identification of potential sources of systematic error. Also, internal consistency within the series allows outlying data to be rejected more easily. Most of the measured vapor pressures agreed within the stated uncertainty range. Deviations mostly occurred for vapor pressure values approaching the lower detection limit of a technique. The good agreement between the measurement techniques (some of which are sensitive to the mass
Series-parallel method of direct solar array regulation
Gooder, S. T.
1976-01-01
A 40 watt experimental solar array was directly regulated by shorting out appropriate combinations of series and parallel segments of a solar array. Regulation switches were employed to control the array at various set-point voltages between 25 and 40 volts. Regulation to within + or - 0.5 volt was obtained over a range of solar array temperatures and illumination levels as an active load was varied from open circuit to maximum available power. A fourfold reduction in regulation switch power dissipation was achieved with series-parallel regulation as compared to the usual series-only switching for direct solar array regulation.
Summation of Divergent Series and Zeldovich's Regularization Method
International Nuclear Information System (INIS)
Mur, V.D.; Pozdnyakov, S.G.; Popruzhenko, S.V.; Popov, V.S.
2005-01-01
A method for summing divergent series, including perturbation-theory series, is considered. This method is an analog of Zeldovich's regularization method in the theory of quasistationary states. It is shown that the method in question is more powerful than the well-known Abel and Borel methods, but that it is compatible with them (that is, it leads to the same value for the sum of a series). The constraints on the parameter domain that arise upon the removal of the regularization of divergent integrals by this method are discussed. The dynamical Stark shifts and widths of loosely bound s states in the field of a circularly polarized electromagnetic wave are calculated at various values of the Keldysh adiabaticity parameter and the multiquantum parameter
Wang, Dong; Borthwick, Alistair G; He, Handan; Wang, Yuankun; Zhu, Jieyu; Lu, Yuan; Xu, Pengcheng; Zeng, Xiankui; Wu, Jichun; Wang, Lachun; Zou, Xinqing; Liu, Jiufu; Zou, Ying; He, Ruimin
2018-01-01
Accurate, fast forecasting of hydro-meteorological time series is presently a major challenge in drought and flood mitigation. This paper proposes a hybrid approach, wavelet de-noising (WD) and Rank-Set Pair Analysis (RSPA), that takes full advantage of a combination of the two approaches to improve forecasts of hydro-meteorological time series. WD allows decomposition and reconstruction of a time series by the wavelet transform, and hence separation of the noise from the original series. RSPA, a more reliable and efficient version of Set Pair Analysis, is integrated with WD to form the hybrid WD-RSPA approach. Two types of hydro-meteorological data sets with different characteristics and different levels of human influences at some representative stations are used to illustrate the WD-RSPA approach. The approach is also compared to three other generic methods: the conventional Auto Regressive Integrated Moving Average (ARIMA) method, Artificial Neural Networks (ANNs) (BP-error Back Propagation, MLP-Multilayer Perceptron and RBF-Radial Basis Function), and RSPA alone. Nine error metrics are used to evaluate the model performance. Compared to three other generic methods, the results generated by WD-REPA model presented invariably smaller error measures which means the forecasting capability of the WD-REPA model is better than other models. The results show that WD-RSPA is accurate, feasible, and effective. In particular, WD-RSPA is found to be the best among the various generic methods compared in this paper, even when the extreme events are included within a time series. Copyright © 2017 Elsevier Inc. All rights reserved.
Standard-Setting Methods as Measurement Processes
Nichols, Paul; Twing, Jon; Mueller, Canda D.; O'Malley, Kimberly
2010-01-01
Some writers in the measurement literature have been skeptical of the meaningfulness of achievement standards and described the standard-setting process as blatantly arbitrary. We argue that standard setting is more appropriately conceived of as a measurement process similar to student assessment. The construct being measured is the panelists'…
Seismic assessment of a site using the time series method
International Nuclear Information System (INIS)
Krutzik, N.J.; Rotaru, I.; Bobei, M.; Mingiuc, C.; Serban, V.; Androne, M.
2001-01-01
1. To increase the safety of a NPP located on a seismic site, the seismic acceleration level to which the NPP should be qualified must be as representative as possible for that site, with a conservative degree of safety but not too exaggerated. 2. The consideration of the seismic events affecting the site as independent events and the use of statistic methods to define some safety levels with very low annual occurrence probabilities (10 -4 ) may lead to some exaggerations of the seismic safety level. 3. The use of some very high values for the seismic accelerations imposed by the seismic safety levels required by the hazard analysis may lead to very expensive technical solutions that can make the plant operation more difficult and increase the maintenance costs. 4. The consideration of seismic events as a time series with dependence among the events produced may lead to a more representative assessment of a NPP site seismic activity and consequently to a prognosis on the seismic level values to which the NPP would be ensured throughout its life-span. That prognosis should consider the actual seismic activity (including small earthquakes in real time) of the focuses that affect the plant site. The method is useful for two purposes: a) research, i.e. homogenizing the history data basis by the generation of earthquakes during periods lacking information and correlation of the information with the existing information. The aim is to perform the hazard analysis using a homogeneous data set in order to determine the seismic design data for a site; b) operation, i.e. the performance of a prognosis on the seismic activity on a certain site and consideration of preventive measures to minimize the possible effects of an earthquake. 5. The paper proposes the application of Autoregressive Time Series to issue a prognosis on the seismic activity of a focus and presents the analysis on Vrancea focus that affects Cernavoda NPP site by this method. 6. The paper also presents the
Summation of divergent series and Zel'dovich's regularization method
International Nuclear Information System (INIS)
Mur, V.D.; Pozdnyakov, S.G.; Popruzhenko, S.V.; Popov, V.S.
2005-01-01
The method of summation of divergent series, including series of a perturbation theory, which is an analog of the Zel'dovich regularization procedure in the theory of quasistationary states is considered. It is shown that this method is more powerful than the well-known Abel and Borel methods, but compatible with them (i. e., gives the same value for the sum of the series). The restrictions to the range of parameters which appear after removal of the regularization of integrals by this method are discussed. The dynamical Stark shifts and widths of weakly bound s states in a field of circularly polarized electromagnetic wave are calculated at different values of the Keldysh adiabaticity parameter and multiquantum parameter [ru
Time Series Analysis of Insar Data: Methods and Trends
Osmanoglu, Batuhan; Sunar, Filiz; Wdowinski, Shimon; Cano-Cabral, Enrique
2015-01-01
Time series analysis of InSAR data has emerged as an important tool for monitoring and measuring the displacement of the Earth's surface. Changes in the Earth's surface can result from a wide range of phenomena such as earthquakes, volcanoes, landslides, variations in ground water levels, and changes in wetland water levels. Time series analysis is applied to interferometric phase measurements, which wrap around when the observed motion is larger than one-half of the radar wavelength. Thus, the spatio-temporal ''unwrapping" of phase observations is necessary to obtain physically meaningful results. Several different algorithms have been developed for time series analysis of InSAR data to solve for this ambiguity. These algorithms may employ different models for time series analysis, but they all generate a first-order deformation rate, which can be compared to each other. However, there is no single algorithm that can provide optimal results in all cases. Since time series analyses of InSAR data are used in a variety of applications with different characteristics, each algorithm possesses inherently unique strengths and weaknesses. In this review article, following a brief overview of InSAR technology, we discuss several algorithms developed for time series analysis of InSAR data using an example set of results for measuring subsidence rates in Mexico City.
Almost Free Modules Set-Theoretic Methods
Eklof, PC
1990-01-01
This is an extended treatment of the set-theoretic techniques which have transformed the study of abelian group and module theory over the last 15 years. Part of the book is new work which does not appear elsewhere in any form. In addition, a large body of material which has appeared previously (in scattered and sometimes inaccessible journal articles) has been extensively reworked and in many cases given new and improved proofs. The set theory required is carefully developed with algebraists in mind, and the independence results are derived from explicitly stated axioms. The book contains exe
Financial time series analysis based on information categorization method
Tian, Qiang; Shang, Pengjian; Feng, Guochen
2014-12-01
The paper mainly applies the information categorization method to analyze the financial time series. The method is used to examine the similarity of different sequences by calculating the distances between them. We apply this method to quantify the similarity of different stock markets. And we report the results of similarity in US and Chinese stock markets in periods 1991-1998 (before the Asian currency crisis), 1999-2006 (after the Asian currency crisis and before the global financial crisis), and 2007-2013 (during and after global financial crisis) by using this method. The results show the difference of similarity between different stock markets in different time periods and the similarity of the two stock markets become larger after these two crises. Also we acquire the results of similarity of 10 stock indices in three areas; it means the method can distinguish different areas' markets from the phylogenetic trees. The results show that we can get satisfactory information from financial markets by this method. The information categorization method can not only be used in physiologic time series, but also in financial time series.
Set-theoretic methods in control
Blanchini, Franco
2015-01-01
The second edition of this monograph describes the set-theoretic approach for the control and analysis of dynamic systems, both from a theoretical and practical standpoint. This approach is linked to fundamental control problems, such as Lyapunov stability analysis and stabilization, optimal control, control under constraints, persistent disturbance rejection, and uncertain systems analysis and synthesis. Completely self-contained, this book provides a solid foundation of mathematical techniques and applications, extensive references to the relevant literature, and numerous avenues for further theoretical study. All the material from the first edition has been updated to reflect the most recent developments in the field, and a new chapter on switching systems has been added. Each chapter contains examples, case studies, and exercises to allow for a better understanding of theoretical concepts by practical application. The mathematical language is kept to the minimum level necessary for the adequate for...
Minimum entropy density method for the time series analysis
Lee, Jeong Won; Park, Joongwoo Brian; Jo, Hang-Hyun; Yang, Jae-Suk; Moon, Hie-Tae
2009-01-01
The entropy density is an intuitive and powerful concept to study the complicated nonlinear processes derived from physical systems. We develop the minimum entropy density method (MEDM) to detect the structure scale of a given time series, which is defined as the scale in which the uncertainty is minimized, hence the pattern is revealed most. The MEDM is applied to the financial time series of Standard and Poor’s 500 index from February 1983 to April 2006. Then the temporal behavior of structure scale is obtained and analyzed in relation to the information delivery time and efficient market hypothesis.
Generalized series method in the theory of atomic nucleus
International Nuclear Information System (INIS)
Gorbatov, A.M.
1991-01-01
On a hypersphere of a prescribed radius the so-called genealogical basis has been constructed. By making use of this basis, the many-body Schroedinger equation has been obtained for bound states of various physical systems. The genealogical series method, being in general outline the extension of the angular potential functions method, deals with the potential harmonics of any generation needed. The new approach provides an exact numerical description of the hadron systems with two-body higher interaction
Methods for obtaining sorption data from uranium-series disequilibria
International Nuclear Information System (INIS)
Finnegan, D.L.; Bryant, E.A.
1987-12-01
Two possible methods have been identified for obtaining in situ retardation factors from measurements of uranium-series disequilibria at Yucca Mountain. The first method would make use of the enhanced 234 U/ 238 U ratio in groundwater to derive a signature for exchangeable uranium sorbed on the rock; the exchangeable uranium would be leached and assayed. The second method would use the ratio of 222 Rn to 234 U in solution, corrected for weathering, to infer the retardation factor for uranium. Similar methods could be applied to thorium and radium
Identification of Dynamic Loads Based on Second-Order Taylor-Series Expansion Method
Directory of Open Access Journals (Sweden)
Xiaowang Li
2016-01-01
Full Text Available A new method based on the second-order Taylor-series expansion is presented to identify the structural dynamic loads in the time domain. This algorithm expresses the response vectors as Taylor-series approximation and then a series of formulas are deduced. As a result, an explicit discrete equation which associates system response, system characteristic, and input excitation together is set up. In a multi-input-multi-output (MIMO numerical simulation study, sinusoidal excitation and white noise excitation are applied on a cantilever beam, respectively, to illustrate the effectiveness of this algorithm. One also makes a comparison between the new method and conventional state space method. The results show that the proposed method can obtain a more accurate identified force time history whether the responses are polluted by noise or not.
DEFF Research Database (Denmark)
Madsen, Henrik; Rasmussen, Peter F.; Rosbjerg, Dan
1997-01-01
Two different models for analyzing extreme hydrologic events, based on, respectively, partial duration series (PDS) and annual maximum series (AMS), are compared. The PDS model assumes a generalized Pareto distribution for modeling threshold exceedances corresponding to a generalized extreme value......). In the case of ML estimation, the PDS model provides the most efficient T-year event estimator. In the cases of MOM and PWM estimation, the PDS model is generally preferable for negative shape parameters, whereas the AMS model yields the most efficient estimator for positive shape parameters. A comparison...... of the considered methods reveals that in general, one should use the PDS model with MOM estimation for negative shape parameters, the PDS model with exponentially distributed exceedances if the shape parameter is close to zero, the AMS model with MOM estimation for moderately positive shape parameters, and the PDS...
Taylor-series method for four-nucleon wave functions
International Nuclear Information System (INIS)
Sandulescu, A.; Tarnoveanu, I.; Rizea, M.
1977-09-01
Taylor-series method for transforming the infinite or finite well two-nucleon wave functions from individual coordinates to relative and c.m. coordinates, by expanding the single particle shell model wave functions around c.m. of the system, is generalized to four-nucleon wave functions. Also the connections with the Talmi-Moshinsky method for two and four harmonic oscillator wave functions are deduced. For both methods Fortran IV programs for the expansion coefficients have been written and the equivalence of corresponding expressions numerically proved. (author)
Time series analysis methods and applications for flight data
Zhang, Jianye
2017-01-01
This book focuses on different facets of flight data analysis, including the basic goals, methods, and implementation techniques. As mass flight data possesses the typical characteristics of time series, the time series analysis methods and their application for flight data have been illustrated from several aspects, such as data filtering, data extension, feature optimization, similarity search, trend monitoring, fault diagnosis, and parameter prediction, etc. An intelligent information-processing platform for flight data has been established to assist in aircraft condition monitoring, training evaluation and scientific maintenance. The book will serve as a reference resource for people working in aviation management and maintenance, as well as researchers and engineers in the fields of data analysis and data mining.
Which DTW Method Applied to Marine Univariate Time Series Imputation
Phan , Thi-Thu-Hong; Caillault , Émilie; Lefebvre , Alain; Bigand , André
2017-01-01
International audience; Missing data are ubiquitous in any domains of applied sciences. Processing datasets containing missing values can lead to a loss of efficiency and unreliable results, especially for large missing sub-sequence(s). Therefore, the aim of this paper is to build a framework for filling missing values in univariate time series and to perform a comparison of different similarity metrics used for the imputation task. This allows to suggest the most suitable methods for the imp...
The power series method in the effectiveness factor calculations
Filipich, C. P.; Villa, L. T.; Grossi, Ricardo Oscar
2017-01-01
In the present paper, exact analytical solutions are obtained for nonlinear ordinary differential equations which appear in complex diffusionreaction processes. A technique based on the power series method is used. Numerical results were computed for a number of cases which correspond to boundary value problems available in the literature. Additionally, new numerical results were generated for several important cases. Fil: Filipich, C. P.. Universidad Tecnológica Nacional. Facultad Regiona...
A window-based time series feature extraction method.
Katircioglu-Öztürk, Deniz; Güvenir, H Altay; Ravens, Ursula; Baykal, Nazife
2017-10-01
This study proposes a robust similarity score-based time series feature extraction method that is termed as Window-based Time series Feature ExtraCtion (WTC). Specifically, WTC generates domain-interpretable results and involves significantly low computational complexity thereby rendering itself useful for densely sampled and populated time series datasets. In this study, WTC is applied to a proprietary action potential (AP) time series dataset on human cardiomyocytes and three precordial leads from a publicly available electrocardiogram (ECG) dataset. This is followed by comparing WTC in terms of predictive accuracy and computational complexity with shapelet transform and fast shapelet transform (which constitutes an accelerated variant of the shapelet transform). The results indicate that WTC achieves a slightly higher classification performance with significantly lower execution time when compared to its shapelet-based alternatives. With respect to its interpretable features, WTC has a potential to enable medical experts to explore definitive common trends in novel datasets. Copyright © 2017 Elsevier Ltd. All rights reserved.
A robust anomaly based change detection method for time-series remote sensing images
Shoujing, Yin; Qiao, Wang; Chuanqing, Wu; Xiaoling, Chen; Wandong, Ma; Huiqin, Mao
2014-03-01
Time-series remote sensing images record changes happening on the earth surface, which include not only abnormal changes like human activities and emergencies (e.g. fire, drought, insect pest etc.), but also changes caused by vegetation phenology and climate changes. Yet, challenges occur in analyzing global environment changes and even the internal forces. This paper proposes a robust Anomaly Based Change Detection method (ABCD) for time-series images analysis by detecting abnormal points in data sets, which do not need to follow a normal distribution. With ABCD we can detect when and where changes occur, which is the prerequisite condition of global change studies. ABCD was tested initially with 10-day SPOT VGT NDVI (Normalized Difference Vegetation Index) times series tracking land cover type changes, seasonality and noise, then validated to real data in a large area in Jiangxi, south of China. Initial results show that ABCD can precisely detect spatial and temporal changes from long time series images rapidly.
Methods for deconvolving sparse positive delta function series
International Nuclear Information System (INIS)
Trussell, H.J.; Schwalbe, L.A.
1981-01-01
Sparse delta function series occur as data in many chemical analyses and seismic methods. These original data are often sufficiently degraded by the recording instrument response that the individual delta function peaks are difficult to distinguish and measure. A method, which has been used to measure these peaks, is to fit a parameterized model by a nonlinear least-squares fitting algorithm. The deconvolution approaches described have the advantage of not requiring a parameterized point spread function, nor do they expect a fixed number of peaks. Two new methods are presented. The maximum power technique is reviewed. A maximum a posteriori technique is introduced. Results on both simulated and real data by the two methods are presented. The characteristics of the data can determine which method gives superior results. 5 figures
Statistical methods of parameter estimation for deterministically chaotic time series
Pisarenko, V. F.; Sornette, D.
2004-03-01
We discuss the possibility of applying some standard statistical methods (the least-square method, the maximum likelihood method, and the method of statistical moments for estimation of parameters) to deterministically chaotic low-dimensional dynamic system (the logistic map) containing an observational noise. A “segmentation fitting” maximum likelihood (ML) method is suggested to estimate the structural parameter of the logistic map along with the initial value x1 considered as an additional unknown parameter. The segmentation fitting method, called “piece-wise” ML, is similar in spirit but simpler and has smaller bias than the “multiple shooting” previously proposed. Comparisons with different previously proposed techniques on simulated numerical examples give favorable results (at least, for the investigated combinations of sample size N and noise level). Besides, unlike some suggested techniques, our method does not require the a priori knowledge of the noise variance. We also clarify the nature of the inherent difficulties in the statistical analysis of deterministically chaotic time series and the status of previously proposed Bayesian approaches. We note the trade off between the need of using a large number of data points in the ML analysis to decrease the bias (to guarantee consistency of the estimation) and the unstable nature of dynamical trajectories with exponentially fast loss of memory of the initial condition. The method of statistical moments for the estimation of the parameter of the logistic map is discussed. This method seems to be the unique method whose consistency for deterministically chaotic time series is proved so far theoretically (not only numerically).
Sivov, Oleg Viktorovich
Series compensated lines are protected from overvoltage by metal-oxide-varistors (MOVs) connected in parallel with the capacitor bank. The nonlinear characteristics of MOV devices add complexity to fault analysis and distance protection operation. During faults, the impedance of the line is modified by an equivalent impedance of the parallel MOV/capacitor circuit, which affects the distance protection. The intermittent wind generation introduces additional complexity to the system performance and distance protection. Wind variation affects the fault current level and equivalent MOV/capacitor impedance during a fault, and hence the distance relay operation. This thesis studies the impact of the intermittent wind power generation on the operation of MOV during faults. For the purpose of simulation, an equivalent wind farm model is proposed to generate a wind generation profile using wind farm generation from California independent system operator (ISO) as a guide for wind power variation to perform the study. The IEEE 12-bus test system is modified to include MOV-protected series capacitor and the equivalent wind farm model. The modified test system is simulated in the MATLAB/Simulink environment. The study has been achieved considering three phase and single line to ground (SLG) faults on the series compensated line to show the effect of wind variation on the MOV operation. This thesis proposes an adaptive setting method for the mho relay distance protection of series compensated line considering effects of wind power variation and MOV operation. The distributed parameters of a transmission line are taken into account to avoid overreaching and underreaching of distance relays. The study shows that variable wind power affects system power flow and fault current in the compensated line during a fault which affects the operation of MOVs for different fault conditions. The equivalent per-phase impedance of the MOV/capacitor circuit has an effect on the system operation
Harris, Claire; Green, Sally; Ramsey, Wayne; Allen, Kelly; King, Richard
2017-01-01
This is the first in a series of papers reporting Sustainability in Health care by Allocating Resources Effectively (SHARE). The SHARE Program is an investigation of concepts, opportunities, methods and implications for evidence-based investment and disinvestment in health technologies and clinical practices in a local healthcare setting. The papers in this series are targeted at clinicians, managers, policy makers, health service researchers and implementation scientists working in this cont...
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
Transport and diffusion of material quantities on propagating interfaces via level set methods
Adalsteinsson, D
2003-01-01
We develop theory and numerical algorithms to apply level set methods to problems involving the transport and diffusion of material quantities in a level set framework. Level set methods are computational techniques for tracking moving interfaces; they work by embedding the propagating interface as the zero level set of a higher dimensional function, and then approximate the solution of the resulting initial value partial differential equation using upwind finite difference schemes. The traditional level set method works in the trace space of the evolving interface, and hence disregards any parameterization in the interface description. Consequently, material quantities on the interface which themselves are transported under the interface motion are not easily handled in this framework. We develop model equations and algorithmic techniques to extend the level set method to include these problems. We demonstrate the accuracy of our approach through a series of test examples and convergence studies.
Transport and diffusion of material quantities on propagating interfaces via level set methods
International Nuclear Information System (INIS)
Adalsteinsson, David; Sethian, J.A.
2003-01-01
We develop theory and numerical algorithms to apply level set methods to problems involving the transport and diffusion of material quantities in a level set framework. Level set methods are computational techniques for tracking moving interfaces; they work by embedding the propagating interface as the zero level set of a higher dimensional function, and then approximate the solution of the resulting initial value partial differential equation using upwind finite difference schemes. The traditional level set method works in the trace space of the evolving interface, and hence disregards any parameterization in the interface description. Consequently, material quantities on the interface which themselves are transported under the interface motion are not easily handled in this framework. We develop model equations and algorithmic techniques to extend the level set method to include these problems. We demonstrate the accuracy of our approach through a series of test examples and convergence studies
Directory of Open Access Journals (Sweden)
Yolcu Ufuk
2016-06-01
Full Text Available Fuzzy time series methods based on the fuzzy set theory proposed by Zadeh (1965 was first introduced by Song and Chissom (1993. Since fuzzy time series methods do not have the assumptions that traditional time series do and have effective forecasting performance, the interest on fuzzy time series approaches is increasing rapidly. Fuzzy time series methods have been used in almost all areas, such as environmental science, economy and finance. The concepts of labour force participation and unemployment have great importance in terms of both the economy and sociology of countries. For this reason there are many studies on their forecasting. In this study, we aim to forecast the labour force participation and unemployment rate in Poland and Turkey using different fuzzy time series methods.
Normalization methods in time series of platelet function assays
Van Poucke, Sven; Zhang, Zhongheng; Roest, Mark; Vukicevic, Milan; Beran, Maud; Lauwereins, Bart; Zheng, Ming-Hua; Henskens, Yvonne; Lancé, Marcus; Marcus, Abraham
2016-01-01
Abstract Platelet function can be quantitatively assessed by specific assays such as light-transmission aggregometry, multiple-electrode aggregometry measuring the response to adenosine diphosphate (ADP), arachidonic acid, collagen, and thrombin-receptor activating peptide and viscoelastic tests such as rotational thromboelastometry (ROTEM). The task of extracting meaningful statistical and clinical information from high-dimensional data spaces in temporal multivariate clinical data represented in multivariate time series is complex. Building insightful visualizations for multivariate time series demands adequate usage of normalization techniques. In this article, various methods for data normalization (z-transformation, range transformation, proportion transformation, and interquartile range) are presented and visualized discussing the most suited approach for platelet function data series. Normalization was calculated per assay (test) for all time points and per time point for all tests. Interquartile range, range transformation, and z-transformation demonstrated the correlation as calculated by the Spearman correlation test, when normalized per assay (test) for all time points. When normalizing per time point for all tests, no correlation could be abstracted from the charts as was the case when using all data as 1 dataset for normalization. PMID:27428217
Hybrid perturbation methods based on statistical time series models
San-Juan, Juan Félix; San-Martín, Montserrat; Pérez, Iván; López, Rosario
2016-04-01
In this work we present a new methodology for orbit propagation, the hybrid perturbation theory, based on the combination of an integration method and a prediction technique. The former, which can be a numerical, analytical or semianalytical theory, generates an initial approximation that contains some inaccuracies derived from the fact that, in order to simplify the expressions and subsequent computations, not all the involved forces are taken into account and only low-order terms are considered, not to mention the fact that mathematical models of perturbations not always reproduce physical phenomena with absolute precision. The prediction technique, which can be based on either statistical time series models or computational intelligence methods, is aimed at modelling and reproducing missing dynamics in the previously integrated approximation. This combination results in the precision improvement of conventional numerical, analytical and semianalytical theories for determining the position and velocity of any artificial satellite or space debris object. In order to validate this methodology, we present a family of three hybrid orbit propagators formed by the combination of three different orders of approximation of an analytical theory and a statistical time series model, and analyse their capability to process the effect produced by the flattening of the Earth. The three considered analytical components are the integration of the Kepler problem, a first-order and a second-order analytical theories, whereas the prediction technique is the same in the three cases, namely an additive Holt-Winters method.
Series interconnected photovoltaic cells and method for making same
Albright, Scot P.; Chamberlin, Rhodes R.; Thompson, Roger A.
1995-01-01
A novel photovoltaic module (10) and method for constructing the same are disclosed. The module (10) includes a plurality of photovoltaic cells (12) formed on a substrate (14) and laterally separated by interconnection regions (15). Each cell (12) includes a bottom electrode (16), a photoactive layer (18) and a top electrode layer (20). Adjacent cells (12) are connected in electrical series by way of a conductive-buffer line (22). The buffer line (22) is also useful in protecting the bottom electrode (16) against severing during downstream layer cutting processes.
Segmenting the Parotid Gland using Registration and Level Set Methods
DEFF Research Database (Denmark)
Hollensen, Christian; Hansen, Mads Fogtmann; Højgaard, Liselotte
. The method was evaluated on a test set consisting of 8 corresponding data sets. The attained total volume Dice coefficient and mean Haussdorff distance were 0.61 ± 0.20 and 15.6 ± 7.4 mm respectively. The method has improvement potential which could be exploited in order for clinical introduction....
Identifying Heterogeneities in Subsurface Environment using the Level Set Method
Energy Technology Data Exchange (ETDEWEB)
Lei, Hongzhuan [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Lu, Zhiming [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Vesselinov, Velimir Valentinov [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
2016-08-25
These are slides from a presentation on identifying heterogeneities in subsurface environment using the level set method. The slides start with the motivation, then explain Level Set Method (LSM), the algorithms, some examples are given, and finally future work is explained.
Differentiability properties of the efficient (u,q2)-set in the Markowitz portfolio selection method
Kriens, J.; Strijbosch, L.W.G.; Vörös, J.
1994-01-01
The set of efficient (Rho2)-combinations in the (Rho2)-plane of the Markowitz portfolio selection method consists of a series of strictly convex parabola. In the transition points from one parabola to the next one, the curve may be indifferentiable. The article gives necessary and sufficient
A Comparison of Various Forecasting Methods for Autocorrelated Time Series
Directory of Open Access Journals (Sweden)
Karin Kandananond
2012-07-01
Full Text Available The accuracy of forecasts significantly affects the overall performance of a whole supply chain system. Sometimes, the nature of consumer products might cause difficulties in forecasting for the future demands because of its complicated structure. In this study, two machine learning methods, artificial neural network (ANN and support vector machine (SVM, and a traditional approach, the autoregressive integrated moving average (ARIMA model, were utilized to predict the demand for consumer products. The training data used were the actual demand of six different products from a consumer product company in Thailand. Initially, each set of data was analysed using Ljung‐Box‐Q statistics to test for autocorrelation. Afterwards, each method was applied to different sets of data. The results indicated that the SVM method had a better forecast quality (in terms of MAPE than ANN and ARIMA in every category of products.
Fuzzy Linear Regression for the Time Series Data which is Fuzzified with SMRGT Method
Directory of Open Access Journals (Sweden)
Seçil YALAZ
2016-10-01
Full Text Available Our work on regression and classification provides a new contribution to the analysis of time series used in many areas for years. Owing to the fact that convergence could not obtained with the methods used in autocorrelation fixing process faced with time series regression application, success is not met or fall into obligation of changing the models’ degree. Changing the models’ degree may not be desirable in every situation. In our study, recommended for these situations, time series data was fuzzified by using the simple membership function and fuzzy rule generation technique (SMRGT and to estimate future an equation has created by applying fuzzy least square regression (FLSR method which is a simple linear regression method to this data. Although SMRGT has success in determining the flow discharge in open channels and can be used confidently for flow discharge modeling in open canals, as well as in pipe flow with some modifications, there is no clue about that this technique is successful in fuzzy linear regression modeling. Therefore, in order to address the luck of such a modeling, a new hybrid model has been described within this study. In conclusion, to demonstrate our methods’ efficiency, classical linear regression for time series data and linear regression for fuzzy time series data were applied to two different data sets, and these two approaches performances were compared by using different measures.
Sector Identification in a Set of Stock Return Time Series Traded at the London Stock Exchange
Coronnello, C.; Tumminello, M.; Lillo, F.; Micciche, S.; Mantegna, R. N.
2005-09-01
We compare some methods recently used in the literature to detect the existence of a certain degree of common behavior of stock returns belonging to the same economic sector. Specifically, we discuss methods based on random matrix theory and hierarchical clustering techniques. We apply these methods to a portfolio of stocks traded at the London Stock Exchange. The investigated time series are recorded both at a daily time horizon and at a 5-minute time horizon. The correlation coefficient matrix is very different at different time horizons confirming that more structured correlation coefficient matrices are observed for long time horizons. All the considered methods are able to detect economic information and the presence of clusters characterized by the economic sector of stocks. However, different methods present a different degree of sensitivity with respect to different sectors. Our comparative analysis suggests that the application of just a single method could not be able to extract all the economic information present in the correlation coefficient matrix of a stock portfolio.
Seismic assessment of a site using the time series method
International Nuclear Information System (INIS)
Krutzik, N.J.; Rotaru, I.; Bobei, M.; Mingiuc, C.; Serban, V.; Androne, M.
1997-01-01
To increase the safety of a NPP located on a seismic site, the seismic acceleration level to which the NPP should be qualified must be as representative as possible for that site, with a conservative degree of safety but not too exaggerated. The consideration of the seismic events affecting the site as independent events and the use of statistic methods to define some safety levels with very low annual occurrence probability (10 -4 ) may lead to some exaggerations of the seismic safety level. The use of some very high value for the seismic acceleration imposed by the seismic safety levels required by the hazard analysis may lead to very costly technical solutions that can make the plant operation more difficult and increase maintenance costs. The considerations of seismic events as a time series with dependence among the events produced, may lead to a more representative assessment of a NPP site seismic activity and consequently to a prognosis on the seismic level values to which the NPP would be ensured throughout its life-span. That prognosis should consider the actual seismic activity (including small earthquakes in real time) of the focuses that affect the plant site. The paper proposes the applications of Autoregressive Time Series to issue a prognosis on the seismic activity of a focus and presents the analysis on Vrancea focus that affects NPP Cernavoda site, by this method. The paper also presents the manner to analyse the focus activity as per the new approach and it assesses the maximum seismic acceleration that may affect NPP Cernavoda throughout its life-span (∼ 30 years). Development and applications of new mathematical analysis method, both for long - and short - time intervals, may lead to important contributions in the process of foretelling the seismic events in the future. (authors)
Divergent series, summability and resurgence III resurgent methods and the first Painlevé equation
Delabaere, Eric
2016-01-01
The aim of this volume is two-fold. First, to show how the resurgent methods introduced in volume 1 can be applied efficiently in a non-linear setting; to this end further properties of the resurgence theory must be developed. Second, to analyze the fundamental example of the First Painlevé equation. The resurgent analysis of singularities is pushed all the way up to the so-called “bridge equation”, which concentrates all information about the non-linear Stokes phenomenon at infinity of the First Painlevé equation. The third in a series of three, entitled Divergent Series, Summability and Resurgence, this volume is aimed at graduate students, mathematicians and theoretical physicists who are interested in divergent power series and related problems, such as the Stokes phenomenon. The prerequisites are a working knowledge of complex analysis at the first-year graduate level and of the theory of resurgence, as presented in volume 1. .
A level set method for multiple sclerosis lesion segmentation.
Zhao, Yue; Guo, Shuxu; Luo, Min; Shi, Xue; Bilello, Michel; Zhang, Shaoxiang; Li, Chunming
2018-06-01
In this paper, we present a level set method for multiple sclerosis (MS) lesion segmentation from FLAIR images in the presence of intensity inhomogeneities. We use a three-phase level set formulation of segmentation and bias field estimation to segment MS lesions and normal tissue region (including GM and WM) and CSF and the background from FLAIR images. To save computational load, we derive a two-phase formulation from the original multi-phase level set formulation to segment the MS lesions and normal tissue regions. The derived method inherits the desirable ability to precisely locate object boundaries of the original level set method, which simultaneously performs segmentation and estimation of the bias field to deal with intensity inhomogeneity. Experimental results demonstrate the advantages of our method over other state-of-the-art methods in terms of segmentation accuracy. Copyright © 2017 Elsevier Inc. All rights reserved.
Volume Sculpting Using the Level-Set Method
DEFF Research Database (Denmark)
Bærentzen, Jakob Andreas; Christensen, Niels Jørgen
2002-01-01
In this paper, we propose the use of the Level--Set Method as the underlying technology of a volume sculpting system. The main motivation is that this leads to a very generic technique for deformation of volumetric solids. In addition, our method preserves a distance field volume representation....... A scaling window is used to adapt the Level--Set Method to local deformations and to allow the user to control the intensity of the tool. Level--Set based tools have been implemented in an interactive sculpting system, and we show sculptures created using the system....
On multiple level-set regularization methods for inverse problems
International Nuclear Information System (INIS)
DeCezaro, A; Leitão, A; Tai, X-C
2009-01-01
We analyze a multiple level-set method for solving inverse problems with piecewise constant solutions. This method corresponds to an iterated Tikhonov method for a particular Tikhonov functional G α based on TV–H 1 penalization. We define generalized minimizers for our Tikhonov functional and establish an existence result. Moreover, we prove convergence and stability results of the proposed Tikhonov method. A multiple level-set algorithm is derived from the first-order optimality conditions for the Tikhonov functional G α , similarly as the iterated Tikhonov method. The proposed multiple level-set method is tested on an inverse potential problem. Numerical experiments show that the method is able to recover multiple objects as well as multiple contrast levels
Jolivet, R.; Simons, M.
2018-02-01
Interferometric synthetic aperture radar time series methods aim to reconstruct time-dependent ground displacements over large areas from sets of interferograms in order to detect transient, periodic, or small-amplitude deformation. Because of computational limitations, most existing methods consider each pixel independently, ignoring important spatial covariances between observations. We describe a framework to reconstruct time series of ground deformation while considering all pixels simultaneously, allowing us to account for spatial covariances, imprecise orbits, and residual atmospheric perturbations. We describe spatial covariances by an exponential decay function dependent of pixel-to-pixel distance. We approximate the impact of imprecise orbit information and residual long-wavelength atmosphere as a low-order polynomial function. Tests on synthetic data illustrate the importance of incorporating full covariances between pixels in order to avoid biased parameter reconstruction. An example of application to the northern Chilean subduction zone highlights the potential of this method.
Multiattribute Grey Target Decision Method Based on Soft Set Theory
Directory of Open Access Journals (Sweden)
Xia Wang
2014-01-01
Full Text Available With respect to the Multiattribute decision-making problems in which the evaluation attribute sets are different and the evaluating values of alternatives are interval grey numbers, a multiattribute grey target decision-making method in which the attribute sets are different was proposed. The concept of grey soft set was defined, and its “AND” operation was assigned by combining the intersection operation of grey number. The expression approach of new grey soft set of attribute sets considering by all decision makers were gained by applying the “AND” operation of grey soft set, and the weights of synthesis attribute were proved. The alternatives were ranked according to the size of distance of bull’s eyes of each alternative under synthetic attribute sets. The green supplier selection was illustrated to demonstrate the effectiveness of proposed model.
A parametric level-set method for partially discrete tomography
A. Kadu (Ajinkya); T. van Leeuwen (Tristan); K.J. Batenburg (Joost)
2017-01-01
textabstractThis paper introduces a parametric level-set method for tomographic reconstruction of partially discrete images. Such images consist of a continuously varying background and an anomaly with a constant (known) grey-value. We express the geometry of the anomaly using a level-set function,
Integration of educational methods and physical settings: Design ...
African Journals Online (AJOL)
... setting without having an architectural background. The theoretical framework of the research allows designers to consider key features and users' possible activities in High/ Scope settings and shape their designs accordingly. Keywords: daily activity; design; High/Scope education; interior space; teaching method ...
Comparison of Co-Temporal Modeling Algorithms on Sparse Experimental Time Series Data Sets.
Allen, Edward E; Norris, James L; John, David J; Thomas, Stan J; Turkett, William H; Fetrow, Jacquelyn S
2010-01-01
Multiple approaches for reverse-engineering biological networks from time-series data have been proposed in the computational biology literature. These approaches can be classified by their underlying mathematical algorithms, such as Bayesian or algebraic techniques, as well as by their time paradigm, which includes next-state and co-temporal modeling. The types of biological relationships, such as parent-child or siblings, discovered by these algorithms are quite varied. It is important to understand the strengths and weaknesses of the various algorithms and time paradigms on actual experimental data. We assess how well the co-temporal implementations of three algorithms, continuous Bayesian, discrete Bayesian, and computational algebraic, can 1) identify two types of entity relationships, parent and sibling, between biological entities, 2) deal with experimental sparse time course data, and 3) handle experimental noise seen in replicate data sets. These algorithms are evaluated, using the shuffle index metric, for how well the resulting models match literature models in terms of siblings and parent relationships. Results indicate that all three co-temporal algorithms perform well, at a statistically significant level, at finding sibling relationships, but perform relatively poorly in finding parent relationships.
Approximate k-NN delta test minimization method using genetic algorithms: Application to time series
Mateo, F; Gadea, Rafael; Sovilj, Dusan
2010-01-01
In many real world problems, the existence of irrelevant input variables (features) hinders the predictive quality of the models used to estimate the output variables. In particular, time series prediction often involves building large regressors of artificial variables that can contain irrelevant or misleading information. Many techniques have arisen to confront the problem of accurate variable selection, including both local and global search strategies. This paper presents a method based on genetic algorithms that intends to find a global optimum set of input variables that minimize the Delta Test criterion. The execution speed has been enhanced by substituting the exact nearest neighbor computation by its approximate version. The problems of scaling and projection of variables have been addressed. The developed method works in conjunction with MATLAB's Genetic Algorithm and Direct Search Toolbox. The goodness of the proposed methodology has been evaluated on several popular time series examples, and also ...
Livran, J; Parente, C; Riddone, G; Rybkowski, D; Veillet, N
2000-01-01
Three pre-series Test Cells of the LHC Cryogenic Distribution Line (QRL) [1], manufactured by three European industrial companies, will be tested in the year 2000 to qualify the design chosen and verify the thermal and mechanical performances. A dedicated test stand (170 m x 13 m) has been built for extensive testing and performance assessment of the pre-series units in parallel. They will be fed with saturated liquid helium at 4.2 K supplied by a mobile helium dewar. In addition, LN2 cooled helium will be used for cool-down and thermal shielding. For each of the three pre-series units, a set of end boxes has been designed and manufactured at CERN. This paper presents the layout of the cryogenic system for the pre-series units, the calorimetric methods as well as the results of the thermal calculation of the end box test.
Efficiency of Choice Set Generation Methods for Bicycle Routes
DEFF Research Database (Denmark)
Halldórsdóttir, Katrín; Rieser-Schüssler, Nadine; W. Axhausen, Kay
behaviour, observed choices and alternatives composing the choice set of each cyclist are necessary. However, generating the alternative choice sets can prove challenging. This paper analyses the efficiency of various choice set generation methods for bicycle routes in order to contribute to our...... travelling information with GPS loggers, compared to self-reported RP data, is more accurate geographic locations and routes. Also, the GPS traces give more reliable information on times and prevent trip underreporting, and it is possible to collect information on many trips by the same person without...
Univariate Time Series Prediction of Solar Power Using a Hybrid Wavelet-ARMA-NARX Prediction Method
Energy Technology Data Exchange (ETDEWEB)
Nazaripouya, Hamidreza; Wang, Yubo; Chu, Chi-Cheng; Pota, Hemanshu; Gadh, Rajit
2016-05-02
This paper proposes a new hybrid method for super short-term solar power prediction. Solar output power usually has a complex, nonstationary, and nonlinear characteristic due to intermittent and time varying behavior of solar radiance. In addition, solar power dynamics is fast and is inertia less. An accurate super short-time prediction is required to compensate for the fluctuations and reduce the impact of solar power penetration on the power system. The objective is to predict one step-ahead solar power generation based only on historical solar power time series data. The proposed method incorporates discrete wavelet transform (DWT), Auto-Regressive Moving Average (ARMA) models, and Recurrent Neural Networks (RNN), while the RNN architecture is based on Nonlinear Auto-Regressive models with eXogenous inputs (NARX). The wavelet transform is utilized to decompose the solar power time series into a set of richer-behaved forming series for prediction. ARMA model is employed as a linear predictor while NARX is used as a nonlinear pattern recognition tool to estimate and compensate the error of wavelet-ARMA prediction. The proposed method is applied to the data captured from UCLA solar PV panels and the results are compared with some of the common and most recent solar power prediction methods. The results validate the effectiveness of the proposed approach and show a considerable improvement in the prediction precision.
Harris, Claire; Green, Sally; Ramsey, Wayne; Allen, Kelly; King, Richard
2017-05-04
This is the first in a series of papers reporting Sustainability in Health care by Allocating Resources Effectively (SHARE). The SHARE Program is an investigation of concepts, opportunities, methods and implications for evidence-based investment and disinvestment in health technologies and clinical practices in a local healthcare setting. The papers in this series are targeted at clinicians, managers, policy makers, health service researchers and implementation scientists working in this context. This paper presents an overview of the organisation-wide, systematic, integrated, evidence-based approach taken by one Australian healthcare network and provides an introduction and guide to the suite of papers reporting the experiences and outcomes.
Level set method for image segmentation based on moment competition
Min, Hai; Wang, Xiao-Feng; Huang, De-Shuang; Jin, Jing; Wang, Hong-Zhi; Li, Hai
2015-05-01
We propose a level set method for image segmentation which introduces the moment competition and weakly supervised information into the energy functional construction. Different from the region-based level set methods which use force competition, the moment competition is adopted to drive the contour evolution. Here, a so-called three-point labeling scheme is proposed to manually label three independent points (weakly supervised information) on the image. Then the intensity differences between the three points and the unlabeled pixels are used to construct the force arms for each image pixel. The corresponding force is generated from the global statistical information of a region-based method and weighted by the force arm. As a result, the moment can be constructed and incorporated into the energy functional to drive the evolving contour to approach the object boundary. In our method, the force arm can take full advantage of the three-point labeling scheme to constrain the moment competition. Additionally, the global statistical information and weakly supervised information are successfully integrated, which makes the proposed method more robust than traditional methods for initial contour placement and parameter setting. Experimental results with performance analysis also show the superiority of the proposed method on segmenting different types of complicated images, such as noisy images, three-phase images, images with intensity inhomogeneity, and texture images.
TIME SERIES MODELS OF THREE SETS OF RXTE OBSERVATIONS OF 4U 1543–47
International Nuclear Information System (INIS)
Koen, C.
2013-01-01
The X-ray nova 4U 1543–47 was in a different physical state (low/hard, high/soft, and very high) during the acquisition of each of the three time series analyzed in this paper. Standard time series models of the autoregressive moving average (ARMA) family are fitted to these series. The low/hard data can be adequately modeled by a simple low-order model with fixed coefficients, once the slowly varying mean count rate has been accounted for. The high/soft series requires a higher order model, or an ARMA model with variable coefficients. The very high state is characterized by a succession of 'dips', with roughly equal depths. These seem to appear independently of one another. The underlying stochastic series can again be modeled by an ARMA form, or roughly as the sum of an ARMA series and white noise. The structuring of each model in terms of short-lived aperiodic and 'quasi-periodic' components is discussed.
Optimizing distance-based methods for large data sets
Scholl, Tobias; Brenner, Thomas
2015-10-01
Distance-based methods for measuring spatial concentration of industries have received an increasing popularity in the spatial econometrics community. However, a limiting factor for using these methods is their computational complexity since both their memory requirements and running times are in {{O}}(n^2). In this paper, we present an algorithm with constant memory requirements and shorter running time, enabling distance-based methods to deal with large data sets. We discuss three recent distance-based methods in spatial econometrics: the D&O-Index by Duranton and Overman (Rev Econ Stud 72(4):1077-1106, 2005), the M-function by Marcon and Puech (J Econ Geogr 10(5):745-762, 2010) and the Cluster-Index by Scholl and Brenner (Reg Stud (ahead-of-print):1-15, 2014). Finally, we present an alternative calculation for the latter index that allows the use of data sets with millions of firms.
A local level set method based on a finite element method for unstructured meshes
International Nuclear Information System (INIS)
Ngo, Long Cu; Choi, Hyoung Gwon
2016-01-01
A local level set method for unstructured meshes has been implemented by using a finite element method. A least-square weighted residual method was employed for implicit discretization to solve the level set advection equation. By contrast, a direct re-initialization method, which is directly applicable to the local level set method for unstructured meshes, was adopted to re-correct the level set function to become a signed distance function after advection. The proposed algorithm was constructed such that the advection and direct reinitialization steps were conducted only for nodes inside the narrow band around the interface. Therefore, in the advection step, the Gauss–Seidel method was used to update the level set function using a node-by-node solution method. Some benchmark problems were solved by using the present local level set method. Numerical results have shown that the proposed algorithm is accurate and efficient in terms of computational time
A local level set method based on a finite element method for unstructured meshes
Energy Technology Data Exchange (ETDEWEB)
Ngo, Long Cu; Choi, Hyoung Gwon [School of Mechanical Engineering, Seoul National University of Science and Technology, Seoul (Korea, Republic of)
2016-12-15
A local level set method for unstructured meshes has been implemented by using a finite element method. A least-square weighted residual method was employed for implicit discretization to solve the level set advection equation. By contrast, a direct re-initialization method, which is directly applicable to the local level set method for unstructured meshes, was adopted to re-correct the level set function to become a signed distance function after advection. The proposed algorithm was constructed such that the advection and direct reinitialization steps were conducted only for nodes inside the narrow band around the interface. Therefore, in the advection step, the Gauss–Seidel method was used to update the level set function using a node-by-node solution method. Some benchmark problems were solved by using the present local level set method. Numerical results have shown that the proposed algorithm is accurate and efficient in terms of computational time.
A Level Set Discontinuous Galerkin Method for Free Surface Flows
DEFF Research Database (Denmark)
Grooss, Jesper; Hesthaven, Jan
2006-01-01
We present a discontinuous Galerkin method on a fully unstructured grid for the modeling of unsteady incompressible fluid flows with free surfaces. The surface is modeled by embedding and represented by a levelset. We discuss the discretization of the flow equations and the level set equation...
A Memory and Computation Efficient Sparse Level-Set Method
Laan, Wladimir J. van der; Jalba, Andrei C.; Roerdink, Jos B.T.M.
Since its introduction, the level set method has become the favorite technique for capturing and tracking moving interfaces, and found applications in a wide variety of scientific fields. In this paper we present efficient data structures and algorithms for tracking dynamic interfaces through the
DEFF Research Database (Denmark)
Byrge, Christian
2018-01-01
Five training sets including 450 unique thinking direction cards and 120 exercise cards. Designed for Educational Purposes.......Five training sets including 450 unique thinking direction cards and 120 exercise cards. Designed for Educational Purposes....
Landscape democracy, three sets of values, and the connoisseur method
DEFF Research Database (Denmark)
Arler, Finn; Mellqvist, Helena
2015-01-01
for argument. It examines various methods that have been used to try to make landscape decisions more democratic. In the last part of the paper the connoisseur method is introduced. This method emphasises stakeholder participation in deliberative processes with a particular focus on place-based knowledge......The European Landscape Convention has brought up the question of democracy in relation to landscape transformation, but without a clear definition of democracy. This paper conceptualises democracy in relation to three main sets of values related to self-determination, co-determination and respect...
A novel time series link prediction method: Learning automata approach
Moradabadi, Behnaz; Meybodi, Mohammad Reza
2017-09-01
Link prediction is a main social network challenge that uses the network structure to predict future links. The common link prediction approaches to predict hidden links use a static graph representation where a snapshot of the network is analyzed to find hidden or future links. For example, similarity metric based link predictions are a common traditional approach that calculates the similarity metric for each non-connected link and sort the links based on their similarity metrics and label the links with higher similarity scores as the future links. Because people activities in social networks are dynamic and uncertainty, and the structure of the networks changes over time, using deterministic graphs for modeling and analysis of the social network may not be appropriate. In the time-series link prediction problem, the time series link occurrences are used to predict the future links In this paper, we propose a new time series link prediction based on learning automata. In the proposed algorithm for each link that must be predicted there is one learning automaton and each learning automaton tries to predict the existence or non-existence of the corresponding link. To predict the link occurrence in time T, there is a chain consists of stages 1 through T - 1 and the learning automaton passes from these stages to learn the existence or non-existence of the corresponding link. Our preliminary link prediction experiments with co-authorship and email networks have provided satisfactory results when time series link occurrences are considered.
Long-memory time series theory and methods
Palma, Wilfredo
2007-01-01
Wilfredo Palma, PhD, is Chairman and Professor of Statistics in the Department of Statistics at Pontificia Universidad Católica de Chile. Dr. Palma has published several refereed articles and has received over a dozen academic honors and awards. His research interests include time series analysis, prediction theory, state space systems, linear models, and econometrics.
A deep level set method for image segmentation
Tang, Min; Valipour, Sepehr; Zhang, Zichen Vincent; Cobzas, Dana; MartinJagersand
2017-01-01
This paper proposes a novel image segmentation approachthat integrates fully convolutional networks (FCNs) with a level setmodel. Compared with a FCN, the integrated method can incorporatesmoothing and prior information to achieve an accurate segmentation.Furthermore, different than using the level set model as a post-processingtool, we integrate it into the training phase to fine-tune the FCN. Thisallows the use of unlabeled data during training in a semi-supervisedsetting. Using two types o...
Winter Holts Oscillatory Method: A New Method of Resampling in Time Series.
Directory of Open Access Journals (Sweden)
Muhammad Imtiaz Subhani
2016-12-01
Full Text Available The core proposition behind this research is to create innovative methods of bootstrapping that can be applied in time series data. In order to find new methods of bootstrapping, various methods were reviewed; The data of automotive Sales, Market Shares and Net Exports of the top 10 countries, which includes China, Europe, United States of America (USA, Japan, Germany, South Korea, India, Mexico, Brazil, Spain and, Canada from 2002 to 2014 were collected through various sources which includes UN Comtrade, Index Mundi and World Bank. The findings of this paper confirmed that Bootstrapping for resampling through winter forecasting by Oscillation and Average methods give more robust results than the winter forecasting by any general methods.
A working-set framework for sequential convex approximation methods
DEFF Research Database (Denmark)
Stolpe, Mathias
2008-01-01
We present an active-set algorithmic framework intended as an extension to existing implementations of sequential convex approximation methods for solving nonlinear inequality constrained programs. The framework is independent of the choice of approximations and the stabilization technique used...... to guarantee global convergence of the method. The algorithm works directly on the nonlinear constraints in the convex sub-problems and solves a sequence of relaxations of the current sub-problem. The algorithm terminates with the optimal solution to the sub-problem after solving a finite number of relaxations....
Nonlinear time series theory, methods and applications with R examples
Douc, Randal; Stoffer, David
2014-01-01
FOUNDATIONSLinear ModelsStochastic Processes The Covariance World Linear Processes The Multivariate Cases Numerical Examples ExercisesLinear Gaussian State Space Models Model Basics Filtering, Smoothing, and Forecasting Maximum Likelihood Estimation Smoothing Splines and the Kalman Smoother Asymptotic Distribution of the MLE Missing Data Modifications Structural Component Models State-Space Models with Correlated Errors Exercises Beyond Linear ModelsNonlinear Non-Gaussian Data Volterra Series Expansion Cumulants and Higher-Order Spectra Bilinear Models Conditionally Heteroscedastic Models Thre
GenoSets: visual analytic methods for comparative genomics.
Directory of Open Access Journals (Sweden)
Aurora A Cain
Full Text Available Many important questions in biology are, fundamentally, comparative, and this extends to our analysis of a growing number of sequenced genomes. Existing genomic analysis tools are often organized around literal views of genomes as linear strings. Even when information is highly condensed, these views grow cumbersome as larger numbers of genomes are added. Data aggregation and summarization methods from the field of visual analytics can provide abstracted comparative views, suitable for sifting large multi-genome datasets to identify critical similarities and differences. We introduce a software system for visual analysis of comparative genomics data. The system automates the process of data integration, and provides the analysis platform to identify and explore features of interest within these large datasets. GenoSets borrows techniques from business intelligence and visual analytics to provide a rich interface of interactive visualizations supported by a multi-dimensional data warehouse. In GenoSets, visual analytic approaches are used to enable querying based on orthology, functional assignment, and taxonomic or user-defined groupings of genomes. GenoSets links this information together with coordinated, interactive visualizations for both detailed and high-level categorical analysis of summarized data. GenoSets has been designed to simplify the exploration of multiple genome datasets and to facilitate reasoning about genomic comparisons. Case examples are included showing the use of this system in the analysis of 12 Brucella genomes. GenoSets software and the case study dataset are freely available at http://genosets.uncc.edu. We demonstrate that the integration of genomic data using a coordinated multiple view approach can simplify the exploration of large comparative genomic data sets, and facilitate reasoning about comparisons and features of interest.
Gradient augmented level set method for phase change simulations
Anumolu, Lakshman; Trujillo, Mario F.
2018-01-01
A numerical method for the simulation of two-phase flow with phase change based on the Gradient-Augmented-Level-set (GALS) strategy is presented. Sharp capturing of the vaporization process is enabled by: i) identification of the vapor-liquid interface, Γ (t), at the subgrid level, ii) discontinuous treatment of thermal physical properties (except for μ), and iii) enforcement of mass, momentum, and energy jump conditions, where the gradients of the dependent variables are obtained at Γ (t) and are consistent with their analytical expression, i.e. no local averaging is applied. Treatment of the jump in velocity and pressure at Γ (t) is achieved using the Ghost Fluid Method. The solution of the energy equation employs the sub-grid knowledge of Γ (t) to discretize the temperature Laplacian using second-order one-sided differences, i.e. the numerical stencil completely resides within each respective phase. To carefully evaluate the benefits or disadvantages of the GALS approach, the standard level set method is implemented and compared against the GALS predictions. The results show the expected trend that interface identification and transport are predicted noticeably better with GALS over the standard level set. This benefit carries over to the prediction of the Laplacian and temperature gradients in the neighborhood of the interface, which are directly linked to the calculation of the vaporization rate. However, when combining the calculation of interface transport and reinitialization with two-phase momentum and energy, the benefits of GALS are to some extent neutralized, and the causes for this behavior are identified and analyzed. Overall the additional computational costs associated with GALS are almost the same as those using the standard level set technique.
A SPIRAL-BASED DOWNSCALING METHOD FOR GENERATING 30 M TIME SERIES IMAGE DATA
Directory of Open Access Journals (Sweden)
B. Liu
2017-09-01
Full Text Available The spatial detail and updating frequency of land cover data are important factors influencing land surface dynamic monitoring applications in high spatial resolution scale. However, the fragmentized patches and seasonal variable of some land cover types (e. g. small crop field, wetland make it labor-intensive and difficult in the generation of land cover data. Utilizing the high spatial resolution multi-temporal image data is a possible solution. Unfortunately, the spatial and temporal resolution of available remote sensing data like Landsat or MODIS datasets can hardly satisfy the minimum mapping unit and frequency of current land cover mapping / updating at the same time. The generation of high resolution time series may be a compromise to cover the shortage in land cover updating process. One of popular way is to downscale multi-temporal MODIS data with other high spatial resolution auxiliary data like Landsat. But the usual manner of downscaling pixel based on a window may lead to the underdetermined problem in heterogeneous area, result in the uncertainty of some high spatial resolution pixels. Therefore, the downscaled multi-temporal data can hardly reach high spatial resolution as Landsat data. A spiral based method was introduced to downscale low spatial and high temporal resolution image data to high spatial and high temporal resolution image data. By the way of searching the similar pixels around the adjacent region based on the spiral, the pixel set was made up in the adjacent region pixel by pixel. The underdetermined problem is prevented to a large extent from solving the linear system when adopting the pixel set constructed. With the help of ordinary least squares, the method inverted the endmember values of linear system. The high spatial resolution image was reconstructed on the basis of high spatial resolution class map and the endmember values band by band. Then, the high spatial resolution time series was formed with these
SET: A Pupil Detection Method Using Sinusoidal Approximation
Directory of Open Access Journals (Sweden)
Amir-Homayoun eJavadi
2015-04-01
Full Text Available Mobile eye-tracking in external environments remains challenging, despite recent advances in eye-tracking software and hardware engineering. Many current methods fail to deal with the vast range of outdoor lighting conditions and the speed at which these can change. This confines experiments to artificial environments where conditions must be tightly controlled. Additionally, the emergence of low-cost eye tracking devices calls for the development of analysis tools that enable non-technical researchers to process the output of their images. We have developed a fast and accurate method (known as ‘SET’ that is suitable even for natural environments with uncontrolled, dynamic and even extreme lighting conditions. We compared the performance of SET with that of two open-source alternatives by processing two collections of eye images: images of natural outdoor scenes with extreme lighting variations (‘Natural’; and images of less challenging indoor scenes (‘CASIA-Iris-Thousand’. We show that SET excelled in outdoor conditions and was faster, without significant loss of accuracy, indoors. SET offers a low cost eye-tracking solution, delivering high performance even in challenging outdoor environments. It is offered through an open-source MATLAB toolkit as well as a dynamic-link library (‘DLL’, which can be imported into many programming languages including C# and Visual Basic in Windows OS (www.eyegoeyetracker.co.uk.
[Teaching methods for clinical settings: a literature review].
Brugnolli, Anna; Benaglio, Carla
2017-01-01
. Teaching Methods for clinical settings: a review. The teaching process during internship requires several methods to promote the acquisition of more complex technical skills such as relational, decisional and planning abilities. To describe effective teaching methods to promote the learning of relational, decisional and planning skills. A literature review of the teaching methods that have proven most effective, most appreciated by students, and most frequently used in Italian nursing schools. Clinical teaching is a central element to transform clinical experiences during internship in professional competences. The students are gradually brought to become more independent, because they are offered opportunities to practice in real contexts, to receive feedback, to have positive role models, to become more autonomous: all elements that facilitate and potentiate learning. Clinical teaching should be based on a variety of methods. The students value a gradual progression both in clinical experiences and teaching strategies from more supervised methods to methods more oriented towards reflecting on clinical practice and self-directed learning.
Basis set approach in the constrained interpolation profile method
International Nuclear Information System (INIS)
Utsumi, T.; Koga, J.; Yabe, T.; Ogata, Y.; Matsunaga, E.; Aoki, T.; Sekine, M.
2003-07-01
We propose a simple polynomial basis-set that is easily extendable to any desired higher-order accuracy. This method is based on the Constrained Interpolation Profile (CIP) method and the profile is chosen so that the subgrid scale solution approaches the real solution by the constraints from the spatial derivative of the original equation. Thus the solution even on the subgrid scale becomes consistent with the master equation. By increasing the order of the polynomial, this solution quickly converges. 3rd and 5th order polynomials are tested on the one-dimensional Schroedinger equation and are proved to give solutions a few orders of magnitude higher in accuracy than conventional methods for lower-lying eigenstates. (author)
Optimisation-Based Solution Methods for Set Partitioning Models
DEFF Research Database (Denmark)
Rasmussen, Matias Sevel
The scheduling of crew, i.e. the construction of work schedules for crew members, is often not a trivial task, but a complex puzzle. The task is complicated by rules, restrictions, and preferences. Therefore, manual solutions as well as solutions from standard software packages are not always su......_cient with respect to solution quality and solution time. Enhancement of the overall solution quality as well as the solution time can be of vital importance to many organisations. The _elds of operations research and mathematical optimisation deal with mathematical modelling of di_cult scheduling problems (among...... other topics). The _elds also deal with the development of sophisticated solution methods for these mathematical models. This thesis describes the set partitioning model which has been widely used for modelling crew scheduling problems. Integer properties for the set partitioning model are shown...
Magri, Alphonso William
algorithm. The best-fit parameters were used to create 3D parametric images. Compartmental modeling evaluation was based on the ability of parameter values to differentiate between tissue types. This evaluation was used on registered and unregistered image series and found that registration improved results. (5) PET and MR parametric images were registered through FEM- and FFD-based registration. Parametric image registration was evaluated using similarity measurements, target registration error, and qualitative comparison. Comparing FFD and FEM-based registration results showed that the FEM method is superior. This five-step process constitutes a novel multifaceted approach to a nonsurgical breast biopsy that successfully executes each step. Comparison of this method to biopsy still needs to be done with a larger set of subject data.
Setting health research priorities using the CHNRI method: III. Involving stakeholders
Directory of Open Access Journals (Sweden)
Sachiyo Yoshida
2016-06-01
Full Text Available Setting health research priorities is a complex and value–driven process. The introduction of the Child Health and Nutrition Research Initiative (CHNRI method has made the process of setting research priorities more transparent and inclusive, but much of the process remains in the hands of funders and researchers, as described in the previous two papers in this series. However, the value systems of numerous other important stakeholders, particularly those on the receiving end of health research products, are very rarely addressed in any process of priority setting. Inclusion of a larger and more diverse group of stakeholders in the process would result in a better reflection of the system of values of the broader community, resulting in recommendations that are more legitimate and acceptable.
Trend analysis using non-stationary time series clustering based on the finite element method
Gorji Sefidmazgi, M.; Sayemuzzaman, M.; Homaifar, A.; Jha, M. K.; Liess, S.
2014-01-01
In order to analyze low-frequency variability of climate, it is useful to model the climatic time series with multiple linear trends and locate the times of significant changes. In this paper, we have used non-stationary time series clustering to find change points in the trends. Clustering in a multi-dimensional non-stationary time series is challenging, since the problem is mathematically ill-posed. Clustering based on the finite element method (FEM) is one of the methods ...
Analysis method set up to check against adulterated export honey
International Nuclear Information System (INIS)
Lyon, G.L.
2001-01-01
Over the past few years, North America has experienced occasional problems with the adulteration of honey, mainly by additions of other, cheaper sugar to increase bulk and lower production costs. The main addition was usually high fructose corn syrup, which had a similar chemical composition to that of honey. As a consequence of this type of adulteration, a method for its detection was developed using isotope ratio mass spectroscopy (IRMS). This was later refined to be more sensitive and is now specified as an Official Test. The Institute of Geological and Nuclear Sciences has now set up the analysis method to the international criteria at the Rafter Stable Isotope Laboratory in Lower Hutt. 2 refs
The Interval-Valued Triangular Fuzzy Soft Set and Its Method of Dynamic Decision Making
Directory of Open Access Journals (Sweden)
Xiaoguo Chen
2014-01-01
Full Text Available A concept of interval-valued triangular fuzzy soft set is presented, and some operations of “AND,” “OR,” intersection, union and complement, and so forth are defined. Then some relative properties are discussed and several conclusions are drawn. A dynamic decision making model is built based on the definition of interval-valued triangular fuzzy soft set, in which period weight is determined by the exponential decay method. The arithmetic weighted average operator of interval-valued triangular fuzzy soft set is given by the aggregating thought, thereby aggregating interval-valued triangular fuzzy soft sets of different time-series into a collective interval-valued triangular fuzzy soft set. The formulas of selection and decision values of different objects are given; therefore the optimal decision making is achieved according to the decision values. Finally, the steps of this method are concluded, and one example is given to explain the application of the method.
Takotsubo Cardiomyopathy in the Setting of Immersion Pulmonary Edema: Case Series
Reed, Tara; Sorrentino, Dante; Azuma, Steven
2015-01-01
Immersion Pulmonary Edema is a unique medical condition being increasingly described in the medical literature as sudden-onset pulmonary edema in the setting of scuba diving and or swimming. Case reports have associated immersion pulmonary edema with cardiac dysfunction, but there are no known case reports describing submersion pulmonary edema resulting in Takotsubo cardiomyopathy. We report on three patients with unique presentations of immersion pulmonary edema with associated Takotsubo car...
A comparison of cosegregation analysis methods for the clinical setting.
Rañola, John Michael O; Liu, Quanhui; Rosenthal, Elisabeth A; Shirts, Brian H
2018-04-01
Quantitative cosegregation analysis can help evaluate the pathogenicity of genetic variants. However, genetics professionals without statistical training often use simple methods, reporting only qualitative findings. We evaluate the potential utility of quantitative cosegregation in the clinical setting by comparing three methods. One thousand pedigrees each were simulated for benign and pathogenic variants in BRCA1 and MLH1 using United States historical demographic data to produce pedigrees similar to those seen in the clinic. These pedigrees were analyzed using two robust methods, full likelihood Bayes factors (FLB) and cosegregation likelihood ratios (CSLR), and a simpler method, counting meioses. Both FLB and CSLR outperform counting meioses when dealing with pathogenic variants, though counting meioses is not far behind. For benign variants, FLB and CSLR greatly outperform as counting meioses is unable to generate evidence for benign variants. Comparing FLB and CSLR, we find that the two methods perform similarly, indicating that quantitative results from either of these methods could be combined in multifactorial calculations. Combining quantitative information will be important as isolated use of cosegregation in single families will yield classification for less than 1% of variants. To encourage wider use of robust cosegregation analysis, we present a website ( http://www.analyze.myvariant.org ) which implements the CSLR, FLB, and Counting Meioses methods for ATM, BRCA1, BRCA2, CHEK2, MEN1, MLH1, MSH2, MSH6, and PMS2. We also present an R package, CoSeg, which performs the CSLR analysis on any gene with user supplied parameters. Future variant classification guidelines should allow nuanced inclusion of cosegregation evidence against pathogenicity.
CUDA based Level Set Method for 3D Reconstruction of Fishes from Large Acoustic Data
DEFF Research Database (Denmark)
Sharma, Ojaswa; Anton, François
2009-01-01
Acoustic images present views of underwater dynamics, even in high depths. With multi-beam echo sounders (SONARs), it is possible to capture series of 2D high resolution acoustic images. 3D reconstruction of the water column and subsequent estimation of fish abundance and fish species identificat...... of suppressing threshold and show its convergence as the evolution proceeds. We also present a GPU based streaming computation of the method using NVIDIA's CUDA framework to handle large volume data-sets. Our implementation is optimised for memory usage to handle large volumes....
Empirical method to measure stochasticity and multifractality in nonlinear time series
Lin, Chih-Hao; Chang, Chia-Seng; Li, Sai-Ping
2013-12-01
An empirical algorithm is used here to study the stochastic and multifractal nature of nonlinear time series. A parameter can be defined to quantitatively measure the deviation of the time series from a Wiener process so that the stochasticity of different time series can be compared. The local volatility of the time series under study can be constructed using this algorithm, and the multifractal structure of the time series can be analyzed by using this local volatility. As an example, we employ this method to analyze financial time series from different stock markets. The result shows that while developed markets evolve very much like an Ito process, the emergent markets are far from efficient. Differences about the multifractal structures and leverage effects between developed and emergent markets are discussed. The algorithm used here can be applied in a similar fashion to study time series of other complex systems.
The ab initio model potential method. Second series transition metal elements
International Nuclear Information System (INIS)
Barandiaran, Z.; Seijo, L.; Huzinaga, S.
1990-01-01
The ab initio core method potential model (AIMP) has already been presented in its nonrelativistic version and applied to the main group and first series transition metal elements [J. Chem. Phys. 86, 2132 (1987); 91, 7011 (1989)]. In this paper we extend the AIMP method to include relativistic effects within the Cowan--Griffin approximation and we present relativistic Zn-like core model potentials and valence basis sets, as well as their nonrelativistic Zn-like core and Kr-like core counterparts. The pilot molecular calculations on YO, TcO, AgO, and AgH reveal that the 4p orbital is indeed a core orbital only at the end part of the series, whereas the 4s orbital can be safely frozen from Y to Cd. The all-electron and model potential results agree in 0.01--0.02 A in R e and 25--50 cm -1 in bar ν e if the same type of valence part of the basis set is used. The comparison of the relativistic results on AgH with those of the all-electron Dirac--Fock calculations by Lee and McLean is satisfactory: the absolute value of R e is reproduced within the 0.01 A margin and the relativistic contraction of 0.077 A is also very well reproduced (0.075 A). Finally, the relative magnitude of the effects of the core orbital change, mass--velocity potential, and Darwin potential on the net relativistic effects are analyzed in the four molecules studied
Trend analysis using non-stationary time series clustering based on the finite element method
Gorji Sefidmazgi, M.; Sayemuzzaman, M.; Homaifar, A.; Jha, M. K.; Liess, S.
2014-05-01
In order to analyze low-frequency variability of climate, it is useful to model the climatic time series with multiple linear trends and locate the times of significant changes. In this paper, we have used non-stationary time series clustering to find change points in the trends. Clustering in a multi-dimensional non-stationary time series is challenging, since the problem is mathematically ill-posed. Clustering based on the finite element method (FEM) is one of the methods that can analyze multidimensional time series. One important attribute of this method is that it is not dependent on any statistical assumption and does not need local stationarity in the time series. In this paper, it is shown how the FEM-clustering method can be used to locate change points in the trend of temperature time series from in situ observations. This method is applied to the temperature time series of North Carolina (NC) and the results represent region-specific climate variability despite higher frequency harmonics in climatic time series. Next, we investigated the relationship between the climatic indices with the clusters/trends detected based on this clustering method. It appears that the natural variability of climate change in NC during 1950-2009 can be explained mostly by AMO and solar activity.
Low-derivative operators of the Standard Model effective field theory via Hilbert series methods
Energy Technology Data Exchange (ETDEWEB)
Lehman, Landon; Martin, Adam [Department of Physics, University of Notre Dame,Nieuwland Science Hall, Notre Dame, IN 46556 (United States)
2016-02-12
In this work, we explore an extension of Hilbert series techniques to count operators that include derivatives. For sufficiently low-derivative operators, we conjecture an algorithm that gives the number of invariant operators, properly accounting for redundancies due to the equations of motion and integration by parts. Specifically, the conjectured technique can be applied whenever there is only one Lorentz invariant for a given partitioning of derivatives among the fields. At higher numbers of derivatives, equation of motion redundancies can be removed, but the increased number of Lorentz contractions spoils the subtraction of integration by parts redundancies. While restricted, this technique is sufficient to automatically recreate the complete set of invariant operators of the Standard Model effective field theory for dimensions 6 and 7 (for arbitrary numbers of flavors). At dimension 8, the algorithm does not automatically generate the complete operator set; however, it suffices for all but five classes of operators. For these remaining classes, there is a well defined procedure to manually determine the number of invariants. Assuming our method is correct, we derive a set of 535 dimension-8 N{sub f}=1 operators.
Low-derivative operators of the Standard Model effective field theory via Hilbert series methods
International Nuclear Information System (INIS)
Lehman, Landon; Martin, Adam
2016-01-01
In this work, we explore an extension of Hilbert series techniques to count operators that include derivatives. For sufficiently low-derivative operators, we conjecture an algorithm that gives the number of invariant operators, properly accounting for redundancies due to the equations of motion and integration by parts. Specifically, the conjectured technique can be applied whenever there is only one Lorentz invariant for a given partitioning of derivatives among the fields. At higher numbers of derivatives, equation of motion redundancies can be removed, but the increased number of Lorentz contractions spoils the subtraction of integration by parts redundancies. While restricted, this technique is sufficient to automatically recreate the complete set of invariant operators of the Standard Model effective field theory for dimensions 6 and 7 (for arbitrary numbers of flavors). At dimension 8, the algorithm does not automatically generate the complete operator set; however, it suffices for all but five classes of operators. For these remaining classes, there is a well defined procedure to manually determine the number of invariants. Assuming our method is correct, we derive a set of 535 dimension-8 N_f=1 operators.
Series: Utilization of Differential Equations and Methods for Solving Them in Medical Physics (4).
Murase, Kenya
2016-01-01
Partial differential equations are often used in the field of medical physics. In this (final) issue, the methods for solving the partial differential equations were introduced, which include separation of variables, integral transform (Fourier and Fourier-sine transforms), Green's function, and series expansion methods. Some examples were also introduced, in which the integral transform and Green's function methods were applied to solving Pennes' bioheat transfer equation and the Fourier series expansion method was applied to Navier-Stokes equation for analyzing the wall shear stress in blood vessels.Finally, the author hopes that this series will be helpful for people who engage in medical physics.
Methods for evaluating cervical range of motion in trauma settings
Directory of Open Access Journals (Sweden)
Voss Sarah
2012-08-01
Full Text Available Abstract Immobilisation of the cervical spine is a common procedure following traumatic injury. This is often precautionary as the actual incidence of spinal injury is low. Nonetheless, stabilisation of the head and neck is an important part of pre-hospital care due to the catastrophic damage that may follow if further unrestricted movement occurs in the presence of an unstable spinal injury. Currently available collars are limited by the potential for inadequate immobilisation and complications caused by pressure on the patient’s skin, restricted airway access and compression of the jugular vein. Alternative approaches to cervical spine immobilisation are being considered, and the investigation of these new methods requires a standardised approach to the evaluation of neck movement. This review summarises the research methods and scientific technology that have been used to assess and measure cervical range of motion, and which are likely to underpin future research in this field. A systematic search of international literature was conducted to evaluate the methodologies used to assess the extremes of movement that can be achieved in six domains. 34 papers were included in the review. These studies used a range of methodologies, but study quality was generally low. Laboratory investigations and biomechanical studies have gradually given way to methods that more accurately reflect the real-life situations in which cervical spine immobilisation occurs. Latterly, new approaches using virtual reality and simulation have been developed. Coupled with modern electromagnetic tracking technology this has considerable potential for effective application in future research. However, use of these technologies in real life settings can be problematic and more research is needed.
Topology optimization of hyperelastic structures using a level set method
Chen, Feifei; Wang, Yiqiang; Wang, Michael Yu; Zhang, Y. F.
2017-12-01
Soft rubberlike materials, due to their inherent compliance, are finding widespread implementation in a variety of applications ranging from assistive wearable technologies to soft material robots. Structural design of such soft and rubbery materials necessitates the consideration of large nonlinear deformations and hyperelastic material models to accurately predict their mechanical behaviour. In this paper, we present an effective level set-based topology optimization method for the design of hyperelastic structures that undergo large deformations. The method incorporates both geometric and material nonlinearities where the strain and stress measures are defined within the total Lagrange framework and the hyperelasticity is characterized by the widely-adopted Mooney-Rivlin material model. A shape sensitivity analysis is carried out, in the strict sense of the material derivative, where the high-order terms involving the displacement gradient are retained to ensure the descent direction. As the design velocity enters into the shape derivative in terms of its gradient and divergence terms, we develop a discrete velocity selection strategy. The whole optimization implementation undergoes a two-step process, where the linear optimization is first performed and its optimized solution serves as the initial design for the subsequent nonlinear optimization. It turns out that this operation could efficiently alleviate the numerical instability and facilitate the optimization process. To demonstrate the validity and effectiveness of the proposed method, three compliance minimization problems are studied and their optimized solutions present significant mechanical benefits of incorporating the nonlinearities, in terms of remarkable enhancement in not only the structural stiffness but also the critical buckling load.
Comparison of transfer entropy methods for financial time series
He, Jiayi; Shang, Pengjian
2017-09-01
There is a certain relationship between the global financial markets, which creates an interactive network of global finance. Transfer entropy, a measurement for information transfer, offered a good way to analyse the relationship. In this paper, we analysed the relationship between 9 stock indices from the U.S., Europe and China (from 1995 to 2015) by using transfer entropy (TE), effective transfer entropy (ETE), Rényi transfer entropy (RTE) and effective Rényi transfer entropy (ERTE). We compared the four methods in the sense of the effectiveness for identification of the relationship between stock markets. In this paper, two kinds of information flows are given. One reveals that the U.S. took the leading position when in terms of lagged-current cases, but when it comes to the same date, China is the most influential. And ERTE could provide superior results.
Reliability Quantification Method for Safety Critical Software Based on a Finite Test Set
International Nuclear Information System (INIS)
Shin, Sung Min; Kim, Hee Eun; Kang, Hyun Gook; Lee, Seung Jun
2014-01-01
Software inside of digitalized system have very important role because it may cause irreversible consequence and affect the whole system as common cause failure. However, test-based reliability quantification method for some safety critical software has limitations caused by difficulties in developing input sets as a form of trajectory which is series of successive values of variables. To address these limitations, this study proposed another method which conduct the test using combination of single values of variables. To substitute the trajectory form of input using combination of variables, the possible range of each variable should be identified. For this purpose, assigned range of each variable, logical relations between variables, plant dynamics under certain situation, and characteristics of obtaining information of digital device are considered. A feasibility of the proposed method was confirmed through an application to the Reactor Protection System (RPS) software trip logic
International Nuclear Information System (INIS)
Corana, A.; Bortolan, G.; Casaleggio, A.
2004-01-01
We present and compare two automatic methods for dimension estimation from time series. Both methods, based on conceptually different approaches, work on the derivative of the bi-logarithmic plot of the correlation integral versus the correlation length (log-log plot). The first method searches for the most probable dimension values (MPDV) and associates to each of them a possible scaling region. The second one searches for the most flat intervals (MFI) in the derivative of the log-log plot. The automatic procedures include the evaluation of the candidate scaling regions using two reliability indices. The data set used to test the methods consists of time series from known model attractors with and without the addition of noise, structured time series, and electrocardiographic signals from the MIT-BIH ECG database. Statistical analysis of results was carried out by means of paired t-test, and no statistically significant differences were found in the large majority of the trials. Consistent results are also obtained dealing with 'difficult' time series. In general for a more robust and reliable estimate, the use of both methods may represent a good solution when time series from complex systems are analyzed. Although we present results for the correlation dimension only, the procedures can also be used for the automatic estimation of generalized q-order dimensions and pointwise dimension. We think that the proposed methods, eliminating the need of operator intervention, allow a faster and more objective analysis, thus improving the usefulness of dimension analysis for the characterization of time series obtained from complex dynamical systems
Rough sets selected methods and applications in management and engineering
Peters, Georg; Ślęzak, Dominik; Yao, Yiyu
2012-01-01
Introduced in the early 1980s, Rough Set Theory has become an important part of soft computing in the last 25 years. This book provides a practical, context-based analysis of rough set theory, with each chapter exploring a real-world application of Rough Sets.
Finite test sets development method for test execution of safety critical software
International Nuclear Information System (INIS)
Shin, Sung Min; Kim, Hee Eun; Kang, Hyun Gook; Lee, Sung Jiun
2014-01-01
The V and V method has been utilized for this safety critical software, while SRGM has difficulties because of lack of failure occurrence data on developing phase. For the safety critical software, however, failure data cannot be gathered after installation in real plant when we consider the severe consequence. Therefore, to complement the V and V method, the test-based method need to be developed. Some studies on test-based reliability quantification method for safety critical software have been conducted in nuclear field. These studies provide useful guidance on generating test sets. An important concept of the guidance is that the test sets represent 'trajectories' (a series of successive values for the input variables of a program that occur during the operation of the software over time) in the space of inputs to the software.. Actually, the inputs to the software depends on the state of plant at that time, and these inputs form a new internal state of the software by changing values of some variables. In other words, internal state of the software at specific timing depends on the history of past inputs. Here the internal state of the software which can be changed by past inputs is named as Context of Software (CoS). In a certain CoS, a software failure occurs when a fault is triggered by some inputs. To cover the failure occurrence mechanism of a software, preceding researches insist that the inputs should be a trajectory form. However, in this approach, there are two critical problems. One is the length of the trajectory input. Input trajectory should long enough to cover failure mechanism, but the enough length is not clear. What is worse, to cover some accident scenario, one set of input should represent dozen hours of successive values. The other problem is number of tests needed. To satisfy a target reliability with reasonable confidence level, very large number of test sets are required. Development of this number of test sets is a herculean
Predictive Active Set Selection Methods for Gaussian Processes
DEFF Research Database (Denmark)
Henao, Ricardo; Winther, Ole
2012-01-01
We propose an active set selection framework for Gaussian process classification for cases when the dataset is large enough to render its inference prohibitive. Our scheme consists of a two step alternating procedure of active set update rules and hyperparameter optimization based upon marginal...... high impact to the classifier decision process while removing those that are less relevant. We introduce two active set rules based on different criteria, the first one prefers a model with interpretable active set parameters whereas the second puts computational complexity first, thus a model...... with active set parameters that directly control its complexity. We also provide both theoretical and empirical support for our active set selection strategy being a good approximation of a full Gaussian process classifier. Our extensive experiments show that our approach can compete with state...
A prediction method based on wavelet transform and multiple models fusion for chaotic time series
International Nuclear Information System (INIS)
Zhongda, Tian; Shujiang, Li; Yanhong, Wang; Yi, Sha
2017-01-01
In order to improve the prediction accuracy of chaotic time series, a prediction method based on wavelet transform and multiple models fusion is proposed. The chaotic time series is decomposed and reconstructed by wavelet transform, and approximate components and detail components are obtained. According to different characteristics of each component, least squares support vector machine (LSSVM) is used as predictive model for approximation components. At the same time, an improved free search algorithm is utilized for predictive model parameters optimization. Auto regressive integrated moving average model (ARIMA) is used as predictive model for detail components. The multiple prediction model predictive values are fusion by Gauss–Markov algorithm, the error variance of predicted results after fusion is less than the single model, the prediction accuracy is improved. The simulation results are compared through two typical chaotic time series include Lorenz time series and Mackey–Glass time series. The simulation results show that the prediction method in this paper has a better prediction.
Angular quadrature sets for the streaming ray method in x-y geometry
International Nuclear Information System (INIS)
England, R.; Filippone, W.L.
1983-01-01
Steaming ray (SR) computations normally employ a set of specially selected ray directions. For x-y geometry, these directions are not uniformly spaced in the azimuthal angle, nor do they conform to any of the standard quadrature sets in current use. For simplicity in all previous SR computations, uniform angular weights were used. This note investigates two methods--a bisection scheme and a Fourier scheme--for selecting more appropriate azimuthal angular weights. In the bisection scheme, the azimuthal weight assigned to an SR direction is half the angular spread (in the x-y plane) between its two adjacent ray directions. In the Fourier method, the weights are chosen such that the number of terms in a Fourier series exactly integrable on the interval (0, 2π) is maximized. Several sample calculations have been performed. While both the Fourier and bisection weights showed significant advantage over the uniform weights used previously, the Fourier scheme appears to be the best method. Lists of bisection and Fourier weights are given for quadrature sets containing 4, 8, 12, ..., 60 azimuthal SR directions
Directory of Open Access Journals (Sweden)
Guo Zheng-Hong
2016-01-01
Full Text Available In this article, the Sumudu transform series expansion method is used to handle the local fractional Laplace equation arising in the steady fractal heat-transfer problem via local fractional calculus.
A multiple-scale power series method for solving nonlinear ordinary differential equations
Directory of Open Access Journals (Sweden)
Chein-Shan Liu
2016-02-01
Full Text Available The power series solution is a cheap and effective method to solve nonlinear problems, like the Duffing-van der Pol oscillator, the Volterra population model and the nonlinear boundary value problems. A novel power series method by considering the multiple scales $R_k$ in the power term $(t/R_k^k$ is developed, which are derived explicitly to reduce the ill-conditioned behavior in the data interpolation. In the method a huge value times a tiny value is avoided, such that we can decrease the numerical instability and which is the main reason to cause the failure of the conventional power series method. The multiple scales derived from an integral can be used in the power series expansion, which provide very accurate numerical solutions of the problems considered in this paper.
A large set of potential past, present and future hydro-meteorological time series for the UK
Directory of Open Access Journals (Sweden)
B. P. Guillod
2018-01-01
Full Text Available Hydro-meteorological extremes such as drought and heavy precipitation can have large impacts on society and the economy. With potentially increasing risks associated with such events due to climate change, properly assessing the associated impacts and uncertainties is critical for adequate adaptation. However, the application of risk-based approaches often requires large sets of extreme events, which are not commonly available. Here, we present such a large set of hydro-meteorological time series for recent past and future conditions for the United Kingdom based on weather@home 2, a modelling framework consisting of a global climate model (GCM driven by observed or projected sea surface temperature (SST and sea ice which is downscaled to 25 km over the European domain by a regional climate model (RCM. Sets of 100 time series are generated for each of (i a historical baseline (1900–2006, (ii five near-future scenarios (2020–2049 and (iii five far-future scenarios (2070–2099. The five scenarios in each future time slice all follow the Representative Concentration Pathway 8.5 (RCP8.5 and sample the range of sea surface temperature and sea ice changes from CMIP5 (Coupled Model Intercomparison Project Phase 5 models. Validation of the historical baseline highlights good performance for temperature and potential evaporation, but substantial seasonal biases in mean precipitation, which are corrected using a linear approach. For extremes in low precipitation over a long accumulation period ( > 3 months and shorter-duration high precipitation (1–30 days, the time series generally represents past statistics well. Future projections show small precipitation increases in winter but large decreases in summer on average, leading to an overall drying, consistently with the most recent UK Climate Projections (UKCP09 but larger in magnitude than the latter. Both drought and high-precipitation events are projected to increase in frequency and
A large set of potential past, present and future hydro-meteorological time series for the UK
Guillod, Benoit P.; Jones, Richard G.; Dadson, Simon J.; Coxon, Gemma; Bussi, Gianbattista; Freer, James; Kay, Alison L.; Massey, Neil R.; Sparrow, Sarah N.; Wallom, David C. H.; Allen, Myles R.; Hall, Jim W.
2018-01-01
Hydro-meteorological extremes such as drought and heavy precipitation can have large impacts on society and the economy. With potentially increasing risks associated with such events due to climate change, properly assessing the associated impacts and uncertainties is critical for adequate adaptation. However, the application of risk-based approaches often requires large sets of extreme events, which are not commonly available. Here, we present such a large set of hydro-meteorological time series for recent past and future conditions for the United Kingdom based on weather@home 2, a modelling framework consisting of a global climate model (GCM) driven by observed or projected sea surface temperature (SST) and sea ice which is downscaled to 25 km over the European domain by a regional climate model (RCM). Sets of 100 time series are generated for each of (i) a historical baseline (1900-2006), (ii) five near-future scenarios (2020-2049) and (iii) five far-future scenarios (2070-2099). The five scenarios in each future time slice all follow the Representative Concentration Pathway 8.5 (RCP8.5) and sample the range of sea surface temperature and sea ice changes from CMIP5 (Coupled Model Intercomparison Project Phase 5) models. Validation of the historical baseline highlights good performance for temperature and potential evaporation, but substantial seasonal biases in mean precipitation, which are corrected using a linear approach. For extremes in low precipitation over a long accumulation period ( > 3 months) and shorter-duration high precipitation (1-30 days), the time series generally represents past statistics well. Future projections show small precipitation increases in winter but large decreases in summer on average, leading to an overall drying, consistently with the most recent UK Climate Projections (UKCP09) but larger in magnitude than the latter. Both drought and high-precipitation events are projected to increase in frequency and intensity in most regions
Localized atomic basis set in the projector augmented wave method
DEFF Research Database (Denmark)
Larsen, Ask Hjorth; Vanin, Marco; Mortensen, Jens Jørgen
2009-01-01
We present an implementation of localized atomic-orbital basis sets in the projector augmented wave (PAW) formalism within the density-functional theory. The implementation in the real-space GPAW code provides a complementary basis set to the accurate but computationally more demanding grid...
Lepot, M.J.; Aubin, Jean Baptiste; Clemens, F.H.L.R.
2017-01-01
A thorough review has been performed on interpolation methods to fill gaps in time-series, efficiency criteria, and uncertainty quantifications. On one hand, there are numerous available methods: interpolation, regression, autoregressive, machine learning methods, etc. On the other hand, there are
Trend analysis of time-series data: A novel method for untargeted metabolite discovery
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
DEFF Research Database (Denmark)
Sørup, Hjalte Jomo Danielsen; Georgiadis, Stylianos; Gregersen, Ida Bülow
2017-01-01
Urban water infrastructure has very long planning horizons, and planning is thus very dependent on reliable estimates of the impacts of climate change. Many urban water systems are designed using time series with a high temporal resolution. To assess the impact of climate change on these systems......, similarly high-resolution precipitation time series for future climate are necessary. Climate models cannot at their current resolutions provide these time series at the relevant scales. Known methods for stochastic downscaling of climate change to urban hydrological scales have known shortcomings...... in constructing realistic climate-changed precipitation time series at the sub-hourly scale. In the present study we present a deterministic methodology to perturb historical precipitation time series at the minute scale to reflect non-linear expectations to climate change. The methodology shows good skill...
Short-term prediction method of wind speed series based on fractal interpolation
International Nuclear Information System (INIS)
Xiu, Chunbo; Wang, Tiantian; Tian, Meng; Li, Yanqing; Cheng, Yi
2014-01-01
Highlights: • An improved fractal interpolation prediction method is proposed. • The chaos optimization algorithm is used to obtain the iterated function system. • The fractal extrapolate interpolation prediction of wind speed series is performed. - Abstract: In order to improve the prediction performance of the wind speed series, the rescaled range analysis is used to analyze the fractal characteristics of the wind speed series. An improved fractal interpolation prediction method is proposed to predict the wind speed series whose Hurst exponents are close to 1. An optimization function which is composed of the interpolation error and the constraint items of the vertical scaling factors in the fractal interpolation iterated function system is designed. The chaos optimization algorithm is used to optimize the function to resolve the optimal vertical scaling factors. According to the self-similarity characteristic and the scale invariance, the fractal extrapolate interpolation prediction can be performed by extending the fractal characteristic from internal interval to external interval. Simulation results show that the fractal interpolation prediction method can get better prediction result than others for the wind speed series with the fractal characteristic, and the prediction performance of the proposed method can be improved further because the fractal characteristic of its iterated function system is similar to that of the predicted wind speed series
Analytical one parameter method for PID motion controller settings
van Dijk, Johannes; Aarts, Ronald G.K.M.
2012-01-01
In this paper analytical expressions for PID-controllers settings for electromechanical motion systems are presented. It will be shown that by an adequate frequency domain oriented parametrization, the parameters of a PID-controller are analytically dependent on one variable only, the cross-over
Level set methods for inverse scattering—some recent developments
International Nuclear Information System (INIS)
Dorn, Oliver; Lesselier, Dominique
2009-01-01
We give an update on recent techniques which use a level set representation of shapes for solving inverse scattering problems, completing in that matter the exposition made in (Dorn and Lesselier 2006 Inverse Problems 22 R67) and (Dorn and Lesselier 2007 Deformable Models (New York: Springer) pp 61–90), and bringing it closer to the current state of the art
Improved time series prediction with a new method for selection of model parameters
International Nuclear Information System (INIS)
Jade, A M; Jayaraman, V K; Kulkarni, B D
2006-01-01
A new method for model selection in prediction of time series is proposed. Apart from the conventional criterion of minimizing RMS error, the method also minimizes the error on the distribution of singularities, evaluated through the local Hoelder estimates and its probability density spectrum. Predictions of two simulated and one real time series have been done using kernel principal component regression (KPCR) and model parameters of KPCR have been selected employing the proposed as well as the conventional method. Results obtained demonstrate that the proposed method takes into account the sharp changes in a time series and improves the generalization capability of the KPCR model for better prediction of the unseen test data. (letter to the editor)
Verger, Aleixandre; Baret, F.; Weiss, M.; Kandasamy, S.; Vermote, E.
2013-01-01
Consistent, continuous, and long time series of global biophysical variables derived from satellite data are required for global change research. A novel climatology fitting approach called CACAO (Consistent Adjustment of the Climatology to Actual Observations) is proposed to reduce noise and fill gaps in time series by scaling and shifting the seasonal climatological patterns to the actual observations. The shift and scale CACAO parameters adjusted for each season allow quantifying shifts in the timing of seasonal phenology and inter-annual variations in magnitude as compared to the average climatology. CACAO was assessed first over simulated daily Leaf Area Index (LAI) time series with varying fractions of missing data and noise. Then, performances were analyzed over actual satellite LAI products derived from AVHRR Long-Term Data Record for the 1981-2000 period over the BELMANIP2 globally representative sample of sites. Comparison with two widely used temporal filtering methods-the asymmetric Gaussian (AG) model and the Savitzky-Golay (SG) filter as implemented in TIMESAT-revealed that CACAO achieved better performances for smoothing AVHRR time series characterized by high level of noise and frequent missing observations. The resulting smoothed time series captures well the vegetation dynamics and shows no gaps as compared to the 50-60% of still missing data after AG or SG reconstructions. Results of simulation experiments as well as confrontation with actual AVHRR time series indicate that the proposed CACAO method is more robust to noise and missing data than AG and SG methods for phenology extraction.
Energy Technology Data Exchange (ETDEWEB)
Niehof, Jonathan T.; Morley, Steven K.
2012-01-01
We review and develop techniques to determine associations between series of discrete events. The bootstrap, a nonparametric statistical method, allows the determination of the significance of associations with minimal assumptions about the underlying processes. We find the key requirement for this method: one of the series must be widely spaced in time to guarantee the theoretical applicability of the bootstrap. If this condition is met, the calculated significance passes a reasonableness test. We conclude with some potential future extensions and caveats on the applicability of these methods. The techniques presented have been implemented in a Python-based software toolkit.
Residual power series method for fractional Sharma-Tasso-Olever equation
Directory of Open Access Journals (Sweden)
Amit Kumar
2016-02-01
Full Text Available In this paper, we introduce a modified analytical approximate technique to obtain solution of time fractional Sharma-Tasso-Olever equation. First, we present an alternative framework of the Residual power series method (RPSM which can be used simply and effectively to handle nonlinear fractional differential equations arising in several physical phenomena. This method is basically based on the generalized Taylor series formula and residual error function. A good result is found between our solution and the given solution. It is shown that the proposed method is reliable, efficient and easy to implement on all kinds of fractional nonlinear problems arising in science and technology.
International Nuclear Information System (INIS)
Voyant, Cyril; Motte, Fabrice; Fouilloy, Alexis; Notton, Gilles; Paoli, Christophe; Nivet, Marie-Laure
2017-01-01
Integration of unpredictable renewable energy sources into electrical networks intensifies the complexity of the grid management due to their intermittent and unforeseeable nature. Because of the strong increase of solar power generation the prediction of solar yields becomes more and more important. Electrical operators need an estimation of the future production. For nowcasting and short term forecasting, the usual technics based on machine learning need large historical data sets of good quality during the training phase of predictors. However data are not always available and induce an advanced maintenance of meteorological stations, making the method inapplicable for poor instrumented or isolated sites. In this work, we propose intuitive methodologies based on the Kalman filter use (also known as linear quadratic estimation), able to predict a global radiation time series without the need of historical data. The accuracy of these methods is compared to other classical data driven methods, for different horizons of prediction and time steps. The proposed approach shows interesting capabilities allowing to improve quasi-systematically the prediction. For one to 10 h horizons Kalman model performances are competitive in comparison to more sophisticated models such as ANN which require both consistent historical data sets and computational resources. - Highlights: • Solar radiation forecasting with time series formalism. • Trainless approach compared to machine learning methods. • Very simple method dedicated to solar irradiation forecasting with high accuracy.
Comparative evaluation of different methods of setting hygienic standards
International Nuclear Information System (INIS)
Ramzaev, P.V.; Rodionova, L.F.; Mashneva, N.I.
1978-01-01
Long-term experiments were carried out on white mice and rats to study the relative importance of various procedures used in setting hygienic standards for exposure to adverse factors. A variety of radionuclides and chemical substances were tested and the sensitivities to them of various indices of the bodily state were determined. For each index, statistically significant minimal effective concentrations of substances were established
Yozgatligil, Ceylan; Aslan, Sipan; Iyigun, Cem; Batmaz, Inci
2013-04-01
This study aims to compare several imputation methods to complete the missing values of spatio-temporal meteorological time series. To this end, six imputation methods are assessed with respect to various criteria including accuracy, robustness, precision, and efficiency for artificially created missing data in monthly total precipitation and mean temperature series obtained from the Turkish State Meteorological Service. Of these methods, simple arithmetic average, normal ratio (NR), and NR weighted with correlations comprise the simple ones, whereas multilayer perceptron type neural network and multiple imputation strategy adopted by Monte Carlo Markov Chain based on expectation-maximization (EM-MCMC) are computationally intensive ones. In addition, we propose a modification on the EM-MCMC method. Besides using a conventional accuracy measure based on squared errors, we also suggest the correlation dimension (CD) technique of nonlinear dynamic time series analysis which takes spatio-temporal dependencies into account for evaluating imputation performances. Depending on the detailed graphical and quantitative analysis, it can be said that although computational methods, particularly EM-MCMC method, are computationally inefficient, they seem favorable for imputation of meteorological time series with respect to different missingness periods considering both measures and both series studied. To conclude, using the EM-MCMC algorithm for imputing missing values before conducting any statistical analyses of meteorological data will definitely decrease the amount of uncertainty and give more robust results. Moreover, the CD measure can be suggested for the performance evaluation of missing data imputation particularly with computational methods since it gives more precise results in meteorological time series.
International Nuclear Information System (INIS)
Ermakov, A.I.; Belousov, V.V.
2007-01-01
Relaxation effect of functions of the basis sets (BS) STO-3G and 6-31G* on their equilibration in the series of isoelectron molecules: LiF, BeO, BN and C 2 is considered. Values of parameters (exponential factor of basis functions, orbital exponents of Gauss primitives and coefficients of their grouping) of basis functions in molecules are discovered using the criterion of minimum of energy by the unlimited Hartree-Fock method calculations (UHF) with the help of direct optimization of parameters: the simplex-method and Rosenbrock method. Certain schemes of optimization differing by the amount of varying parameters have been done. Interaction of basis functions parameters of concerned sets through medium values of the Gauss exponents is established. Effects of relaxation on the change of full energy and relative errors of the calculations of interatomic distances, normal oscillations frequencies, dissociation energy and other properties of molecules are considered. Change of full energy during the relaxation of basis functions (RBF) STO-3G and 6-31G* amounts 1100 and 80 kJ/mol correspondingly, and it is in need of the account during estimation of energetic characteristics, especially for systems with high-polar chemical bonds. The relaxation BS STO-3G practically in all considered cases improves description of molecular properties, whereas the relaxation BS 6-31G* lightly effects on its equilibration [ru
Extension and Enhancement Methods for Setting Data Quality Objectives
Energy Technology Data Exchange (ETDEWEB)
D. Goodman
2000-03-01
The project developed statistical tools for the application of decision theory and operations research methods, including cost-benefit analysis, to the DQO process for environmental clean up. A pilot study was conducted, using these methods at the Hanford site, to estimate vadose zone contamination plumes under the SX tank farm, and to help plan further sampling.
Extension and Enhancement Methods for Setting Data Quality Objectives
International Nuclear Information System (INIS)
Goodman, D.
2000-01-01
The project developed statistical tools for the application of decision theory and operations research methods, including cost-benefit analysis, to the DQO process for environmental clean up. A pilot study was conducted, using these methods at the Hanford site, to estimate vadose zone contamination plumes under the SX tank farm, and to help plan further sampling
Directory of Open Access Journals (Sweden)
Mathieu Lepot
2017-10-01
Full Text Available A thorough review has been performed on interpolation methods to fill gaps in time-series, efficiency criteria, and uncertainty quantifications. On one hand, there are numerous available methods: interpolation, regression, autoregressive, machine learning methods, etc. On the other hand, there are many methods and criteria to estimate efficiencies of these methods, but uncertainties on the interpolated values are rarely calculated. Furthermore, while they are estimated according to standard methods, the prediction uncertainty is not taken into account: a discussion is thus presented on the uncertainty estimation of interpolated/extrapolated data. Finally, some suggestions for further research and a new method are proposed.
[Series: Utilization of Differential Equations and Methods for Solving Them in Medical Physics (2)].
Murase, Kenya
2015-01-01
In this issue, symbolic methods for solving differential equations were firstly introduced. Of the symbolic methods, Laplace transform method was also introduced together with some examples, in which this method was applied to solving the differential equations derived from a two-compartment kinetic model and an equivalent circuit model for membrane potential. Second, series expansion methods for solving differential equations were introduced together with some examples, in which these methods were used to solve Bessel's and Legendre's differential equations. In the next issue, simultaneous differential equations and various methods for solving these differential equations will be introduced together with some examples in medical physics.
DEFF Research Database (Denmark)
Rosted, P; Bundgaard, M; Gordon, S
2010-01-01
BACKGROUND: Anxiety related to dental treatment is a common phenomenon that has a significant impact on the provision of appropriate dental care. The aim of this case series was to examine the effect of acupuncture given prior to dental treatment on the level of anxiety. METHODS: Eight dentists...... a median BAI score of 26.5 at baseline. The BAI score was assessed before and after the acupuncture treatment. All patients received acupuncture treatment for 5 min prior to the planned dental treatment using the points GV20 and EX6. RESULTS: There was a significant reduction in median value of BAI scores...... after treatment with acupuncture (26.5 reduced to 11.5; pacupuncture treatment. Previously this had only been possible in six cases. CONCLUSION: Acupuncture prior to dental treatment has a beneficial effect...
Jackson, John E. (Editor); Horowitz, Richard (Editor)
1986-01-01
The main purpose of the data catalog series is to provide descriptive references to data generated by space science flight missions. The data sets described include all of the actual holdings of the Space Science Data Center (NSSDC), all data sets for which direct contact information is available, and some data collections held and serviced by foreign investigators, NASA and other U.S. government agencies. This volume contains narrative descriptions of data sets from low and medium altitude scientific spacecraft and investigations. The following spacecraft series are included: Mariner, Pioneer, Pioneer Venus, Venera, Viking, Voyager, and Helios. Separate indexes to the planetary and interplanetary missions are also provided.
Schofield, Norman J. (Editor); Parthasarathy, R. (Editor); Hills, H. Kent (Editor)
1988-01-01
The main purpose of the data catalog series is to provide descriptive references to data generated by space science flight missions. The data sets described include all of the actual holdings of the Space Science Data Center (NSSDC), all data sets for which direct contact information is available, and some data collections held and serviced by foreign investigators, NASA and other U.S. government agencies. This volume contains narrative descriptions of data sets from geostationary and high altitude scientific spacecraft and investigations. The following spacecraft series are included: Mariner, Pioneer, Pioneer Venus, Venera, Viking, Voyager, and Helios. Separate indexes to the planetary and interplanetary missions are also provided.
Directory of Open Access Journals (Sweden)
Shohag Barman
Full Text Available Inferring a gene regulatory network from time-series gene expression data in systems biology is a challenging problem. Many methods have been suggested, most of which have a scalability limitation due to the combinatorial cost of searching a regulatory set of genes. In addition, they have focused on the accurate inference of a network structure only. Therefore, there is a pressing need to develop a network inference method to search regulatory genes efficiently and to predict the network dynamics accurately.In this study, we employed a Boolean network model with a restricted update rule scheme to capture coarse-grained dynamics, and propose a novel mutual information-based Boolean network inference (MIBNI method. Given time-series gene expression data as an input, the method first identifies a set of initial regulatory genes using mutual information-based feature selection, and then improves the dynamics prediction accuracy by iteratively swapping a pair of genes between sets of the selected regulatory genes and the other genes. Through extensive simulations with artificial datasets, MIBNI showed consistently better performance than six well-known existing methods, REVEAL, Best-Fit, RelNet, CST, CLR, and BIBN in terms of both structural and dynamics prediction accuracy. We further tested the proposed method with two real gene expression datasets for an Escherichia coli gene regulatory network and a fission yeast cell cycle network, and also observed better results using MIBNI compared to the six other methods.Taken together, MIBNI is a promising tool for predicting both the structure and the dynamics of a gene regulatory network.
Methods of mathematical modeling using polynomials of algebra of sets
Kazanskiy, Alexandr; Kochetkov, Ivan
2018-03-01
The article deals with the construction of discrete mathematical models for solving applied problems arising from the operation of building structures. Security issues in modern high-rise buildings are extremely serious and relevant, and there is no doubt that interest in them will only increase. The territory of the building is divided into zones for which it is necessary to observe. Zones can overlap and have different priorities. Such situations can be described using formulas algebra of sets. Formulas can be programmed, which makes it possible to work with them using computer models.
Device and Method for Gathering Ensemble Data Sets
Racette, Paul E. (Inventor)
2014-01-01
An ensemble detector uses calibrated noise references to produce ensemble sets of data from which properties of non-stationary processes may be extracted. The ensemble detector comprising: a receiver; a switching device coupled to the receiver, the switching device configured to selectively connect each of a plurality of reference noise signals to the receiver; and a gain modulation circuit coupled to the receiver and configured to vary a gain of the receiver based on a forcing signal; whereby the switching device selectively connects each of the plurality of reference noise signals to the receiver to produce an output signal derived from the plurality of reference noise signals and the forcing signal.
A cluster merging method for time series microarray with production values.
Chira, Camelia; Sedano, Javier; Camara, Monica; Prieto, Carlos; Villar, Jose R; Corchado, Emilio
2014-09-01
A challenging task in time-course microarray data analysis is to cluster genes meaningfully combining the information provided by multiple replicates covering the same key time points. This paper proposes a novel cluster merging method to accomplish this goal obtaining groups with highly correlated genes. The main idea behind the proposed method is to generate a clustering starting from groups created based on individual temporal series (representing different biological replicates measured in the same time points) and merging them by taking into account the frequency by which two genes are assembled together in each clustering. The gene groups at the level of individual time series are generated using several shape-based clustering methods. This study is focused on a real-world time series microarray task with the aim to find co-expressed genes related to the production and growth of a certain bacteria. The shape-based clustering methods used at the level of individual time series rely on identifying similar gene expression patterns over time which, in some models, are further matched to the pattern of production/growth. The proposed cluster merging method is able to produce meaningful gene groups which can be naturally ranked by the level of agreement on the clustering among individual time series. The list of clusters and genes is further sorted based on the information correlation coefficient and new problem-specific relevant measures. Computational experiments and results of the cluster merging method are analyzed from a biological perspective and further compared with the clustering generated based on the mean value of time series and the same shape-based algorithm.
Methods to Increase Educational Effectiveness in an Adult Correctional Setting.
Kuster, Byron
1998-01-01
A correctional educator reflects on methods that improve instructional effectiveness. These include teacher-student collaboration, clear goals, student accountability, positive classroom atmosphere, high expectations, and mutual respect. (SK)
R/S method for evaluation of pollutant time series in environmental quality assessment
Directory of Open Access Journals (Sweden)
Bu Quanmin
2008-12-01
Full Text Available The significance of the fluctuation and randomness of the time series of each pollutant in environmental quality assessment is described for the first time in this paper. A comparative study was made of three different computing methods: the same starting point method, the striding averaging method, and the stagger phase averaging method. All of them can be used to calculate the Hurst index, which quantifies fluctuation and randomness. This study used real water quality data from Shazhu monitoring station on Taihu Lake in Wuxi, Jiangsu Province. The results show that, of the three methods, the stagger phase averaging method is best for calculating the Hurst index of a pollutant time series from the perspective of statistical regularity.
An evaluation of dynamic mutuality measurements and methods in cyclic time series
Xia, Xiaohua; Huang, Guitian; Duan, Na
2010-12-01
Several measurements and techniques have been developed to detect dynamic mutuality and synchronicity of time series in econometrics. This study aims to compare the performances of five methods, i.e., linear regression, dynamic correlation, Markov switching models, concordance index and recurrence quantification analysis, through numerical simulations. We evaluate the abilities of these methods to capture structure changing and cyclicity in time series and the findings of this paper would offer guidance to both academic and empirical researchers. Illustration examples are also provided to demonstrate the subtle differences of these techniques.
Guérin, Charles-Antoine; Grilli, Stéphan T.
2018-01-01
We present a new method for inverting ocean surface currents from beam-forming HF radar data. In contrast with the classical method, which inverts radial currents based on shifts of the main Bragg line in the radar Doppler spectrum, the method works in the temporal domain and inverts currents from the amplitude modulation of the I and Q radar time series. Based on this principle, we propose a Maximum Likelihood approach, which can be combined with a Bayesian inference method assuming a prior current distribution, to infer values of the radial surface currents. We assess the method performance by using synthetic radar signal as well as field data, and systematically comparing results with those of the Doppler method. The new method is found advantageous for its robustness to noise at long range, its ability to accommodate shorter time series, and the possibility to use a priori information to improve the estimates. Limitations are related to current sign errors at far-ranges and biased estimates for small current values and very short samples. We apply the new technique to a data set from a typical 13.5 MHz WERA radar, acquired off of Vancouver Island, BC, and show that it can potentially improve standard synoptic current mapping.
R package imputeTestbench to compare imputations methods for univariate time series
Bokde, Neeraj; Kulat, Kishore; Beck, Marcus W; Asencio-Cortés, Gualberto
2016-01-01
This paper describes the R package imputeTestbench that provides a testbench for comparing imputation methods for missing data in univariate time series. The imputeTestbench package can be used to simulate the amount and type of missing data in a complete dataset and compare filled data using different imputation methods. The user has the option to simulate missing data by removing observations completely at random or in blocks of different sizes. Several default imputation methods are includ...
[Series: Utilization of Differential Equations and Methods for Solving Them in Medical Physics (1)].
Murase, Kenya
2014-01-01
Utilization of differential equations and methods for solving them in medical physics are presented. First, the basic concept and the kinds of differential equations were overviewed. Second, separable differential equations and well-known first-order and second-order differential equations were introduced, and the methods for solving them were described together with several examples. In the next issue, the symbolic and series expansion methods for solving differential equations will be mainly introduced.
Hanford Site groundwater monitoring: Setting, sources and methods
International Nuclear Information System (INIS)
Hartman, M.J.
2000-01-01
Groundwater monitoring is conducted on the Hanford Site to meet the requirements of the Resource Conservation and Recovery Act of 1976 (RCRA); Comprehensive Environmental Response, Compensation, and Liability Act of 1980 (CERCLA); U.S. Department of Energy (DOE) orders; and the Washington Administrative Code. Results of monitoring are published annually (e.g., PNNL-11989). To reduce the redundancy of these annual reports, background information that does not change significantly from year to year has been extracted from the annual report and published in this companion volume. This report includes a description of groundwater monitoring requirements, site hydrogeology, and waste sites that have affected groundwater quality or that require groundwater monitoring. Monitoring networks and methods for sampling, analysis, and interpretation are summarized. Vadose zone monitoring methods and statistical methods also are described. Whenever necessary, updates to information contained in this document will be published in future groundwater annual reports
Hanford Site groundwater monitoring: Setting, sources and methods
Energy Technology Data Exchange (ETDEWEB)
M.J. Hartman
2000-04-11
Groundwater monitoring is conducted on the Hanford Site to meet the requirements of the Resource Conservation and Recovery Act of 1976 (RCRA); Comprehensive Environmental Response, Compensation, and Liability Act of 1980 (CERCLA); U.S. Department of Energy (DOE) orders; and the Washington Administrative Code. Results of monitoring are published annually (e.g., PNNL-11989). To reduce the redundancy of these annual reports, background information that does not change significantly from year to year has been extracted from the annual report and published in this companion volume. This report includes a description of groundwater monitoring requirements, site hydrogeology, and waste sites that have affected groundwater quality or that require groundwater monitoring. Monitoring networks and methods for sampling, analysis, and interpretation are summarized. Vadose zone monitoring methods and statistical methods also are described. Whenever necessary, updates to information contained in this document will be published in future groundwater annual reports.
Methods for setting objectives and mission breakdown structure
DEFF Research Database (Denmark)
Riis, Eva
2013-01-01
Projects should create value for the organisations that instigate them or that will make use of their outcomes. This requires there be greater attention paid to defining the value expected of them, and it intensifies the need to formulate clear project objectives. Both tasks are complicated by th...... by the lack of a common terminology when setting objectives. This paper will propose concepts and a tool that should have a natural place in every project manager's toolbox.......Projects should create value for the organisations that instigate them or that will make use of their outcomes. This requires there be greater attention paid to defining the value expected of them, and it intensifies the need to formulate clear project objectives. Both tasks are complicated...
Methods for extracellular vesicles isolation in a hospital setting
Directory of Open Access Journals (Sweden)
Matías eSáenz-Cuesta
2015-02-01
Full Text Available The research in extracellular vesicles (EVs has been rising during the last decade. However, there is no clear consensus on the most accurate protocol to isolate and analyze them. Besides, most of the current protocols are difficult to implement in a hospital setting due to being very time consuming or to requirements of specific infrastructure. Thus, our aim is to compare five different protocols (comprising two different medium-speed differential centrifugation protocols; commercially polymeric precipitation -exoquick-; acid precipitation; and ultracentrifugation for blood and urine samples to determine the most suitable one for the isolation of EVs. Nanoparticle tracking analysis, flow cytometry, western blot, electronic microscopy and spectrophotometry were used to characterize basic aspects of EVs such us concentration, size distribution, cell-origin and transmembrane markers and RNA concentration. The highest EV concentrations were obtained using the exoquick protocol, followed by both differential centrifugation protocols, while the ultracentrifugation and acid-precipitation protocols yielded considerably lower EV concentrations. The five protocols isolated EVs of similar characteristics regarding markers and RNA concentration however standard protocol recovered only small EVs. EV isolated with exoquick presented difficult to be analyzed with western blot. The RNA concentrations obtained from urine-derived EVs were similar to those obtained from blood-derived ones, despite the urine EV concentration being 10 to 20 times lower. We consider that a medium-speed differential centrifugation could be suitable to be applied in a hospital setting due to require the simplest infrastructure and recover higher concentration of EV than standard protocol. A workflow from sampling to characterization of EVs is proposed.
Wheel set run profile renewing method effectiveness estimation
Somov, Dmitrij; Bazaras, Žilvinas; Žukauskaite, Orinta
2010-01-01
At all the repair enterprises, despite decreased rim wear-off resistance, after every grinding only geometry wheel profile parameters are renewed. Exploit wheel rim work edge decrease tendency is noticed what induces acquiring new wheels. This is related to considerable axle load and train speed increase and also because of wheel work edge repair method imperfection.
A level set method for vapor bubble dynamics
Can, E.; Prosperetti, Andrea
2012-01-01
This paper describes a finite-difference computational method suitable for the simulation of vapor–liquid (or gas–liquid) flows in which the dynamical effects of the vapor can be approximated by a time-dependent, spatially uniform pressure acting on the interface. In such flows it is not necessary
Energy Technology Data Exchange (ETDEWEB)
Motozawa, Masaaki, E-mail: motozawa.masaaki@shizuoka.ac.jp [Shizuoka University, 3-5-1 Johoku, Naka-ku, Hamamatsu-shi, Shizuoka 432-8561 (Japan); Muraoka, Takashi [Shizuoka University, 3-5-1 Johoku, Naka-ku, Hamamatsu-shi, Shizuoka 432-8561 (Japan); Motosuke, Masahiro, E-mail: mot@rs.tus.ac.jp [Tokyo University of Science, 6-3-1 Niijuku, Katsushika-ku, Tokyo 125-8585 (Japan); Fukuta, Mitsuhiro, E-mail: fukuta.mitsuhiro@shizuoka.ac.jp [Shizuoka University, 3-5-1 Johoku, Naka-ku, Hamamatsu-shi, Shizuoka 432-8561 (Japan)
2017-04-15
It can be expected that the thermal diffusivity of a magnetic fluid varies from time to time after applying a magnetic field because of the growth of the inner structure of a magnetic fluid such as chain-like clusters. In this study, time series variation of the thermal diffusivity of a magnetic fluid caused by applying a magnetic field was investigated experimentally. For the measurement of time series variation of thermal diffusivity, we attempted to apply the forced Rayleigh scattering method (FRSM), which has high temporal and high spatial resolution. We set up an optical system for the FRSM and measured the thermal diffusivity. A magnetic field was applied to a magnetic fluid in parallel and perpendicular to the heat flux direction, and the magnetic field intensity was 70 mT. The FRSM was successfully applied to measurement of the time series variation of the magnetic fluid from applying a magnetic field. The results show that a characteristic configuration in the time series variation of the thermal diffusivity of magnetic fluid was obtained in the case of applying a magnetic field parallel to the heat flux direction. In contrast, in the case of applying a magnetic field perpendicular to the heat flux, the thermal diffusivity of the magnetic fluid hardly changed during measurement. - Highlights: • Thermal diffusivity was measured by forced Rayleigh scattering method (FRSM). • FRSM has high temporal and high spatial resolutions for measurement. • We attempted to apply FRSM to magnetic fluid (MF). • Time series variation of thermal diffusivity of MF was successfully measured by FRSM. • Anisotropic thermal diffusivity of magnetic fluid was also successfully confirmed.
Swain, Sushree Diptimayee; Ray, Pravat Kumar; Mohanty, K. B.
2016-06-01
This research paper discover the design of a shunt Passive Power Filter (PPF) in Hybrid Series Active Power Filter (HSAPF) that employs a novel analytic methodology which is superior than FFT analysis. This novel approach consists of the estimation, detection and classification of the signals. The proposed method is applied to estimate, detect and classify the power quality (PQ) disturbance such as harmonics. This proposed work deals with three methods: the harmonic detection through wavelet transform method, the harmonic estimation by Kalman Filter algorithm and harmonic classification by decision tree method. From different type of mother wavelets in wavelet transform method, the db8 is selected as suitable mother wavelet because of its potency on transient response and crouched oscillation at frequency domain. In harmonic compensation process, the detected harmonic is compensated through Hybrid Series Active Power Filter (HSAPF) based on Instantaneous Reactive Power Theory (IRPT). The efficacy of the proposed method is verified in MATLAB/SIMULINK domain and as well as with an experimental set up. The obtained results confirm the superiority of the proposed methodology than FFT analysis. This newly proposed PPF is used to make the conventional HSAPF more robust and stable.
Steepest descent method for set-valued locally accretive mappings
International Nuclear Information System (INIS)
Chidume, C.E.
1993-05-01
Let E be a real q-uniformly smooth Banach space. Suppose T is a set-valued locally strongly accretive map with open domain D(T) in E and that 0 is an element of Tx has a solution x* in D(T). Then there exists a neighbourhood B in D(T) of x* and a real number r 1 >0 such that for any r>r 1 and some real sequence {c n }, any initial guess x 1 is an element of B and any single-valued selection T 0 of T, the sequence {x n } generated from x 1 by x n+1 =x n -c n T 0 x n , n≥1, remains in D(T) and converges strongly to x* with ||x n -x*|| O(n -(q-1)/ q). A related result deals with iterative approximation of a solution of the equation f is an element of x+Ax when A is a locally accretive map. Our theorems generalize important known results and resolve a problem of interest. (author). 39 refs
Directory of Open Access Journals (Sweden)
SURE KÖME
2014-12-01
Full Text Available In this paper, we investigated the effect of Magnus Series Expansion Method on homogeneous stiff ordinary differential equations with different stiffness ratios. A Magnus type integrator is used to obtain numerical solutions of two different examples of stiff problems and exact and approximate results are tabulated. Furthermore, absolute error graphics are demonstrated in detail.
Accuracy and Sensitivity of a Method of Jump Detection, Evaluated by Simulated Time Series
Czech Academy of Sciences Publication Activity Database
Chapanov, Y.; Ron, Cyril; Vondrák, Jan
2017-01-01
Roč. 14, č. 1 (2017), s. 73-82 ISSN 1214-9705 R&D Projects: GA ČR GA13-15943S Institutional support: RVO:67985815 Keywords : time series * data jump detection * high-sensitive method Subject RIV: DE - Earth Magnetism, Geodesy, Geography OBOR OECD: Physical geography Impact factor: 0.699, year: 2016
Hof, AL; Boom, H; Robinson, C; Rutten, W; Neuman, M; Wijkstra, H
1997-01-01
With a newly developed Controlled-Release Ergometer the complete characteristic of the series elastic component can be measured in human muscles. Previous estimates were based on the resonance method: muscle elasticity was assessed from the resonance frequency of the muscle elasticity connected to a
Thermal oil recovery method using self-contained windelectric sets
Belsky, A. A.; Korolyov, I. A.
2018-05-01
The paper reviews challenges associated with questions of efficiency of thermal methods of impact on productive oil strata. The concept of using electrothermal complexes with WEG power supply for the indicated purposes was proposed and justified, their operating principles, main advantages and disadvantages, as well as a schematechnical solution for the implementation of the intensification of oil extraction, were considered. A mathematical model for finding the operating characteristics of WEG is presented and its main energy parameters are determined. The adequacy of the mathematical model is confirmed by laboratory simulation stand tests with nominal parameters.
[Proposal of a method for collective analysis of work-related accidents in the hospital setting].
Osório, Claudia; Machado, Jorge Mesquita Huet; Minayo-Gomez, Carlos
2005-01-01
The article presents a method for the analysis of work-related accidents in hospitals, with the double aim of analyzing accidents in light of actual work activity and enhancing the vitality of the various professions that comprise hospital work. This process involves both research and intervention, combining knowledge output with training of health professionals, fostering expanded participation by workers in managing their daily work. The method consists of stimulating workers to recreate the situation in which a given accident occurred, shifting themselves to the position of observers of their own work. In the first stage of analysis, workers are asked to show the work analyst how the accident occurred; in the second stage, the work accident victim and analyst jointly record the described series of events in a diagram; in the third, the resulting record is re-discussed and further elaborated; in the fourth, the work accident victim and analyst evaluate and implement measures aimed to prevent the accident from recurring. The article concludes by discussing the method's possibilities and limitations in the hospital setting.
Turbulence time series data hole filling using Karhunen-Loeve and ARIMA methods
International Nuclear Information System (INIS)
Chang, M P J L; Nazari, H; Font, C O; Gilbreath, G C; Oh, E
2007-01-01
Measurements of optical turbulence time series data using unattended instruments over long time intervals inevitably lead to data drop-outs or degraded signals. We present a comparison of methods using both Principal Component Analysis, which is also known as the Karhunen-Loeve decomposition, and ARIMA that seek to correct for these event-induced and mechanically-induced signal drop-outs and degradations. We report on the quality of the correction by examining the Intrinsic Mode Functions generated by Empirical Mode Decomposition. The data studied are optical turbulence parameter time series from a commercial long path length optical anemometer/scintillometer, measured over several hundred metres in outdoor environments
International Nuclear Information System (INIS)
Dong, Xiangyuan; Guo, Shuqing
2008-01-01
In this paper, a novel image reconstruction method for electrical capacitance tomography (ECT) based on the combined series and parallel model is presented. A regularization technique is used to obtain a stabilized solution of the inverse problem. Also, the adaptive coefficient of the combined model is deduced by numerical optimization. Simulation results indicate that it can produce higher quality images when compared to the algorithm based on the parallel or series models for the cases tested in this paper. It provides a new algorithm for ECT application
Stevens, Anita; Köke, Albère; van der Weijden, Trudy; Beurskens, Anna
2017-08-31
Patient participation and goal setting appear to be difficult in daily physiotherapy practice, and practical methods are lacking. An existing patient-specific instrument, Patient-Specific Complaints (PSC), was therefore optimized into a new Patient Specific Goal-setting method (PSG). The aims of this study were to examine the feasibility of the PSG in daily physiotherapy practice, and to explore the potential impact of the new method. We conducted a process evaluation within a non-controlled intervention study. Community-based physiotherapists were instructed on how to work with the PSG in three group training sessions. The PSG is a six-step method embedded across the physiotherapy process, in which patients are stimulated to participate in the goal-setting process by: identifying problematic activities, prioritizing them, scoring their abilities, setting goals, planning and evaluating. Quantitative and qualitative data were collected among patients and physiotherapists by recording consultations and assessing patient files, questionnaires and written reflection reports. Data were collected from 51 physiotherapists and 218 patients, and 38 recordings and 219 patient files were analysed. The PSG steps were performed as intended, but the 'setting goals' and 'planning treatment' steps were not performed in detail. The patients and physiotherapists were positive about the method, and the physiotherapists perceived increased patient participation. They became aware of the importance of engaging patients in a dialogue, instead of focusing on gathering information. The lack of integration in the electronic patient system was a major barrier for optimal use in practice. Although the self-reported actual use of the PSG, i.e. informing and involving patients, and client-centred competences had improved, this was not completely confirmed by the objectively observed behaviour. The PSG is a feasible method and tends to have impact on increasing patient participation in the goal-setting
Horowitz, Richard (Compiler); Jackson, John E. (Compiler); Cameron, Winifred S. (Compiler)
1987-01-01
The main purpose of the data catalog series is to provide descriptive references to data generated by space science flight missions. The data sets described include all of the actual holdings of the Space Science Data Center (NSSDC), all data sets for which direct contact information is available, and some data collections held and serviced by foreign investigators, NASA and other U.S. government agencies. This volume contains narrative descriptions of planetary and heliocentric spacecraft and associated experiments. The following spacecraft series are included: Mariner, Pioneer, Pioneer Venus, Venera, Viking, Voyager, and Helios. Separate indexes to the planetary and interplanetary missions are also provided.
International Nuclear Information System (INIS)
Thireou, Trias; Rubio Guivernau, Jose Luis; Atlamazoglou, Vassilis; Ledesma, Maria Jesus; Pavlopoulos, Sotiris; Santos, Andres; Kontaxakis, George
2006-01-01
A realistic dynamic positron-emission tomography (PET) thoracic study was generated, using the 4D NURBS-based (non-uniform rational B-splines) cardiac-torso (NCAT) phantom and a sophisticated model of the PET imaging process, simulating two solitary pulmonary nodules. Three data reduction and blind source separation methods were applied to the simulated data: principal component analysis, independent component analysis and similarity mapping. All methods reduced the initial amount of image data to a smaller, comprehensive and easily managed set of parametric images, where structures were separated based on their different kinetic characteristics and the lesions were readily identified. The results indicate that the above-mentioned methods can provide an accurate tool for the support of both visual inspection and subsequent detailed kinetic analysis of the dynamic series via compartmental or non-compartmental models
New significance test methods for Fourier analysis of geophysical time series
Directory of Open Access Journals (Sweden)
Z. Zhang
2011-09-01
Full Text Available When one applies the discrete Fourier transform to analyze finite-length time series, discontinuities at the data boundaries will distort its Fourier power spectrum. In this paper, based on a rigid statistics framework, we present a new significance test method which can extract the intrinsic feature of a geophysical time series very well. We show the difference in significance level compared with traditional Fourier tests by analyzing the Arctic Oscillation (AO and the Nino3.4 time series. In the AO, we find significant peaks at about 2.8, 4.3, and 5.7 yr periods and in Nino3.4 at about 12 yr period in tests against red noise. These peaks are not significant in traditional tests.
Papacharalampous, Georgia; Tyralis, Hristos; Koutsoyiannis, Demetris
2018-02-01
We investigate the predictability of monthly temperature and precipitation by applying automatic univariate time series forecasting methods to a sample of 985 40-year-long monthly temperature and 1552 40-year-long monthly precipitation time series. The methods include a naïve one based on the monthly values of the last year, as well as the random walk (with drift), AutoRegressive Fractionally Integrated Moving Average (ARFIMA), exponential smoothing state-space model with Box-Cox transformation, ARMA errors, Trend and Seasonal components (BATS), simple exponential smoothing, Theta and Prophet methods. Prophet is a recently introduced model inspired by the nature of time series forecasted at Facebook and has not been applied to hydrometeorological time series before, while the use of random walk, BATS, simple exponential smoothing and Theta is rare in hydrology. The methods are tested in performing multi-step ahead forecasts for the last 48 months of the data. We further investigate how different choices of handling the seasonality and non-normality affect the performance of the models. The results indicate that: (a) all the examined methods apart from the naïve and random walk ones are accurate enough to be used in long-term applications; (b) monthly temperature and precipitation can be forecasted to a level of accuracy which can barely be improved using other methods; (c) the externally applied classical seasonal decomposition results mostly in better forecasts compared to the automatic seasonal decomposition used by the BATS and Prophet methods; and (d) Prophet is competitive, especially when it is combined with externally applied classical seasonal decomposition.
Finite test sets development method for test execution of safety critical software
International Nuclear Information System (INIS)
El-Bordany Ayman; Yun, Won Young
2014-01-01
It reads inputs, computes new states, and updates output for each scan cycle. Korea Nuclear Instrumentation and Control System (KNICS) has recently developed a fully digitalized Reactor Protection System (RPS) based on PLD. As a digital system, this RPS is equipped with a dedicated software. The Reliability of this software is crucial to NPPs safety where its malfunction may cause irreversible consequences and affect the whole system as a Common Cause Failure (CCF). To guarantee the reliability of the whole system, the reliability of this software needs to be quantified. There are three representative methods for software reliability quantification, namely the Verification and Validation (V and V) quality-based method, the Software Reliability Growth Model (SRGM), and the test-based method. An important concept of the guidance is that the test sets represent 'trajectories' (a series of successive values for the input variables of a program that occur during the operation of the software over time) in the space of inputs to the software.. Actually, the inputs to the software depends on the state of plant at that time, and these inputs form a new internal state of the software by changing values of some variables. In other words, internal state of the software at specific timing depends on the history of past inputs. Here the internal state of the software which can be changed by past inputs is named as Context of Software (CoS). In a certain CoS, a software failure occurs when a fault is triggered by some inputs. To cover the failure occurrence mechanism of a software, preceding researches insist that the inputs should be a trajectory form. However, in this approach, there are two critical problems. One is the length of the trajectory input. Input trajectory should long enough to cover failure mechanism, but the enough length is not clear. What is worse, to cover some accident scenario, one set of input should represent dozen hours of successive values
Directory of Open Access Journals (Sweden)
Huan-Yu Bi
2015-09-01
Full Text Available The Principle of Maximum Conformality (PMC eliminates QCD renormalization scale-setting uncertainties using fundamental renormalization group methods. The resulting scale-fixed pQCD predictions are independent of the choice of renormalization scheme and show rapid convergence. The coefficients of the scale-fixed couplings are identical to the corresponding conformal series with zero β-function. Two all-orders methods for systematically implementing the PMC-scale setting procedure for existing high order calculations are discussed in this article. One implementation is based on the PMC-BLM correspondence (PMC-I; the other, more recent, method (PMC-II uses the Rδ-scheme, a systematic generalization of the minimal subtraction renormalization scheme. Both approaches satisfy all of the principles of the renormalization group and lead to scale-fixed and scheme-independent predictions at each finite order. In this work, we show that PMC-I and PMC-II scale-setting methods are in practice equivalent to each other. We illustrate this equivalence for the four-loop calculations of the annihilation ratio Re+e− and the Higgs partial width Γ(H→bb¯. Both methods lead to the same resummed (‘conformal’ series up to all orders. The small scale differences between the two approaches are reduced as additional renormalization group {βi}-terms in the pQCD expansion are taken into account. We also show that special degeneracy relations, which underly the equivalence of the two PMC approaches and the resulting conformal features of the pQCD series, are in fact general properties of non-Abelian gauge theory.
Year Ahead Demand Forecast of City Natural Gas Using Seasonal Time Series Methods
Directory of Open Access Journals (Sweden)
Mustafa Akpinar
2016-09-01
Full Text Available Consumption of natural gas, a major clean energy source, increases as energy demand increases. We studied specifically the Turkish natural gas market. Turkey’s natural gas consumption increased as well in parallel with the world‘s over the last decade. This consumption growth in Turkey has led to the formation of a market structure for the natural gas industry. This significant increase requires additional investments since a rise in consumption capacity is expected. One of the reasons for the consumption increase is the user-based natural gas consumption influence. This effect yields imbalances in demand forecasts and if the error rates are out of bounds, penalties may occur. In this paper, three univariate statistical methods, which have not been previously investigated for mid-term year-ahead monthly natural gas forecasting, are used to forecast natural gas demand in Turkey’s Sakarya province. Residential and low-consumption commercial data is used, which may contain seasonality. The goal of this paper is minimizing more or less gas tractions on mid-term consumption while improving the accuracy of demand forecasting. In forecasting models, seasonality and single variable impacts reinforce forecasts. This paper studies time series decomposition, Holt-Winters exponential smoothing and autoregressive integrated moving average (ARIMA methods. Here, 2011–2014 monthly data were prepared and divided into two series. The first series is 2011–2013 monthly data used for finding seasonal effects and model requirements. The second series is 2014 monthly data used for forecasting. For the ARIMA method, a stationary series was prepared and transformation process prior to forecasting was done. Forecasting results confirmed that as the computation complexity of the model increases, forecasting accuracy increases with lower error rates. Also, forecasting errors and the coefficients of determination values give more consistent results. Consequently
Dakos, Vasilis; Carpenter, Stephen R.; Brock, William A.; Ellison, Aaron M.; Guttal, Vishwesha; Ives, Anthony R.; Kéfi, Sonia; Livina, Valerie; Seekell, David A.; van Nes, Egbert H.; Scheffer, Marten
2012-01-01
Many dynamical systems, including lakes, organisms, ocean circulation patterns, or financial markets, are now thought to have tipping points where critical transitions to a contrasting state can happen. Because critical transitions can occur unexpectedly and are difficult to manage, there is a need for methods that can be used to identify when a critical transition is approaching. Recent theory shows that we can identify the proximity of a system to a critical transition using a variety of so-called ‘early warning signals’, and successful empirical examples suggest a potential for practical applicability. However, while the range of proposed methods for predicting critical transitions is rapidly expanding, opinions on their practical use differ widely, and there is no comparative study that tests the limitations of the different methods to identify approaching critical transitions using time-series data. Here, we summarize a range of currently available early warning methods and apply them to two simulated time series that are typical of systems undergoing a critical transition. In addition to a methodological guide, our work offers a practical toolbox that may be used in a wide range of fields to help detect early warning signals of critical transitions in time series data. PMID:22815897
The Fourier decomposition method for nonlinear and non-stationary time series analysis.
Singh, Pushpendra; Joshi, Shiv Dutt; Patney, Rakesh Kumar; Saha, Kaushik
2017-03-01
for many decades, there has been a general perception in the literature that Fourier methods are not suitable for the analysis of nonlinear and non-stationary data. In this paper, we propose a novel and adaptive Fourier decomposition method (FDM), based on the Fourier theory, and demonstrate its efficacy for the analysis of nonlinear and non-stationary time series. The proposed FDM decomposes any data into a small number of 'Fourier intrinsic band functions' (FIBFs). The FDM presents a generalized Fourier expansion with variable amplitudes and variable frequencies of a time series by the Fourier method itself. We propose an idea of zero-phase filter bank-based multivariate FDM (MFDM), for the analysis of multivariate nonlinear and non-stationary time series, using the FDM. We also present an algorithm to obtain cut-off frequencies for MFDM. The proposed MFDM generates a finite number of band-limited multivariate FIBFs (MFIBFs). The MFDM preserves some intrinsic physical properties of the multivariate data, such as scale alignment, trend and instantaneous frequency. The proposed methods provide a time-frequency-energy (TFE) distribution that reveals the intrinsic structure of a data. Numerical computations and simulations have been carried out and comparison is made with the empirical mode decomposition algorithms.
Multi-phase flow monitoring with electrical impedance tomography using level set based method
International Nuclear Information System (INIS)
Liu, Dong; Khambampati, Anil Kumar; Kim, Sin; Kim, Kyung Youn
2015-01-01
Highlights: • LSM has been used for shape reconstruction to monitor multi-phase flow using EIT. • Multi-phase level set model for conductivity is represented by two level set functions. • LSM handles topological merging and breaking naturally during evolution process. • To reduce the computational time, a narrowband technique was applied. • Use of narrowband and optimization approach results in efficient and fast method. - Abstract: In this paper, a level set-based reconstruction scheme is applied to multi-phase flow monitoring using electrical impedance tomography (EIT). The proposed scheme involves applying a narrowband level set method to solve the inverse problem of finding the interface between the regions having different conductivity values. The multi-phase level set model for the conductivity distribution inside the domain is represented by two level set functions. The key principle of the level set-based method is to implicitly represent the shape of interface as the zero level set of higher dimensional function and then solve a set of partial differential equations. The level set-based scheme handles topological merging and breaking naturally during the evolution process. It also offers several advantages compared to traditional pixel-based approach. Level set-based method for multi-phase flow is tested with numerical and experimental data. It is found that level set-based method has better reconstruction performance when compared to pixel-based method
Directory of Open Access Journals (Sweden)
Yanzhu Hu
2016-09-01
Full Text Available Complex network methodology is very useful for complex system exploration. However, the relationships among variables in complex systems are usually not clear. Therefore, inferring association networks among variables from their observed data has been a popular research topic. We propose a method, named small-shuffle symbolic transfer entropy spectrum (SSSTES, for inferring association networks from multivariate time series. The method can solve four problems for inferring association networks, i.e., strong correlation identification, correlation quantification, direction identification and temporal relation identification. The method can be divided into four layers. The first layer is the so-called data layer. Data input and processing are the things to do in this layer. In the second layer, we symbolize the model data, original data and shuffled data, from the previous layer and calculate circularly transfer entropy with different time lags for each pair of time series variables. Thirdly, we compose transfer entropy spectrums for pairwise time series with the previous layer’s output, a list of transfer entropy matrix. We also identify the correlation level between variables in this layer. In the last layer, we build a weighted adjacency matrix, the value of each entry representing the correlation level between pairwise variables, and then get the weighted directed association network. Three sets of numerical simulated data from a linear system, a nonlinear system and a coupled Rossler system are used to show how the proposed approach works. Finally, we apply SSSTES to a real industrial system and get a better result than with two other methods.
A LEVEL SET BASED SHAPE OPTIMIZATION METHOD FOR AN ELLIPTIC OBSTACLE PROBLEM
Burger, Martin; Matevosyan, Norayr; Wolfram, Marie-Therese
2011-01-01
analysis of the level set method in terms of viscosity solutions. To our knowledge this is the first complete analysis of a level set method for a nonlocal shape optimization problem. Finally, we discuss the implementation of the methods and illustrate its
Directory of Open Access Journals (Sweden)
Pavel Zaskalicky
2008-01-01
Full Text Available Reluctance stepper motors are becoming to be very attractive transducer to conversion of electric signal to the mechanical position. Due to its simple construction is reluctance machine considered a very reliable machine which not requiring any maintenance. Present paper proposes a mathematical method of an analytical calculus of a phase current and electromagnetic torque of the motor via Fourier series. Saturation effect and winding reluctance are neglected.
Forecasting with quantitative methods the impact of special events in time series
Nikolopoulos, Konstantinos
2010-01-01
Abstract Quantitative methods are very successful for producing baseline forecasts of time series; however these models fail to forecast neither the timing nor the impact of special events such as promotions or strikes. In most of the cases the timing of such events is not known so they are usually referred as shocks (economics) or special events (forecasting). Sometimes the timing of such events is known a priori (i.e. a future promotion); but even then the impact of the forthcom...
Detecting method for crude oil price fluctuation mechanism under different periodic time series
International Nuclear Information System (INIS)
Gao, Xiangyun; Fang, Wei; An, Feng; Wang, Yue
2017-01-01
Highlights: • We proposed the concept of autoregressive modes to indicate the fluctuation patterns. • We constructed transmission networks for studying the fluctuation mechanism. • There are different fluctuation mechanism under different periodic time series. • Only a few types of autoregressive modes control the fluctuations in crude oil price. • There are cluster effects during the fluctuation mechanism of autoregressive modes. - Abstract: Current existing literatures can characterize the long-term fluctuation of crude oil price time series, however, it is difficult to detect the fluctuation mechanism specifically under short term. Because each fluctuation pattern for one short period contained in a long-term crude oil price time series have dynamic characteristics of diversity; in other words, there exhibit various fluctuation patterns in different short periods and transmit to each other, which reflects the reputedly complicate and chaotic oil market. Thus, we proposed an incorporated method to detect the fluctuation mechanism, which is the evolution of the different fluctuation patterns over time from the complex network perspective. We divided crude oil price time series into segments using sliding time windows, and defined autoregressive modes based on regression models to indicate the fluctuation patterns of each segment. Hence, the transmissions between different types of autoregressive modes over time form a transmission network that contains rich dynamic information. We then capture transmission characteristics of autoregressive modes under different periodic time series through the structure features of the transmission networks. The results indicate that there are various autoregressive modes with significantly different statistical characteristics under different periodic time series. However, only a few types of autoregressive modes and transmission patterns play a major role in the fluctuation mechanism of the crude oil price, and these
Comparison of time-series registration methods in breast dynamic infrared imaging
Riyahi-Alam, S.; Agostini, V.; Molinari, F.; Knaflitz, M.
2015-03-01
Automated motion reduction in dynamic infrared imaging is on demand in clinical applications, since movement disarranges time-temperature series of each pixel, thus originating thermal artifacts that might bias the clinical decision. All previously proposed registration methods are feature based algorithms requiring manual intervention. The aim of this work is to optimize the registration strategy specifically for Breast Dynamic Infrared Imaging and to make it user-independent. We implemented and evaluated 3 different 3D time-series registration methods: 1. Linear affine, 2. Non-linear Bspline, 3. Demons applied to 12 datasets of healthy breast thermal images. The results are evaluated through normalized mutual information with average values of 0.70 ±0.03, 0.74 ±0.03 and 0.81 ±0.09 (out of 1) for Affine, Bspline and Demons registration, respectively, as well as breast boundary overlap and Jacobian determinant of the deformation field. The statistical analysis of the results showed that symmetric diffeomorphic Demons' registration method outperforms also with the best breast alignment and non-negative Jacobian values which guarantee image similarity and anatomical consistency of the transformation, due to homologous forces enforcing the pixel geometric disparities to be shortened on all the frames. We propose Demons' registration as an effective technique for time-series dynamic infrared registration, to stabilize the local temperature oscillation.
Hansen, J V; Nelson, R D
1997-01-01
Ever since the initial planning for the 1997 Utah legislative session, neural-network forecasting techniques have provided valuable insights for analysts forecasting tax revenues. These revenue estimates are critically important since agency budgets, support for education, and improvements to infrastructure all depend on their accuracy. Underforecasting generates windfalls that concern taxpayers, whereas overforecasting produces budget shortfalls that cause inadequately funded commitments. The pattern finding ability of neural networks gives insightful and alternative views of the seasonal and cyclical components commonly found in economic time series data. Two applications of neural networks to revenue forecasting clearly demonstrate how these models complement traditional time series techniques. In the first, preoccupation with a potential downturn in the economy distracts analysis based on traditional time series methods so that it overlooks an emerging new phenomenon in the data. In this case, neural networks identify the new pattern that then allows modification of the time series models and finally gives more accurate forecasts. In the second application, data structure found by traditional statistical tools allows analysts to provide neural networks with important information that the networks then use to create more accurate models. In summary, for the Utah revenue outlook, the insights that result from a portfolio of forecasts that includes neural networks exceeds the understanding generated from strictly statistical forecasting techniques. In this case, the synergy clearly results in the whole of the portfolio of forecasts being more accurate than the sum of the individual parts.
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.
A Two-Dimensional Solar Tracking Stationary Guidance Method Based on Feature-Based Time Series
Directory of Open Access Journals (Sweden)
Keke Zhang
2018-01-01
Full Text Available The amount of satellite energy acquired has a direct impact on operational capacities of the satellite. As for practical high functional density microsatellites, solar tracking guidance design of solar panels plays an extremely important role. Targeted at stationary tracking problems incurred in a new system that utilizes panels mounted in the two-dimensional turntable to acquire energies to the greatest extent, a two-dimensional solar tracking stationary guidance method based on feature-based time series was proposed under the constraint of limited satellite attitude coupling control capability. By analyzing solar vector variation characteristics within an orbit period and solar vector changes within the whole life cycle, such a method could be adopted to establish a two-dimensional solar tracking guidance model based on the feature-based time series to realize automatic switching of feature-based time series and stationary guidance under the circumstance of different β angles and the maximum angular velocity control, which was applicable to near-earth orbits of all orbital inclination. It was employed to design a two-dimensional solar tracking stationary guidance system, and a mathematical simulation for guidance performance was carried out in diverse conditions under the background of in-orbit application. The simulation results show that the solar tracking accuracy of two-dimensional stationary guidance reaches 10∘ and below under the integrated constraints, which meet engineering application requirements.
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
Meshgi, Ali; Schmitter, Petra; Babovic, Vladan; Chui, Ting Fong May
2014-11-01
Developing reliable methods to estimate stream baseflow has been a subject of interest due to its importance in catchment response and sustainable watershed management. However, to date, in the absence of complex numerical models, baseflow is most commonly estimated using statistically derived empirical approaches that do not directly incorporate physically-meaningful information. On the other hand, Artificial Intelligence (AI) tools such as Genetic Programming (GP) offer unique capabilities to reduce the complexities of hydrological systems without losing relevant physical information. This study presents a simple-to-use empirical equation to estimate baseflow time series using GP so that minimal data is required and physical information is preserved. A groundwater numerical model was first adopted to simulate baseflow for a small semi-urban catchment (0.043 km2) located in Singapore. GP was then used to derive an empirical equation relating baseflow time series to time series of groundwater table fluctuations, which are relatively easily measured and are physically related to baseflow generation. The equation was then generalized for approximating baseflow in other catchments and validated for a larger vegetation-dominated basin located in the US (24 km2). Overall, this study used GP to propose a simple-to-use equation to predict baseflow time series based on only three parameters: minimum daily baseflow of the entire period, area of the catchment and groundwater table fluctuations. It serves as an alternative approach for baseflow estimation in un-gauged systems when only groundwater table and soil information is available, and is thus complementary to other methods that require discharge measurements.
International Nuclear Information System (INIS)
Sims, C.S.; Killough, G.G.
1983-01-01
Various segments of the health physics community advocate the use of different sets of neutron fluence-to-dose equivalent conversion factors as a function of energy and different methods of interpolation between discrete points in those data sets. The major data sets and interpolation methods are used to calculate the spectrum average fluence-to-dose equivalent conversion factors for five spectra associated with the various shielded conditions of the Health Physics Research Reactor. The results obtained by use of the different data sets and interpolation methods are compared and discussed. (author)
Grimm, C. A.
This document contains two units that examine integral transforms and series expansions. In the first module, the user is expected to learn how to use the unified method presented to obtain Laplace transforms, Fourier transforms, complex Fourier series, real Fourier series, and half-range sine series for given piecewise continuous functions. In…
Numerical simulation of stratified shear flow using a higher order Taylor series expansion method
Energy Technology Data Exchange (ETDEWEB)
Iwashige, Kengo; Ikeda, Takashi [Hitachi, Ltd. (Japan)
1995-09-01
A higher order Taylor series expansion method is applied to two-dimensional numerical simulation of stratified shear flow. In the present study, central difference scheme-like method is adopted for an even expansion order, and upwind difference scheme-like method is adopted for an odd order, and the expansion order is variable. To evaluate the effects of expansion order upon the numerical results, a stratified shear flow test in a rectangular channel (Reynolds number = 1.7x10{sup 4}) is carried out, and the numerical velocity and temperature fields are compared with experimental results measured by laser Doppler velocimetry thermocouples. The results confirm that the higher and odd order methods can simulate mean velocity distributions, root-mean-square velocity fluctuations, Reynolds stress, temperature distributions, and root-mean-square temperature fluctuations.
Solving Fokker-Planck Equations on Cantor Sets Using Local Fractional Decomposition Method
Directory of Open Access Journals (Sweden)
Shao-Hong Yan
2014-01-01
Full Text Available The local fractional decomposition method is applied to approximate the solutions for Fokker-Planck equations on Cantor sets with local fractional derivative. The obtained results give the present method that is very effective and simple for solving the differential equations on Cantor set.
International Nuclear Information System (INIS)
Ishikawa, Nobuyuki; Suzuki, Katsuo
1999-01-01
Having advantages of setting independently feedback characteristics such as disturbance rejection specification and reference response characteristics, two-degree-of-freedom (2DOF) control is widely utilized to improve the control performance. The ordinary design method such as model matching usually derives high-ordered feedforward element of 2DOF controller. In this paper, we propose a new design method for low order feedforward element which is based on Pade approximation of the denominator series expansion. The features of the proposed method are as follows: (1) it is suited to realize reference response characteristics in low frequency region, (2) the order of the feedforward element can be selected apart from the feedback element. These are essential to the 2DOF controller design. With this method, 2DOF reactor power controller is designed and its control performance is evaluated by numerical simulation with reactor dynamics model. For this evaluation, it is confirmed that the controller designed by the proposed method possesses equivalent control characteristics to the controller by the ordinary model matching method. (author)
A Fast Multi-layer Subnetwork Connection Method for Time Series InSAR Technique
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WU Hong'an
2016-10-01
Full Text Available Nowadays, times series interferometric synthetic aperture radar (InSAR technique has been widely used in ground deformation monitoring, especially in urban areas where lots of stable point targets can be detected. However, in standard time series InSAR technique, affected by atmospheric correlation distance and the threshold of linear model coherence, the Delaunay triangulation for connecting point targets can be easily separated into many discontinuous subnetworks. Thus it is difficult to retrieve ground deformation in non-urban areas. In order to monitor ground deformation in large areas efficiently, a novel multi-layer subnetwork connection (MLSC method is proposed for connecting all subnetworks. The advantage of the method is that it can quickly reduce the number of subnetworks with valid edges layer-by-layer. This method is compared with the existing complex network connecting mehod. The experimental results demonstrate that the data processing time of the proposed method is only 32.56% of the latter one.
A Time-Series Water Level Forecasting Model Based on Imputation and Variable Selection Method.
Yang, Jun-He; Cheng, Ching-Hsue; Chan, Chia-Pan
2017-01-01
Reservoirs are important for households and impact the national economy. This paper proposed a time-series forecasting model based on estimating a missing value followed by variable selection to forecast the reservoir's water level. This study collected data from the Taiwan Shimen Reservoir as well as daily atmospheric data from 2008 to 2015. The two datasets are concatenated into an integrated dataset based on ordering of the data as a research dataset. The proposed time-series forecasting model summarily has three foci. First, this study uses five imputation methods to directly delete the missing value. Second, we identified the key variable via factor analysis and then deleted the unimportant variables sequentially via the variable selection method. Finally, the proposed model uses a Random Forest to build the forecasting model of the reservoir's water level. This was done to compare with the listing method under the forecasting error. These experimental results indicate that the Random Forest forecasting model when applied to variable selection with full variables has better forecasting performance than the listing model. In addition, this experiment shows that the proposed variable selection can help determine five forecast methods used here to improve the forecasting capability.
A Time-Series Water Level Forecasting Model Based on Imputation and Variable Selection Method
Directory of Open Access Journals (Sweden)
Jun-He Yang
2017-01-01
Full Text Available Reservoirs are important for households and impact the national economy. This paper proposed a time-series forecasting model based on estimating a missing value followed by variable selection to forecast the reservoir’s water level. This study collected data from the Taiwan Shimen Reservoir as well as daily atmospheric data from 2008 to 2015. The two datasets are concatenated into an integrated dataset based on ordering of the data as a research dataset. The proposed time-series forecasting model summarily has three foci. First, this study uses five imputation methods to directly delete the missing value. Second, we identified the key variable via factor analysis and then deleted the unimportant variables sequentially via the variable selection method. Finally, the proposed model uses a Random Forest to build the forecasting model of the reservoir’s water level. This was done to compare with the listing method under the forecasting error. These experimental results indicate that the Random Forest forecasting model when applied to variable selection with full variables has better forecasting performance than the listing model. In addition, this experiment shows that the proposed variable selection can help determine five forecast methods used here to improve the forecasting capability.
Francis, Jill J; O'Connor, Denise; Curran, Janet
2012-04-24
Behaviour change is key to increasing the uptake of evidence into healthcare practice. Designing behaviour-change interventions first requires problem analysis, ideally informed by theory. Yet the large number of partly overlapping theories of behaviour makes it difficult to select the most appropriate theory. The need for an overarching theoretical framework of behaviour change was addressed in research in which 128 explanatory constructs from 33 theories of behaviour were identified and grouped. The resulting Theoretical Domains Framework (TDF) appears to be a helpful basis for investigating implementation problems. Research groups in several countries have conducted TDF-based studies. It seems timely to bring together the experience of these teams in a thematic series to demonstrate further applications and to report key developments. This overview article describes the TDF, provides a brief critique of the framework, and introduces this thematic series.In a brief review to assess the extent of TDF-based research, we identified 133 papers that cite the framework. Of these, 17 used the TDF as the basis for empirical studies to explore health professionals' behaviour. The identified papers provide evidence of the impact of the TDF on implementation research. Two major strengths of the framework are its theoretical coverage and its capacity to elicit beliefs that could signify key mediators of behaviour change. The TDF provides a useful conceptual basis for assessing implementation problems, designing interventions to enhance healthcare practice, and understanding behaviour-change processes. We discuss limitations and research challenges and introduce papers in this series.
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.
Age of Saurashtra miliolites by U-Th decay series methods: possible implications to their origin
International Nuclear Information System (INIS)
Hussain, N.; Bhandari, N.; Ramanathan, K.R.; Somayajulu, B.L.K.
1980-01-01
The miliolite deposits of Saurashtra have been dated by 234 U, 230 Th, 231 Pa and 14 C methods. Concordant ages of approximately 10 5 years using the U decay series isotopes are obtained which agree with the ages of the coral reefs of Okha-Dwaraka coast suggesting a contemporaneous origin for both. The lower 14 C ages (<= 40,000 years) may be due to a recent influx of seawater or ground water. Quartz and clay minerals together constitute only <= 10% by weight, as such the aeolin characteristics of quartz grains may not be relevant to the origin of the miliolites. (auth.)
The partial duration series method in regional index-flood modeling
DEFF Research Database (Denmark)
Madsen, Henrik; Rosbjerg, Dan
1997-01-01
A regional index-flood method based on the partial duration series model is introduced. The model comprises the assumptions of a Poisson-distributed number of threshold exceedances and generalized Pareto (GP) distributed peak magnitudes. The regional T-year event estimator is based on a regional...... estimator is superior to the at-site estimator even in extremely heterogenous regions, the performance of the regional estimator being relatively better in regions with a negative shape parameter. When the record length increases, the relative performance of the regional estimator decreases, but it is still...
Regularization of the Fourier series of discontinuous functions by various summation methods
Energy Technology Data Exchange (ETDEWEB)
Ahmad, S.S.; Beghi, L. (Padua Univ. (Italy). Seminario Matematico)
1983-07-01
In this paper the regularization by various summation methods of the Fourier series of functions containing discontinuities of the first and second kind are studied and the results of the numerical analyses referring to some typical periodic functions are presented. In addition to the Cesaro and Lanczos weightings, a new (i.e. cosine) weighting for accelerating the convergence rate is proposed. A comparison with the results obtained by Garibotti and Massaro with the punctual Pade approximants (PPA) technique in case of a periodic step function is also carried out.
Age of Saurashtra miliolites by U-Th decay series methods: possible implications to their origin
Energy Technology Data Exchange (ETDEWEB)
Hussain, N; Bhandari, N; Ramanathan, K R; Somayajulu, B L.K. [Physical Research Lab., Ahmedabad (India)
1980-03-01
The miliolite deposits of Saurashtra have been dated by /sup 234/U, /sup 230/Th, /sup 231/Pa and /sup 14/C methods. Concordant ages of approximately 10/sup 5/ years using the U decay series isotopes are obtained which agree with the ages of the coral reefs of Okha-Dwaraka coast suggesting a contemporaneous origin for both. The lower /sup 14/C ages (<= 40,000 years) may be due to a recent influx of seawater or ground water. Quartz and clay minerals together constitute only <= 10% by weight, as such the aeolin characteristics of quartz grains may not be relevant to the origin of the miliolites.
Teaching to Think: Applying the Socratic Method outside the Law School Setting
Peterson, Evan
2009-01-01
An active learning process has the potential to provide educational benefits above-and-beyond what they might receive from more traditional, passive approaches. The Socratic Method is a unique approach to passive learning that facilitates critical thinking, open-mindedness, and teamwork. By imposing a series of guided questions to students, an…
Comparative study on gene set and pathway topology-based enrichment methods.
Bayerlová, Michaela; Jung, Klaus; Kramer, Frank; Klemm, Florian; Bleckmann, Annalen; Beißbarth, Tim
2015-10-22
Enrichment analysis is a popular approach to identify pathways or sets of genes which are significantly enriched in the context of differentially expressed genes. The traditional gene set enrichment approach considers a pathway as a simple gene list disregarding any knowledge of gene or protein interactions. In contrast, the new group of so called pathway topology-based methods integrates the topological structure of a pathway into the analysis. We comparatively investigated gene set and pathway topology-based enrichment approaches, considering three gene set and four topological methods. These methods were compared in two extensive simulation studies and on a benchmark of 36 real datasets, providing the same pathway input data for all methods. In the benchmark data analysis both types of methods showed a comparable ability to detect enriched pathways. The first simulation study was conducted with KEGG pathways, which showed considerable gene overlaps between each other. In this study with original KEGG pathways, none of the topology-based methods outperformed the gene set approach. Therefore, a second simulation study was performed on non-overlapping pathways created by unique gene IDs. Here, methods accounting for pathway topology reached higher accuracy than the gene set methods, however their sensitivity was lower. We conducted one of the first comprehensive comparative works on evaluating gene set against pathway topology-based enrichment methods. The topological methods showed better performance in the simulation scenarios with non-overlapping pathways, however, they were not conclusively better in the other scenarios. This suggests that simple gene set approach might be sufficient to detect an enriched pathway under realistic circumstances. Nevertheless, more extensive studies and further benchmark data are needed to systematically evaluate these methods and to assess what gain and cost pathway topology information introduces into enrichment analysis. Both
Lagarde, Nathalie; Zagury, Jean-François; Montes, Matthieu
2015-07-27
Virtual screening methods are commonly used nowadays in drug discovery processes. However, to ensure their reliability, they have to be carefully evaluated. The evaluation of these methods is often realized in a retrospective way, notably by studying the enrichment of benchmarking data sets. To this purpose, numerous benchmarking data sets were developed over the years, and the resulting improvements led to the availability of high quality benchmarking data sets. However, some points still have to be considered in the selection of the active compounds, decoys, and protein structures to obtain optimal benchmarking data sets.
A simple mass-conserved level set method for simulation of multiphase flows
Yuan, H.-Z.; Shu, C.; Wang, Y.; Shu, S.
2018-04-01
In this paper, a modified level set method is proposed for simulation of multiphase flows with large density ratio and high Reynolds number. The present method simply introduces a source or sink term into the level set equation to compensate the mass loss or offset the mass increase. The source or sink term is derived analytically by applying the mass conservation principle with the level set equation and the continuity equation of flow field. Since only a source term is introduced, the application of the present method is as simple as the original level set method, but it can guarantee the overall mass conservation. To validate the present method, the vortex flow problem is first considered. The simulation results are compared with those from the original level set method, which demonstrates that the modified level set method has the capability of accurately capturing the interface and keeping the mass conservation. Then, the proposed method is further validated by simulating the Laplace law, the merging of two bubbles, a bubble rising with high density ratio, and Rayleigh-Taylor instability with high Reynolds number. Numerical results show that the mass is a well-conserved by the present method.
Directory of Open Access Journals (Sweden)
Kazuo Iijima
Full Text Available Clinical studies for assessing the effectiveness and safety in a premarketing setting are conducted under time and cost constraints. In recent years, postmarketing data analysis has been given more attention. However, to our knowledge, no studies have compared the effectiveness and the safety between the pre- and postmarketing settings. In this study, we aimed to investigate the importance of the postmarketing data analysis using clinical data.Studies on capsule endoscopy with rich clinical data in both pre- and postmarketing settings were selected for the analysis. For effectiveness, clinical studies published before October 10, 2015 comparing capsule endoscopy and conventional flexible endoscopy measuring the detection ratio of obscure gastrointestinal bleeding were selected (premarketing: 4 studies and postmarketing: 8 studies from PubMed (MEDLINE, Cochrane Library, EMBASE and Web of Science. Among the 12 studies, 5 were blinded and 7 were non-blinded. A time series meta-analysis was conducted. Effectiveness (odds ratio decreased in the postmarketing setting (premarketing: 5.19 [95% confidence interval: 3.07-8.76] vs. postmarketing: 1.48 [0.81-2.69]. The change in odds ratio was caused by the increase in the detection ratio with flexible endoscopy as the control group. The efficacy of capsule endoscopy did not change between pre- and postmarketing settings. Heterogeneity (I2 increased in the postmarketing setting because of one study. For safety, in terms of endoscope retention in the body, data from the approval summary and adverse event reports were analyzed. The incidence of retention decreased in the postmarketing setting (premarketing: 0.75% vs postmarketing: 0.095%. The introduction of the new patency capsule for checking the patency of the digestive tract might contribute to the decrease.Effectiveness and safety could change in the postmarketing setting. Therefore, time series meta-analyses could be useful to continuously monitor the
Directory of Open Access Journals (Sweden)
Frederic D Sigoillot
Full Text Available Automated time-lapse microscopy can visualize proliferation of large numbers of individual cells, enabling accurate measurement of the frequency of cell division and the duration of interphase and mitosis. However, extraction of quantitative information by manual inspection of time-lapse movies is too time-consuming to be useful for analysis of large experiments.Here we present an automated time-series approach that can measure changes in the duration of mitosis and interphase in individual cells expressing fluorescent histone 2B. The approach requires analysis of only 2 features, nuclear area and average intensity. Compared to supervised learning approaches, this method reduces processing time and does not require generation of training data sets. We demonstrate that this method is as sensitive as manual analysis in identifying small changes in interphase or mitotic duration induced by drug or siRNA treatment.This approach should facilitate automated analysis of high-throughput time-lapse data sets to identify small molecules or gene products that influence timing of cell division.
Directory of Open Access Journals (Sweden)
Ivan Arismendi
2017-12-01
Full Text Available Intermittent and ephemeral streams represent more than half of the length of the global river network. Dryland freshwater ecosystems are especially vulnerable to changes in human-related water uses as well as shifts in terrestrial climates. Yet, the description and quantification of patterns of flow permanence in these systems is challenging mostly due to difficulties in instrumentation. Here, we took advantage of existing stream temperature datasets in dryland streams in the northwest Great Basin desert, USA, to extract critical information on climate-sensitive patterns of flow permanence. We used a signal detection technique, Hidden Markov Models (HMMs, to extract information from daily time series of stream temperature to diagnose patterns of stream drying. Specifically, we applied HMMs to time series of daily standard deviation (SD of stream temperature (i.e., dry stream channels typically display highly variable daily temperature records compared to wet stream channels between April and August (2015–2016. We used information from paired stream and air temperature data loggers as well as co-located stream temperature data loggers with electrical resistors as confirmatory sources of the timing of stream drying. We expanded our approach to an entire stream network to illustrate the utility of the method to detect patterns of flow permanence over a broader spatial extent. We successfully identified and separated signals characteristic of wet and dry stream conditions and their shifts over time. Most of our study sites within the entire stream network exhibited a single state over the entire season (80%, but a portion of them showed one or more shifts among states (17%. We provide recommendations to use this approach based on a series of simple steps. Our findings illustrate a successful method that can be used to rigorously quantify flow permanence regimes in streams using existing records of stream temperature.
Arismendi, Ivan; Dunham, Jason B.; Heck, Michael; Schultz, Luke; Hockman-Wert, David
2017-01-01
Intermittent and ephemeral streams represent more than half of the length of the global river network. Dryland freshwater ecosystems are especially vulnerable to changes in human-related water uses as well as shifts in terrestrial climates. Yet, the description and quantification of patterns of flow permanence in these systems is challenging mostly due to difficulties in instrumentation. Here, we took advantage of existing stream temperature datasets in dryland streams in the northwest Great Basin desert, USA, to extract critical information on climate-sensitive patterns of flow permanence. We used a signal detection technique, Hidden Markov Models (HMMs), to extract information from daily time series of stream temperature to diagnose patterns of stream drying. Specifically, we applied HMMs to time series of daily standard deviation (SD) of stream temperature (i.e., dry stream channels typically display highly variable daily temperature records compared to wet stream channels) between April and August (2015–2016). We used information from paired stream and air temperature data loggers as well as co-located stream temperature data loggers with electrical resistors as confirmatory sources of the timing of stream drying. We expanded our approach to an entire stream network to illustrate the utility of the method to detect patterns of flow permanence over a broader spatial extent. We successfully identified and separated signals characteristic of wet and dry stream conditions and their shifts over time. Most of our study sites within the entire stream network exhibited a single state over the entire season (80%), but a portion of them showed one or more shifts among states (17%). We provide recommendations to use this approach based on a series of simple steps. Our findings illustrate a successful method that can be used to rigorously quantify flow permanence regimes in streams using existing records of stream temperature.
A LEVEL SET BASED SHAPE OPTIMIZATION METHOD FOR AN ELLIPTIC OBSTACLE PROBLEM
Burger, Martin
2011-04-01
In this paper, we construct a level set method for an elliptic obstacle problem, which can be reformulated as a shape optimization problem. We provide a detailed shape sensitivity analysis for this reformulation and a stability result for the shape Hessian at the optimal shape. Using the shape sensitivities, we construct a geometric gradient flow, which can be realized in the context of level set methods. We prove the convergence of the gradient flow to an optimal shape and provide a complete analysis of the level set method in terms of viscosity solutions. To our knowledge this is the first complete analysis of a level set method for a nonlocal shape optimization problem. Finally, we discuss the implementation of the methods and illustrate its behavior through several computational experiments. © 2011 World Scientific Publishing Company.
Directory of Open Access Journals (Sweden)
Michelle Helena van Velthoven
2013-12-01
Full Text Available We set up a collaboration between researchers in China and the UK that aimed to explore the use of mHealth in China. This is the first paper in a series of papers on a large mHealth project part of this collaboration. This paper included the aims and objectives of the mHealth project, our field site, and the detailed methods of two studies.
Hybrid approach for detection of dental caries based on the methods FCM and level sets
Chaabene, Marwa; Ben Ali, Ramzi; Ejbali, Ridha; Zaied, Mourad
2017-03-01
This paper presents a new technique for detection of dental caries that is a bacterial disease that destroys the tooth structure. In our approach, we have achieved a new segmentation method that combines the advantages of fuzzy C mean algorithm and level set method. The results obtained by the FCM algorithm will be used by Level sets algorithm to reduce the influence of the noise effect on the working of each of these algorithms, to facilitate level sets manipulation and to lead to more robust segmentation. The sensitivity and specificity confirm the effectiveness of proposed method for caries detection.
A High-Performance Parallel FDTD Method Enhanced by Using SSE Instruction Set
Directory of Open Access Journals (Sweden)
Dau-Chyrh Chang
2012-01-01
Full Text Available We introduce a hardware acceleration technique for the parallel finite difference time domain (FDTD method using the SSE (streaming (single instruction multiple data SIMD extensions instruction set. The implementation of SSE instruction set to parallel FDTD method has achieved the significant improvement on the simulation performance. The benchmarks of the SSE acceleration on both the multi-CPU workstation and computer cluster have demonstrated the advantages of (vector arithmetic logic unit VALU acceleration over GPU acceleration. Several engineering applications are employed to demonstrate the performance of parallel FDTD method enhanced by SSE instruction set.
An Active Power Sharing Method among Distributed Energy Sources in an Islanded Series Micro-Grid
Directory of Open Access Journals (Sweden)
Wei-Man Yang
2014-11-01
Full Text Available Active power-sharing among distributed energy sources (DESs is not only an important way to realize optimal operation of micro-grids, but also the key to maintaining stability for islanded operation. Due to the unique configuration of series micro-grids (SMGs, the power-sharing method adopted in an ordinary AC, DC, and hybrid AC/DC system cannot be directly applied into SMGs. Power-sharing in one SMG with multiple DESs involves two aspects. On the one hand, capacitor voltage stability based on an energy storage system (ESS in the DC link must be complemented. Actually, this is a problem of power allocation between the generating unit and the ESS in the DES; an extensively researched, similar problem has been grid-off distributed power generation, for which there are good solutions. On the other hand, power-sharing among DESs should be considered to optimize the operation of a series micro-grid. In this paper, a novel method combining master control with auxiliary control is proposed. Master action of a quasi-proportional resonant controller is responsible for stability of the islanded SMG; auxiliary action based on state of charge (SOC realizes coordinated allocation of load power among the source. At the same time, it is important to ensure that the auxiliary control does not influence the master action.
Cooling load calculation by the radiant time series method - effect of solar radiation models
Energy Technology Data Exchange (ETDEWEB)
Costa, Alexandre M.S. [Universidade Estadual de Maringa (UEM), PR (Brazil)], E-mail: amscosta@uem.br
2010-07-01
In this work was analyzed numerically the effect of three different models for solar radiation on the cooling load calculated by the radiant time series' method. The solar radiation models implemented were clear sky, isotropic sky and anisotropic sky. The radiant time series' method (RTS) was proposed by ASHRAE (2001) for replacing the classical methods of cooling load calculation, such as TETD/TA. The method is based on computing the effect of space thermal energy storage on the instantaneous cooling load. The computing is carried out by splitting the heat gain components in convective and radiant parts. Following the radiant part is transformed using time series, which coefficients are a function of the construction type and heat gain (solar or non-solar). The transformed result is added to the convective part, giving the instantaneous cooling load. The method was applied for investigate the influence for an example room. The location used was - 23 degree S and 51 degree W and the day was 21 of January, a typical summer day in the southern hemisphere. The room was composed of two vertical walls with windows exposed to outdoors with azimuth angles equals to west and east directions. The output of the different models of solar radiation for the two walls in terms of direct and diffuse components as well heat gains were investigated. It was verified that the clear sky exhibited the less conservative (higher values) for the direct component of solar radiation, with the opposite trend for the diffuse component. For the heat gain, the clear sky gives the higher values, three times higher for the peek hours than the other models. Both isotropic and anisotropic models predicted similar magnitude for the heat gain. The same behavior was also verified for the cooling load. The effect of room thermal inertia was decreasing the cooling load during the peak hours. On the other hand the higher thermal inertia values are the greater for the non peak hours. The effect
Wang, Jun; Zhou, Bi-hua; Zhou, Shu-dao; Sheng, Zheng
2015-01-01
The paper proposes a novel function expression method to forecast chaotic time series, using an improved genetic-simulated annealing (IGSA) algorithm to establish the optimum function expression that describes the behavior of time series. In order to deal with the weakness associated with the genetic algorithm, the proposed algorithm incorporates the simulated annealing operation which has the strong local search ability into the genetic algorithm to enhance the performance of optimization; besides, the fitness function and genetic operators are also improved. Finally, the method is applied to the chaotic time series of Quadratic and Rossler maps for validation. The effect of noise in the chaotic time series is also studied numerically. The numerical results verify that the method can forecast chaotic time series with high precision and effectiveness, and the forecasting precision with certain noise is also satisfactory. It can be concluded that the IGSA algorithm is energy-efficient and superior.
Robust fault detection of linear systems using a computationally efficient set-membership method
DEFF Research Database (Denmark)
Tabatabaeipour, Mojtaba; Bak, Thomas
2014-01-01
In this paper, a computationally efficient set-membership method for robust fault detection of linear systems is proposed. The method computes an interval outer-approximation of the output of the system that is consistent with the model, the bounds on noise and disturbance, and the past measureme...... is trivially parallelizable. The method is demonstrated for fault detection of a hydraulic pitch actuator of a wind turbine. We show the effectiveness of the proposed method by comparing our results with two zonotope-based set-membership methods....
Adjustment method for embedded metrology engine in an EM773 series microcontroller.
Blazinšek, Iztok; Kotnik, Bojan; Chowdhury, Amor; Kačič, Zdravko
2015-09-01
This paper presents the problems of implementation and adjustment (calibration) of a metrology engine embedded in NXP's EM773 series microcontroller. The metrology engine is used in a smart metering application to collect data about energy utilization and is controlled with the use of metrology engine adjustment (calibration) parameters. The aim of this research is to develop a method which would enable the operators to find and verify the optimum parameters which would ensure the best possible accuracy. Properly adjusted (calibrated) metrology engines can then be used as a base for variety of products used in smart and intelligent environments. This paper focuses on the problems encountered in the development, partial automatisation, implementation and verification of this method. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.
Factors Analysis And Profit Achievement For Trading Company By Using Rough Set Method
Directory of Open Access Journals (Sweden)
Muhammad Ardiansyah Sembiring
2017-06-01
Full Text Available This research has been done to analysis the financial raport fortrading company and it is intimately related to some factors which determine the profit of company. The result of this reseach is showed about New Knowledge and perform of the rule. In discussion, by followed data mining process and using Rough Set method. Rough Set is to analyzed the performance of the result. This reseach will be assist to the manager of company with draw the intactandobjective. Rough set method is also to difined the rule of discovery process and started the formation about Decision System, Equivalence Class, Discernibility Matrix, Discernibility Matrix Modulo D, Reduction and General Rules. Rough set method is efective model about the performing analysis in the company. Keywords : Data Mining, General Rules, Profit,. Rough Set.
Method of nuclear reactor control using a variable temperature load dependent set point
International Nuclear Information System (INIS)
Kelly, J.J.; Rambo, G.E.
1982-01-01
A method and apparatus for controlling a nuclear reactor in response to a variable average reactor coolant temperature set point is disclosed. The set point is dependent upon percent of full power load demand. A manually-actuated ''droop mode'' of control is provided whereby the reactor coolant temperature is allowed to drop below the set point temperature a predetermined amount wherein the control is switched from reactor control rods exclusively to feedwater flow
Directory of Open Access Journals (Sweden)
Miguel Hage Amaro
2012-12-01
Full Text Available PURPOSE: To report the response of choroidal neovascularization (CNV to intravitreal ranibizumab treatment in the setting of age-related macular degeneration (AMD with extensive pre-existing geographic atrophy (GA and a revision paper. METHODS: This is a revision paper and a retrospective case series of 10 eyes in nine consecutive patients from a photographic database. The patients were actively treated with ranibizumab for neovascular AMD with extensive pre-existing GA. Patients were included if they had GA at or adjacent to the foveal center that was present before the development of CNV. The best corrected visual acuity and optical coherence tomography (OCT analysis of the central macular thickness were recorded for each visit. Serial injections of ranibizumab were administered until there was resolution of any subretinal fluid clinically or on OCT. Data over the entire follow-up period were analyzed for overall visual and OCT changes. All patients had been followed for at least 2 years since diagnosis. RESULTS: The patients received an average of 6 ± 3 intravitreal injections over the treatment period. Eight eyes had reduced retinal thickening on OCT. On average, the central macular thickness was reduced by 94 ± 101 µm. Eight eyes had improvement of one or more lines of vision, where as one eye had dramatic vision loss and one had no change. The average treatment outcome for all patients was -0.07 ± 4.25 logMAR units, which corresponded to a gain of 0.6 ± 4.4 lines of Snellen acuity. The treatment resulted in a good anatomic response with the disappearance of the subretinal fluid, improved visual acuity, and stabilized final visual results. CONCLUSION: The results of this case series suggest that the use of an intravitreal anti-vascular endothelial growth factor (VEGF agent (ranibizumab for CNV in AMD with extensive pre-existing GA is effective. Our results are not as striking as published results from large-scale trials of anti
Discrete Data Qualification System and Method Comprising Noise Series Fault Detection
Fulton, Christopher; Wong, Edmond; Melcher, Kevin; Bickford, Randall
2013-01-01
A Sensor Data Qualification (SDQ) function has been developed that allows the onboard flight computers on NASA s launch vehicles to determine the validity of sensor data to ensure that critical safety and operational decisions are not based on faulty sensor data. This SDQ function includes a novel noise series fault detection algorithm for qualification of the output data from LO2 and LH2 low-level liquid sensors. These sensors are positioned in a launch vehicle s propellant tanks in order to detect propellant depletion during a rocket engine s boost operating phase. This detection capability can prevent the catastrophic situation where the engine operates without propellant. The output from each LO2 and LH2 low-level liquid sensor is a discrete valued signal that is expected to be in either of two states, depending on whether the sensor is immersed (wet) or exposed (dry). Conventional methods for sensor data qualification, such as threshold limit checking, are not effective for this type of signal due to its discrete binary-state nature. To address this data qualification challenge, a noise computation and evaluation method, also known as a noise fault detector, was developed to detect unreasonable statistical characteristics in the discrete data stream. The method operates on a time series of discrete data observations over a moving window of data points and performs a continuous examination of the resulting observation stream to identify the presence of anomalous characteristics. If the method determines the existence of anomalous results, the data from the sensor is disqualified for use by other monitoring or control functions.
A Body of Work Standard-Setting Method with Construct Maps
Wyse, Adam E.; Bunch, Michael B.; Deville, Craig; Viger, Steven G.
2014-01-01
This article describes a novel variation of the Body of Work method that uses construct maps to overcome problems of transparency, rater inconsistency, and scores gaps commonly occurring with the Body of Work method. The Body of Work method with construct maps was implemented to set cut-scores for two separate K-12 assessment programs in a large…
Muhammad, Akram; Musavarah, Sarwar
2016-01-01
In this research study, we introduce the concept of bipolar neutrosophic graphs. We present the dominating and independent sets of bipolar neutrosophic graphs. We describe novel multiple criteria decision making methods based on bipolar neutrosophic sets and bipolar neutrosophic graphs. We also develop an algorithm for computing domination in bipolar neutrosophic graphs.
Personal Goal Setting and Quality of Life: A Mixed Methods Study of Adult Professionals
Ingraham, Frank
2017-01-01
This mixed methods study was designed to examine the potential impactful relationship between personal goal setting and the quality of life satisfaction (built upon the Goal Setting Theory of motivation and performance). The study aimed to determine how influential the goal achievement process is (or is not) regarding personal fulfillment and…
Improved vertical streambed flux estimation using multiple diurnal temperature methods in series
Irvine, Dylan J.; Briggs, Martin A.; Cartwright, Ian; Scruggs, Courtney; Lautz, Laura K.
2017-01-01
Analytical solutions that use diurnal temperature signals to estimate vertical fluxes between groundwater and surface water based on either amplitude ratios (Ar) or phase shifts (Δϕ) produce results that rarely agree. Analytical solutions that simultaneously utilize Ar and Δϕ within a single solution have more recently been derived, decreasing uncertainty in flux estimates in some applications. Benefits of combined (ArΔϕ) methods also include that thermal diffusivity and sensor spacing can be calculated. However, poor identification of either Ar or Δϕ from raw temperature signals can lead to erratic parameter estimates from ArΔϕ methods. An add-on program for VFLUX 2 is presented to address this issue. Using thermal diffusivity selected from an ArΔϕ method during a reliable time period, fluxes are recalculated using an Ar method. This approach maximizes the benefits of the Ar and ArΔϕ methods. Additionally, sensor spacing calculations can be used to identify periods with unreliable flux estimates, or to assess streambed scour. Using synthetic and field examples, the use of these solutions in series was particularly useful for gaining conditions where fluxes exceeded 1 m/d.
Directory of Open Access Journals (Sweden)
Michael Ruisi
2013-01-01
Full Text Available Prinzmetal angina or vasospastic angina is a clinical phenomenon that is often transient and self-resolving. Clinically it is associated with ST elevations on the electrocardiogram, and initially it may be difficult to differentiate from an acute myocardial infarction. The vasospasm induced in this setting occurs in normal or mildly to moderately diseased vessels and can be triggered by a number of etiologies including smoking, changes in autonomic activity, or drug ingestion. While the ischemia induced is usually transient, myocardial infarction and life-threatening arrhythmias can occur in 25% of cases. We present the case of a 65-year-old female where repetitive intermittent coronary vasospasm culminated in transmural infarction in the setting of gastrointestinal bleeding. This case highlights the mortality associated with prinzmetal angina and the importance of recognizing the underlying etiology.
Gene set analysis: limitations in popular existing methods and proposed improvements.
Mishra, Pashupati; Törönen, Petri; Leino, Yrjö; Holm, Liisa
2014-10-01
Gene set analysis is the analysis of a set of genes that collectively contribute to a biological process. Most popular gene set analysis methods are based on empirical P-value that requires large number of permutations. Despite numerous gene set analysis methods developed in the past decade, the most popular methods still suffer from serious limitations. We present a gene set analysis method (mGSZ) based on Gene Set Z-scoring function (GSZ) and asymptotic P-values. Asymptotic P-value calculation requires fewer permutations, and thus speeds up the gene set analysis process. We compare the GSZ-scoring function with seven popular gene set scoring functions and show that GSZ stands out as the best scoring function. In addition, we show improved performance of the GSA method when the max-mean statistics is replaced by the GSZ scoring function. We demonstrate the importance of both gene and sample permutations by showing the consequences in the absence of one or the other. A comparison of asymptotic and empirical methods of P-value estimation demonstrates a clear advantage of asymptotic P-value over empirical P-value. We show that mGSZ outperforms the state-of-the-art methods based on two different evaluations. We compared mGSZ results with permutation and rotation tests and show that rotation does not improve our asymptotic P-values. We also propose well-known asymptotic distribution models for three of the compared methods. mGSZ is available as R package from cran.r-project.org. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
Wu’s Characteristic Set Method for SystemVerilog Assertions Verification
Directory of Open Access Journals (Sweden)
Xinyan Gao
2013-01-01
Full Text Available We propose a verification solution based on characteristic set of Wu’s method towards SystemVerilog assertion checking over digital circuit systems. We define a suitable subset of SVAs so that an efficient polynomial modeling mechanism for both circuit descriptions and assertions can be applied. We present an algorithm framework based on the algebraic representations using characteristic set of polynomial system. This symbolic algebraic approach is a useful supplement to the existent verification methods based on simulation.
RESEARCH PRIORITY-SETTING IN PAPUA NEW GUINEA: POLICIES, METHODS AND PRACTICALITIES
Omuru, Eric; Kingwell, Ross S.
2000-01-01
Agricultural research priority-setting at best promotes the effective and efficient use of scarce research resources. This paper reviews firstly the priority-setting methods used in Papua New Guinea for agricultural R&D and examines the practicalities of implementing these and other methods. Secondly, this paper reports on key factors affecting the strategic directions for agricultural R&D in Papua New Guinea. These factors include:(i) the long term trends in international crop prices; (ii) l...
Knowledge Reduction Based on Divide and Conquer Method in Rough Set Theory
Directory of Open Access Journals (Sweden)
Feng Hu
2012-01-01
Full Text Available The divide and conquer method is a typical granular computing method using multiple levels of abstraction and granulations. So far, although some achievements based on divided and conquer method in the rough set theory have been acquired, the systematic methods for knowledge reduction based on divide and conquer method are still absent. In this paper, the knowledge reduction approaches based on divide and conquer method, under equivalence relation and under tolerance relation, are presented, respectively. After that, a systematic approach, named as the abstract process for knowledge reduction based on divide and conquer method in rough set theory, is proposed. Based on the presented approach, two algorithms for knowledge reduction, including an algorithm for attribute reduction and an algorithm for attribute value reduction, are presented. Some experimental evaluations are done to test the methods on uci data sets and KDDCUP99 data sets. The experimental results illustrate that the proposed approaches are efficient to process large data sets with good recognition rate, compared with KNN, SVM, C4.5, Naive Bayes, and CART.
Wang, Wen-Chuan; Chau, Kwok-Wing; Cheng, Chun-Tian; Qiu, Lin
2009-08-01
SummaryDeveloping a hydrological forecasting model based on past records is crucial to effective hydropower reservoir management and scheduling. Traditionally, time series analysis and modeling is used for building mathematical models to generate hydrologic records in hydrology and water resources. Artificial intelligence (AI), as a branch of computer science, is capable of analyzing long-series and large-scale hydrological data. In recent years, it is one of front issues to apply AI technology to the hydrological forecasting modeling. In this paper, autoregressive moving-average (ARMA) models, artificial neural networks (ANNs) approaches, adaptive neural-based fuzzy inference system (ANFIS) techniques, genetic programming (GP) models and support vector machine (SVM) method are examined using the long-term observations of monthly river flow discharges. The four quantitative standard statistical performance evaluation measures, the coefficient of correlation ( R), Nash-Sutcliffe efficiency coefficient ( E), root mean squared error (RMSE), mean absolute percentage error (MAPE), are employed to evaluate the performances of various models developed. Two case study river sites are also provided to illustrate their respective performances. The results indicate that the best performance can be obtained by ANFIS, GP and SVM, in terms of different evaluation criteria during the training and validation phases.
River catchment rainfall series analysis using additive Holt-Winters method
Puah, Yan Jun; Huang, Yuk Feng; Chua, Kuan Chin; Lee, Teang Shui
2016-03-01
Climate change is receiving more attention from researchers as the frequency of occurrence of severe natural disasters is getting higher. Tropical countries like Malaysia have no distinct four seasons; rainfall has become the popular parameter to assess climate change. Conventional ways that determine rainfall trends can only provide a general result in single direction for the whole study period. In this study, rainfall series were modelled using additive Holt-Winters method to examine the rainfall pattern in Langat River Basin, Malaysia. Nine homogeneous series of more than 25 years data and less than 10% missing data were selected. Goodness of fit of the forecasted models was measured. It was found that seasonal rainfall model forecasts are generally better than the monthly rainfall model forecasts. Three stations in the western region exhibited increasing trend. Rainfall in southern region showed fluctuation. Increasing trends were discovered at stations in the south-eastern region except the seasonal analysis at station 45253. Decreasing trend was found at station 2818110 in the east, while increasing trend was shown at station 44320 that represents the north-eastern region. The accuracies of both rainfall model forecasts were tested using the recorded data of years 2010-2012. Most of the forecasts are acceptable.
Timetable-based simulation method for choice set generation in large-scale public transport networks
DEFF Research Database (Denmark)
Rasmussen, Thomas Kjær; Anderson, Marie Karen; Nielsen, Otto Anker
2016-01-01
The composition and size of the choice sets are a key for the correct estimation of and prediction by route choice models. While existing literature has posed a great deal of attention towards the generation of path choice sets for private transport problems, the same does not apply to public...... transport problems. This study proposes a timetable-based simulation method for generating path choice sets in a multimodal public transport network. Moreover, this study illustrates the feasibility of its implementation by applying the method to reproduce 5131 real-life trips in the Greater Copenhagen Area...... and to assess the choice set quality in a complex multimodal transport network. Results illustrate the applicability of the algorithm and the relevance of the utility specification chosen for the reproduction of real-life path choices. Moreover, results show that the level of stochasticity used in choice set...
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
Multi person detection and tracking based on hierarchical level-set method
Khraief, Chadia; Benzarti, Faouzi; Amiri, Hamid
2018-04-01
In this paper, we propose an efficient unsupervised method for mutli-person tracking based on hierarchical level-set approach. The proposed method uses both edge and region information in order to effectively detect objects. The persons are tracked on each frame of the sequence by minimizing an energy functional that combines color, texture and shape information. These features are enrolled in covariance matrix as region descriptor. The present method is fully automated without the need to manually specify the initial contour of Level-set. It is based on combined person detection and background subtraction methods. The edge-based is employed to maintain a stable evolution, guide the segmentation towards apparent boundaries and inhibit regions fusion. The computational cost of level-set is reduced by using narrow band technique. Many experimental results are performed on challenging video sequences and show the effectiveness of the proposed method.
A Nonparametric, Multiple Imputation-Based Method for the Retrospective Integration of Data Sets
Carrig, Madeline M.; Manrique-Vallier, Daniel; Ranby, Krista W.; Reiter, Jerome P.; Hoyle, Rick H.
2015-01-01
Complex research questions often cannot be addressed adequately with a single data set. One sensible alternative to the high cost and effort associated with the creation of large new data sets is to combine existing data sets containing variables related to the constructs of interest. The goal of the present research was to develop a flexible, broadly applicable approach to the integration of disparate data sets that is based on nonparametric multiple imputation and the collection of data from a convenient, de novo calibration sample. We demonstrate proof of concept for the approach by integrating three existing data sets containing items related to the extent of problematic alcohol use and associations with deviant peers. We discuss both necessary conditions for the approach to work well and potential strengths and weaknesses of the method compared to other data set integration approaches. PMID:26257437
Archer, Louise; Francis, Becky; Miller, Sarah; Taylor, Becky; Tereshchenko, Antonina; Mazenod, Anna; Pepper, David; Travers, Mary-Claire
2018-01-01
"Setting" is a widespread practice in the UK, despite little evidence of its efficacy and substantial evidence of its detrimental impact on those allocated to the lowest sets. Taking a Bourdieusian approach, we propose that setting can be understood as a practice through which the social and cultural reproduction of dominant power…
International Nuclear Information System (INIS)
Gutierrez, Rafael M.; Useche, Gina M.; Buitrago, Elias
2007-01-01
We present a procedure developed to detect stochastic and deterministic information contained in empirical time series, useful to characterize and make models of different aspects of complex phenomena represented by such data. This procedure is applied to a seismological time series to obtain new information to study and understand geological phenomena. We use concepts and methods from nonlinear dynamics and maximum entropy. The mentioned method allows an optimal analysis of the available information
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
A time series approach to inferring groundwater recharge using the water table fluctuation method
Crosbie, Russell S.; Binning, Philip; Kalma, Jetse D.
2005-01-01
The water table fluctuation method for determining recharge from precipitation and water table measurements was originally developed on an event basis. Here a new multievent time series approach is presented for inferring groundwater recharge from long-term water table and precipitation records. Additional new features are the incorporation of a variable specific yield based upon the soil moisture retention curve, proper accounting for the Lisse effect on the water table, and the incorporation of aquifer drainage so that recharge can be detected even if the water table does not rise. A methodology for filtering noise and non-rainfall-related water table fluctuations is also presented. The model has been applied to 2 years of field data collected in the Tomago sand beds near Newcastle, Australia. It is shown that gross recharge estimates are very sensitive to time step size and specific yield. Properly accounting for the Lisse effect is also important to determining recharge.
"Rehabilitation schools for scoliosis" thematic series: describing the methods and results
Directory of Open Access Journals (Sweden)
Grivas Theodoros B
2010-12-01
Full Text Available Abstract The Scoliosis Rehabilitation model begins with the correct diagnosis and evaluation of the patient, to make treatment decisions oriented to the patient. The treatment is based on observation, education, scoliosis specific exercises, and bracing. The state of research in the field of conservative treatment is insufficient. There is some evidence supporting scoliosis specific exercises as a part of the rehabilitation treatment, however, the evidence is poor and the different methods are not known by most of the scientific community. The only way to improve the knowledge and understanding of the different physiotherapy methodologies (specific exercises, integrated into the whole rehabilitation program, is to establish a single and comprehensive source of information about it. This is what the SCOLIOSIS Journal is going to do through the "Rehabilitation Schools for Scoliosis" Thematic Series, where technical papers coming from the different schools will be published.
Mendoza-Rosas, Ana Teresa; De la Cruz-Reyna, Servando
2008-09-01
The probabilistic analysis of volcanic eruption time series is an essential step for the assessment of volcanic hazard and risk. Such series describe complex processes involving different types of eruptions over different time scales. A statistical method linking geological and historical eruption time series is proposed for calculating the probabilities of future eruptions. The first step of the analysis is to characterize the eruptions by their magnitudes. As is the case in most natural phenomena, lower magnitude events are more frequent, and the behavior of the eruption series may be biased by such events. On the other hand, eruptive series are commonly studied using conventional statistics and treated as homogeneous Poisson processes. However, time-dependent series, or sequences including rare or extreme events, represented by very few data of large eruptions require special methods of analysis, such as the extreme-value theory applied to non-homogeneous Poisson processes. Here we propose a general methodology for analyzing such processes attempting to obtain better estimates of the volcanic hazard. This is done in three steps: Firstly, the historical eruptive series is complemented with the available geological eruption data. The linking of these series is done assuming an inverse relationship between the eruption magnitudes and the occurrence rate of each magnitude class. Secondly, we perform a Weibull analysis of the distribution of repose time between successive eruptions. Thirdly, the linked eruption series are analyzed as a non-homogeneous Poisson process with a generalized Pareto distribution as intensity function. As an application, the method is tested on the eruption series of five active polygenetic Mexican volcanoes: Colima, Citlaltépetl, Nevado de Toluca, Popocatépetl and El Chichón, to obtain hazard estimates.
Predicting hepatitis B monthly incidence rates using weighted Markov chains and time series methods.
Shahdoust, Maryam; Sadeghifar, Majid; Poorolajal, Jalal; Javanrooh, Niloofar; Amini, Payam
2015-01-01
Hepatitis B (HB) is a major global mortality. Accurately predicting the trend of the disease can provide an appropriate view to make health policy disease prevention. This paper aimed to apply three different to predict monthly incidence rates of HB. This historical cohort study was conducted on the HB incidence data of Hamadan Province, the west of Iran, from 2004 to 2012. Weighted Markov Chain (WMC) method based on Markov chain theory and two time series models including Holt Exponential Smoothing (HES) and SARIMA were applied on the data. The results of different applied methods were compared to correct percentages of predicted incidence rates. The monthly incidence rates were clustered into two clusters as state of Markov chain. The correct predicted percentage of the first and second clusters for WMC, HES and SARIMA methods was (100, 0), (84, 67) and (79, 47) respectively. The overall incidence rate of HBV is estimated to decrease over time. The comparison of results of the three models indicated that in respect to existing seasonality trend and non-stationarity, the HES had the most accurate prediction of the incidence rates.
An Investigation of Undefined Cut Scores with the Hofstee Standard-Setting Method
Wyse, Adam E.; Babcock, Ben
2017-01-01
This article provides an overview of the Hofstee standard-setting method and illustrates several situations where the Hofstee method will produce undefined cut scores. The situations where the cut scores will be undefined involve cases where the line segment derived from the Hofstee ratings does not intersect the score distribution curve based on…
METHODS FOR CLUSTERING TIME SERIES DATA ACQUIRED FROM MOBILE HEALTH APPS.
Tignor, Nicole; Wang, Pei; Genes, Nicholas; Rogers, Linda; Hershman, Steven G; Scott, Erick R; Zweig, Micol; Yvonne Chan, Yu-Feng; Schadt, Eric E
2017-01-01
In our recent Asthma Mobile Health Study (AMHS), thousands of asthma patients across the country contributed medical data through the iPhone Asthma Health App on a daily basis for an extended period of time. The collected data included daily self-reported asthma symptoms, symptom triggers, and real time geographic location information. The AMHS is just one of many studies occurring in the context of now many thousands of mobile health apps aimed at improving wellness and better managing chronic disease conditions, leveraging the passive and active collection of data from mobile, handheld smart devices. The ability to identify patient groups or patterns of symptoms that might predict adverse outcomes such as asthma exacerbations or hospitalizations from these types of large, prospectively collected data sets, would be of significant general interest. However, conventional clustering methods cannot be applied to these types of longitudinally collected data, especially survey data actively collected from app users, given heterogeneous patterns of missing values due to: 1) varying survey response rates among different users, 2) varying survey response rates over time of each user, and 3) non-overlapping periods of enrollment among different users. To handle such complicated missing data structure, we proposed a probability imputation model to infer missing data. We also employed a consensus clustering strategy in tandem with the multiple imputation procedure. Through simulation studies under a range of scenarios reflecting real data conditions, we identified favorable performance of the proposed method over other strategies that impute the missing value through low-rank matrix completion. When applying the proposed new method to study asthma triggers and symptoms collected as part of the AMHS, we identified several patient groups with distinct phenotype patterns. Further validation of the methods described in this paper might be used to identify clinically important
A Mapmark method of standard setting as implemented for the National Assessment Governing Board.
Schulz, E Matthew; Mitzel, Howard C
2011-01-01
This article describes a Mapmark standard setting procedure, developed under contract with the National Assessment Governing Board (NAGB). The procedure enhances the bookmark method with spatially representative item maps, holistic feedback, and an emphasis on independent judgment. A rationale for these enhancements, and the bookmark method, is presented, followed by a detailed description of the materials and procedures used in a meeting to set standards for the 2005 National Assessment of Educational Progress (NAEP) in Grade 12 mathematics. The use of difficulty-ordered content domains to provide holistic feedback is a particularly novel feature of the method. Process evaluation results comparing Mapmark to Anghoff-based methods previously used for NAEP standard setting are also presented.
An accurate conservative level set/ghost fluid method for simulating turbulent atomization
International Nuclear Information System (INIS)
Desjardins, Olivier; Moureau, Vincent; Pitsch, Heinz
2008-01-01
This paper presents a novel methodology for simulating incompressible two-phase flows by combining an improved version of the conservative level set technique introduced in [E. Olsson, G. Kreiss, A conservative level set method for two phase flow, J. Comput. Phys. 210 (2005) 225-246] with a ghost fluid approach. By employing a hyperbolic tangent level set function that is transported and re-initialized using fully conservative numerical schemes, mass conservation issues that are known to affect level set methods are greatly reduced. In order to improve the accuracy of the conservative level set method, high order numerical schemes are used. The overall robustness of the numerical approach is increased by computing the interface normals from a signed distance function reconstructed from the hyperbolic tangent level set by a fast marching method. The convergence of the curvature calculation is ensured by using a least squares reconstruction. The ghost fluid technique provides a way of handling the interfacial forces and large density jumps associated with two-phase flows with good accuracy, while avoiding artificial spreading of the interface. Since the proposed approach relies on partial differential equations, its implementation is straightforward in all coordinate systems, and it benefits from high parallel efficiency. The robustness and efficiency of the approach is further improved by using implicit schemes for the interface transport and re-initialization equations, as well as for the momentum solver. The performance of the method is assessed through both classical level set transport tests and simple two-phase flow examples including topology changes. It is then applied to simulate turbulent atomization of a liquid Diesel jet at Re=3000. The conservation errors associated with the accurate conservative level set technique are shown to remain small even for this complex case
Effect of the absolute statistic on gene-sampling gene-set analysis methods.
Nam, Dougu
2017-06-01
Gene-set enrichment analysis and its modified versions have commonly been used for identifying altered functions or pathways in disease from microarray data. In particular, the simple gene-sampling gene-set analysis methods have been heavily used for datasets with only a few sample replicates. The biggest problem with this approach is the highly inflated false-positive rate. In this paper, the effect of absolute gene statistic on gene-sampling gene-set analysis methods is systematically investigated. Thus far, the absolute gene statistic has merely been regarded as a supplementary method for capturing the bidirectional changes in each gene set. Here, it is shown that incorporating the absolute gene statistic in gene-sampling gene-set analysis substantially reduces the false-positive rate and improves the overall discriminatory ability. Its effect was investigated by power, false-positive rate, and receiver operating curve for a number of simulated and real datasets. The performances of gene-set analysis methods in one-tailed (genome-wide association study) and two-tailed (gene expression data) tests were also compared and discussed.
Wu, Zi Yi; Xie, Ping; Sang, Yan Fang; Gu, Hai Ting
2018-04-01
The phenomenon of jump is one of the importantly external forms of hydrological variabi-lity under environmental changes, representing the adaption of hydrological nonlinear systems to the influence of external disturbances. Presently, the related studies mainly focus on the methods for identifying the jump positions and jump times in hydrological time series. In contrast, few studies have focused on the quantitative description and classification of jump degree in hydrological time series, which make it difficult to understand the environmental changes and evaluate its potential impacts. Here, we proposed a theatrically reliable and easy-to-apply method for the classification of jump degree in hydrological time series, using the correlation coefficient as a basic index. The statistical tests verified the accuracy, reasonability, and applicability of this method. The relationship between the correlation coefficient and the jump degree of series were described using mathematical equation by derivation. After that, several thresholds of correlation coefficients under different statistical significance levels were chosen, based on which the jump degree could be classified into five levels: no, weak, moderate, strong and very strong. Finally, our method was applied to five diffe-rent observed hydrological time series, with diverse geographic and hydrological conditions in China. The results of the classification of jump degrees in those series were closely accorded with their physically hydrological mechanisms, indicating the practicability of our method.
Farahi, Maria; Rabbani, Hossein; Talebi, Ardeshir; Sarrafzadeh, Omid; Ensafi, Shahab
2015-12-01
Visceral Leishmaniasis is a parasitic disease that affects liver, spleen and bone marrow. According to World Health Organization report, definitive diagnosis is possible just by direct observation of the Leishman body in the microscopic image taken from bone marrow samples. We utilize morphological and CV level set method to segment Leishman bodies in digital color microscopic images captured from bone marrow samples. Linear contrast stretching method is used for image enhancement and morphological method is applied to determine the parasite regions and wipe up unwanted objects. Modified global and local CV level set methods are proposed for segmentation and a shape based stopping factor is used to hasten the algorithm. Manual segmentation is considered as ground truth to evaluate the proposed method. This method is tested on 28 samples and achieved 10.90% mean of segmentation error for global model and 9.76% for local model.
Chaya, S; Dangor, Z; Solomon, F; Nzenze, S A; Izu, A; Madhi, S A
2016-11-01
This study was undertaken at a tertiary hospital in Soweto, a peri-urban low-middle income setting. Mycobacterium tuberculosis meningitis (TBM) is a severe manifestation of extra-pulmonary tuberculosis. To describe the incidence, mortality and clinical features of TBM in human immunodeficiency virus (HIV) infected and non-infected children in South Africa from 2006 to 2011. A retrospective, cross-sectional descriptive study. Electronic databases and individual patient records of all children with a discharge diagnosis of TBM were reviewed to yield incidence rate ratios (IRR) in HIV-infected and non-infected children. Clinical, laboratory and radiological characteristics were compared between HIV-infected and non-infected children with TBM. Overall TBM incidence per 100 000 population in 2006 was 6.9 (95%CI 4.4-10.3) and 9.8 (95%CI 6.9-13.6) in 2009, but had subsequently declined to 3.1 (95%CI 1.6-5.5) by 2011. There was a significant reduction in the IRR of TBM among HIV-infected children (IRR 0.916, P = 0.036). The overall case fatality ratio was 6.7%. Clinical features, cerebrospinal fluid and computed tomography brain findings were similar in HIV-infected and non-infected children. TBM incidence decreased over the study period from 2006 to 2011, and was temporally associated with an increase in the uptake of antiretroviral treatment in HIV-infected individuals.
Setting health research priorities using the CHNRI method: IV. Key conceptual advances
Directory of Open Access Journals (Sweden)
Igor Rudan
2016-06-01
Full Text Available Child Health and Nutrition Research Initiative (CHNRI started as an initiative of the Global Forum for Health Research in Geneva, Switzerland. Its aim was to develop a method that could assist priority setting in health research investments. The first version of the CHNRI method was published in 2007–2008. The aim of this paper was to summarize the history of the development of the CHNRI method and its key conceptual advances.
Yoshida, Sachiyo; Rudan, Igor; Cousens, Simon
2016-06-01
Crowdsourcing has become an increasingly important tool to address many problems - from government elections in democracies, stock market prices, to modern online tools such as TripAdvisor or Internet Movie Database (IMDB). The CHNRI method (the acronym for the Child Health and Nutrition Research Initiative) for setting health research priorities has crowdsourcing as the major component, which it uses to generate, assess and prioritize between many competing health research ideas. We conducted a series of analyses using data from a group of 91 scorers to explore the quantitative properties of their collective opinion. We were interested in the stability of their collective opinion as the sample size increases from 15 to 90. From a pool of 91 scorers who took part in a previous CHNRI exercise, we used sampling with replacement to generate multiple random samples of different size. First, for each sample generated, we identified the top 20 ranked research ideas, among 205 that were proposed and scored, and calculated the concordance with the ranking generated by the 91 original scorers. Second, we used rank correlation coefficients to compare the ranks assigned to all 205 proposed research ideas when samples of different size are used. We also analysed the original pool of 91 scorers to to look for evidence of scoring variations based on scorers' characteristics. The sample sizes investigated ranged from 15 to 90. The concordance for the top 20 scored research ideas increased with sample sizes up to about 55 experts. At this point, the median level of concordance stabilized at 15/20 top ranked questions (75%), with the interquartile range also generally stable (14-16). There was little further increase in overlap when the sample size increased from 55 to 90. When analysing the ranking of all 205 ideas, the rank correlation coefficient increased as the sample size increased, with a median correlation of 0.95 reached at the sample size of 45 experts (median of the rank
Farmer, William H.; Archfield, Stacey A.; Over, Thomas M.; Hay, Lauren E.; LaFontaine, Jacob H.; Kiang, Julie E.
2015-01-01
Effective and responsible management of water resources relies on a thorough understanding of the quantity and quality of available water. Streamgages cannot be installed at every location where streamflow information is needed. As part of its National Water Census, the U.S. Geological Survey is planning to provide streamflow predictions for ungaged locations. In order to predict streamflow at a useful spatial and temporal resolution throughout the Nation, efficient methods need to be selected. This report examines several methods used for streamflow prediction in ungaged basins to determine the best methods for regional and national implementation. A pilot area in the southeastern United States was selected to apply 19 different streamflow prediction methods and evaluate each method by a wide set of performance metrics. Through these comparisons, two methods emerged as the most generally accurate streamflow prediction methods: the nearest-neighbor implementations of nonlinear spatial interpolation using flow duration curves (NN-QPPQ) and standardizing logarithms of streamflow by monthly means and standard deviations (NN-SMS12L). It was nearly impossible to distinguish between these two methods in terms of performance. Furthermore, neither of these methods requires significantly more parameterization in order to be applied: NN-SMS12L requires 24 regional regressions—12 for monthly means and 12 for monthly standard deviations. NN-QPPQ, in the application described in this study, required 27 regressions of particular quantiles along the flow duration curve. Despite this finding, the results suggest that an optimal streamflow prediction method depends on the intended application. Some methods are stronger overall, while some methods may be better at predicting particular statistics. The methods of analysis presented here reflect a possible framework for continued analysis and comprehensive multiple comparisons of methods of prediction in ungaged basins (PUB
Comparison of different methods for the solution of sets of linear equations
International Nuclear Information System (INIS)
Bilfinger, T.; Schmidt, F.
1978-06-01
The application of the conjugate-gradient methods as novel general iterative methods for the solution of sets of linear equations with symmetrical systems matrices led to this paper, where a comparison of these methods with the conventional differently accelerated Gauss-Seidel iteration was carried out. In additon, the direct Cholesky method was also included in the comparison. The studies referred mainly to memory requirement, computing time, speed of convergence, and accuracy of different conditions of the systems matrices, by which also the sensibility of the methods with respect to the influence of truncation errors may be recognized. (orig.) 891 RW [de
Studying learning in the healthcare setting: the potential of quantitative diary methods.
Ciere, Yvette; Jaarsma, Debbie; Visser, Annemieke; Sanderman, Robbert; Snippe, Evelien; Fleer, Joke
2015-08-01
Quantitative diary methods are longitudinal approaches that involve the repeated measurement of aspects of peoples' experience of daily life. In this article, we outline the main characteristics and applications of quantitative diary methods and discuss how their use may further research in the field of medical education. Quantitative diary methods offer several methodological advantages, such as measuring aspects of learning with great detail, accuracy and authenticity. Moreover, they enable researchers to study how and under which conditions learning in the health care setting occurs and in which way learning can be promoted. Hence, quantitative diary methods may contribute to theory development and the optimization of teaching methods in medical education.
Use of simulated data sets to evaluate the fidelity of Metagenomicprocessing methods
Energy Technology Data Exchange (ETDEWEB)
Mavromatis, Konstantinos; Ivanova, Natalia; Barry, Kerri; Shapiro, Harris; Goltsman, Eugene; McHardy, Alice C.; Rigoutsos, Isidore; Salamov, Asaf; Korzeniewski, Frank; Land, Miriam; Lapidus, Alla; Grigoriev, Igor; Richardson, Paul; Hugenholtz, Philip; Kyrpides, Nikos C.
2006-12-01
Metagenomics is a rapidly emerging field of research for studying microbial communities. To evaluate methods presently used to process metagenomic sequences, we constructed three simulated data sets of varying complexity by combining sequencing reads randomly selected from 113 isolate genomes. These data sets were designed to model real metagenomes in terms of complexity and phylogenetic composition. We assembled sampled reads using three commonly used genome assemblers (Phrap, Arachne and JAZZ), and predicted genes using two popular gene finding pipelines (fgenesb and CRITICA/GLIMMER). The phylogenetic origins of the assembled contigs were predicted using one sequence similarity--based (blast hit distribution) and two sequence composition--based (PhyloPythia, oligonucleotide frequencies) binning methods. We explored the effects of the simulated community structure and method combinations on the fidelity of each processing step by comparison to the corresponding isolate genomes. The simulated data sets are available online to facilitate standardized benchmarking of tools for metagenomic analysis.
Use of simulated data sets to evaluate the fidelity of metagenomic processing methods
Energy Technology Data Exchange (ETDEWEB)
Mavromatis, K [U.S. Department of Energy, Joint Genome Institute; Ivanova, N [U.S. Department of Energy, Joint Genome Institute; Barry, Kerrie [U.S. Department of Energy, Joint Genome Institute; Shapiro, Harris [U.S. Department of Energy, Joint Genome Institute; Goltsman, Eugene [U.S. Department of Energy, Joint Genome Institute; McHardy, Alice C. [IBM T. J. Watson Research Center; Rigoutsos, Isidore [IBM T. J. Watson Research Center; Salamov, Asaf [U.S. Department of Energy, Joint Genome Institute; Korzeniewski, Frank [U.S. Department of Energy, Joint Genome Institute; Land, Miriam L [ORNL; Lapidus, Alla L. [U.S. Department of Energy, Joint Genome Institute; Grigoriev, Igor [U.S. Department of Energy, Joint Genome Institute; Hugenholtz, Philip [U.S. Department of Energy, Joint Genome Institute; Kyrpides, Nikos C [U.S. Department of Energy, Joint Genome Institute
2007-01-01
Metagenomics is a rapidly emerging field of research for studying microbial communities. To evaluate methods presently used to process metagenomic sequences, we constructed three simulated data sets of varying complexity by combining sequencing reads randomly selected from 113 isolate genomes. These data sets were designed to model real metagenomes in terms of complexity and phylogenetic composition. We assembled sampled reads using three commonly used genome assemblers (Phrap, Arachne and JAZZ), and predicted genes using two popular gene-finding pipelines (fgenesb and CRITICA/GLIMMER). The phylogenetic origins of the assembled contigs were predicted using one sequence similarity-based ( blast hit distribution) and two sequence composition-based (PhyloPythia, oligonucleotide frequencies) binning methods. We explored the effects of the simulated community structure and method combinations on the fidelity of each processing step by comparison to the corresponding isolate genomes. The simulated data sets are available online to facilitate standardized benchmarking of tools for metagenomic analysis.
Set simulation of a turbulent arc by Monte-Carlo method
International Nuclear Information System (INIS)
Zhukov, M.F.; Devyatov, B.N.; Nazaruk, V.I.
1982-01-01
A method of simulation of turbulent arc fluctuations is suggested which is based on the probabilistic set description of conducting channel displacements over the plane not nodes with taking into account the turbulent eddies causing non-uniformity of the field of displacements. The problem is treated in terms of the random set theory. Methods to control the displacements by varying the local displacement sets are described. A local-set approach in the turbulent arc simulation is used for a statistical study of the arc form evolution in a turbulent gas flow. The method implies the performance of numerical experiments on a computer. Various ways to solve the problem of control of the geometric form of an arc column on a model are described. Under consideration are the problems of organization of physical experiments to obtain the required information for the identification of local sets. The suggested method of the application of mathematical experiments is associated with the principles of an operational game. (author)
Level Set Projection Method for Incompressible Navier-Stokes on Arbitrary Boundaries
Williams-Rioux, Bertrand
2012-01-12
Second order level set projection method for incompressible Navier-Stokes equations is proposed to solve flow around arbitrary geometries. We used rectilinear grid with collocated cell centered velocity and pressure. An explicit Godunov procedure is used to address the nonlinear advection terms, and an implicit Crank-Nicholson method to update viscous effects. An approximate pressure projection is implemented at the end of the time stepping using multigrid as a conventional fast iterative method. The level set method developed by Osher and Sethian [17] is implemented to address real momentum and pressure boundary conditions by the advection of a distance function, as proposed by Aslam [3]. Numerical results for the Strouhal number and drag coefficients validated the model with good accuracy for flow over a cylinder in the parallel shedding regime (47 < Re < 180). Simulations for an array of cylinders and an oscillating cylinder were performed, with the latter demonstrating our methods ability to handle dynamic boundary conditions.
Application of the level set method for multi-phase flow computation in fusion engineering
International Nuclear Information System (INIS)
Luo, X-Y.; Ni, M-J.; Ying, A.; Abdou, M.
2006-01-01
Numerical simulation of multi-phase flow is essential to evaluate the feasibility of a liquid protection scheme for the power plant chamber. The level set method is one of the best methods for computing and analyzing the motion of interface among the multi-phase flow. This paper presents a general formula for the second-order projection method combined with the level set method to simulate unsteady incompressible multi-phase flow with/out phase change flow encountered in fusion science and engineering. The third-order ENO scheme and second-order semi-implicit Crank-Nicholson scheme is used to update the convective and diffusion term. The numerical results show this method can handle the complex deformation of the interface and the effect of liquid-vapor phase change will be included in the future work
DEFF Research Database (Denmark)
Xu, Shenzhi; Ai, Xiaomeng; Fang, Jiakun
2017-01-01
Photovoltaic (PV) power generation has made considerable developments in recent years. But its intermittent and volatility of its output has seriously affected the security operation of the power system. In order to better understand the PV generation and provide sufficient data support...... for analysis the impacts, a novel generation method for PV power time series combining decomposition technique and Markov chain theory is presented in this paper. It digs important factors from historical data from existing PV plants and then reproduce new data with similar patterns. In detail, the proposed...... method first decomposes the PV power time series into ideal output curve, amplitude parameter series and random fluctuating component three parts. Then generating daily ideal output curve by the extraction of typical daily data, amplitude parameter series based on the Markov chain Monte Carlo (MCMC...
Robust boundary detection of left ventricles on ultrasound images using ASM-level set method.
Zhang, Yaonan; Gao, Yuan; Li, Hong; Teng, Yueyang; Kang, Yan
2015-01-01
Level set method has been widely used in medical image analysis, but it has difficulties when being used in the segmentation of left ventricular (LV) boundaries on echocardiography images because the boundaries are not very distinguish, and the signal-to-noise ratio of echocardiography images is not very high. In this paper, we introduce the Active Shape Model (ASM) into the traditional level set method to enforce shape constraints. It improves the accuracy of boundary detection and makes the evolution more efficient. The experiments conducted on the real cardiac ultrasound image sequences show a positive and promising result.
Directory of Open Access Journals (Sweden)
Užga-Rebrovs Oļegs
2017-12-01
Full Text Available Fuzzy inference systems are widely used in various areas of human activity. Their most widespread use lies in the field of fuzzy control of technical devices of different kind. Another direction of using fuzzy inference systems is modelling and assessment of different kind of risks under insufficient or missing objective initial data. Fuzzy inference is concluded by the procedure of defuzzification of the resulting fuzzy sets. A large number of techniques for implementing the defuzzification procedure are available nowadays. The paper presents a comparative analysis of some widespread methods of fuzzy set defuzzification, and proposes the most appropriate methods in the context of ecological risk assessment.
Directory of Open Access Journals (Sweden)
James Lee
2017-02-01
Full Text Available The increasing professionalism of sports persons and desire of consumers to imitate this has led to an increased metrification of sport. This has been driven in no small part by the widespread availability of comparatively cheap assessment technologies and, more recently, wearable technologies. Historically, whilst these have produced large data sets, often only the most rudimentary analysis has taken place (Wisbey et al in: “Quantifying movement demands of AFL football using GPS tracking”. This paucity of analysis is due in no small part to the challenges of analysing large sets of data that are often from disparate data sources to glean useful key performance indicators, which has been a largely a labour intensive process. This paper presents a framework that can be cloud based for the gathering, storing and algorithmic interpretation of large and inhomogeneous time series data sets. The framework is architecture based and technology agnostic in the data sources it can gather, and presents a model for multi set analysis for inter- and intra- devices and individual subject matter. A sample implementation demonstrates the utility of the framework for sports performance data collected from distributed inertial sensors in the sport of swimming.
Directory of Open Access Journals (Sweden)
Marko Mladineo
2016-12-01
Full Text Available In the last 20 years, priority setting in mine actions, i.e. in humanitarian demining, has become an increasingly important topic. Given that mine action projects require management and decision-making based on a multi -criteria approach, multi-criteria decision-making methods like PROMETHEE and AHP have been used worldwide for priority setting. However, from the aspect of mine action, where stakeholders in the decision-making process for priority setting are project managers, local politicians, leaders of different humanitarian organizations, or similar, applying these methods can be difficult. Therefore, a specialized web-based decision support system (Web DSS for priority setting, developed as part of the FP7 project TIRAMISU, has been extended using a module for developing custom priority setting scenarios in line with an exceptionally easy, user-friendly approach. The idea behind this research is to simplify the multi-criteria analysis based on the PROMETHEE method. Therefore, a simplified PROMETHEE method based on statistical analysis for automated suggestions of parameters such as preference function thresholds, interactive selection of criteria weights, and easy input of criteria evaluations is presented in this paper. The result is web-based DSS that can be applied worldwide for priority setting in mine action. Additionally, the management of mine action projects is supported using modules for providing spatial data based on the geographic information system (GIS. In this paper, the benefits and limitations of a simplified PROMETHEE method are presented using a case study involving mine action projects, and subsequently, certain proposals are given for the further research.
Novel method of finding extreme edges in a convex set of N-dimension vectors
Hu, Chia-Lun J.
2001-11-01
As we published in the last few years, for a binary neural network pattern recognition system to learn a given mapping {Um mapped to Vm, m=1 to M} where um is an N- dimension analog (pattern) vector, Vm is a P-bit binary (classification) vector, the if-and-only-if (IFF) condition that this network can learn this mapping is that each i-set in {Ymi, m=1 to M} (where Ymithere existsVmiUm and Vmi=+1 or -1, is the i-th bit of VR-m).)(i=1 to P and there are P sets included here.) Is POSITIVELY, LINEARLY, INDEPENDENT or PLI. We have shown that this PLI condition is MORE GENERAL than the convexity condition applied to a set of N-vectors. In the design of old learning machines, we know that if a set of N-dimension analog vectors form a convex set, and if the machine can learn the boundary vectors (or extreme edges) of this set, then it can definitely learn the inside vectors contained in this POLYHEDRON CONE. This paper reports a new method and new algorithm to find the boundary vectors of a convex set of ND analog vectors.
A Fourier-series-based kernel-independent fast multipole method
International Nuclear Information System (INIS)
Zhang Bo; Huang Jingfang; Pitsianis, Nikos P.; Sun Xiaobai
2011-01-01
We present in this paper a new kernel-independent fast multipole method (FMM), named as FKI-FMM, for pairwise particle interactions with translation-invariant kernel functions. FKI-FMM creates, using numerical techniques, sufficiently accurate and compressive representations of a given kernel function over multi-scale interaction regions in the form of a truncated Fourier series. It provides also economic operators for the multipole-to-multipole, multipole-to-local, and local-to-local translations that are typical and essential in the FMM algorithms. The multipole-to-local translation operator, in particular, is readily diagonal and does not dominate in arithmetic operations. FKI-FMM provides an alternative and competitive option, among other kernel-independent FMM algorithms, for an efficient application of the FMM, especially for applications where the kernel function consists of multi-physics and multi-scale components as those arising in recent studies of biological systems. We present the complexity analysis and demonstrate with experimental results the FKI-FMM performance in accuracy and efficiency.
ROS evaluation for a series of CNTs and their derivatives using an ESR method with DMPO
International Nuclear Information System (INIS)
Tsuruoka, S; Noguchi, T; Endo, M; Tristan, F; Terrones, M; Takeuchi, K; Koyama, K; Usui, Y; Matsumoto, H; Saito, N; Porter, D W; Castranova, V
2013-01-01
Carbon nanotubes (CNTs) are important materials in advanced industries. It is a concern that pulmonary exposure to CNTs may induce carcinogenic responses. It has been recently reported that CNTs scavenge ROS though non-carbon fibers generate ROS. A comprehensive evaluation of ROS scavenging using various kinds of CNTs has not been demonstrated well. The present work specifically investigates ROS scavenging capabilities with a series of CNTs and their derivatives that were physically treated, and with the number of commercially available CNTs. CNT concentrations were controlled at 0.2 through 0.6 wt%. The ROS scavenging rate was measured by ESR with DMPO. Interestingly, the ROS scavenging rate was not only influenced by physical treatments, but was also dependent on individual manufacturing methods. Ratio of CNTs to DMPO/ hydrogen peroxide is a key parameter to obtain appropriate ROS quenching results for comparison of CNTs. The present results suggest that dangling bonds are not a sole factor for scavenging, and electron transfer on the CNT surface is not clearly determined to be the sole mechanism to explain ROS scavenging.
ROS evaluation for a series of CNTs and their derivatives using an ESR method with DMPO.
Tsuruoka, S; Takeuchi, K; Koyama, K; Noguchi, T; Endo, M; Tristan, F; Terrones, M; Matsumoto, H; Saito, N; Usui, Y; Porter, D W; Castranova, V
Carbon nanotubes (CNTs) are important materials in advanced industries. It is a concern that pulmonary exposure to CNTs may induce carcinogenic responses. It has been recently reported that CNTs scavenge ROS though non-carbon fibers generate ROS. A comprehensive evaluation of ROS scavenging using various kinds of CNTs has not been demonstrated well. The present work specifically investigates ROS scavenging capabilities with a series of CNTs and their derivatives that were physically treated, and with the number of commercially available CNTs. CNT concentrations were controlled at 0.2 through 0.6 wt%. The ROS scavenging rate was measured by ESR with DMPO. Interestingly, the ROS scavenging rate was not only influenced by physical treatments, but was also dependent on individual manufacturing methods. Ratio of CNTs to DMPO/ hydrogen peroxide is a key parameter to obtain appropriate ROS quenching results for comparison of CNTs. The present results suggest that dangling bonds are not a sole factor for scavenging, and electron transfer on the CNT surface is not clearly determined to be the sole mechanism to explain ROS scavenging.
A Cartesian Adaptive Level Set Method for Two-Phase Flows
Ham, F.; Young, Y.-N.
2003-01-01
In the present contribution we develop a level set method based on local anisotropic Cartesian adaptation as described in Ham et al. (2002). Such an approach should allow for the smallest possible Cartesian grid capable of resolving a given flow. The remainder of the paper is organized as follows. In section 2 the level set formulation for free surface calculations is presented and its strengths and weaknesses relative to the other free surface methods reviewed. In section 3 the collocated numerical method is described. In section 4 the method is validated by solving the 2D and 3D drop oscilation problem. In section 5 we present some results from more complex cases including the 3D drop breakup in an impulsively accelerated free stream, and the 3D immiscible Rayleigh-Taylor instability. Conclusions are given in section 6.
Reconstruction of thin electromagnetic inclusions by a level-set method
International Nuclear Information System (INIS)
Park, Won-Kwang; Lesselier, Dominique
2009-01-01
In this contribution, we consider a technique of electromagnetic imaging (at a single, non-zero frequency) which uses the level-set evolution method for reconstructing a thin inclusion (possibly made of disconnected parts) with either dielectric or magnetic contrast with respect to the embedding homogeneous medium. Emphasis is on the proof of the concept, the scattering problem at hand being so far based on a two-dimensional scalar model. To do so, two level-set functions are employed; the first one describes location and shape, and the other one describes connectivity and length. Speeds of evolution of the level-set functions are calculated via the introduction of Fréchet derivatives of a least-square cost functional. Several numerical experiments on noiseless and noisy data as well illustrate how the proposed method behaves
International Nuclear Information System (INIS)
Liu, J.; Lan, T.; Qin, H.
2017-01-01
Traditional data cleaning identifies dirty data by classifying original data sequences, which is a class-imbalanced problem since the proportion of incorrect data is much less than the proportion of correct ones for most diagnostic systems in Magnetic Confinement Fusion (MCF) devices. When using machine learning algorithms to classify diagnostic data based on class-imbalanced training set, most classifiers are biased towards the major class and show very poor classification rates on the minor class. By transforming the direct classification problem about original data sequences into a classification problem about the physical similarity between data sequences, the class-balanced effect of Time-Domain Global Similarity (TDGS) method on training set structure is investigated in this paper. Meanwhile, the impact of improved training set structure on data cleaning performance of TDGS method is demonstrated with an application example in EAST POlarimetry-INTerferometry (POINT) system.
Level set methods for detonation shock dynamics using high-order finite elements
Energy Technology Data Exchange (ETDEWEB)
Dobrev, V. A. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Grogan, F. C. [Univ. of California, San Diego, CA (United States); Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Kolev, T. V. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Rieben, R [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Tomov, V. Z. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
2017-05-26
Level set methods are a popular approach to modeling evolving interfaces. We present a level set ad- vection solver in two and three dimensions using the discontinuous Galerkin method with high-order nite elements. During evolution, the level set function is reinitialized to a signed distance function to maintain ac- curacy. Our approach leads to stable front propagation and convergence on high-order, curved, unstructured meshes. The ability of the solver to implicitly track moving fronts lends itself to a number of applications; in particular, we highlight applications to high-explosive (HE) burn and detonation shock dynamics (DSD). We provide results for two- and three-dimensional benchmark problems as well as applications to DSD.
International Nuclear Information System (INIS)
Kari, R.E.; Mezey, P.G.; Csizmadia, I.G.
1975-01-01
Expressions are given for calculating the energy gradient vector in the exponent space of Gaussian basis sets and a technique to optimize orbital exponents using the method of conjugate gradients is described. The method is tested on the (9/sups/5/supp/) Gaussian basis space and optimum exponents are determined for the carbon atom. The analysis of the results shows that the calculated one-electron properties converge more slowly to their optimum values than the total energy converges to its optimum value. In addition, basis sets approximating the optimum total energy very well can still be markedly improved for the prediction of one-electron properties. For smaller basis sets, this improvement does not warrant the necessary expense
DEFF Research Database (Denmark)
Otomori, Masaki; Yamada, Takayuki; Izui, Kazuhiro
2012-01-01
This paper presents a level set-based topology optimization method for the design of negative permeability dielectric metamaterials. Metamaterials are artificial materials that display extraordinary physical properties that are unavailable with natural materials. The aim of the formulated...... optimization problem is to find optimized layouts of a dielectric material that achieve negative permeability. The presence of grayscale areas in the optimized configurations critically affects the performance of metamaterials, positively as well as negatively, but configurations that contain grayscale areas...... are highly impractical from an engineering and manufacturing point of view. Therefore, a topology optimization method that can obtain clear optimized configurations is desirable. Here, a level set-based topology optimization method incorporating a fictitious interface energy is applied to a negative...
Houston, Lauren; Probst, Yasmine; Martin, Allison
2018-05-18
Data audits within clinical settings are extensively used as a major strategy to identify errors, monitor study operations and ensure high-quality data. However, clinical trial guidelines are non-specific in regards to recommended frequency, timing and nature of data audits. The absence of a well-defined data quality definition and method to measure error undermines the reliability of data quality assessment. This review aimed to assess the variability of source data verification (SDV) auditing methods to monitor data quality in a clinical research setting. The scientific databases MEDLINE, Scopus and Science Direct were searched for English language publications, with no date limits applied. Studies were considered if they included data from a clinical trial or clinical research setting and measured and/or reported data quality using a SDV auditing method. In total 15 publications were included. The nature and extent of SDV audit methods in the articles varied widely, depending upon the complexity of the source document, type of study, variables measured (primary or secondary), data audit proportion (3-100%) and collection frequency (6-24 months). Methods for coding, classifying and calculating error were also inconsistent. Transcription errors and inexperienced personnel were the main source of reported error. Repeated SDV audits using the same dataset demonstrated ∼40% improvement in data accuracy and completeness over time. No description was given in regards to what determines poor data quality in clinical trials. A wide range of SDV auditing methods are reported in the published literature though no uniform SDV auditing method could be determined for "best practice" in clinical trials. Published audit methodology articles are warranted for the development of a standardised SDV auditing method to monitor data quality in clinical research settings. Copyright © 2018. Published by Elsevier Inc.
A perturbation method for dark solitons based on a complete set of the squared Jost solutions
International Nuclear Information System (INIS)
Ao Shengmei; Yan Jiaren
2005-01-01
A perturbation method for dark solitons is developed, which is based on the construction and the rigorous proof of the complete set of squared Jost solutions. The general procedure solving the adiabatic solution of perturbed nonlinear Schroedinger + equation, the time-evolution equation of dark soliton parameters and a formula for calculating the first-order correction are given. The method can also overcome the difficulties resulting from the non-vanishing boundary condition
A scalable method for identifying frequent subtrees in sets of large phylogenetic trees.
Ramu, Avinash; Kahveci, Tamer; Burleigh, J Gordon
2012-10-03
We consider the problem of finding the maximum frequent agreement subtrees (MFASTs) in a collection of phylogenetic trees. Existing methods for this problem often do not scale beyond datasets with around 100 taxa. Our goal is to address this problem for datasets with over a thousand taxa and hundreds of trees. We develop a heuristic solution that aims to find MFASTs in sets of many, large phylogenetic trees. Our method works in multiple phases. In the first phase, it identifies small candidate subtrees from the set of input trees which serve as the seeds of larger subtrees. In the second phase, it combines these small seeds to build larger candidate MFASTs. In the final phase, it performs a post-processing step that ensures that we find a frequent agreement subtree that is not contained in a larger frequent agreement subtree. We demonstrate that this heuristic can easily handle data sets with 1000 taxa, greatly extending the estimation of MFASTs beyond current methods. Although this heuristic does not guarantee to find all MFASTs or the largest MFAST, it found the MFAST in all of our synthetic datasets where we could verify the correctness of the result. It also performed well on large empirical data sets. Its performance is robust to the number and size of the input trees. Overall, this method provides a simple and fast way to identify strongly supported subtrees within large phylogenetic hypotheses.
Convex Coverage Set Methods for Multi-Objective Collaborative Decision Making
Roijers, D.M.; Lomuscio, A.; Scerri, P.; Bazzan, A.; Huhns, M.
2014-01-01
My research is aimed at finding efficient coordination methods for multi-objective collaborative multi-agent decision theoretic planning. Key to coordinating efficiently in these settings is exploiting loose couplings between agents. We proposed two algorithms for the case in which the agents need
Review of the different methods to derive average spacing from resolved resonance parameters sets
International Nuclear Information System (INIS)
Fort, E.; Derrien, H.; Lafond, D.
1979-12-01
The average spacing of resonances is an important parameter for statistical model calculations, especially concerning non fissile nuclei. The different methods to derive this average value from resonance parameters sets have been reviewed and analyzed in order to tentatively detect their respective weaknesses and propose recommendations. Possible improvements are suggested
The black-body radiation inversion problem, its instability and a new universal function set method
International Nuclear Information System (INIS)
Ye, JiPing; Ji, FengMin; Wen, Tao; Dai, Xian-Xi; Dai, Ji-Xin; Evenson, William E.
2006-01-01
The black-body radiation inversion (BRI) problem is ill-posed and requires special techniques to achieve stable solutions. In this Letter, the universal function set method (UFS), is developed in BRI. An improved unique existence theorem is proposed. Asymptotic behavior control (ABC) is introduced. A numerical example shows that practical calculations are possible with UFS
Rudan, Igor; Yoshida, Sachiyo; Wazny, Kerri; Chan, Kit Yee; Cousens, Simon
2016-06-01
The CHNRI method for setting health research priorities has crowdsourcing as the major component. It uses the collective opinion of a group of experts to generate, assess and prioritize between many competing health research ideas. It is difficult to compare the accuracy of human individual and collective opinions in predicting uncertain future outcomes before the outcomes are known. However, this limitation does not apply to existing knowledge, which is an important component underlying opinion. In this paper, we report several experiments to explore the quantitative properties of human collective knowledge and discuss their relevance to the CHNRI method. We conducted a series of experiments in groups of about 160 (range: 122-175) undergraduate Year 2 medical students to compare their collective knowledge to their individual knowledge. We asked them to answer 10 questions on each of the following: (i) an area in which they have a degree of expertise (undergraduate Year 1 medical curriculum); (ii) an area in which they likely have some knowledge (general knowledge); and (iii) an area in which they are not expected to have any knowledge (astronomy). We also presented them with 20 pairs of well-known celebrities and asked them to identify the older person of the pair. In all these experiments our goal was to examine how the collective answer compares to the distribution of students' individual answers. When answering the questions in their own area of expertise, the collective answer (the median) was in the top 20.83% of the most accurate individual responses; in general knowledge, it was in the top 11.93%; and in an area with no expertise, the group answer was in the top 7.02%. However, the collective answer based on mean values fared much worse, ranging from top 75.60% to top 95.91%. Also, when confronted with guessing the older of the two celebrities, the collective response was correct in 18/20 cases (90%), while the 8 most successful individuals among the
Rudan, Igor; Yoshida, Sachiyo; Chan, Kit Yee; Sridhar, Devi; Wazny, Kerri; Nair, Harish; Sheikh, Aziz; Tomlinson, Mark; Lawn, Joy E; Bhutta, Zulfiqar A; Bahl, Rajiv; Chopra, Mickey; Campbell, Harry; El Arifeen, Shams; Black, Robert E; Cousens, Simon
2017-06-01
Several recent reviews of the methods used to set research priorities have identified the CHNRI method (acronym derived from the "Child Health and Nutrition Research Initiative") as an approach that clearly became popular and widely used over the past decade. In this paper we review the first 50 examples of application of the CHNRI method, published between 2007 and 2016, and summarize the most important messages that emerged from those experiences. We conducted a literature review to identify the first 50 examples of application of the CHNRI method in chronological order. We searched Google Scholar, PubMed and so-called grey literature. Initially, between 2007 and 2011, the CHNRI method was mainly used for setting research priorities to address global child health issues, although the first cases of application outside this field (eg, mental health, disabilities and zoonoses) were also recorded. Since 2012 the CHNRI method was used more widely, expanding into the topics such as adolescent health, dementia, national health policy and education. The majority of the exercises were focused on issues that were only relevant to low- and middle-income countries, and national-level applications are on the rise. The first CHNRI-based articles adhered to the five recommended priority-setting criteria, but by 2016 more than two-thirds of all conducted exercises departed from recommendations, modifying the CHNRI method to suit each particular exercise. This was done not only by changing the number of criteria used, but also by introducing some entirely new criteria (eg, "low cost", "sustainability", "acceptability", "feasibility", "relevance" and others). The popularity of the CHNRI method in setting health research priorities can be attributed to several key conceptual advances that have addressed common concerns. The method is systematic in nature, offering an acceptable framework for handling many research questions. It is also transparent and replicable, because it
Directory of Open Access Journals (Sweden)
Levi Lopes Teixeira
2015-12-01
Full Text Available Time series forecasting is widely used in various areas of human knowledge, especially in the planning and strategic direction of companies. The success of this task depends on the forecasting techniques applied. In this paper, a hybrid approach to project time series is suggested. To validate the methodology, a time series already modeled by other authors was chosen, allowing the comparison of results. The proposed methodology includes the following techniques: wavelet shrinkage, wavelet decomposition at level r, and artificial neural networks (ANN. Firstly, a time series to be forecasted is submitted to the proposed wavelet filtering method, which decomposes it to components of trend and linear residue. Then, both are decomposed via level r wavelet decomposition, generating r + 1 Wavelet Components (WCs for each one; and then each WC is individually modeled by an ANN. Finally, the predictions for all WCs are linearly combined, producing forecasts to the underlying time series. For evaluating purposes, the time series of Canadian Lynx has been used, and all results achieved by the proposed method were better than others in existing literature.
Advances in time series methods and applications the A. Ian McLeod festschrift
Stanford, David; Yu, Hao
2016-01-01
This volume reviews and summarizes some of A. I. McLeod's significant contributions to time series analysis. It also contains original contributions to the field and to related areas by participants of the festschrift held in June 2014 and friends of Dr. McLeod. Covering a diverse range of state-of-the-art topics, this volume well balances applied and theoretical research across fourteen contributions by experts in the field. It will be of interest to researchers and practitioners in time series, econometricians, and graduate students in time series or econometrics, as well as environmental statisticians, data scientists, statisticians interested in graphical models, and researchers in quantitative risk management.
Online monitoring of oil film using electrical capacitance tomography and level set method
International Nuclear Information System (INIS)
Xue, Q.; Ma, M.; Sun, B. Y.; Cui, Z. Q.; Wang, H. X.
2015-01-01
In the application of oil-air lubrication system, electrical capacitance tomography (ECT) provides a promising way for monitoring oil film in the pipelines by reconstructing cross sectional oil distributions in real time. While in the case of small diameter pipe and thin oil film, the thickness of the oil film is hard to be observed visually since the interface of oil and air is not obvious in the reconstructed images. And the existence of artifacts in the reconstructions has seriously influenced the effectiveness of image segmentation techniques such as level set method. Besides, level set method is also unavailable for online monitoring due to its low computation speed. To address these problems, a modified level set method is developed: a distance regularized level set evolution formulation is extended to image two-phase flow online using an ECT system, a narrowband image filter is defined to eliminate the influence of artifacts, and considering the continuity of the oil distribution variation, the detected oil-air interface of a former image can be used as the initial contour for the detection of the subsequent frame; thus, the propagation from the initial contour to the boundary can be greatly accelerated, making it possible for real time tracking. To testify the feasibility of the proposed method, an oil-air lubrication facility with 4 mm inner diameter pipe is measured in normal operation using an 8-electrode ECT system. Both simulation and experiment results indicate that the modified level set method is capable of visualizing the oil-air interface accurately online
Forecasting ocean wave energy: A Comparison of the ECMWF wave model with time series methods
DEFF Research Database (Denmark)
Reikard, Gordon; Pinson, Pierre; Bidlot, Jean
2011-01-01
Recently, the technology has been developed to make wave farms commercially viable. Since electricity is perishable, utilities will be interested in forecasting ocean wave energy. The horizons involved in short-term management of power grids range from as little as a few hours to as long as several...... days. In selecting a method, the forecaster has a choice between physics-based models and statistical techniques. A further idea is to combine both types of models. This paper analyzes the forecasting properties of a well-known physics-based model, the European Center for Medium-Range Weather Forecasts...... (ECMWF) Wave Model, and two statistical techniques, time-varying parameter regressions and neural networks. Thirteen data sets at locations in the Atlantic and Pacific Oceans and the Gulf of Mexico are tested. The quantities to be predicted are the significant wave height, the wave period, and the wave...
International Nuclear Information System (INIS)
Anderson, Ryan B.; Bell, James F.; Wiens, Roger C.; Morris, Richard V.; Clegg, Samuel M.
2012-01-01
We investigated five clustering and training set selection methods to improve the accuracy of quantitative chemical analysis of geologic samples by laser induced breakdown spectroscopy (LIBS) using partial least squares (PLS) regression. The LIBS spectra were previously acquired for 195 rock slabs and 31 pressed powder geostandards under 7 Torr CO 2 at a stand-off distance of 7 m at 17 mJ per pulse to simulate the operational conditions of the ChemCam LIBS instrument on the Mars Science Laboratory Curiosity rover. The clustering and training set selection methods, which do not require prior knowledge of the chemical composition of the test-set samples, are based on grouping similar spectra and selecting appropriate training spectra for the partial least squares (PLS2) model. These methods were: (1) hierarchical clustering of the full set of training spectra and selection of a subset for use in training; (2) k-means clustering of all spectra and generation of PLS2 models based on the training samples within each cluster; (3) iterative use of PLS2 to predict sample composition and k-means clustering of the predicted compositions to subdivide the groups of spectra; (4) soft independent modeling of class analogy (SIMCA) classification of spectra, and generation of PLS2 models based on the training samples within each class; (5) use of Bayesian information criteria (BIC) to determine an optimal number of clusters and generation of PLS2 models based on the training samples within each cluster. The iterative method and the k-means method using 5 clusters showed the best performance, improving the absolute quadrature root mean squared error (RMSE) by ∼ 3 wt.%. The statistical significance of these improvements was ∼ 85%. Our results show that although clustering methods can modestly improve results, a large and diverse training set is the most reliable way to improve the accuracy of quantitative LIBS. In particular, additional sulfate standards and specifically
Using Machine Learning Methods Jointly to Find Better Set of Rules in Data Mining
Directory of Open Access Journals (Sweden)
SUG Hyontai
2017-01-01
Full Text Available Rough set-based data mining algorithms are one of widely accepted machine learning technologies because of their strong mathematical background and capability of finding optimal rules based on given data sets only without room for prejudiced views to be inserted on the data. But, because the algorithms find rules very precisely, we may confront with the overfitting problem. On the other hand, association rule algorithms find rules of association, where the association resides between sets of items in database. The algorithms find itemsets that occur more than given minimum support, so that they can find the itemsets practically in reasonable time even for very large databases by supplying the minimum support appropriately. In order to overcome the problem of the overfitting problem in rough set-based algorithms, first we find large itemsets, after that we select attributes that cover the large itemsets. By using the selected attributes only, we may find better set of rules based on rough set theory. Results from experiments support our suggested method.
Benchmarking Methods and Data Sets for Ligand Enrichment Assessment in Virtual Screening
Xia, Jie; Tilahun, Ermias Lemma; Reid, Terry-Elinor; Zhang, Liangren; Wang, Xiang Simon
2014-01-01
Retrospective small-scale virtual screening (VS) based on benchmarking data sets has been widely used to estimate ligand enrichments of VS approaches in the prospective (i.e. real-world) efforts. However, the intrinsic differences of benchmarking sets to the real screening chemical libraries can cause biased assessment. Herein, we summarize the history of benchmarking methods as well as data sets and highlight three main types of biases found in benchmarking sets, i.e. “analogue bias”, “artificial enrichment” and “false negative”. In addition, we introduced our recent algorithm to build maximum-unbiased benchmarking sets applicable to both ligand-based and structure-based VS approaches, and its implementations to three important human histone deacetylase (HDAC) isoforms, i.e. HDAC1, HDAC6 and HDAC8. The Leave-One-Out Cross-Validation (LOO CV) demonstrates that the benchmarking sets built by our algorithm are maximum-unbiased in terms of property matching, ROC curves and AUCs. PMID:25481478
Benchmarking methods and data sets for ligand enrichment assessment in virtual screening.
Xia, Jie; Tilahun, Ermias Lemma; Reid, Terry-Elinor; Zhang, Liangren; Wang, Xiang Simon
2015-01-01
Retrospective small-scale virtual screening (VS) based on benchmarking data sets has been widely used to estimate ligand enrichments of VS approaches in the prospective (i.e. real-world) efforts. However, the intrinsic differences of benchmarking sets to the real screening chemical libraries can cause biased assessment. Herein, we summarize the history of benchmarking methods as well as data sets and highlight three main types of biases found in benchmarking sets, i.e. "analogue bias", "artificial enrichment" and "false negative". In addition, we introduce our recent algorithm to build maximum-unbiased benchmarking sets applicable to both ligand-based and structure-based VS approaches, and its implementations to three important human histone deacetylases (HDACs) isoforms, i.e. HDAC1, HDAC6 and HDAC8. The leave-one-out cross-validation (LOO CV) demonstrates that the benchmarking sets built by our algorithm are maximum-unbiased as measured by property matching, ROC curves and AUCs. Copyright © 2014 Elsevier Inc. All rights reserved.
International Nuclear Information System (INIS)
Samrout, M.; Yalaoui, F.; Cha-hat telet, E.; Chebbo, N.
2005-01-01
This article is based on a previous study made by Bris, Chatelet and Yalaoui [Bris R, Chatelet E, Yalaoui F. New method to minimise the preventive maintenance cost of series-parallel systems. Reliab Eng Syst Saf 2003;82:247-55]. They use genetic algorithm to minimize preventive maintenance cost problem for the series-parallel systems. We propose to improve their results developing a new method based on another technique, the Ant Colony Optimization (ACO). The resolution consists in determining the solution vector of system component inspection periods, T P . Those calculations were applied within the programming tool Matlab. Thus, highly interesting results and improvements of previous studies were obtained
A multilevel, level-set method for optimizing eigenvalues in shape design problems
International Nuclear Information System (INIS)
Haber, E.
2004-01-01
In this paper, we consider optimal design problems that involve shape optimization. The goal is to determine the shape of a certain structure such that it is either as rigid or as soft as possible. To achieve this goal we combine two new ideas for an efficient solution of the problem. First, we replace the eigenvalue problem with an approximation by using inverse iteration. Second, we use a level set method but rather than propagating the front we use constrained optimization methods combined with multilevel continuation techniques. Combining these two ideas we obtain a robust and rapid method for the solution of the optimal design problem
Microwave imaging of dielectric cylinder using level set method and conjugate gradient algorithm
International Nuclear Information System (INIS)
Grayaa, K.; Bouzidi, A.; Aguili, T.
2011-01-01
In this paper, we propose a computational method for microwave imaging cylinder and dielectric object, based on combining level set technique and the conjugate gradient algorithm. By measuring the scattered field, we tried to retrieve the shape, localisation and the permittivity of the object. The forward problem is solved by the moment method, while the inverse problem is reformulate in an optimization one and is solved by the proposed scheme. It found that the proposed method is able to give good reconstruction quality in terms of the reconstructed shape and permittivity.
A Time-Series Water Level Forecasting Model Based on Imputation and Variable Selection Method
Jun-He Yang; Ching-Hsue Cheng; Chia-Pan Chan
2017-01-01
Reservoirs are important for households and impact the national economy. This paper proposed a time-series forecasting model based on estimating a missing value followed by variable selection to forecast the reservoir's water level. This study collected data from the Taiwan Shimen Reservoir as well as daily atmospheric data from 2008 to 2015. The two datasets are concatenated into an integrated dataset based on ordering of the data as a research dataset. The proposed time-series forecasting m...
Comparison of different Methods for Univariate Time Series Imputation in R
Moritz, Steffen; Sardá, Alexis; Bartz-Beielstein, Thomas; Zaefferer, Martin; Stork, Jörg
2015-01-01
Missing values in datasets are a well-known problem and there are quite a lot of R packages offering imputation functions. But while imputation in general is well covered within R, it is hard to find functions for imputation of univariate time series. The problem is, most standard imputation techniques can not be applied directly. Most algorithms rely on inter-attribute correlations, while univariate time series imputation needs to employ time dependencies. This paper provides an overview of ...
Azuaje, Francisco; Zheng, Huiru; Camargo, Anyela; Wang, Haiying
2011-08-01
The discovery of novel disease biomarkers is a crucial challenge for translational bioinformatics. Demonstration of both their classification power and reproducibility across independent datasets are essential requirements to assess their potential clinical relevance. Small datasets and multiplicity of putative biomarker sets may explain lack of predictive reproducibility. Studies based on pathway-driven discovery approaches have suggested that, despite such discrepancies, the resulting putative biomarkers tend to be implicated in common biological processes. Investigations of this problem have been mainly focused on datasets derived from cancer research. We investigated the predictive and functional concordance of five methods for discovering putative biomarkers in four independently-generated datasets from the cardiovascular disease domain. A diversity of biosignatures was identified by the different methods. However, we found strong biological process concordance between them, especially in the case of methods based on gene set analysis. With a few exceptions, we observed lack of classification reproducibility using independent datasets. Partial overlaps between our putative sets of biomarkers and the primary studies exist. Despite the observed limitations, pathway-driven or gene set analysis can predict potentially novel biomarkers and can jointly point to biomedically-relevant underlying molecular mechanisms. Copyright © 2011 Elsevier Inc. All rights reserved.
Rudan, Igor; Gibson, Jennifer L.; Ameratunga, Shanthi; El Arifeen, Shams; Bhutta, Zulfiqar A.; Black, Maureen; Black, Robert E.; Brown, Kenneth H.; Campbell, Harry; Carneiro, Ilona; Chan, Kit Yee; Chandramohan, Daniel; Chopra, Mickey; Cousens, Simon; Darmstadt, Gary L.; Gardner, Julie Meeks; Hess, Sonja Y.; Hyder, Adnan A.; Kapiriri, Lydia; Kosek, Margaret; Lanata, Claudio F.; Lansang, Mary Ann; Lawn, Joy; Tomlinson, Mark; Tsai, Alexander C.; Webster, Jayne
2008-01-01
This article provides detailed guidelines for the implementation of systematic method for setting priorities in health research investments that was recently developed by Child Health and Nutrition Research Initiative (CHNRI). The target audience for the proposed method are international agencies, large research funding donors, and national governments and policy-makers. The process has the following steps: (i) selecting the managers of the process; (ii) specifying the context and risk management preferences; (iii) discussing criteria for setting health research priorities; (iv) choosing a limited set of the most useful and important criteria; (v) developing means to assess the likelihood that proposed health research options will satisfy the selected criteria; (vi) systematic listing of a large number of proposed health research options; (vii) pre-scoring check of all competing health research options; (viii) scoring of health research options using the chosen set of criteria; (ix) calculating intermediate scores for each health research option; (x) obtaining further input from the stakeholders; (xi) adjusting intermediate scores taking into account the values of stakeholders; (xii) calculating overall priority scores and assigning ranks; (xiii) performing an analysis of agreement between the scorers; (xiv) linking computed research priority scores with investment decisions; (xv) feedback and revision. The CHNRI method is a flexible process that enables prioritizing health research investments at any level: institutional, regional, national, international, or global. PMID:19090596
Thorndahl, S; Willems, P
2008-01-01
Failure of urban drainage systems may occur due to surcharge or flooding at specific manholes in the system, or due to overflows from combined sewer systems to receiving waters. To quantify the probability or return period of failure, standard approaches make use of the simulation of design storms or long historical rainfall series in a hydrodynamic model of the urban drainage system. In this paper, an alternative probabilistic method is investigated: the first-order reliability method (FORM). To apply this method, a long rainfall time series was divided in rainstorms (rain events), and each rainstorm conceptualized to a synthetic rainfall hyetograph by a Gaussian shape with the parameters rainstorm depth, duration and peak intensity. Probability distributions were calibrated for these three parameters and used on the basis of the failure probability estimation, together with a hydrodynamic simulation model to determine the failure conditions for each set of parameters. The method takes into account the uncertainties involved in the rainstorm parameterization. Comparison is made between the failure probability results of the FORM method, the standard method using long-term simulations and alternative methods based on random sampling (Monte Carlo direct sampling and importance sampling). It is concluded that without crucial influence on the modelling accuracy, the FORM is very applicable as an alternative to traditional long-term simulations of urban drainage systems.
The Interval-Valued Triangular Fuzzy Soft Set and Its Method of Dynamic Decision Making
Xiaoguo Chen; Hong Du; Yue Yang
2014-01-01
A concept of interval-valued triangular fuzzy soft set is presented, and some operations of “AND,” “OR,” intersection, union and complement, and so forth are defined. Then some relative properties are discussed and several conclusions are drawn. A dynamic decision making model is built based on the definition of interval-valued triangular fuzzy soft set, in which period weight is determined by the exponential decay method. The arithmetic weighted average operator of interval-valued triangular...
A Survey on Methods for Reconstructing Surfaces from Unorganized Point Sets
Directory of Open Access Journals (Sweden)
Vilius Matiukas
2011-08-01
Full Text Available This paper addresses the issue of reconstructing and visualizing surfaces from unorganized point sets. These can be acquired using different techniques, such as 3D-laser scanning, computerized tomography, magnetic resonance imaging and multi-camera imaging. The problem of reconstructing surfaces from their unorganized point sets is common for many diverse areas, including computer graphics, computer vision, computational geometry or reverse engineering. The paper presents three alternative methods that all use variations in complementary cones to triangulate and reconstruct the tested 3D surfaces. The article evaluates and contrasts three alternatives.Article in English
Doctors' use of mobile devices in the clinical setting: a mixed methods study.
Nerminathan, Arany; Harrison, Amanda; Phelps, Megan; Alexander, Shirley; Scott, Karen M
2017-03-01
Mobile device use has become almost ubiquitous in daily life and therefore includes use by doctors in clinical settings. There has been little study as to the patterns of use and impact this has on doctors in the workplace and how negatively or positively it impacts at the point of care. To explore how doctors use mobile devices in the clinical setting and understand drivers for use. A mixed methods study was used with doctors in a paediatric and adult teaching hospital in 2013. A paper-based survey examined mobile device usage data by doctors in the clinical setting. Focus groups explored doctors' reasons for using or refraining from using mobile devices in the clinical setting, and their attitudes about others' use. The survey, completed by 109 doctors, showed that 91% owned a smartphone and 88% used their mobile devices frequently in the clinical setting. Trainees were more likely than consultants to use their mobile devices for learning and accessing information related to patient care, as well as for personal communication unrelated to work. Focus group data highlighted a range of factors that influenced doctors to use personal mobile devices in the clinical setting, including convenience for medical photography, and factors that limited use. Distraction in the clinical setting due to use of mobile devices was a key issue. Personal experience and confidence in using mobile devices affected their use, and was guided by role modelling and expectations within a medical team. Doctors use mobile devices to enhance efficiency in the workplace. In the current environment, doctors are making their own decisions based on balancing the risks and benefits of using mobile devices in the clinical setting. There is a need for guidelines around acceptable and ethical use that is patient-centred and that respects patient privacy. © 2016 Royal Australasian College of Physicians.
Evaluation of three methods for hemoglobin measurement in a blood donor setting
Directory of Open Access Journals (Sweden)
Jacob Rosenblit
1999-05-01
Full Text Available CONTEXT: The hemoglobin (Hb level is the most-used parameter for screening blood donors for the presence of anemia, one of the most-used methods for measuring Hb levels is based on photometric detection of cyanmetahemoglobin, as an alternative to this technology, HemoCue has developed a photometric method based on the determination of azide metahemoglobin. OBJECTIVE: To evaluate the performance of three methods for hemoglobin (Hb determination in a blood bank setting. DESIGN: Prospective study utilizing blood samples to compare methods for Hb determination. SETTING: Hemotherapy Service of the Hospital Israelita Albert Einstein, a private institution in the tertiary health care system. SAMPLE: Serial blood samples were collected from 259 individuals during the period from March to June 1996. MAIN MEASUREMENTS: Test performances and their comparisons were assessed by the analysis of coefficients of variation (CV, linear regression and mean differences. RESULTS: The CV for the three methods were: Coulter 0.68%, Cobas 0.82% and HemoCue 0.69%. There was no difference between the mean Hb determination for the three methods (p>0.05. The Coulter and Cobas methods showed the best agreement and the HemoCue method gave a lower Hb determination when compared to both the Coulter and Cobas methods. However, pairs of methods involving the HemoCue seem to have narrower limits of agreement (± 0.78 and ± 1.02 than the Coulter and Cobas combination (± 1.13. CONCLUSION: The three methods provide good agreement for hemoglobin determination.
A level set method for cupping artifact correction in cone-beam CT
International Nuclear Information System (INIS)
Xie, Shipeng; Li, Haibo; Ge, Qi; Li, Chunming
2015-01-01
Purpose: To reduce cupping artifacts and improve the contrast-to-noise ratio in cone-beam computed tomography (CBCT). Methods: A level set method is proposed to reduce cupping artifacts in the reconstructed image of CBCT. The authors derive a local intensity clustering property of the CBCT image and define a local clustering criterion function of the image intensities in a neighborhood of each point. This criterion function defines an energy in terms of the level set functions, which represent a segmentation result and the cupping artifacts. The cupping artifacts are estimated as a result of minimizing this energy. Results: The cupping artifacts in CBCT are reduced by an average of 90%. The results indicate that the level set-based algorithm is practical and effective for reducing the cupping artifacts and preserving the quality of the reconstructed image. Conclusions: The proposed method focuses on the reconstructed image without requiring any additional physical equipment, is easily implemented, and provides cupping correction through a single-scan acquisition. The experimental results demonstrate that the proposed method successfully reduces the cupping artifacts
Stabilized Conservative Level Set Method with Adaptive Wavelet-based Mesh Refinement
Shervani-Tabar, Navid; Vasilyev, Oleg V.
2016-11-01
This paper addresses one of the main challenges of the conservative level set method, namely the ill-conditioned behavior of the normal vector away from the interface. An alternative formulation for reconstruction of the interface is proposed. Unlike the commonly used methods which rely on the unit normal vector, Stabilized Conservative Level Set (SCLS) uses a modified renormalization vector with diminishing magnitude away from the interface. With the new formulation, in the vicinity of the interface the reinitialization procedure utilizes compressive flux and diffusive terms only in the normal direction to the interface, thus, preserving the conservative level set properties, while away from the interfaces the directional diffusion mechanism automatically switches to homogeneous diffusion. The proposed formulation is robust and general. It is especially well suited for use with adaptive mesh refinement (AMR) approaches due to need for a finer resolution in the vicinity of the interface in comparison with the rest of the domain. All of the results were obtained using the Adaptive Wavelet Collocation Method, a general AMR-type method, which utilizes wavelet decomposition to adapt on steep gradients in the solution while retaining a predetermined order of accuracy.
Directory of Open Access Journals (Sweden)
Liying Geng
2014-03-01
Full Text Available More than 20 techniques have been developed to de-noise time-series vegetation index data from different satellite sensors to reconstruct long time-series data sets. Although many studies have compared Normalized Difference Vegetation Index (NDVI noise-reduction techniques, few studies have compared these techniques systematically and comprehensively. This study tested eight techniques for smoothing different vegetation types using different types of multi-temporal NDVI data (Advanced Very High Resolution Radiometer (AVHRR (Global Inventory Modeling and Map Studies (GIMMS and Pathfinder AVHRR Land (PAL, Satellite Pour l’ Observation de la Terre (SPOT VEGETATION (VGT, and Moderate Resolution Imaging Spectroradiometer (MODIS (Terra with the ultimate purpose of determining the best reconstruction technique for each type of vegetation captured with four satellite sensors. These techniques include the modified best index slope extraction (M-BISE technique, the Savitzky-Golay (S-G technique, the mean value iteration filter (MVI technique, the asymmetric Gaussian (A-G technique, the double logistic (D-L technique, the changing-weight filter (CW technique, the interpolation for data reconstruction (IDR technique, and the Whittaker smoother (WS technique. These techniques were evaluated by calculating the root mean square error (RMSE, the Akaike Information Criterion (AIC, and the Bayesian Information Criterion (BIC. The results indicate that the S-G, CW, and WS techniques perform better than the other tested techniques, while the IDR, M-BISE, and MVI techniques performed worse than the other techniques. The best de-noise technique varies with different vegetation types and NDVI data sources. The S-G performs best in most situations. In addition, the CW and WS are effective techniques that were exceeded only by the S-G technique. The assessment results are consistent in terms of the three evaluation indexes for GIMMS, PAL, and SPOT data in the study
A mass conserving level set method for detailed numerical simulation of liquid atomization
Energy Technology Data Exchange (ETDEWEB)
Luo, Kun; Shao, Changxiao [State Key Laboratory of Clean Energy Utilization, Zhejiang University, Hangzhou 310027 (China); Yang, Yue [State Key Laboratory of Turbulence and Complex Systems, Peking University, Beijing 100871 (China); Fan, Jianren, E-mail: fanjr@zju.edu.cn [State Key Laboratory of Clean Energy Utilization, Zhejiang University, Hangzhou 310027 (China)
2015-10-01
An improved mass conserving level set method for detailed numerical simulations of liquid atomization is developed to address the issue of mass loss in the existing level set method. This method introduces a mass remedy procedure based on the local curvature at the interface, and in principle, can ensure the absolute mass conservation of the liquid phase in the computational domain. Three benchmark cases, including Zalesak's disk, a drop deforming in a vortex field, and the binary drop head-on collision, are simulated to validate the present method, and the excellent agreement with exact solutions or experimental results is achieved. It is shown that the present method is able to capture the complex interface with second-order accuracy and negligible additional computational cost. The present method is then applied to study more complex flows, such as a drop impacting on a liquid film and the swirling liquid sheet atomization, which again, demonstrates the advantages of mass conservation and the capability to represent the interface accurately.
Application of the Laplace transform method for computational modelling of radioactive decay series
Energy Technology Data Exchange (ETDEWEB)
Oliveira, Deise L.; Damasceno, Ralf M.; Barros, Ricardo C. [Univ. do Estado do Rio de Janeiro (IME/UERJ) (Brazil). Programa de Pos-graduacao em Ciencias Computacionais
2012-03-15
It is well known that when spent fuel is removed from the core, it is still composed of considerable amount of radioactive elements with significant half-lives. Most actinides, in particular plutonium, fall into this category, and have to be safely disposed of. One solution is to store the long-lived spent fuel as it is, by encasing and burying it deep underground in a stable geological formation. This implies estimating the transmutation of these radioactive elements with time. Therefore, we describe in this paper the application of the Laplace transform technique in matrix formulation to analytically solve initial value problems that mathematically model radioactive decay series. Given the initial amount of each type of radioactive isotopes in the decay series, the computer code generates the amount at a given time of interest, or may plot a graph of the evolution in time of the amount of each type of isotopes in the series. This computer code, that we refer to as the LTRad{sub L} code, where L is the number of types of isotopes belonging to the series, was developed using the Scilab free platform for numerical computation and can model one segment or the entire chain of any of the three radioactive series existing on Earth today. Numerical results are given to typical model problems to illustrate the computer code efficiency and accuracy. (orig.)
Application of the Laplace transform method for computational modelling of radioactive decay series
International Nuclear Information System (INIS)
Oliveira, Deise L.; Damasceno, Ralf M.; Barros, Ricardo C.
2012-01-01
It is well known that when spent fuel is removed from the core, it is still composed of considerable amount of radioactive elements with significant half-lives. Most actinides, in particular plutonium, fall into this category, and have to be safely disposed of. One solution is to store the long-lived spent fuel as it is, by encasing and burying it deep underground in a stable geological formation. This implies estimating the transmutation of these radioactive elements with time. Therefore, we describe in this paper the application of the Laplace transform technique in matrix formulation to analytically solve initial value problems that mathematically model radioactive decay series. Given the initial amount of each type of radioactive isotopes in the decay series, the computer code generates the amount at a given time of interest, or may plot a graph of the evolution in time of the amount of each type of isotopes in the series. This computer code, that we refer to as the LTRad L code, where L is the number of types of isotopes belonging to the series, was developed using the Scilab free platform for numerical computation and can model one segment or the entire chain of any of the three radioactive series existing on Earth today. Numerical results are given to typical model problems to illustrate the computer code efficiency and accuracy. (orig.)
Formal Analysis of SET and NSL Protocols Using the Interpretation Functions-Based Method
Directory of Open Access Journals (Sweden)
Hanane Houmani
2012-01-01
Full Text Available Most applications in the Internet such as e-banking and e-commerce use the SET and the NSL protocols to protect the communication channel between the client and the server. Then, it is crucial to ensure that these protocols respect some security properties such as confidentiality, authentication, and integrity. In this paper, we analyze the SET and the NSL protocols with respect to the confidentiality (secrecy property. To perform this analysis, we use the interpretation functions-based method. The main idea behind the interpretation functions-based technique is to give sufficient conditions that allow to guarantee that a cryptographic protocol respects the secrecy property. The flexibility of the proposed conditions allows the verification of daily-life protocols such as SET and NSL. Also, this method could be used under different assumptions such as a variety of intruder abilities including algebraic properties of cryptographic primitives. The NSL protocol, for instance, is analyzed with and without the homomorphism property. We show also, using the SET protocol, the usefulness of this approach to correct weaknesses and problems discovered during the analysis.
Two Surface-Tension Formulations For The Level Set Interface-Tracking Method
International Nuclear Information System (INIS)
Shepel, S.V.; Smith, B.L.
2005-01-01
The paper describes a comparative study of two surface-tension models for the Level Set interface tracking method. In both models, the surface tension is represented as a body force, concentrated near the interface, but the technical implementation of the two options is different. The first is based on a traditional Level Set approach, in which the surface tension is distributed over a narrow band around the interface using a smoothed Delta function. In the second model, which is based on the integral form of the fluid-flow equations, the force is imposed only in those computational cells through which the interface passes. Both models have been incorporated into the Finite-Element/Finite-Volume Level Set method, previously implemented into the commercial Computational Fluid Dynamics (CFD) code CFX-4. A critical evaluation of the two models, undertaken in the context of four standard Level Set benchmark problems, shows that the first model, based on the smoothed Delta function approach, is the more general, and more robust, of the two. (author)
Variational Level Set Method for Two-Stage Image Segmentation Based on Morphological Gradients
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Zemin Ren
2014-01-01
Full Text Available We use variational level set method and transition region extraction techniques to achieve image segmentation task. The proposed scheme is done by two steps. We first develop a novel algorithm to extract transition region based on the morphological gradient. After this, we integrate the transition region into a variational level set framework and develop a novel geometric active contour model, which include an external energy based on transition region and fractional order edge indicator function. The external energy is used to drive the zero level set toward the desired image features, such as object boundaries. Due to this external energy, the proposed model allows for more flexible initialization. The fractional order edge indicator function is incorporated into the length regularization term to diminish the influence of noise. Moreover, internal energy is added into the proposed model to penalize the deviation of the level set function from a signed distance function. The results evolution of the level set function is the gradient flow that minimizes the overall energy functional. The proposed model has been applied to both synthetic and real images with promising results.
Fault Diagnosis Method of Polymerization Kettle Equipment Based on Rough Sets and BP Neural Network
Directory of Open Access Journals (Sweden)
Shu-zhi Gao
2013-01-01
Full Text Available Polyvinyl chloride (PVC polymerizing production process is a typical complex controlled object, with complexity features, such as nonlinear, multivariable, strong coupling, and large time-delay. Aiming at the real-time fault diagnosis and optimized monitoring requirements of the large-scale key polymerization equipment of PVC production process, a real-time fault diagnosis strategy is proposed based on rough sets theory with the improved discernibility matrix and BP neural networks. The improved discernibility matrix is adopted to reduct the attributes of rough sets in order to decrease the input dimensionality of fault characteristics effectively. Levenberg-Marquardt BP neural network is trained to diagnose the polymerize faults according to the reducted decision table, which realizes the nonlinear mapping from fault symptom set to polymerize fault set. Simulation experiments are carried out combining with the industry history datum to show the effectiveness of the proposed rough set neural networks fault diagnosis method. The proposed strategy greatly increased the accuracy rate and efficiency of the polymerization fault diagnosis system.
Phase-of-flight method for setting the accelerating fields in the ion linear accelerator
International Nuclear Information System (INIS)
Dvortsov, S.V.; Lomize, L.G.
1983-01-01
For setting amplitudes and phases of accelerating fields in multiresonator ion accelerators presently Δt-procedure is used. The determination and setting of two unknown parameters of RF-field (amplitude and phase) in n-resonator is made according to the two increments of particle time-of-flight, measured experimentally: according to the change of the particle time-of-flight Δt 1 in the n-resonator, during the field switching in the resonator, and according to the change of Δt 2 of the time-of-flight in (n+1) resonator without RF-field with the switching of accelerating field in the n-resonator. When approaching the accelerator exit the particle energy increases, relative energy increment decreases and the accuracy of setting decreases. To enchance the accuracy of accelerating fields setting in a linear ion accelerator a phase-of-flight method is developed, in which for the setting of accelerating fields the measured time-of-flight increment Δt only in one resonator is used (the one in which the change of amplitude and phase is performed). Results of simulation of point bunch motion in the IYaI AN USSR linear accelerator are presented
Harman, Nate
2016-01-01
We consider the following counting problem related to the card game SET: How many $k$-element SET-free sets are there in an $n$-dimensional SET deck? Through a series of algebraic reformulations and reinterpretations, we show the answer to this question satisfies two polynomiality conditions.
A level-set method for two-phase flows with soluble surfactant
Xu, Jian-Jun; Shi, Weidong; Lai, Ming-Chih
2018-01-01
A level-set method is presented for solving two-phase flows with soluble surfactant. The Navier-Stokes equations are solved along with the bulk surfactant and the interfacial surfactant equations. In particular, the convection-diffusion equation for the bulk surfactant on the irregular moving domain is solved by using a level-set based diffusive-domain method. A conservation law for the total surfactant mass is derived, and a re-scaling procedure for the surfactant concentrations is proposed to compensate for the surfactant mass loss due to numerical diffusion. The whole numerical algorithm is easy for implementation. Several numerical simulations in 2D and 3D show the effects of surfactant solubility on drop dynamics under shear flow.
Evaluation of two-phase flow solvers using Level Set and Volume of Fluid methods
Bilger, C.; Aboukhedr, M.; Vogiatzaki, K.; Cant, R. S.
2017-09-01
Two principal methods have been used to simulate the evolution of two-phase immiscible flows of liquid and gas separated by an interface. These are the Level-Set (LS) method and the Volume of Fluid (VoF) method. Both methods attempt to represent the very sharp interface between the phases and to deal with the large jumps in physical properties associated with it. Both methods have their own strengths and weaknesses. For example, the VoF method is known to be prone to excessive numerical diffusion, while the basic LS method has some difficulty in conserving mass. Major progress has been made in remedying these deficiencies, and both methods have now reached a high level of physical accuracy. Nevertheless, there remains an issue, in that each of these methods has been developed by different research groups, using different codes and most importantly the implementations have been fine tuned to tackle different applications. Thus, it remains unclear what are the remaining advantages and drawbacks of each method relative to the other, and what might be the optimal way to unify them. In this paper, we address this gap by performing a direct comparison of two current state-of-the-art variations of these methods (LS: RCLSFoam and VoF: interPore) and implemented in the same code (OpenFoam). We subject both methods to a pair of benchmark test cases while using the same numerical meshes to examine a) the accuracy of curvature representation, b) the effect of tuning parameters, c) the ability to minimise spurious velocities and d) the ability to tackle fluids with very different densities. For each method, one of the test cases is chosen to be fairly benign while the other test case is expected to present a greater challenge. The results indicate that both methods can be made to work well on both test cases, while displaying different sensitivity to the relevant parameters.
New Multi-Criteria Group Decision-Making Method Based on Vague Set Theory
Kuo-Sui Lin
2016-01-01
In light of the deficiencies and limitations for existing score functions, Lin has proposed a more effective and reasonable new score function for measuring vague values. By using Lin’s score function and a new weighted aggregation score function, an algorithm for multi-criteria group decision-making method was proposed to solve vague set based group decision-making problems under vague environments. Finally, a numerical example was illustrated to show the effectiveness of the proposed multi-...
Set up of a method for the adjustment of resonance parameters on integral experiments
International Nuclear Information System (INIS)
Blaise, P.
1996-01-01
Resonance parameters for actinides play a significant role in the neutronic characteristics of all reactor types. All the major integral parameters strongly depend on the nuclear data of the isotopes in the resonance-energy regions.The author sets up a method for the adjustment of resonance parameters taking into account the self-shielding effects and restricting the cross section deconvolution problem to a limited energy region. (N.T.)
Group supervision in a private setting: Practice and method for theory and practice in psychotherapy
Directory of Open Access Journals (Sweden)
Graziana Mangiacavallo
2015-05-01
Full Text Available The report aims to tell the experience of a supervision group in a private setting. The group consists of professional psychotherapists driven by the more experienced practitioner, who shares a clinical reasoning on psychotherapy with younger colleagues. The report aims to present the supervision group as a methode and to showcase its features. The supervision group becomes a container of professional experiences that speak of the new way of doing psychotherapy.
Special values of the hypergeometric series
Ebisu, Akihito
2017-01-01
In this paper, the author presents a new method for finding identities for hypergeoemtric series, such as the (Gauss) hypergeometric series, the generalized hypergeometric series and the Appell-Lauricella hypergeometric series. Furthermore, using this method, the author gets identities for the hypergeometric series F(a,b;c;x) and shows that values of F(a,b;c;x) at some points x can be expressed in terms of gamma functions, together with certain elementary functions. The author tabulates the values of F(a,b;c;x) that can be obtained with this method and finds that this set includes almost all previously known values and many previously unknown values.
Comparing simple root phenotyping methods on a core set of rice genotypes.
Shrestha, R; Al-Shugeairy, Z; Al-Ogaidi, F; Munasinghe, M; Radermacher, M; Vandenhirtz, J; Price, A H
2014-05-01
Interest in belowground plant growth is increasing, especially in relation to arguments that shallow-rooted cultivars are efficient at exploiting soil phosphorus while deep-rooted ones will access water at depth. However, methods for assessing roots in large numbers of plants are diverse and direct comparisons of methods are rare. Three methods for measuring root growth traits were evaluated for utility in discriminating rice cultivars: soil-filled rhizotrons, hydroponics and soil-filled pots whose bottom was sealed with a non-woven fabric (a potential method for assessing root penetration ability). A set of 38 rice genotypes including the OryzaSNP set of 20 cultivars, additional parents of mapping populations and products of marker-assisted selection for root QTLs were assessed. A novel method of image analysis for assessing rooting angles from rhizotron photographs was employed. The non-woven fabric was the easiest yet least discriminatory method, while the rhizotron was highly discriminatory and allowed the most traits to be measured but required more than three times the labour of the other methods. The hydroponics was both easy and discriminatory, allowed temporal measurements, but is most likely to suffer from artefacts. Image analysis of rhizotrons compared favourably to manual methods for discriminating between cultivars. Previous observations that cultivars from the indica subpopulation have shallower rooting angles than aus or japonica cultivars were confirmed in the rhizotrons, and indica and temperate japonicas had lower maximum root lengths in rhizotrons and hydroponics. It is concluded that rhizotrons are the preferred method for root screening, particularly since root angles can be assessed. © 2013 German Botanical Society and The Royal Botanical Society of the Netherlands.
International Nuclear Information System (INIS)
Masaoudi, H.; Falgueres, Ch.; Bahain, J.J.; Moncel, M.H.
1997-01-01
The site of Payre is located in Ardeche. Several archaeological layers containing lithic artefacts of Middle Palaeolithic were found. These artefacts lie associated with carbonate formations which are good chronostratigraphic markers. The U-series and ESR methods on bones and stalagmitic floors placed the human occupation between isotopic marine stages 7 and 4. (authors)
Ipek, Hava; Calik, Muammer
2008-01-01
Based on students' alternative conceptions of the topics "electric circuits", "electric charge flows within an electric circuit", "how the brightness of bulbs and the resistance changes in series and parallel circuits", the current study aims to present a combination of different conceptual change methods within a four-step constructivist teaching…
Approaches, tools and methods used for setting priorities in health research in the 21st century
Yoshida, Sachiyo
2016-01-01
Background Health research is difficult to prioritize, because the number of possible competing ideas for research is large, the outcome of research is inherently uncertain, and the impact of research is difficult to predict and measure. A systematic and transparent process to assist policy makers and research funding agencies in making investment decisions is a permanent need. Methods To obtain a better understanding of the landscape of approaches, tools and methods used to prioritize health research, I conducted a methodical review using the PubMed database for the period 2001–2014. Results A total of 165 relevant studies were identified, in which health research prioritization was conducted. They most frequently used the CHNRI method (26%), followed by the Delphi method (24%), James Lind Alliance method (8%), the Combined Approach Matrix (CAM) method (2%) and the Essential National Health Research method (priorities were set. A further 19% used a combination of expert panel interview and focus group discussion (“consultation process”) but provided few details, while a further 2% used approaches that were clearly described, but not established as a replicable method. Online surveys that were not accompanied by face–to–face meetings were used in 8% of studies, while 9% used a combination of literature review and questionnaire to scrutinise the research options for prioritization among the participating experts. Conclusion The number of priority setting exercises in health research published in PubMed–indexed journals is increasing, especially since 2010. These exercises are being conducted at a variety of levels, ranging from the global level to the level of an individual hospital. With the development of new tools and methods which have a well–defined structure – such as the CHNRI method, James Lind Alliance Method and Combined Approach Matrix – it is likely that the Delphi method and non–replicable consultation processes will gradually be
Directory of Open Access Journals (Sweden)
Chris Cheadle
2007-01-01
Full Text Available Background: Microarray technology has become highly valuable for identifying complex global changes in gene expression patterns. The assignment of functional information to these complex patterns remains a challenging task in effectively interpreting data and correlating results from across experiments, projects and laboratories. Methods which allow the rapid and robust evaluation of multiple functional hypotheses increase the power of individual researchers to data mine gene expression data more efficiently.Results: We have developed (gene set matrix analysis GSMA as a useful method for the rapid testing of group-wise up- or downregulation of gene expression simultaneously for multiple lists of genes (gene sets against entire distributions of gene expression changes (datasets for single or multiple experiments. The utility of GSMA lies in its flexibility to rapidly poll gene sets related by known biological function or as designated solely by the end-user against large numbers of datasets simultaneously.Conclusions: GSMA provides a simple and straightforward method for hypothesis testing in which genes are tested by groups across multiple datasets for patterns of expression enrichment.
Deriving the probability of a linear opinion pooling method being superior to a set of alternatives
International Nuclear Information System (INIS)
Bolger, Donnacha; Houlding, Brett
2017-01-01
Linear opinion pools are a common method for combining a set of distinct opinions into a single succinct opinion, often to be used in a decision making task. In this paper we consider a method, termed the Plug-in approach, for determining the weights to be assigned in this linear pool, in a manner that can be deemed as rational in some sense, while incorporating multiple forms of learning over time into its process. The environment that we consider is one in which every source in the pool is herself a decision maker (DM), in contrast to the more common setting in which expert judgments are amalgamated for use by a single DM. We discuss a simulation study that was conducted to show the merits of our technique, and demonstrate how theoretical probabilistic arguments can be used to exactly quantify the probability of this technique being superior (in terms of a probability density metric) to a set of alternatives. Illustrations are given of simulated proportions converging to these true probabilities in a range of commonly used distributional cases. - Highlights: • A novel context for combination of expert opinion is provided. • A dynamic reliability assessment method is stated, justified by properties and a data study. • The theoretical grounding underlying the data-driven justification is explored. • We conclude with areas for expansion and further relevant research.
Ye, Jun
2016-01-01
An interval neutrosophic set (INS) is a subclass of a neutrosophic set and a generalization of an interval-valued intuitionistic fuzzy set, and then the characteristics of INS are independently described by the interval numbers of its truth-membership, indeterminacy-membership, and falsity-membership degrees. However, the exponential parameters (weights) of all the existing exponential operational laws of INSs and the corresponding exponential aggregation operators are crisp values in interval neutrosophic decision making problems. As a supplement, this paper firstly introduces new exponential operational laws of INSs, where the bases are crisp values or interval numbers and the exponents are interval neutrosophic numbers (INNs), which are basic elements in INSs. Then, we propose an interval neutrosophic weighted exponential aggregation (INWEA) operator and a dual interval neutrosophic weighted exponential aggregation (DINWEA) operator based on these exponential operational laws and introduce comparative methods based on cosine measure functions for INNs and dual INNs. Further, we develop decision-making methods based on the INWEA and DINWEA operators. Finally, a practical example on the selecting problem of global suppliers is provided to illustrate the applicability and rationality of the proposed methods.
Directory of Open Access Journals (Sweden)
Pingping Chi
2013-03-01
Full Text Available The interval neutrosophic set (INS can be easier to express the incomplete, indeterminate and inconsistent information, and TOPSIS is one of the most commonly used and effective method for multiple attribute decision making, however, in general, it can only process the attribute values with crisp numbers. In this paper, we have extended TOPSIS to INS, and with respect to the multiple attribute decision making problems in which the attribute weights are unknown and the attribute values take the form of INSs, we proposed an expanded TOPSIS method. Firstly, the definition of INS and the operational laws are given, and distance between INSs is defined. Then, the attribute weights are determined based on the Maximizing deviation method and an extended TOPSIS method is developed to rank the alternatives. Finally, an illustrative example is given to verify the developed approach and to demonstrate its practicality and effectiveness.
Approaches, tools and methods used for setting priorities in health research in the 21(st) century.
Yoshida, Sachiyo
2016-06-01
Health research is difficult to prioritize, because the number of possible competing ideas for research is large, the outcome of research is inherently uncertain, and the impact of research is difficult to predict and measure. A systematic and transparent process to assist policy makers and research funding agencies in making investment decisions is a permanent need. To obtain a better understanding of the landscape of approaches, tools and methods used to prioritize health research, I conducted a methodical review using the PubMed database for the period 2001-2014. A total of 165 relevant studies were identified, in which health research prioritization was conducted. They most frequently used the CHNRI method (26%), followed by the Delphi method (24%), James Lind Alliance method (8%), the Combined Approach Matrix (CAM) method (2%) and the Essential National Health Research method (priorities were set. A further 19% used a combination of expert panel interview and focus group discussion ("consultation process") but provided few details, while a further 2% used approaches that were clearly described, but not established as a replicable method. Online surveys that were not accompanied by face-to-face meetings were used in 8% of studies, while 9% used a combination of literature review and questionnaire to scrutinise the research options for prioritization among the participating experts. The number of priority setting exercises in health research published in PubMed-indexed journals is increasing, especially since 2010. These exercises are being conducted at a variety of levels, ranging from the global level to the level of an individual hospital. With the development of new tools and methods which have a well-defined structure - such as the CHNRI method, James Lind Alliance Method and Combined Approach Matrix - it is likely that the Delphi method and non-replicable consultation processes will gradually be replaced by these emerging tools, which offer more
Simulation of ion behavior in an open three-dimensional Paul trap using a power series method
Energy Technology Data Exchange (ETDEWEB)
Herbane, Mustapha Said, E-mail: mherbane@hotmail.com [King Khalid University, Faculty of Science, Department of Physics, P.O. Box 9004, Abha (Saudi Arabia); Berriche, Hamid [King Khalid University, Faculty of Science, Department of Physics, P.O. Box 9004, Abha (Saudi Arabia); Laboratoire des Interfaces et Matériaux Avancés, Physics Department, College of Science, University of Monastir, 5019 Monastir (Tunisia); Abd El-hady, Alaa [King Khalid University, Faculty of Science, Department of Physics, P.O. Box 9004, Abha (Saudi Arabia); Department of Physics, Faculty of Science, Zagazig University, Zagazig 44519 (Egypt); Al Shahrani, Ghadah [King Khalid University, Faculty of Science, Department of Physics, P.O. Box 9004, Abha (Saudi Arabia); Ban, Gilles; Fléchard, Xavier; Liénard, Etienne [LPC CAEN-ENSICAEN, 6 Boulevard du Marechal Juin, 14050 Caen Cedex (France)
2014-07-01
Simulations of the dynamics of ions trapped in a Paul trap with terms in the potential up to the order 10 have been carried out. The power series method is used to solve numerically the equations of motion of the ions. The stability diagram has been studied and the buffer gas cooling has been implemented by a Monte Carlo method. The dipole excitation was also included. The method has been applied to an existing trap and it has shown good agreement with the experimental results and previous simulations using other methods. - Highlights: • Paul trap with potentials up to the order 10. • Series solution of the ions equations of motion. • Hard sphere model for the simulation of the buffer gas cooling and simulation of the dipolar excitation.
International Nuclear Information System (INIS)
Kopsaftopoulos, Fotis P; Fassois, Spilios D
2011-01-01
A comparative assessment of several vibration based statistical time series methods for Structural Health Monitoring (SHM) is presented via their application to a scale aircraft skeleton laboratory structure. A brief overview of the methods, which are either scalar or vector type, non-parametric or parametric, and pertain to either the response-only or excitation-response cases, is provided. Damage diagnosis, including both the detection and identification subproblems, is tackled via scalar or vector vibration signals. The methods' effectiveness is assessed via repeated experiments under various damage scenarios, with each scenario corresponding to the loosening of one or more selected bolts. The results of the study confirm the 'global' damage detection capability and effectiveness of statistical time series methods for SHM.
Karpušenkaitė, Aistė; Ruzgas, Tomas; Denafas, Gintaras
2018-05-01
The aim of the study was to create a hybrid forecasting method that could produce higher accuracy forecasts than previously used 'pure' time series methods. Mentioned methods were already tested with total automotive waste, hazardous automotive waste, and total medical waste generation, but demonstrated at least a 6% error rate in different cases and efforts were made to decrease it even more. Newly developed hybrid models used a random start generation method to incorporate different time-series advantages and it helped to increase the accuracy of forecasts by 3%-4% in hazardous automotive waste and total medical waste generation cases; the new model did not increase the accuracy of total automotive waste generation forecasts. Developed models' abilities to forecast short- and mid-term forecasts were tested using prediction horizon.
Setting health research priorities using the CHNRI method: IV. Key conceptual advances.
Rudan, Igor
2016-06-01
Child Health and Nutrition Research Initiative (CHNRI) started as an initiative of the Global Forum for Health Research in Geneva, Switzerland. Its aim was to develop a method that could assist priority setting in health research investments. The first version of the CHNRI method was published in 2007-2008. The aim of this paper was to summarize the history of the development of the CHNRI method and its key conceptual advances. The guiding principle of the CHNRI method is to expose the potential of many competing health research ideas to reduce disease burden and inequities that exist in the population in a feasible and cost-effective way. The CHNRI method introduced three key conceptual advances that led to its increased popularity in comparison to other priority-setting methods and processes. First, it proposed a systematic approach to listing a large number of possible research ideas, using the "4D" framework (description, delivery, development and discovery research) and a well-defined "depth" of proposed research ideas (research instruments, avenues, options and questions). Second, it proposed a systematic approach for discriminating between many proposed research ideas based on a well-defined context and criteria. The five "standard" components of the context are the population of interest, the disease burden of interest, geographic limits, time scale and the preferred style of investing with respect to risk. The five "standard" criteria proposed for prioritization between research ideas are answerability, effectiveness, deliverability, maximum potential for disease burden reduction and the effect on equity. However, both the context and the criteria can be flexibly changed to meet the specific needs of each priority-setting exercise. Third, it facilitated consensus development through measuring collective optimism on each component of each research idea among a larger group of experts using a simple scoring system. This enabled the use of the knowledge of
David Helman; Itamar M. Lensky; Naama Tessler; Yagil Osem
2015-01-01
We present an efficient method for monitoring woody (i.e., evergreen) and herbaceous (i.e., ephemeral) vegetation in Mediterranean forests at a sub pixel scale from Normalized Difference Vegetation Index (NDVI) time series derived from the Moderate Resolution Imaging Spectroradiometer (MODIS). The method is based on the distinct development periods of those vegetation components. In the dry season, herbaceous vegetation is absent or completely dry in Mediterranean forests. Thus the mean NDVI ...
Directory of Open Access Journals (Sweden)
Subanar Subanar
2006-01-01
Full Text Available Recently, one of the central topics for the neural networks (NN community is the issue of data preprocessing on the use of NN. In this paper, we will investigate this topic particularly on the effect of Decomposition method as data processing and the use of NN for modeling effectively time series with both trend and seasonal patterns. Limited empirical studies on seasonal time series forecasting with neural networks show that some find neural networks are able to model seasonality directly and prior deseasonalization is not necessary, and others conclude just the opposite. In this research, we study particularly on the effectiveness of data preprocessing, including detrending and deseasonalization by applying Decomposition method on NN modeling and forecasting performance. We use two kinds of data, simulation and real data. Simulation data are examined on multiplicative of trend and seasonality patterns. The results are compared to those obtained from the classical time series model. Our result shows that a combination of detrending and deseasonalization by applying Decomposition method is the effective data preprocessing on the use of NN for forecasting trend and seasonal time series.
A method for patient set-up guidance in radiotherapy using augmented reality
International Nuclear Information System (INIS)
Talbot, J.; Meyer, J.; Watts, R.; Grasset, R.
2009-01-01
Full text: A system for patient set-up in external beam radiotherapy was developed using Augmented Reality (AR). Live images of the linac treatment couch and patient were obtained with video cameras and displayed on a nearby monitor. A 3D model of the patient's external contour was obtained from planning CT data, and AR tracking software was used to superimpose the model onto the video images in the correct position for treatment. Throughout set-up and treatment, the user can view the monitor and visually confirm that the patient is positioned correctly. To ensure that the virtual contour was displayed in the correct position, a process was devised to register the coordinates of the linac with the camera images. A cube with AR tracking markers attached to its faces was constructed for alignment with the isocentre using room lasers or cone-beam CT. The performance of the system was investigated in a clinical environment by using it to position an anthropomorphic phantom without the aid of additional set-up methods. The positioning errors were determined by means of CBCT and image registration. The translational set-up errors were found to be less than 2.4 mm and the rotational errors less than 0.3 0 . This proof-of-principle study has demonstrated the feasibility of using AR for patient position and pose guidance.
Development of a set of benchmark problems to verify numerical methods for solving burnup equations
International Nuclear Information System (INIS)
Lago, Daniel; Rahnema, Farzad
2017-01-01
Highlights: • Description transmutation chain benchmark problems. • Problems for validating numerical methods for solving burnup equations. • Analytical solutions for the burnup equations. • Numerical solutions for the burnup equations. - Abstract: A comprehensive set of transmutation chain benchmark problems for numerically validating methods for solving burnup equations was created. These benchmark problems were designed to challenge both traditional and modern numerical methods used to solve the complex set of ordinary differential equations used for tracking the change in nuclide concentrations over time due to nuclear phenomena. Given the development of most burnup solvers is done for the purpose of coupling with an established transport solution method, these problems provide a useful resource in testing and validating the burnup equation solver before coupling for use in a lattice or core depletion code. All the relevant parameters for each benchmark problem are described. Results are also provided in the form of reference solutions generated by the Mathematica tool, as well as additional numerical results from MATLAB.
Failure Mode and Effect Analysis using Soft Set Theory and COPRAS Method
Directory of Open Access Journals (Sweden)
Ze-Ling Wang
2017-01-01
Full Text Available Failure mode and effect analysis (FMEA is a risk management technique frequently applied to enhance the system performance and safety. In recent years, many researchers have shown an intense interest in improving FMEA due to inherent weaknesses associated with the classical risk priority number (RPN method. In this study, we develop a new risk ranking model for FMEA based on soft set theory and COPRAS method, which can deal with the limitations and enhance the performance of the conventional FMEA. First, trapezoidal fuzzy soft set is adopted to manage FMEA team membersr linguistic assessments on failure modes. Then, a modified COPRAS method is utilized for determining the ranking order of the failure modes recognized in FMEA. Especially, we treat the risk factors as interdependent and employ the Choquet integral to obtain the aggregate risk of failures in the new FMEA approach. Finally, a practical FMEA problem is analyzed via the proposed approach to demonstrate its applicability and effectiveness. The result shows that the FMEA model developed in this study outperforms the traditional RPN method and provides a more reasonable risk assessment of failure modes.
Energy Technology Data Exchange (ETDEWEB)
Anderson, Ryan B., E-mail: randerson@astro.cornell.edu [Cornell University Department of Astronomy, 406 Space Sciences Building, Ithaca, NY 14853 (United States); Bell, James F., E-mail: Jim.Bell@asu.edu [Arizona State University School of Earth and Space Exploration, Bldg.: INTDS-A, Room: 115B, Box 871404, Tempe, AZ 85287 (United States); Wiens, Roger C., E-mail: rwiens@lanl.gov [Los Alamos National Laboratory, P.O. Box 1663 MS J565, Los Alamos, NM 87545 (United States); Morris, Richard V., E-mail: richard.v.morris@nasa.gov [NASA Johnson Space Center, 2101 NASA Parkway, Houston, TX 77058 (United States); Clegg, Samuel M., E-mail: sclegg@lanl.gov [Los Alamos National Laboratory, P.O. Box 1663 MS J565, Los Alamos, NM 87545 (United States)
2012-04-15
We investigated five clustering and training set selection methods to improve the accuracy of quantitative chemical analysis of geologic samples by laser induced breakdown spectroscopy (LIBS) using partial least squares (PLS) regression. The LIBS spectra were previously acquired for 195 rock slabs and 31 pressed powder geostandards under 7 Torr CO{sub 2} at a stand-off distance of 7 m at 17 mJ per pulse to simulate the operational conditions of the ChemCam LIBS instrument on the Mars Science Laboratory Curiosity rover. The clustering and training set selection methods, which do not require prior knowledge of the chemical composition of the test-set samples, are based on grouping similar spectra and selecting appropriate training spectra for the partial least squares (PLS2) model. These methods were: (1) hierarchical clustering of the full set of training spectra and selection of a subset for use in training; (2) k-means clustering of all spectra and generation of PLS2 models based on the training samples within each cluster; (3) iterative use of PLS2 to predict sample composition and k-means clustering of the predicted compositions to subdivide the groups of spectra; (4) soft independent modeling of class analogy (SIMCA) classification of spectra, and generation of PLS2 models based on the training samples within each class; (5) use of Bayesian information criteria (BIC) to determine an optimal number of clusters and generation of PLS2 models based on the training samples within each cluster. The iterative method and the k-means method using 5 clusters showed the best performance, improving the absolute quadrature root mean squared error (RMSE) by {approx} 3 wt.%. The statistical significance of these improvements was {approx} 85%. Our results show that although clustering methods can modestly improve results, a large and diverse training set is the most reliable way to improve the accuracy of quantitative LIBS. In particular, additional sulfate standards and
Numerical Modelling of Three-Fluid Flow Using The Level-set Method
Li, Hongying; Lou, Jing; Shang, Zhi
2014-11-01
This work presents a numerical model for simulation of three-fluid flow involving two different moving interfaces. These interfaces are captured using the level-set method via two different level-set functions. A combined formulation with only one set of conservation equations for the whole physical domain, consisting of the three different immiscible fluids, is employed. Numerical solution is performed on a fixed mesh using the finite volume method. Surface tension effect is incorporated using the Continuum Surface Force model. Validation of the present model is made against available results for stratified flow and rising bubble in a container with a free surface. Applications of the present model are demonstrated by a variety of three-fluid flow systems including (1) three-fluid stratified flow, (2) two-fluid stratified flow carrying the third fluid in the form of drops and (3) simultaneous rising and settling of two drops in a stationary third fluid. The work is supported by a Thematic and Strategic Research from A*STAR, Singapore (Ref. #: 1021640075).
Directory of Open Access Journals (Sweden)
Q. Zhang
2018-02-01
Full Text Available River water-quality time series often exhibit fractal scaling, which here refers to autocorrelation that decays as a power law over some range of scales. Fractal scaling presents challenges to the identification of deterministic trends because (1 fractal scaling has the potential to lead to false inference about the statistical significance of trends and (2 the abundance of irregularly spaced data in water-quality monitoring networks complicates efforts to quantify fractal scaling. Traditional methods for estimating fractal scaling – in the form of spectral slope (β or other equivalent scaling parameters (e.g., Hurst exponent – are generally inapplicable to irregularly sampled data. Here we consider two types of estimation approaches for irregularly sampled data and evaluate their performance using synthetic time series. These time series were generated such that (1 they exhibit a wide range of prescribed fractal scaling behaviors, ranging from white noise (β = 0 to Brown noise (β = 2 and (2 their sampling gap intervals mimic the sampling irregularity (as quantified by both the skewness and mean of gap-interval lengths in real water-quality data. The results suggest that none of the existing methods fully account for the effects of sampling irregularity on β estimation. First, the results illustrate the danger of using interpolation for gap filling when examining autocorrelation, as the interpolation methods consistently underestimate or overestimate β under a wide range of prescribed β values and gap distributions. Second, the widely used Lomb–Scargle spectral method also consistently underestimates β. A previously published modified form, using only the lowest 5 % of the frequencies for spectral slope estimation, has very poor precision, although the overall bias is small. Third, a recent wavelet-based method, coupled with an aliasing filter, generally has the smallest bias and root-mean-squared error among
Zhang, Qian; Harman, Ciaran J.; Kirchner, James W.
2018-02-01
River water-quality time series often exhibit fractal scaling, which here refers to autocorrelation that decays as a power law over some range of scales. Fractal scaling presents challenges to the identification of deterministic trends because (1) fractal scaling has the potential to lead to false inference about the statistical significance of trends and (2) the abundance of irregularly spaced data in water-quality monitoring networks complicates efforts to quantify fractal scaling. Traditional methods for estimating fractal scaling - in the form of spectral slope (β) or other equivalent scaling parameters (e.g., Hurst exponent) - are generally inapplicable to irregularly sampled data. Here we consider two types of estimation approaches for irregularly sampled data and evaluate their performance using synthetic time series. These time series were generated such that (1) they exhibit a wide range of prescribed fractal scaling behaviors, ranging from white noise (β = 0) to Brown noise (β = 2) and (2) their sampling gap intervals mimic the sampling irregularity (as quantified by both the skewness and mean of gap-interval lengths) in real water-quality data. The results suggest that none of the existing methods fully account for the effects of sampling irregularity on β estimation. First, the results illustrate the danger of using interpolation for gap filling when examining autocorrelation, as the interpolation methods consistently underestimate or overestimate β under a wide range of prescribed β values and gap distributions. Second, the widely used Lomb-Scargle spectral method also consistently underestimates β. A previously published modified form, using only the lowest 5 % of the frequencies for spectral slope estimation, has very poor precision, although the overall bias is small. Third, a recent wavelet-based method, coupled with an aliasing filter, generally has the smallest bias and root-mean-squared error among all methods for a wide range of
Comparing two sampling methods to engage hard-to-reach communities in research priority setting
Directory of Open Access Journals (Sweden)
Melissa A. Valerio
2016-10-01
Full Text Available Abstract Background Effective community-partnered and patient-centered outcomes research needs to address community priorities. However, optimal sampling methods to engage stakeholders from hard-to-reach, vulnerable communities to generate research priorities have not been identified. Methods In two similar rural, largely Hispanic communities, a community advisory board guided recruitment of stakeholders affected by chronic pain using a different method in each community: 1 snowball sampling, a chain- referral method or 2 purposive sampling to recruit diverse stakeholders. In both communities, three groups of stakeholders attended a series of three facilitated meetings to orient, brainstorm, and prioritize ideas (9 meetings/community. Using mixed methods analysis, we compared stakeholder recruitment and retention as well as priorities from both communities’ stakeholders on mean ratings of their ideas based on importance and feasibility for implementation in their community. Results Of 65 eligible stakeholders in one community recruited by snowball sampling, 55 (85 % consented, 52 (95 % attended the first meeting, and 36 (65 % attended all 3 meetings. In the second community, the purposive sampling method was supplemented by convenience sampling to increase recruitment. Of 69 stakeholders recruited by this combined strategy, 62 (90 % consented, 36 (58 % attended the first meeting, and 26 (42 % attended all 3 meetings. Snowball sampling recruited more Hispanics and disabled persons (all P < 0.05. Despite differing recruitment strategies, stakeholders from the two communities identified largely similar ideas for research, focusing on non-pharmacologic interventions for management of chronic pain. Ratings on importance and feasibility for community implementation differed only on the importance of massage services (P = 0.045 which was higher for the purposive/convenience sampling group and for city improvements
Study of different effectives on wind energy by using mathematical methods and rough set theory
International Nuclear Information System (INIS)
Marrouf, A.A.
2009-01-01
Analysis of data plays an important role in all fields of life, a huge number of data that results from experimental data in all scientific and social sciences. The analysis of these data was carried out by statistical methods and its representation depended on classical Euclidean geometric concepts.In the 21 st century, new direction for data analysis have been started in applications. These direction depend basically on modern mathematical theories. The quality of data and information can be characterized as interfering and man is unable to distinguish between its vocabularies. The topological methods are the most compatible for this process of analysis for making decision. At the end of 20 th century, a new topological method appeared, this is known by R ough Set Theory Approach , this doesn't depend on external suppositions. It is known as (let data speak). This is good for all types of data. The theory was originated by Pawlak in 1982 [48] as a result of long term program of fundamental research on logical properties of information systems, carried out by him and a group of logicians from Phlish Academy of sciences and the University of Warsaw, Poland. Various real life application of rough sets have shown its usefulness in many domains as civil engineering, medical data analysis, generating of a cement kiln control algorithm from observation of stocker's actions, vibration analysis, air craft pilot performance evaluation, hydrology, pharmacology, image processing and ecology.Variable Precision Rough Set (VPRS)-model is proposed by W. Ziarko [80]. It is a new generalization of the rough set model. It is aimed at handling underlain information and is directly derived from the original model without any additional assumptions.Topology is a mathematical tool to study information systems and variable precision rough sets. Ziarko presumed that the notion of variable precision rough sets depend on special types of topological spaces. In this space, the families of
Energy Technology Data Exchange (ETDEWEB)
Ferreira, A. M.
2004-07-01
This study concerns about different methods for analysing and imputation missing values in wind speed series. The algorithm EM and a methodology derivated from the sequential hot deck have been utilized. Series with missing values imputed are compared with original and complete series, using several criteria, such the wind potential; and appears to exist a significant goodness of fit between the estimates and real values. (Author)
Level set method for optimal shape design of MRAM core. Micromagnetic approach
International Nuclear Information System (INIS)
Melicher, Valdemar; Cimrak, Ivan; Keer, Roger van
2008-01-01
We aim at optimizing the shape of the magnetic core in MRAM memories. The evolution of the magnetization during the writing process is described by the Landau-Lifshitz equation (LLE). The actual shape of the core in one cell is characterized by the coefficient γ. Cost functional f=f(γ) expresses the quality of the writing process having in mind the competition between the full-select and the half-select element. We derive an explicit form of the derivative F=∂f/∂γ which allows for the use of gradient-type methods for the actual computation of the optimized shape (e.g., steepest descend method). The level set method (LSM) is employed for the representation of the piecewise constant coefficient γ
Vazquez-Leal, Hector; Benhammouda, Brahim; Filobello-Nino, Uriel Antonio; Sarmiento-Reyes, Arturo; Jimenez-Fernandez, Victor Manuel; Marin-Hernandez, Antonio; Herrera-May, Agustin Leobardo; Diaz-Sanchez, Alejandro; Huerta-Chua, Jesus
2014-01-01
In this article, we propose the application of a modified Taylor series method (MTSM) for the approximation of nonlinear problems described on finite intervals. The issue of Taylor series method with mixed boundary conditions is circumvented using shooting constants and extra derivatives of the problem. In order to show the benefits of this proposal, three different kinds of problems are solved: three-point boundary valued problem (BVP) of third-order with a hyperbolic sine nonlinearity, two-point BVP for a second-order nonlinear differential equation with an exponential nonlinearity, and a two-point BVP for a third-order nonlinear differential equation with a radical nonlinearity. The result shows that the MTSM method is capable to generate easily computable and highly accurate approximations for nonlinear equations. 34L30.
New method of three-dimensional reconstruction from two-dimensional MR data sets
International Nuclear Information System (INIS)
Wrazidlo, W.; Schneider, S.; Brambs, H.J.; Richter, G.M.; Kauffmann, G.W.; Geiger, B.; Fischer, C.
1989-01-01
In medical diagnosis and therapy, cross-sectional images are obtained by means of US, CT, or MR imaging. The authors propose a new solution to the problem of constructing a shape over a set of cross-sectional contours from two-dimensional (2D) MR data sets. The authors' method reduces the problem of constructing a shape over the cross sections to one of constructing a sequence of partial shapes, each of them connecting two cross sections lying on adjacent planes. The solution makes use of the Delaunay triangulation, which is isomorphic in that specific situation. The authors compute this Delaunay triangulation. Shape reconstruction is then achieved section by pruning Delaunay triangulations
The Train Driver Recovery Problem - a Set Partitioning Based Model and Solution Method
DEFF Research Database (Denmark)
Rezanova, Natalia Jurjevna; Ryan, David
2010-01-01
The need to recover a train driver schedule occurs during major disruptions in the daily railway operations. Based on data from the Danish passenger railway operator DSB S-tog A/S, a solution method to the train driver recovery problem (TDRP) is developed. The TDRP is formulated as a set...... branching strategy using the depth-first search of the Branch & Bound tree. The LP relaxation of the TDRP possesses strong integer properties. We present test scenarios generated from the historical real-life operations data of DSB S-tog A/S. The numerical results show that all but one tested instances...... partitioning problem. We define a disruption neighbourhood by identifying a small set of drivers and train tasks directly affected by the disruption. Based on the disruption neighbourhood, the TDRP model is formed and solved. If the TDRP solution provides a feasible recovery for the drivers within...
Set up of analytical methods for evaluation of specifications of recombinant Hepatitis-B vaccine
Directory of Open Access Journals (Sweden)
Daram M
2009-06-01
Full Text Available "nBackground: Hepatitis B vaccination has been included in routine immunization of all individuals according to WHO recommendations since 1991. Despite successful coverage, 3-5% of recipients fail to mount a desirable protection level of Ab. Vaccine failure results from: emergence of mutation, immune failure of individuals, decrease in vaccine potency, and etc. The quality of Hepatitis B vaccine should be evaluated by a reliable method. "n"nMethods: The amount of vaccine antigen was measured through the in vitro assay of Hepatitis B vaccines which consists of multiple dilutions of the reference material and samples. The preparations were evaluated by Elisa to determine the amount of HBsAg. The data were analyzed by parallel-line analysis software. The in vivo assay was performed by inoculating multiple doses of the reference and sample preparations in Balb/c mice. A control group was also inoculated with vaccine matrix. Four weeks later, the mice sera were evaluated to determine the presence of antibodies against Hepatitis B by Elisa method. The data were analyzed by Probit analysis software. "n"nResults: Both methods were set up in our laboratory by which different batches of Hepatitis B vaccine were evaluated. It was observed that In vivo and In vitro methods provide comparable results. Therefore we can use the in vitro method for routine testing of HB vaccine quality control. "n"nConclusion: In vitro method can be used in place of In vivo method because of its time and cost-effectiveness. Moreover, since no animals are used in in vitro method, it complies well with the 3R concept (Reduction, Refinement, and Replacement of animal testing and the current tendency to use alternative method.
A method of setting limits for the purpose of quality assurance
International Nuclear Information System (INIS)
Sanghangthum, Taweap; Suriyapee, Sivalee; Kim, Gwe-Ya; Pawlicki, Todd
2013-01-01
The result from any assurance measurement needs to be checked against some limits for acceptability. There are two types of limits; those that define clinical acceptability (action limits) and those that are meant to serve as a warning that the measurement is close to the action limits (tolerance limits). Currently, there is no standard procedure to set these limits. In this work, we propose an operational procedure to set tolerance limits and action limits. The approach to establish the limits is based on techniques of quality engineering using control charts and a process capability index. The method is different for tolerance limits and action limits with action limits being categorized into those that are specified and unspecified. The procedure is to first ensure process control using the I-MR control charts. Then, the tolerance limits are set equal to the control chart limits on the I chart. Action limits are determined using the C pm process capability index with the requirements that the process must be in-control. The limits from the proposed procedure are compared to an existing or conventional method. Four examples are investigated: two of volumetric modulated arc therapy (VMAT) point dose quality assurance (QA) and two of routine linear accelerator output QA. The tolerance limits range from about 6% larger to 9% smaller than conventional action limits for VMAT QA cases. For the linac output QA, tolerance limits are about 60% smaller than conventional action limits. The operational procedure describe in this work is based on established quality management tools and will provide a systematic guide to set up tolerance and action limits for different equipment and processes. (paper)
Connor, Thomas H; Smith, Jerome P
2016-09-01
At the present time, the method of choice to determine surface contamination of the workplace with antineoplastic and other hazardous drugs is surface wipe sampling and subsequent sample analysis with a variety of analytical techniques. The purpose of this article is to review current methodology for determining the level of surface contamination with hazardous drugs in healthcare settings and to discuss recent advances in this area. In addition it will provide some guidance for conducting surface wipe sampling and sample analysis for these drugs in healthcare settings. Published studies on the use of wipe sampling to measure hazardous drugs on surfaces in healthcare settings drugs were reviewed. These studies include the use of well-documented chromatographic techniques for sample analysis in addition to newly evolving technology that provides rapid analysis of specific antineoplastic. Methodology for the analysis of surface wipe samples for hazardous drugs are reviewed, including the purposes, technical factors, sampling strategy, materials required, and limitations. The use of lateral flow immunoassay (LFIA) and fluorescence covalent microbead immunosorbent assay (FCMIA) for surface wipe sample evaluation is also discussed. Current recommendations are that all healthc a re settings where antineoplastic and other hazardous drugs are handled include surface wipe sampling as part of a comprehensive hazardous drug-safe handling program. Surface wipe sampling may be used as a method to characterize potential occupational dermal exposure risk and to evaluate the effectiveness of implemented controls and the overall safety program. New technology, although currently limited in scope, may make wipe sampling for hazardous drugs more routine, less costly, and provide a shorter response time than classical analytical techniques now in use.
Developing a digital photography-based method for dietary analysis in self-serve dining settings.
Christoph, Mary J; Loman, Brett R; Ellison, Brenna
2017-07-01
Current population-based methods for assessing dietary intake, including food frequency questionnaires, food diaries, and 24-h dietary recall, are limited in their ability to objectively measure food intake. Digital photography has been identified as a promising addition to these techniques but has rarely been assessed in self-serve settings. We utilized digital photography to examine university students' food choices and consumption in a self-serve dining hall setting. Research assistants took pre- and post-photos of students' plates during lunch and dinner to assess selection (presence), servings, and consumption of MyPlate food groups. Four coders rated the same set of approximately 180 meals for inter-rater reliability analyses; approximately 50 additional meals were coded twice by each coder to assess intra-rater agreement. Inter-rater agreement on the selection, servings, and consumption of food groups was high at 93.5%; intra-rater agreement was similarly high with an average of 95.6% agreement. Coders achieved the highest rates of agreement in assessing if a food group was present on the plate (95-99% inter-rater agreement, depending on food group) and estimating the servings of food selected (81-98% inter-rater agreement). Estimating consumption, particularly for items such as beans and cheese that were often in mixed dishes, was more challenging (77-94% inter-rater agreement). Results suggest that the digital photography method presented is feasible for large studies in real-world environments and can provide an objective measure of food selection, servings, and consumption with a high degree of agreement between coders; however, to make accurate claims about the state of dietary intake in all-you-can-eat, self-serve settings, researchers will need to account for the possibility of diners taking multiple trips through the serving line. Copyright © 2017 Elsevier Ltd. All rights reserved.
Comparing two sampling methods to engage hard-to-reach communities in research priority setting.
Valerio, Melissa A; Rodriguez, Natalia; Winkler, Paula; Lopez, Jaime; Dennison, Meagen; Liang, Yuanyuan; Turner, Barbara J
2016-10-28
Effective community-partnered and patient-centered outcomes research needs to address community priorities. However, optimal sampling methods to engage stakeholders from hard-to-reach, vulnerable communities to generate research priorities have not been identified. In two similar rural, largely Hispanic communities, a community advisory board guided recruitment of stakeholders affected by chronic pain using a different method in each community: 1) snowball sampling, a chain- referral method or 2) purposive sampling to recruit diverse stakeholders. In both communities, three groups of stakeholders attended a series of three facilitated meetings to orient, brainstorm, and prioritize ideas (9 meetings/community). Using mixed methods analysis, we compared stakeholder recruitment and retention as well as priorities from both communities' stakeholders on mean ratings of their ideas based on importance and feasibility for implementation in their community. Of 65 eligible stakeholders in one community recruited by snowball sampling, 55 (85 %) consented, 52 (95 %) attended the first meeting, and 36 (65 %) attended all 3 meetings. In the second community, the purposive sampling method was supplemented by convenience sampling to increase recruitment. Of 69 stakeholders recruited by this combined strategy, 62 (90 %) consented, 36 (58 %) attended the first meeting, and 26 (42 %) attended all 3 meetings. Snowball sampling recruited more Hispanics and disabled persons (all P research, focusing on non-pharmacologic interventions for management of chronic pain. Ratings on importance and feasibility for community implementation differed only on the importance of massage services (P = 0.045) which was higher for the purposive/convenience sampling group and for city improvements/transportation services (P = 0.004) which was higher for the snowball sampling group. In each of the two similar hard-to-reach communities, a community advisory board partnered with researchers
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
Time series analysis in road safety research uisng state space methods
BIJLEVELD, FD
2008-01-01
In this thesis we present a comprehensive study into novel time series models for aggregated road safety data. The models are mainly intended for analysis of indicators relevant to road safety, with a particular focus on how to measure these factors. Such developments may need to be related to or explained by external influences. It is also possible to make forecasts using the models. Relevant indicators include the number of persons killed permonth or year. These statistics are closely watch...
RS-SNP: a random-set method for genome-wide association studies
Directory of Open Access Journals (Sweden)
Mukherjee Sayan
2011-03-01
Full Text Available Abstract Background The typical objective of Genome-wide association (GWA studies is to identify single-nucleotide polymorphisms (SNPs and corresponding genes with the strongest evidence of association (the 'most-significant SNPs/genes' approach. Borrowing ideas from micro-array data analysis, we propose a new method, named RS-SNP, for detecting sets of genes enriched in SNPs moderately associated to the phenotype. RS-SNP assesses whether the number of significant SNPs, with p-value P ≤ α, belonging to a given SNP set is statistically significant. The rationale of proposed method is that two kinds of null hypotheses are taken into account simultaneously. In the first null model the genotype and the phenotype are assumed to be independent random variables and the null distribution is the probability of the number of significant SNPs in greater than observed by chance. The second null model assumes the number of significant SNPs in depends on the size of and not on the identity of the SNPs in . Statistical significance is assessed using non-parametric permutation tests. Results We applied RS-SNP to the Crohn's disease (CD data set collected by the Wellcome Trust Case Control Consortium (WTCCC and compared the results with GENGEN, an approach recently proposed in literature. The enrichment analysis using RS-SNP and the set of pathways contained in the MSigDB C2 CP pathway collection highlighted 86 pathways rich in SNPs weakly associated to CD. Of these, 47 were also indicated to be significant by GENGEN. Similar results were obtained using the MSigDB C5 pathway collection. Many of the pathways found to be enriched by RS-SNP have a well-known connection to CD and often with inflammatory diseases. Conclusions The proposed method is a valuable alternative to other techniques for enrichment analysis of SNP sets. It is well founded from a theoretical and statistical perspective. Moreover, the experimental comparison with GENGEN highlights that it is
Kim, Sang J. (Editor)
1988-01-01
The main purpose of the data catalog series is to provide descriptive references to data generated by space science flight missions. The data sets described include all of the actual holdings of the Space Science Data Center (NSSDC), all data sets for which direct contact information is available, and some data collections held and serviced by foreign investigators, NASA and other U.S. government agencies. This volume contains narrative descriptions of data sets of astronomy, astrophysics, solar physics spacecraft and investigations. The following spacecraft series are included: Mariner, Pioneer, Pioneer Venus, Venera, Viking, Voyager, and Helios. Separate indexes to the planetary and interplanetary missions are also provided.
An improved level set method for brain MR images segmentation and bias correction.
Chen, Yunjie; Zhang, Jianwei; Macione, Jim
2009-10-01
Intensity inhomogeneities cause considerable difficulty in the quantitative analysis of magnetic resonance (MR) images. Thus, bias field estimation is a necessary step before quantitative analysis of MR data can be undertaken. This paper presents a variational level set approach to bias correction and segmentation for images with intensity inhomogeneities. Our method is based on an observation that intensities in a relatively small local region are separable, despite of the inseparability of the intensities in the whole image caused by the overall intensity inhomogeneity. We first define a localized K-means-type clustering objective function for image intensities in a neighborhood around each point. The cluster centers in this objective function have a multiplicative factor that estimates the bias within the neighborhood. The objective function is then integrated over the entire domain to define the data term into the level set framework. Our method is able to capture bias of quite general profiles. Moreover, it is robust to initialization, and thereby allows fully automated applications. The proposed method has been used for images of various modalities with promising results.
Incremental Knowledge Acquisition for WSD: A Rough Set and IL based Method
Directory of Open Access Journals (Sweden)
Xu Huang
2015-07-01
Full Text Available Word sense disambiguation (WSD is one of tricky tasks in natural language processing (NLP as it needs to take into full account all the complexities of language. Because WSD involves in discovering semantic structures from unstructured text, automatic knowledge acquisition of word sense is profoundly difficult. To acquire knowledge about Chinese multi-sense verbs, we introduce an incremental machine learning method which combines rough set method and instance based learning. First, context of a multi-sense verb is extracted into a table; its sense is annotated by a skilled human and stored in the same table. By this way, decision table is formed, and then rules can be extracted within the framework of attributive value reduction of rough set. Instances not entailed by any rule are treated as outliers. When new instances are added to decision table, only the new added and outliers need to be learned further, thus incremental leaning is fulfilled. Experiments show the scale of decision table can be reduced dramatically by this method without performance decline.
A Kalman Filter-Based Method to Generate Continuous Time Series of Medium-Resolution NDVI Images
Directory of Open Access Journals (Sweden)
Fernando Sedano
2014-12-01
Full Text Available A data assimilation method to produce complete temporal sequences of synthetic medium-resolution images is presented. The method implements a Kalman filter recursive algorithm that integrates medium and moderate resolution imagery. To demonstrate the approach, time series of 30-m spatial resolution NDVI images at 16-day time steps were generated using Landsat NDVI images and MODIS NDVI products at four sites with different ecosystems and land cover-land use dynamics. The results show that the time series of synthetic NDVI images captured seasonal land surface dynamics and maintained the spatial structure of the landscape at higher spatial resolution. The time series of synthetic medium-resolution NDVI images were validated within a Monte Carlo simulation framework. Normalized residuals decreased as the number of available observations increased, ranging from 0.2 to below 0.1. Residuals were also significantly lower for time series of synthetic NDVI images generated at combined recursion (smoothing than individually at forward and backward recursions (filtering. Conversely, the uncertainties of the synthetic images also decreased when the number of available observations increased and combined recursions were implemented.
Advanced methods for modeling water-levels and estimating drawdowns with SeriesSEE, an Excel add-in
Halford, Keith; Garcia, C. Amanda; Fenelon, Joe; Mirus, Benjamin B.
2012-12-21
Water-level modeling is used for multiple-well aquifer tests to reliably differentiate pumping responses from natural water-level changes in wells, or “environmental fluctuations.” Synthetic water levels are created during water-level modeling and represent the summation of multiple component fluctuations, including those caused by environmental forcing and pumping. Pumping signals are modeled by transforming step-wise pumping records into water-level changes by using superimposed Theis functions. Water-levels can be modeled robustly with this Theis-transform approach because environmental fluctuations and pumping signals are simulated simultaneously. Water-level modeling with Theis transforms has been implemented in the program SeriesSEE, which is a Microsoft® Excel add-in. Moving average, Theis, pneumatic-lag, and gamma functions transform time series of measured values into water-level model components in SeriesSEE. Earth tides and step transforms are additional computed water-level model components. Water-level models are calibrated by minimizing a sum-of-squares objective function where singular value decomposition and Tikhonov regularization stabilize results. Drawdown estimates from a water-level model are the summation of all Theis transforms minus residual differences between synthetic and measured water levels. The accuracy of drawdown estimates is limited primarily by noise in the data sets, not the Theis-transform approach. Drawdowns much smaller than environmental fluctuations have been detected across major fault structures, at distances of more than 1 mile from the pumping well, and with limited pre-pumping and recovery data at sites across the United States. In addition to water-level modeling, utilities exist in SeriesSEE for viewing, cleaning, manipulating, and analyzing time-series data.
Janik, M; Bossew, P; Kurihara, O
2018-07-15
Machine learning is a class of statistical techniques which has proven to be a powerful tool for modelling the behaviour of complex systems, in which response quantities depend on assumed controls or predictors in a complicated way. In this paper, as our first purpose, we propose the application of machine learning to reconstruct incomplete or irregularly sampled data of time series indoor radon ( 222 Rn). The physical assumption underlying the modelling is that Rn concentration in the air is controlled by environmental variables such as air temperature and pressure. The algorithms "learn" from complete sections of multivariate series, derive a dependence model and apply it to sections where the controls are available, but not the response (Rn), and in this way complete the Rn series. Three machine learning techniques are applied in this study, namely random forest, its extension called the gradient boosting machine and deep learning. For a comparison, we apply the classical multiple regression in a generalized linear model version. Performance of the models is evaluated through different metrics. The performance of the gradient boosting machine is found to be superior to that of the other techniques. By applying learning machines, we show, as our second purpose, that missing data or periods of Rn series data can be reconstructed and resampled on a regular grid reasonably, if data of appropriate physical controls are available. The techniques also identify to which degree the assumed controls contribute to imputing missing Rn values. Our third purpose, though no less important from the viewpoint of physics, is identifying to which degree physical, in this case environmental variables, are relevant as Rn predictors, or in other words, which predictors explain most of the temporal variability of Rn. We show that variables which contribute most to the Rn series reconstruction, are temperature, relative humidity and day of the year. The first two are physical
A method for statistical comparison of data sets and its uses in analysis of nuclear physics data
International Nuclear Information System (INIS)
Bityukov, S.I.; Smirnova, V.V.; Krasnikov, N.V.; Maksimushkina, A.V.; Nikitenko, A.N.
2014-01-01
Authors propose a method for statistical comparison of two data sets. The method is based on the method of statistical comparison of histograms. As an estimator of quality of the decision made, it is proposed to use the value which it is possible to call the probability that the decision (data sets are various) is correct [ru
Utility of qualitative methods in a clinical setting: perinatal care in the Western Province.
Jayasuriya, V
2012-03-01
A peculiar paradox that has been observed in previous studies of antenatal care is where patients are satisfied with the services despite obvious lack of basic facilities. Qualitative methods were used to describe the experience of perinatal care in the Western province with the objective of demonstrating application of this method in a clinical setting. This paper used a 'naturalistic' approach of qualitative methods. In-depth interviews conducted with 20 postnatal mothers delivering in tertiary care institutions in the Western province was tape recorded, transcribed and content analysed. To ensure objectivity and validity of results, the principle investigator received only the anonymised data to prevent any prejudices or pre-conceptions affecting the results. The main themes emerging from the text demonstrated 'naïve trust' in the carer and a state of 'hero worship' where patients were distanced and therefore unable and unwilling to query the decisions made by the carers. This is similar to a state of patient-carer relationship described in a published model known as guarded alliance, where the relationship develops though four phases based on the level of trust and confidence in the relationship. This state explains not only why patients fail to recognise and report any deficiencies in the services but also the need for them to justify the behaviour of caregivers even when it amounts to incompetence and negligence. Qualitative methods allow the researcher to capture experiences in its 'natural' form rather than based on pre-determined protocols or plans, which may be limited to our own understanding and expectations and therefore unable to explain many idiosyncrasies of the programmes. This paper argues favourably for the use of qualitative methods in other clinical settings.
Indian Academy of Sciences (India)
The theory of Fourier series deals with periodic functions. By a periodic ..... including Dirichlet, Riemann and Cantor occupied themselves with the problem of ... to converge only on a set which is negligible in a certain sense (Le. of measure ...
Some free boundary problems in potential flow regime usinga based level set method
Energy Technology Data Exchange (ETDEWEB)
Garzon, M.; Bobillo-Ares, N.; Sethian, J.A.
2008-12-09
Recent advances in the field of fluid mechanics with moving fronts are linked to the use of Level Set Methods, a versatile mathematical technique to follow free boundaries which undergo topological changes. A challenging class of problems in this context are those related to the solution of a partial differential equation posed on a moving domain, in which the boundary condition for the PDE solver has to be obtained from a partial differential equation defined on the front. This is the case of potential flow models with moving boundaries. Moreover the fluid front will possibly be carrying some material substance which will diffuse in the front and be advected by the front velocity, as for example the use of surfactants to lower surface tension. We present a Level Set based methodology to embed this partial differential equations defined on the front in a complete Eulerian framework, fully avoiding the tracking of fluid particles and its known limitations. To show the advantages of this approach in the field of Fluid Mechanics we present in this work one particular application: the numerical approximation of a potential flow model to simulate the evolution and breaking of a solitary wave propagating over a slopping bottom and compare the level set based algorithm with previous front tracking models.
AN EFFICIENT DATA MINING METHOD TO FIND FREQUENT ITEM SETS IN LARGE DATABASE USING TR- FCTM
Directory of Open Access Journals (Sweden)
Saravanan Suba
2016-01-01
Full Text Available Mining association rules in large database is one of most popular data mining techniques for business decision makers. Discovering frequent item set is the core process in association rule mining. Numerous algorithms are available in the literature to find frequent patterns. Apriori and FP-tree are the most common methods for finding frequent items. Apriori finds significant frequent items using candidate generation with more number of data base scans. FP-tree uses two database scans to find significant frequent items without using candidate generation. This proposed TR-FCTM (Transaction Reduction- Frequency Count Table Method discovers significant frequent items by generating full candidates once to form frequency count table with one database scan. Experimental results of TR-FCTM shows that this algorithm outperforms than Apriori and FP-tree.
Studying the properties of Variational Data Assimilation Methods by Applying a Set of Test-Examples
DEFF Research Database (Denmark)
Thomsen, Per Grove; Zlatev, Zahari
2007-01-01
and backward computations are carried out by using the model under consideration and its adjoint equations (both the model and its adjoint are defined by systems of differential equations). The major difficulty is caused by the huge increase of the computational load (normally by a factor more than 100...... assimilation method (numerical algorithms for solving differential equations, splitting procedures and optimization algorithms) have been studied by using these tests. The presentation will include results from testing carried out in the study.......he variational data assimilation methods can successfully be used in different fields of science and engineering. An attempt to utilize available sets of observations in the efforts to improve (i) the models used to study different phenomena (ii) the model results is systematically carried out when...
Numerical simulation of overflow at vertical weirs using a hybrid level set/VOF method
Lv, Xin; Zou, Qingping; Reeve, Dominic
2011-10-01
This paper presents the applications of a newly developed free surface flow model to the practical, while challenging overflow problems for weirs. Since the model takes advantage of the strengths of both the level set and volume of fluid methods and solves the Navier-Stokes equations on an unstructured mesh, it is capable of resolving the time evolution of very complex vortical motions, air entrainment and pressure variations due to violent deformations following overflow of the weir crest. In the present study, two different types of vertical weir, namely broad-crested and sharp-crested, are considered for validation purposes. The calculated overflow parameters such as pressure head distributions, velocity distributions, and water surface profiles are compared against experimental data as well as numerical results available in literature. A very good quantitative agreement has been obtained. The numerical model, thus, offers a good alternative to traditional experimental methods in the study of weir problems.
Directory of Open Access Journals (Sweden)
Jun Bi
2018-04-01
Full Text Available Battery electric vehicles (BEVs reduce energy consumption and air pollution as compared with conventional vehicles. However, the limited driving range and potential long charging time of BEVs create new problems. Accurate charging time prediction of BEVs helps drivers determine travel plans and alleviate their range anxiety during trips. This study proposed a combined model for charging time prediction based on regression and time-series methods according to the actual data from BEVs operating in Beijing, China. After data analysis, a regression model was established by considering the charged amount for charging time prediction. Furthermore, a time-series method was adopted to calibrate the regression model, which significantly improved the fitting accuracy of the model. The parameters of the model were determined by using the actual data. Verification results confirmed the accuracy of the model and showed that the model errors were small. The proposed model can accurately depict the charging time characteristics of BEVs in Beijing.
A voltage control method for an active capacitive DC-link module with series-connected circuit
DEFF Research Database (Denmark)
Wang, Haoran; Wang, Huai; Blaabjerg, Frede
2017-01-01
Many efforts have been made to improve the performance of power electronic systems with active capacitive DC-link module in terms of power density as well as reliability. One of the attractive solution is an active capacitive DC-link with the series-connected circuit because of handling small......-rated power. However, in the existing control method of this circuit, the DC-link current of the backward-stage or forward-stage need to be sensed for extracting the ripple components, which limits the flexibility of the active DC-link module. Thus, in this paper, a voltage control method of an active...... capacitive DC-link module is proposed. Current sensor at the DC-link will be cancel from the circuit. The controller of the series-connected circuit requires internal voltage signals of the DC-link module only, making it possible to be fully independent without any additional connection to the main circuit...
A combined single-multiphase flow formulation of the premixing phase using the level set method
International Nuclear Information System (INIS)
Leskovar, M.; Marn, J.
1999-01-01
The premixing phase of a steam explosion covers the interaction of the melt jet or droplets with the water prior to any steam explosion occurring. To get a better insight of the hydrodynamic processes during the premixing phase beside hot premixing experiments, where the water evaporation is significant, also cold isothermal premixing experiments are performed. The specialty of isothermal premixing experiments is that three phases are involved: the water, the air and the spheres phase, but only the spheres phase mixes with the other two phases whereas the water and air phases do not mix and remain separated by a free surface. Our idea therefore was to treat the isothermal premixing process with a combined single-multiphase flow model. In this combined model the water and air phase are treated as a single phase with discontinuous phase properties at the water air interface, whereas the spheres are treated as usually with a multiphase flow model, where the spheres represent the dispersed phase and the common water-air phase represents the continuous phase. The common water-air phase was described with the front capturing method based on the level set formulation. In the level set formulation, the boundary of two-fluid interfaces is modeled as the zero set of a smooth signed normal distance function defined on the entire physical domain. The boundary is then updated by solving a nonlinear equation of the Hamilton-Jacobi type on the whole domain. With this single-multiphase flow model the Queos isothermal premixing Q08 has been simulated. A numerical analysis using different treatments of the water-air interface (level set, high-resolution and upwind) has been performed for the incompressible and compressible case and the results were compared to experimental measurements.(author)
Fan, Ming; Kuwahara, Hiroyuki; Wang, Xiaolei; Wang, Suojin; Gao, Xin
2015-11-01
Parameter estimation is a challenging computational problem in the reverse engineering of biological systems. Because advances in biotechnology have facilitated wide availability of time-series gene expression data, systematic parameter estimation of gene circuit models from such time-series mRNA data has become an important method for quantitatively dissecting the regulation of gene expression. By focusing on the modeling of gene circuits, we examine here the performance of three types of state-of-the-art parameter estimation methods: population-based methods, online methods and model-decomposition-based methods. Our results show that certain population-based methods are able to generate high-quality parameter solutions. The performance of these methods, however, is heavily dependent on the size of the parameter search space, and their computational requirements substantially increase as the size of the search space increases. In comparison, online methods and model decomposition-based methods are computationally faster alternatives and are less dependent on the size of the search space. Among other things, our results show that a hybrid approach that augments computationally fast methods with local search as a subsequent refinement procedure can substantially increase the quality of their parameter estimates to the level on par with the best solution obtained from the population-based methods while maintaining high computational speed. These suggest that such hybrid methods can be a promising alternative to the more commonly used population-based methods for parameter estimation of gene circuit models when limited prior knowledge about the underlying regulatory mechanisms makes the size of the parameter search space vastly large. © The Author 2015. Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.
Schiavo, B.; Stremme, W.; Grutter, M.; Campion, R.; Rivera, C. I.; Inguaggiato, S.
2017-12-01
The measurement of SO2flux from active volcanoes are of great importance, for monitoring and hazard of volcanic activity, environmental impact and flux emissions related to changes of magmatic activity. Sulfur dioxide total flux from Popocatépetl volcano was determinad using a ultra-violet camera (or SO2 camera) with different band-pass filter. The flux is obteined from the product of the gas concentration over integrated the plume cross-section (slant column in molec/cm2 or ppm*m) and wind velocity data. Model of plume altitude and wind speed measurement are used to calculate a wind velocity, but a new method of sequential images is widely used in several years for this calculation. Volcanic plume measurements, for a total of about 60 days from from January to March 2017, were collected and utilized to generate the SO2 time series. The importance of monitoring and the time series of volcanic gas emissions is described and proven by many scientific studies. A time series of the Popocatépetl volcano will allow us to detect the volcanic gas as well as anomalies in volcanic processes and help to estimate the average SO2 flux of the volcano. We present a detailed description of the posterior correction of the dilution effect, which occurs due to a simplification of the radiative transfer equation. The correction scheme is especial applicable for long term monitoring from a permanent observation site. Images of volcanic SO2 plumes from the active Popocatépetl volcano in Mexico are presented, showing persistent passive degassing. The measurment are taken from the Altzomoni Atmospheric Observatory (19.12N, -98.65W, 3,985 m.a.s.l.), which forms part of the RUOA (www.ruoa.unam.mx) and NDACC (https://www2.acom.ucar.edu/irwg) networks. It is located north of the crater at 11 km distance. The data to calculate SO2 flux (t/d or kg/s) were recorded with the QSI UV camera and processed using Python scripts.
Topology optimization in acoustics and elasto-acoustics via a level-set method
Desai, J.; Faure, A.; Michailidis, G.; Parry, G.; Estevez, R.
2018-04-01
Optimizing the shape and topology (S&T) of structures to improve their acoustic performance is quite challenging. The exact position of the structural boundary is usually of critical importance, which dictates the use of geometric methods for topology optimization instead of standard density approaches. The goal of the present work is to investigate different possibilities for handling topology optimization problems in acoustics and elasto-acoustics via a level-set method. From a theoretical point of view, we detail two equivalent ways to perform the derivation of surface-dependent terms and propose a smoothing technique for treating problems of boundary conditions optimization. In the numerical part, we examine the importance of the surface-dependent term in the shape derivative, neglected in previous studies found in the literature, on the optimal designs. Moreover, we test different mesh adaptation choices, as well as technical details related to the implicit surface definition in the level-set approach. We present results in two and three-space dimensions.
Validation of non-rigid point-set registration methods using a porcine bladder pelvic phantom
Zakariaee, Roja; Hamarneh, Ghassan; Brown, Colin J.; Spadinger, Ingrid
2016-01-01
The problem of accurate dose accumulation in fractionated radiotherapy treatment for highly deformable organs, such as bladder, has garnered increasing interest over the past few years. However, more research is required in order to find a robust and efficient solution and to increase the accuracy over the current methods. The purpose of this study was to evaluate the feasibility and accuracy of utilizing non-rigid (affine or deformable) point-set registration in accumulating dose in bladder of different sizes and shapes. A pelvic phantom was built to house an ex vivo porcine bladder with fiducial landmarks adhered onto its surface. Four different volume fillings of the bladder were used (90, 180, 360 and 480 cc). The performance of MATLAB implementations of five different methods were compared, in aligning the bladder contour point-sets. The approaches evaluated were coherent point drift (CPD), gaussian mixture model, shape context, thin-plate spline robust point matching (TPS-RPM) and finite iterative closest point (ICP-finite). The evaluation metrics included registration runtime, target registration error (TRE), root-mean-square error (RMS) and Hausdorff distance (HD). The reference (source) dataset was alternated through all four points-sets, in order to study the effect of reference volume on the registration outcomes. While all deformable algorithms provided reasonable registration results, CPD provided the best TRE values (6.4 mm), and TPS-RPM yielded the best mean RMS and HD values (1.4 and 6.8 mm, respectively). ICP-finite was the fastest technique and TPS-RPM, the slowest.
Validation of non-rigid point-set registration methods using a porcine bladder pelvic phantom
International Nuclear Information System (INIS)
Zakariaee, Roja; Hamarneh, Ghassan; Brown, Colin J; Spadinger, Ingrid
2016-01-01
The problem of accurate dose accumulation in fractionated radiotherapy treatment for highly deformable organs, such as bladder, has garnered increasing interest over the past few years. However, more research is required in order to find a robust and efficient solution and to increase the accuracy over the current methods. The purpose of this study was to evaluate the feasibility and accuracy of utilizing non-rigid (affine or deformable) point-set registration in accumulating dose in bladder of different sizes and shapes. A pelvic phantom was built to house an ex vivo porcine bladder with fiducial landmarks adhered onto its surface. Four different volume fillings of the bladder were used (90, 180, 360 and 480 cc). The performance of MATLAB implementations of five different methods were compared, in aligning the bladder contour point-sets. The approaches evaluated were coherent point drift (CPD), gaussian mixture model, shape context, thin-plate spline robust point matching (TPS-RPM) and finite iterative closest point (ICP-finite). The evaluation metrics included registration runtime, target registration error (TRE), root-mean-square error (RMS) and Hausdorff distance (HD). The reference (source) dataset was alternated through all four points-sets, in order to study the effect of reference volume on the registration outcomes. While all deformable algorithms provided reasonable registration results, CPD provided the best TRE values (6.4 mm), and TPS-RPM yielded the best mean RMS and HD values (1.4 and 6.8 mm, respectively). ICP-finite was the fastest technique and TPS-RPM, the slowest. (paper)
Stolper, Margreet; Molewijk, Bert; Widdershoven, Guy
2016-07-22
Moral Case Deliberation is a specific form of bioethics education fostering professionals' moral competence in order to deal with their moral questions. So far, few studies focus in detail on Moral Case Deliberation methodologies and their didactic principles. The dilemma method is a structured and frequently used method in Moral Case Deliberation that stimulates methodological reflection and reasoning through a systematic dialogue on an ethical issue experienced in practice. In this paper we present a case-study of a Moral Case Deliberation with the dilemma method in a health care institution for people with an intellectual disability, describing the theoretical background and the practical application of the dilemma method. The dilemma method focuses on moral experiences of participants concerning a concrete dilemma in practice. By an in-depth description of each of the steps of the deliberation process, we elucidate the educational value and didactics of this specific method. The didactics and methodical steps of the dilemma method both supported and structured the dialogical reflection process of the participants. The process shows that the participants learned to recognize the moral dimension of the issue at stake and were able to distinguish various perspectives and reasons in a systematic manner. The facilitator played an important role in the learning process of the participants, by assisting them in focusing on and exploring moral aspects of the case. The reflection and learning process, experienced by the participants, shows competency-based characteristics. The role of the facilitator is that of a Socratic teacher with specific knowledge and skills, fostering reflection, inquiry and dialogue. The specific didactics of the dilemma method is well suited for teaching bioethics in clinical settings. The dilemma method follows an inductive learning approach through a dialogical moral inquiry in which participants develop not only knowledge but also skills
Sriyudthsak, Kansuporn; Iwata, Michio; Hirai, Masami Yokota; Shiraishi, Fumihide
2014-06-01
The availability of large-scale datasets has led to more effort being made to understand characteristics of metabolic reaction networks. However, because the large-scale data are semi-quantitative, and may contain biological variations and/or analytical errors, it remains a challenge to construct a mathematical model with precise parameters using only these data. The present work proposes a simple method, referred to as PENDISC (Parameter Estimation in a N on- DImensionalized S-system with Constraints), to assist the complex process of parameter estimation in the construction of a mathematical model for a given metabolic reaction system. The PENDISC method was evaluated using two simple mathematical models: a linear metabolic pathway model with inhibition and a branched metabolic pathway model with inhibition and activation. The results indicate that a smaller number of data points and rate constant parameters enhances the agreement between calculated values and time-series data of metabolite concentrations, and leads to faster convergence when the same initial estimates are used for the fitting. This method is also shown to be applicable to noisy time-series data and to unmeasurable metabolite concentrations in a network, and to have a potential to handle metabolome data of a relatively large-scale metabolic reaction system. Furthermore, it was applied to aspartate-derived amino acid biosynthesis in Arabidopsis thaliana plant. The result provides confirmation that the mathematical model constructed satisfactorily agrees with the time-series datasets of seven metabolite concentrations.
Reservoir characterisation by a binary level set method and adaptive multiscale estimation
Energy Technology Data Exchange (ETDEWEB)
Nielsen, Lars Kristian
2006-01-15
The main focus of this work is on estimation of the absolute permeability as a solution of an inverse problem. We have both considered a single-phase and a two-phase flow model. Two novel approaches have been introduced and tested numerical for solving the inverse problems. The first approach is a multi scale zonation technique which is treated in Paper A. The purpose of the work in this paper is to find a coarse scale solution based on production data from wells. In the suggested approach, the robustness of an already developed method, the adaptive multi scale estimation (AME), has been improved by utilising information from several candidate solutions generated by a stochastic optimizer. The new approach also suggests a way of combining a stochastic and a gradient search method, which in general is a problematic issue. The second approach is a piecewise constant level set approach and is applied in Paper B, C, D and E. Paper B considers the stationary single-phase problem, while Paper C, D and E use a two-phase flow model. In the two-phase flow problem we have utilised information from both production data in wells and spatially distributed data gathered from seismic surveys. Due to the higher content of information provided by the spatially distributed data, we search solutions on a slightly finer scale than one typically does with only production data included. The applied level set method is suitable for reconstruction of fields with a supposed known facies-type of solution. That is, the solution should be close to piecewise constant. This information is utilised through a strong restriction of the number of constant levels in the estimate. On the other hand, the flexibility in the geometries of the zones is much larger for this method than in a typical zonation approach, for example the multi scale approach applied in Paper A. In all these papers, the numerical studies are done on synthetic data sets. An advantage of synthetic data studies is that the true
Gaspari, Roberto; Rapallo, Arnaldo
2008-06-28
In this work a new method is proposed for the choice of basis functions in diffusion theory (DT) calculations. This method, named hybrid basis approach (HBA), combines the two previously adopted long time sorting procedure (LTSP) and maximum correlation approximation (MCA) techniques; the first emphasizing contributions from the long time dynamics, the latter being based on the local correlations along the chain. In order to fulfill this task, the HBA procedure employs a first order basis set corresponding to a high order MCA one and generates upper order approximations according to LTSP. A test of the method is made first on a melt of cis-1,4-polyisoprene decamers where HBA and LTSP are compared in terms of efficiency. Both convergence properties and numerical stability are improved by the use of the HBA basis set whose performance is evaluated on local dynamics, by computing the correlation times of selected bond vectors along the chain, and on global ones, through the eigenvalues of the diffusion operator L. Further use of the DT with a HBA basis set has been made on a 71-mer of syndiotactic trans-1,2-polypentadiene in toluene solution, whose dynamical properties have been computed with a high order calculation and compared to the "numerical experiment" provided by the molecular dynamics (MD) simulation in explicit solvent. The necessary equilibrium averages have been obtained by a vacuum trajectory of the chain where solvent effects on conformational properties have been reproduced with a proper screening of the nonbonded interactions, corresponding to a definite value of the mean radius of gyration of the polymer in vacuum. Results show a very good agreement between DT calculations and the MD numerical experiment. This suggests a further use of DT methods with the necessary input quantities obtained by the only knowledge of some experimental values, i.e., the mean radius of gyration of the chain and the viscosity of the solution, and by a suitable vacuum
The use of principal component, discriminate and rough sets analysis methods of radiological data
International Nuclear Information System (INIS)
Seddeek, M.K.; Kozae, A.M.; Sharshar, T.; Badran, H.M.
2006-01-01
In this work, computational methods of finding clusters of multivariate data points were explored using principal component analysis (PCA), discriminate analysis (DA) and rough set analysis (RSA) methods. The variables were the concentrations of four natural isotopes and the texture characteristics of 100 sand samples from the coast of North Sinai, Egypt. Beach and dune sands are the two types of samples included. These methods were used to reduce the dimensionality of multivariate data and as classification and clustering methods. The results showed that the classification of sands in the environment of North Sinai is dependent upon the radioactivity contents of the naturally occurring radioactive materials and not upon the characteristics of the sand. The application of DA enables the creation of a classification rule for sand type and it revealed that samples with high negatively values of the first score have the highest contamination of black sand. PCA revealed that radioactivity concentrations alone can be considered to predict the classification of other samples. The results of RSA showed that only one of the concentrations of 238 U, 226 Ra and 232 Th with 40 K content, can characterize the clusters together with characteristics of the sand. Both PCA and RSA result in the following conclusion: 238 U, 226 Ra and 232 Th behave similarly. RSA revealed that one/two of them may not be considered without affecting the body of knowledge
Set-up and methods for SiPM Photo-Detection Efficiency measurements
International Nuclear Information System (INIS)
Zappalà, G.; Acerbi, F.; Ferri, A.; Gola, A.; Paternoster, G.; Zorzi, N.; Piemonte, C.
2016-01-01
In this work, a compact set-up and three different methods to measure the Photo-Detection Efficiency (PDE) of Silicon Photomultipliers (SiPMs) and Single-Photon Avalanche Diodes (SPADs) are presented. The methods, based on either continuous or pulsed light illumination, are discussed in detail and compared in terms of measurement precision and time. For the SiPM, these methods have the feature of minimizing the effect of both the primary and correlated noise on the PDE estimation. The PDE of SiPMs (produced at FBK, Trento, Italy) was measured in a range from UV to NIR, obtaining similar results with all the methods. Furthermore, the advantages of measuring, when possible, the PDE of SPADs (of the same technology and with the same layout of a single SiPM cell) instead of larger devices are also discussed and a direct comparison between measurement results is shown. Using a SPAD, it is possible to reduce the measurement complexity and uncertainty since the correlated noise sources are reduced with respect to the SiPM case.
International Nuclear Information System (INIS)
Surville, J.
2005-12-01
We have developed three main optical methods to study the speckles generated by a smoothed laser source. The first method addresses the measurement of the temporal and spatial correlation functions of the source, with a modified Michelson interferometer. The second one is a pump-probe technique created to shoot a picture of a speckle pattern generated at a set time. And the third one is an evolution of the second method dedicated to time-frequency coding, thanks to a frequency chirped probe pulse. Thus, the speckles can be followed in time and their motion can be described. According to these three methods, the average size and duration of the speckles can be measured. It is also possible to measure the size and the duration of each of them and mostly their velocity in a given direction. All the results obtained have been confronted to the different existing theories. We show that the statistical distributions of the measured speckles'size and speckles'intensity agree satisfactorily with theoretical values
DEFF Research Database (Denmark)
Schneller, Mikkel Bo; Pedersen, Mogens Theisen; Gupta, Nidhi
2015-01-01
We compared the accuracy of five objective methods, including two newly developed methods combining accelerometry and activity type recognition (Acti4), against indirect calorimetry, to estimate total energy expenditure (EE) of different activities in semi-standardized settings. Fourteen particip...
International Nuclear Information System (INIS)
Tonoike, Kotaro; Yamamoto, Toshihiro; Watanabe, Shoichi; Miyoshi, Yoshinori
2003-01-01
As a part of the development of a subcriticality monitoring system, a system which has a time series data acquisition function of detector signals and a real time evaluation function of alpha value with the Feynman-alpha method was established, with which the kinetic parameter (alpha value) was measured at the STACY heterogeneous core. The Hashimoto's difference filter was implemented in the system, which enables the measurement at a critical condition. The measurement result of the new system agreed with the pulsed neutron method. (author)
Energy Technology Data Exchange (ETDEWEB)
Lafuma, J; Nenot, J C; Morin, M [Commissariat a l' Energie Atomique, Fontenay-aux-Roses (France). Centre d' Etudes Nucleaires
1968-07-01
We followed the biological fate of a complex formed on one side with either a rare earth (cerium-144) or a transuranium element (plutonium-239), and on the other side with a chelating agent of the polyamino acid series (EDTA, BAETA, DTPA, TTHA). This method allowed to study: 1 - the in vivo stability of the various complexes and to compare them; 2 - the stability of the complexes as a function of the isotope - chelating agent weight relationships; 3 - the metabolism of the chelating agents resulting in stable complexes, i. e. DTPA and TTHA mainly. This simple method brought out the higher efficiency, of DTPA in chelating rare earths and plutonium and for therapeutic purposes. (authors) [French] La methode consiste a suivre le devenir biologique d'un complexe forme d'une part avec une terre rare (cerium 144) ou un transuranien (plutonium 239) et d'autre part avec un chelateur de la serie des acides polyamines (EDTA, BAETA, DTPA, TTHA). Elle permet d'etudier: 1 - la stabilite in vivo des differents complexes, de les comparer; 2 - la stabilite des complexes en fonction des rapports ponderaux isotope - chelateurs; 3 - le metabolisme des chelateurs formant des complexes stables, essentiellement DTPA et TTHA. Cette methode simple degage la suprematie du DTPA en ce qui concerne la chelation des terres rares et du plutonium, et son utilisation a des fins therapeutiques. (auteurs)
Energy Technology Data Exchange (ETDEWEB)
Lafuma, J.; Nenot, J.C.; Morin, M. [Commissariat a l' Energie Atomique, Fontenay-aux-Roses (France). Centre d' Etudes Nucleaires
1968-07-01
We followed the biological fate of a complex formed on one side with either a rare earth (cerium-144) or a transuranium element (plutonium-239), and on the other side with a chelating agent of the polyamino acid series (EDTA, BAETA, DTPA, TTHA). This method allowed to study: 1 - the in vivo stability of the various complexes and to compare them; 2 - the stability of the complexes as a function of the isotope - chelating agent weight relationships; 3 - the metabolism of the chelating agents resulting in stable complexes, i. e. DTPA and TTHA mainly. This simple method brought out the higher efficiency, of DTPA in chelating rare earths and plutonium and for therapeutic purposes. (authors) [French] La methode consiste a suivre le devenir biologique d'un complexe forme d'une part avec une terre rare (cerium 144) ou un transuranien (plutonium 239) et d'autre part avec un chelateur de la serie des acides polyamines (EDTA, BAETA, DTPA, TTHA). Elle permet d'etudier: 1 - la stabilite in vivo des differents complexes, de les comparer; 2 - la stabilite des complexes en fonction des rapports ponderaux isotope - chelateurs; 3 - le metabolisme des chelateurs formant des complexes stables, essentiellement DTPA et TTHA. Cette methode simple degage la suprematie du DTPA en ce qui concerne la chelation des terres rares et du plutonium, et son utilisation a des fins therapeutiques. (auteurs)
The use of qualitative methods to inform Delphi surveys in core outcome set development.
Keeley, T; Williamson, P; Callery, P; Jones, L L; Mathers, J; Jones, J; Young, B; Calvert, M
2016-05-04
Core outcome sets (COS) help to minimise bias in trials and facilitate evidence synthesis. Delphi surveys are increasingly being used as part of a wider process to reach consensus about what outcomes should be included in a COS. Qualitative research can be used to inform the development of Delphi surveys. This is an advance in the field of COS development and one which is potentially valuable; however, little guidance exists for COS developers on how best to use qualitative methods and what the challenges are. This paper aims to provide early guidance on the potential role and contribution of qualitative research in this area. We hope the ideas we present will be challenged, critiqued and built upon by others exploring the role of qualitative research in COS development. This paper draws upon the experiences of using qualitative methods in the pre-Delphi stage of the development of three different COS. Using these studies as examples, we identify some of the ways that qualitative research might contribute to COS development, the challenges in using such methods and areas where future research is required. Qualitative research can help to identify what outcomes are important to stakeholders; facilitate understanding of why some outcomes may be more important than others, determine the scope of outcomes; identify appropriate language for use in the Delphi survey and inform comparisons between stakeholder data and other sources, such as systematic reviews. Developers need to consider a number of methodological points when using qualitative research: specifically, which stakeholders to involve, how to sample participants, which data collection methods are most appropriate, how to consider outcomes with stakeholders and how to analyse these data. A number of areas for future research are identified. Qualitative research has the potential to increase the research community's confidence in COS, although this will be dependent upon using rigorous and appropriate
Setting the light conditions for measuring root transparency for age-at-death estimation methods.
Adserias-Garriga, Joe; Nogué-Navarro, Laia; Zapico, Sara C; Ubelaker, Douglas H
2018-03-01
Age-at-death estimation is one of the main goals in forensic identification, being an essential parameter to determine the biological profile, narrowing the possibility of identification in cases involving missing persons and unidentified bodies. The study of dental tissues has been long considered as a proper tool for age estimation with several age estimation methods based on them. Dental age estimation methods can be divided into three categories: tooth formation and development, post-formation changes, and histological changes. While tooth formation and growth changes are important for fetal and infant consideration, when the end of dental and skeletal growth is achieved, post-formation or biochemical changes can be applied. Lamendin et al. in J Forensic Sci 37:1373-1379, (1992) developed an adult age estimation method based on root transparency and periodontal recession. The regression formula demonstrated its accuracy of use for 40 to 70-year-old individuals. Later on, Prince and Ubelaker in J Forensic Sci 47(1):107-116, (2002) evaluated the effects of ancestry and sex and incorporated root height into the equation, developing four new regression formulas for males and females of African and European ancestry. Even though root transparency is a key element in the method, the conditions for measuring this element have not been established. The aim of the present study is to set the light conditions measured in lumens that offer greater accuracy when applying the Lamendin et al. method modified by Prince and Ubelaker. The results must be also taken into account in the application of other age estimation methodologies using root transparency to estimate age-at-death.
[Cardiac Synchronization Function Estimation Based on ASM Level Set Segmentation Method].
Zhang, Yaonan; Gao, Yuan; Tang, Liang; He, Ying; Zhang, Huie
At present, there is no accurate and quantitative methods for the determination of cardiac mechanical synchronism, and quantitative determination of the synchronization function of the four cardiac cavities with medical images has a great clinical value. This paper uses the whole heart ultrasound image sequence, and segments the left & right atriums and left & right ventricles of each frame. After the segmentation, the number of pixels in each cavity and in each frame is recorded, and the areas of the four cavities of the image sequence are therefore obtained. The area change curves of the four cavities are further extracted, and the synchronous information of the four cavities is obtained. Because of the low SNR of Ultrasound images, the boundary lines of cardiac cavities are vague, so the extraction of cardiac contours is still a challenging problem. Therefore, the ASM model information is added to the traditional level set method to force the curve evolution process. According to the experimental results, the improved method improves the accuracy of the segmentation. Furthermore, based on the ventricular segmentation, the right and left ventricular systolic functions are evaluated, mainly according to the area changes. The synchronization of the four cavities of the heart is estimated based on the area changes and the volume changes.
Directory of Open Access Journals (Sweden)
Reza Kiani Mavi
2013-01-01
Full Text Available Data envelopment analysis (DEA is used to evaluate the performance of decision making units (DMUs with multiple inputs and outputs in a homogeneous group. In this way, the acquired relative efficiency score for each decision making unit lies between zero and one where a number of them may have an equal efficiency score of one. DEA successfully divides them into two categories of efficient DMUs and inefficient DMUs. A ranking for inefficient DMUs is given but DEA does not provide further information about the efficient DMUs. One of the popular methods for evaluating and ranking DMUs is the common set of weights (CSW method. We generate a CSW model with considering nondiscretionary inputs that are beyond the control of DMUs and using ideal point method. The main idea of this approach is to minimize the distance between the evaluated decision making unit and the ideal decision making unit (ideal point. Using an empirical example we put our proposed model to test by applying it to the data of some 20 bank branches and rank their efficient units.
The Visual Matrix Method: Imagery and Affect in a Group-Based Research Setting
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Lynn Froggett
2015-07-01
Full Text Available The visual matrix is a method for researching shared experience, stimulated by sensory material relevant to a research question. It is led by imagery, visualization and affect, which in the matrix take precedence over discourse. The method enables the symbolization of imaginative and emotional material, which might not otherwise be articulated and allows "unthought" dimensions of experience to emerge into consciousness in a participatory setting. We describe the process of the matrix with reference to the study "Public Art and Civic Engagement" (FROGGETT, MANLEY, ROY, PRIOR & DOHERTY, 2014 in which it was developed and tested. Subsequently, examples of its use in other contexts are provided. Both the matrix and post-matrix discussions are described, as is the interpretive process that follows. Theoretical sources are highlighted: its origins in social dreaming; the atemporal, associative nature of the thinking during and after the matrix which we describe through the Deleuzian idea of the rhizome; and the hermeneutic analysis which draws from object relations theory and the Lorenzerian tradition of scenic understanding. The matrix has been conceptualized as a "scenic rhizome" to account for its distinctive quality and hybrid origins in research practice. The scenic rhizome operates as a "third" between participants and the "objects" of contemplation. We suggest that some of the drawbacks of other group-based methods are avoided in the visual matrix—namely the tendency for inter-personal dynamics to dominate the event. URN: http://nbn-resolving.de/urn:nbn:de:0114-fqs150369
A Novel Method for Predicting Anisakid Nematode Infection of Atlantic Cod Using Rough Set Theory.
Wąsikowska, Barbara; Sobecka, Ewa; Bielat, Iwona; Legierko, Monika; Więcaszek, Beata
2018-03-01
Atlantic cod ( Gadus morhua L.) is one of the most important fish species in the fisheries industries of many countries; however, these fish are often infected with parasites. The detection of pathogenic larval nematodes is usually performed in fish processing facilities by visual examination using candling or by digesting muscles in artificial digestive juices, but these methods are both time and labor intensive. This article presents an innovative approach to the analysis of cod parasites from both the Atlantic and Baltic Sea areas through the application of rough set theory, one of the methods of artificial intelligence, for the prediction of food safety in a food production chain. The parasitological examinations were performed focusing on nematode larvae pathogenic to humans, e.g., Anisakis simplex, Contracaecum osculatum, and Pseudoterranova decipiens. The analysis allowed identification of protocols with which it is possible to make preliminary estimates of the quantity and quality of parasites found in cod catches before detailed analyses are performed. The results indicate that the method used can be an effective analytical tool for these types of data. To achieve this goal, a database is needed that contains the patterns intensity of parasite infections and the conditions of commercial fish species in different localities in their distributions.
A wavelet method for modeling and despiking motion artifacts from resting-state fMRI time series
Patel, Ameera X.; Kundu, Prantik; Rubinov, Mikail; Jones, P. Simon; Vértes, Petra E.; Ersche, Karen D.; Suckling, John; Bullmore, Edward T.
2014-01-01
The impact of in-scanner head movement on functional magnetic resonance imaging (fMRI) signals has long been established as undesirable. These effects have been traditionally corrected by methods such as linear regression of head movement parameters. However, a number of recent independent studies have demonstrated that these techniques are insufficient to remove motion confounds, and that even small movements can spuriously bias estimates of functional connectivity. Here we propose a new data-driven, spatially-adaptive, wavelet-based method for identifying, modeling, and removing non-stationary events in fMRI time series, caused by head movement, without the need for data scrubbing. This method involves the addition of just one extra step, the Wavelet Despike, in standard pre-processing pipelines. With this method, we demonstrate robust removal of a range of different motion artifacts and motion-related biases including distance-dependent connectivity artifacts, at a group and single-subject level, using a range of previously published and new diagnostic measures. The Wavelet Despike is able to accommodate the substantial spatial and temporal heterogeneity of motion artifacts and can consequently remove a range of high and low frequency artifacts from fMRI time series, that may be linearly or non-linearly related to physical movements. Our methods are demonstrated by the analysis of three cohorts of resting-state fMRI data, including two high-motion datasets: a previously published dataset on children (N = 22) and a new dataset on adults with stimulant drug dependence (N = 40). We conclude that there is a real risk of motion-related bias in connectivity analysis of fMRI data, but that this risk is generally manageable, by effective time series denoising strategies designed to attenuate synchronized signal transients induced by abrupt head movements. The Wavelet Despiking software described in this article is freely available for download at www
A wavelet method for modeling and despiking motion artifacts from resting-state fMRI time series.
Patel, Ameera X; Kundu, Prantik; Rubinov, Mikail; Jones, P Simon; Vértes, Petra E; Ersche, Karen D; Suckling, John; Bullmore, Edward T
2014-07-15
The impact of in-scanner head movement on functional magnetic resonance imaging (fMRI) signals has long been established as undesirable. These effects have been traditionally corrected by methods such as linear regression of head movement parameters. However, a number of recent independent studies have demonstrated that these techniques are insufficient to remove motion confounds, and that even small movements can spuriously bias estimates of functional connectivity. Here we propose a new data-driven, spatially-adaptive, wavelet-based method for identifying, modeling, and removing non-stationary events in fMRI time series, caused by head movement, without the need for data scrubbing. This method involves the addition of just one extra step, the Wavelet Despike, in standard pre-processing pipelines. With this method, we demonstrate robust removal of a range of different motion artifacts and motion-related biases including distance-dependent connectivity artifacts, at a group and single-subject level, using a range of previously published and new diagnostic measures. The Wavelet Despike is able to accommodate the substantial spatial and temporal heterogeneity of motion artifacts and can consequently remove a range of high and low frequency artifacts from fMRI time series, that may be linearly or non-linearly related to physical movements. Our methods are demonstrated by the analysis of three cohorts of resting-state fMRI data, including two high-motion datasets: a previously published dataset on children (N=22) and a new dataset on adults with stimulant drug dependence (N=40). We conclude that there is a real risk of motion-related bias in connectivity analysis of fMRI data, but that this risk is generally manageable, by effective time series denoising strategies designed to attenuate synchronized signal transients induced by abrupt head movements. The Wavelet Despiking software described in this article is freely available for download at www
Series: Utilization of Differential Equations and Methods for Solving Them in Medical Physics (3).
Murase, Kenya
2016-01-01
In this issue, simultaneous differential equations were introduced. These differential equations are often used in the field of medical physics. The methods for solving them were also introduced, which include Laplace transform and matrix methods. Some examples were also introduced, in which Laplace transform and matrix methods were applied to solving simultaneous differential equations derived from a three-compartment kinetic model for analyzing the glucose metabolism in tissues and Bloch equations for describing the behavior of the macroscopic magnetization in magnetic resonance imaging.In the next (final) issue, partial differential equations and various methods for solving them will be introduced together with some examples in medical physics.
Setting health research priorities using the CHNRI method: I. Involving funders
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Igor Rudan
2016-06-01
Full Text Available In 2007 and 2008, the World Health Organization's Department for Child and Adolescent Health and Development commissioned five large research priority setting exercises using the CHNRI (Child Health and Nutrition Research Initiative method. The aim was to define research priorities related to the five major causes of child deaths for the period up to the year 2015. The selected causes were childhood pneumonia, diarrhoea, birth asphyxia, neonatal infections and preterm birth/low birth weight. The criteria used for prioritization in all five exercises were the “standard” CHNRI criteria: answerability, effectiveness, deliverability, potential for mortality burden reduction and the effect on equity. Having completed the exercises, the WHO officers were left with another question: how “fundable” were the identified priorities, i.e. how attractive were they to research funders?
Methods for intraoperative, sterile pose-setting of patient-specific microstereotactic frames
Vollmann, Benjamin; Müller, Samuel; Kundrat, Dennis; Ortmaier, Tobias; Kahrs, Lüder A.
2015-03-01
This work proposes new methods for a microstereotactic frame based on bone cement fixation. Microstereotactic frames are under investigation for minimal invasive temporal bone surgery, e.g. cochlear implantation, or for deep brain stimulation, where products are already on the market. The correct pose of the microstereotactic frame is either adjusted outside or inside the operating room and the frame is used for e.g. drill or electrode guidance. We present a patientspecific, disposable frame that allows intraoperative, sterile pose-setting. Key idea of our approach is bone cement between two plates that cures while the plates are positioned with a mechatronics system in the desired pose. This paper includes new designs of microstereotactic frames, a system for alignment and first measurements to analyze accuracy and applicable load.
Ullmann, Gerhild; Williams, Harriet G
2016-07-01
Poor cognitive health a major concern of aging individuals, can compromise independent living. More than 16 million people in the United States are affected by cognitive impairment. We have studied the effects of the Feldenkrais Method(®) on cognitive function. In this case series with three participants cognitive function was assessed with the Trail Making Test A and B at baseline and after the Feldenkrais intervention. All participants improved performance on Trail Making Test A and B after completing the Feldenkrais intervention indicating that Feldenkrais lessons may offset age-related decline in cognitive function. The results of this case series warrant larger scale studies on cognitive outcomes of Feldenkrais interventions in clinical and non-clinical populations. Copyright © 2015 Elsevier Ltd. All rights reserved.
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Enrica Seravalli
2018-01-01
Full Text Available Background and purpose: Local implementation of plan-specific quality assurance (QA methods for intensity-modulated radiotherapy (IMRT and volumetric modulated arc therapy (VMAT treatment plans may vary because of dissimilarities in procedures, equipment and software. The purpose of this work is detecting possible differences between local QA findings and those of an audit, using the same set of treatment plans. Methods: A pre-defined set of clinical plans was devised and imported in the participating institute’s treatment planning system for dose computation. The dose distribution was measured using an ionisation chamber, radiochromic film and an ionisation chamber array. The centres performed their own QA, which was compared to the audit findings. The agreement/disagreement between the audit and the institute QA results were assessed along with the differences between the dose distributions measured by the audit team and computed by the institute. Results: For the majority of the cases the results of the audit were in agreement with the institute QA findings: ionisation chamber: 92%, array: 88%, film: 76% of the total measurements. In only a few of these cases the evaluated measurements failed for both: ionisation chamber: 2%, array: 4%, film: 0% of the total measurements. Conclusion: Using predefined treatment plans, we found that in approximately 80% of the evaluated measurements the results of local QA of IMRT and VMAT plans were in line with the findings of the audit. However, the percentage of agreement/disagreement depended on the characteristics of the measurement equipment used and on the analysis metric. Keywords: Quality assurance, Dosimetry audit, IMRT, VMAT, QA devices
Developing an objective evaluation method to estimate diabetes risk in community-based settings.
Kenya, Sonjia; He, Qing; Fullilove, Robert; Kotler, Donald P
2011-05-01
Exercise interventions often aim to affect abdominal obesity and glucose tolerance, two significant risk factors for type 2 diabetes. Because of limited financial and clinical resources in community and university-based environments, intervention effects are often measured with interviews or questionnaires and correlated with weight loss or body fat indicated by body bioimpedence analysis (BIA). However, self-reported assessments are subject to high levels of bias and low levels of reliability. Because obesity and body fat are correlated with diabetes at different levels in various ethnic groups, data reflecting changes in weight or fat do not necessarily indicate changes in diabetes risk. To determine how exercise interventions affect diabetes risk in community and university-based settings, improved evaluation methods are warranted. We compared a noninvasive, objective measurement technique--regional BIA--with whole-body BIA for its ability to assess abdominal obesity and predict glucose tolerance in 39 women. To determine regional BIA's utility in predicting glucose, we tested the association between the regional BIA method and blood glucose levels. Regional BIA estimates of abdominal fat area were significantly correlated (r = 0.554, P < 0.003) with fasting glucose. When waist circumference and family history of diabetes were added to abdominal fat in multiple regression models, the association with glucose increased further (r = 0.701, P < 0.001). Regional BIA estimates of abdominal fat may predict fasting glucose better than whole-body BIA as well as provide an objective assessment of changes in diabetes risk achieved through physical activity interventions in community settings.
International Nuclear Information System (INIS)
Ma, Jean-Luc
1984-01-01
First, the U-series disequilibrium dating method was re-examined using non-destructive γ-spectrometry. A new low-background (≤ 10 ppb U- equivalent) Ge-HP γ-spectrometer has been used to date travertine with small U-content (∼ 0.1 ppm) and low (≤ 5%) Th/U , content, by comparison with old-limestone γ-spectra. Second, a new ESR dating method has been developed using fossil dental enamel which is rich in U-content (10 - 100 ppm). Both methods were applied to Arago Cave (Tautavel, France): - with an ionium-age of 120 ka (10%), the upper travertine seems to have been set up during the Riss-deglaciation period. - the high (∼ 50%) Th/U-content samples of the intermediate travertine are un-datable. - the ESR-age of EQUUS mosbachensis enamel is 400 ka (10%) for the G-soil of Arago. XXI H. erectus, and 600 ka (10%) for the Q-soil above (- 1 m) of the lower travertine of which Io-age is older than 350 ka. (author)
Application of FFT methods to wind wave data series by adding zeros
Digital Repository Service at National Institute of Oceanography (India)
Varkey, M.J.
A method to add zeros (in FFT methods) to a short data sample (< 2m) to make the sample size equal to 2m is illustrated in this paper. It is found that the spectrum could be computed reliably without any undesirable side lobe effects and variance...
Two-Dimensional Fourier Cosine Series Expansion Method for Pricing Financial Options
Ruijter, M.J.; Oosterlee, C.W.
2012-01-01
The COS method for pricing European and Bermudan options with one underlying asset was developed in [F. Fang and C. W. Oosterlee, SIAM J. Sci. Comput., 31 (2008), pp. 826--848] and [F. Fang and C. W. Oosterlee, Numer. Math., 114 (2009), pp. 27--62]. In this paper, we extend the method to higher
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Natale Ruby
2013-01-01
Full Text Available Abstract Background Many unhealthy dietary and physical activity habits that foster the development of obesity are established by the age of five. Presently, approximately 70 percent of children in the United States are currently enrolled in early childcare facilities, making this an ideal setting to implement and evaluate childhood obesity prevention efforts. We describe here the methods for conducting an obesity prevention randomized trial in the child care setting. Methods/design A randomized, controlled obesity prevention trial is currently being conducted over a three year period (2010-present. The sample consists of 28 low-income, ethnically diverse child care centers with 1105 children (sample is 60% Hispanic, 15% Haitian, 12% Black, 2% non-Hispanic White and 71% of caregivers were born outside of the US. The purpose is to test the efficacy of a parent and teacher role-modeling intervention on children’s nutrition and physical activity behaviors. . The Healthy Caregivers-Healthy Children (HC2 intervention arm schools received a combination of (1 implementing a daily curricula for teachers/parents (the nutritional gatekeepers; (2 implementing a daily curricula for children; (3 technical assistance with meal and snack menu modifications such as including more fresh and less canned produce; and (4 creation of a center policy for dietary requirements for meals and snacks, physical activity and screen time. Control arm schools received an attention control safety curriculum. Major outcome measures include pre-post changes in child body mass index percentile and z score, fruit and vegetable and other nutritious food intake, amount of physical activity, and parental nutrition and physical activity knowledge, attitudes, and beliefs, defined by intentions and behaviors. All measures were administered at the beginning and end of the school year for year one and year two of the study for a total of 4 longitudinal time points for assessment
Analyzing Planck and low redshift data sets with advanced statistical methods
Eifler, Tim
The recent ESA/NASA Planck mission has provided a key data set to constrain cosmology that is most sensitive to physics of the early Universe, such as inflation and primordial NonGaussianity (Planck 2015 results XIII). In combination with cosmological probes of the LargeScale Structure (LSS), the Planck data set is a powerful source of information to investigate late time phenomena (Planck 2015 results XIV), e.g. the accelerated expansion of the Universe, the impact of baryonic physics on the growth of structure, and the alignment of galaxies in their dark matter halos. It is the main objective of this proposal to re-analyze the archival Planck data, 1) with different, more recently developed statistical methods for cosmological parameter inference, and 2) to combine Planck and ground-based observations in an innovative way. We will make the corresponding analysis framework publicly available and believe that it will set a new standard for future CMB-LSS analyses. Advanced statistical methods, such as the Gibbs sampler (Jewell et al 2004, Wandelt et al 2004) have been critical in the analysis of Planck data. More recently, Approximate Bayesian Computation (ABC, see Weyant et al 2012, Akeret et al 2015, Ishida et al 2015, for cosmological applications) has matured to an interesting tool in cosmological likelihood analyses. It circumvents several assumptions that enter the standard Planck (and most LSS) likelihood analyses, most importantly, the assumption that the functional form of the likelihood of the CMB observables is a multivariate Gaussian. Beyond applying new statistical methods to Planck data in order to cross-check and validate existing constraints, we plan to combine Planck and DES data in a new and innovative way and run multi-probe likelihood analyses of CMB and LSS observables. The complexity of multiprobe likelihood analyses scale (non-linearly) with the level of correlations amongst the individual probes that are included. For the multi
Logarithmic Similarity Measure between Interval-Valued Fuzzy Sets and Its Fault Diagnosis Method
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Zhikang Lu
2018-02-01
Full Text Available Fault diagnosis is an important task for the normal operation and maintenance of equipment. In many real situations, the diagnosis data cannot provide deterministic values and are usually imprecise or uncertain. Thus, interval-valued fuzzy sets (IVFSs are very suitable for expressing imprecise or uncertain fault information in real problems. However, existing literature scarcely deals with fault diagnosis problems, such as gasoline engines and steam turbines with IVFSs. However, the similarity measure is one of the important tools in fault diagnoses. Therefore, this paper proposes a new similarity measure of IVFSs based on logarithmic function and its fault diagnosis method for the first time. By the logarithmic similarity measure between the fault knowledge and some diagnosis-testing samples with interval-valued fuzzy information and its relation indices, we can determine the fault type and ranking order of faults corresponding to the relation indices. Then, the misfire fault diagnosis of the gasoline engine and the vibrational fault diagnosis of a turbine are presented to demonstrate the simplicity and effectiveness of the proposed diagnosis method. The fault diagnosis results of gasoline engine and steam turbine show that the proposed diagnosis method not only gives the main fault types of the gasoline engine and steam turbine but also provides useful information for multi-fault analyses and predicting future fault trends. Hence, the logarithmic similarity measure and its fault diagnosis method are main contributions in this study and they provide a useful new way for the fault diagnosis with interval-valued fuzzy information.
American Society for Testing and Materials. Philadelphia
2007-01-01
1.1 This test method covers a procedure for constant immersion exfoliation corrosion (EXCO) testing of high-strength 2XXX and 7XXX series aluminum alloys. Note 1—This test method was originally developed for research and development purposes; however, it is referenced, in specific material specifications, as applicable for evaluating production material (refer to Section 14 on Precision and Bias). 1.2 This test method applies to all wrought products such as sheet, plate, extrusions, and forgings produced from conventional ingot metallurgy process. 1.3 This test method can be used with any form of specimen or part that can be immersed in the test solution. 1.4 This standard does not purport to address all of the safety concerns, if any, associated with its use. It is the responsibility of the user of this standard to establish appropriate safety and health practices and determine the applicability of regulatory limitations prior to use.
The development of a patient-specific method for physiotherapy goal setting: a user-centered design.
Stevens, Anita; Köke, Albère; van der Weijden, Trudy; Beurskens, Anna
2018-08-01
To deliver client-centered care, physiotherapists need to identify the patients' individual treatment goals. However, practical tools for involving patients in goal setting are lacking. The purpose of this study was to improve the frequently used Patient-Specific Complaints instrument in Dutch physiotherapy, and to develop it into a feasible method to improve physiotherapy goal setting. An iterative user-centered design was conducted in co-creation with the physiotherapists and patients, in three phases. Their needs and preferences were identified by means of group meetings and questionnaires. The new method was tested in several field tests in physiotherapy practices. Four main objectives for improvement were formulated: clear instructions for the administration procedure, targeted use across the physiotherapy process, client-activating communication skills, and a client-centered attitude of the physiotherapist. A theoretical goal-setting framework and elements of shared decision making were integrated into the new-called, Patient-Specific Goal-setting method, together with a practical training course. The user-centered approach resulted in a goal-setting method that is fully integrated in the physiotherapy process. The new goal-setting method contributes to a more structured approach to goal setting and enables patient participation and goal-oriented physiotherapy. Before large-scale implementation, its feasibility in physiotherapy practice needs to be investigated. Implications for rehabilitation Involving patients and physiotherapists in the development and testing of a goal-setting method, increases the likelihood of its feasibility in practice. The integration of a goal-setting method into the physiotherapy process offers the opportunity to focus more fully on the patient's goals. Patients should be informed about the aim of every step of the goal-setting process in order to increase their awareness and involvement. Training physiotherapists to use a patient
Accuracy assessment of the ERP prediction method based on analysis of 100-year ERP series
Malkin, Z.; Tissen, V. M.
2012-12-01
A new method has been developed at the Siberian Research Institute of Metrology (SNIIM) for highly accurate prediction of UT1 and Pole motion (PM). In this study, a detailed comparison was made of real-time UT1 predictions made in 2006-2011 and PMpredictions made in 2009-2011making use of the SNIIM method with simultaneous predictions computed at the International Earth Rotation and Reference Systems Service (IERS), USNO. Obtained results have shown that proposed method provides better accuracy at different prediction lengths.
Max-Moerbeck, W.; Richards, J. L.; Hovatta, T.; Pavlidou, V.; Pearson, T. J.; Readhead, A. C. S.
2014-11-01
We present a practical implementation of a Monte Carlo method to estimate the significance of cross-correlations in unevenly sampled time series of data, whose statistical properties are modelled with a simple power-law power spectral density. This implementation builds on published methods; we introduce a number of improvements in the normalization of the cross-correlation function estimate and a bootstrap method for estimating the significance of the cross-correlations. A closely related matter is the estimation of a model for the light curves, which is critical for the significance estimates. We present a graphical and quantitative demonstration that uses simulations to show how common it is to get high cross-correlations for unrelated light curves with steep power spectral densities. This demonstration highlights the dangers of interpreting them as signs of a physical connection. We show that by using interpolation and the Hanning sampling window function we are able to reduce the effects of red-noise leakage and to recover steep simple power-law power spectral densities. We also introduce the use of a Neyman construction for the estimation of the errors in the power-law index of the power spectral density. This method provides a consistent way to estimate the significance of cross-correlations in unevenly sampled time series of data.
GÜRSEL, Onur; ERKEK, Mehmet
2012-01-01
Centrifugal fans are used in most of the manufacturing processes for ventilating and/or air conditioning the manufacturing areas. Because of relatively limited documentation on design of these fans, new designs are developed by experimental method. This method does not only take a lot of time but also increases the costs considerably. Nowadays, most of the companies create 3D models and then conduct analyses by the CFD (computational fluid dynamics) programs and perform some optimizations bef...
Governance of professional nursing practice in a hospital setting: a mixed methods study
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José Luís Guedes dos Santos
2015-12-01
Full Text Available Objective: to elaborate an interpretative model for the governance of professional nursing practice in a hospital setting. Method: a mixed methods study with concurrent triangulation strategy, using data from a cross-sectional study with 106 nurses and a Grounded Theory study with 63 participants. The quantitative data were collected through the Brazilian Nursing Work Index - Revised and underwent descriptive statistical analysis. Qualitative data were obtained from interviews and analyzed through initial, selective and focused coding. Results: based on the results obtained with the Brazilian Nursing Work Index - Revised, it is possible to state that nurses perceived that they had autonomy, control over the environment, good relationships with physicians and organizational support for nursing governance. The governance of the professional nursing practice is based on the management of nursing care and services carried out by the nurses. To perform these tasks, nurses aim to get around the constraints of the organizational support and develop management knowledge and skills. Conclusion: it is important to reorganize the structures and processes of nursing governance, especially the support provided by the organization for the management practices of nurses.
Modeling of Two-Phase Flow in Rough-Walled Fracture Using Level Set Method
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Yunfeng Dai
2017-01-01
Full Text Available To describe accurately the flow characteristic of fracture scale displacements of immiscible fluids, an incompressible two-phase (crude oil and water flow model incorporating interfacial forces and nonzero contact angles is developed. The roughness of the two-dimensional synthetic rough-walled fractures is controlled with different fractal dimension parameters. Described by the Navier–Stokes equations, the moving interface between crude oil and water is tracked using level set method. The method accounts for differences in densities and viscosities of crude oil and water and includes the effect of interfacial force. The wettability of the rough fracture wall is taken into account by defining the contact angle and slip length. The curve of the invasion pressure-water volume fraction is generated by modeling two-phase flow during a sudden drainage. The volume fraction of water restricted in the rough-walled fracture is calculated by integrating the water volume and dividing by the total cavity volume of the fracture while the two-phase flow is quasistatic. The effect of invasion pressure of crude oil, roughness of fracture wall, and wettability of the wall on two-phase flow in rough-walled fracture is evaluated.
Measurement of thermally ablated lesions in sonoelastographic images using level set methods
Castaneda, Benjamin; Tamez-Pena, Jose Gerardo; Zhang, Man; Hoyt, Kenneth; Bylund, Kevin; Christensen, Jared; Saad, Wael; Strang, John; Rubens, Deborah J.; Parker, Kevin J.
2008-03-01
The capability of sonoelastography to detect lesions based on elasticity contrast can be applied to monitor the creation of thermally ablated lesion. Currently, segmentation of lesions depicted in sonoelastographic images is performed manually which can be a time consuming process and prone to significant intra- and inter-observer variability. This work presents a semi-automated segmentation algorithm for sonoelastographic data. The user starts by planting a seed in the perceived center of the lesion. Fast marching methods use this information to create an initial estimate of the lesion. Subsequently, level set methods refine its final shape by attaching the segmented contour to edges in the image while maintaining smoothness. The algorithm is applied to in vivo sonoelastographic images from twenty five thermal ablated lesions created in porcine livers. The estimated area is compared to results from manual segmentation and gross pathology images. Results show that the algorithm outperforms manual segmentation in accuracy, inter- and intra-observer variability. The processing time per image is significantly reduced.
Elliptical tiling method to generate a 2-dimensional set of templates for gravitational wave search
International Nuclear Information System (INIS)
Arnaud, Nicolas; Barsuglia, Matteo; Bizouard, Marie-Anne; Brisson, Violette; Cavalier, Fabien; Davier, Michel; Hello, Patrice; Kreckelbergh, Stephane; Porter, Edward K.
2003-01-01
Searching for a signal depending on unknown parameters in a noisy background with matched filtering techniques always requires an analysis of the data with several templates in parallel in order to ensure a proper match between the filter and the real waveform. The key feature of such an implementation is the design of the filter bank which must be small to limit the computational cost while keeping the detection efficiency as high as possible. This paper presents a geometrical method that allows one to cover the corresponding physical parameter space by a set of ellipses, each of them being associated with a given template. After the description of the main characteristics of the algorithm, the method is applied in the field of gravitational wave (GW) data analysis, for the search of damped sine signals. Such waveforms are expected to be produced during the deexcitation phase of black holes - the so-called 'ringdown' signals - and are also encountered in some numerically computed supernova signals. First, the number of templates N computed by the method is similar to its analytical estimation, despite the overlaps between neighbor templates and the border effects. Moreover, N is small enough to test for the first time the performances of the set of templates for different choices of the minimal match MM, the parameter used to define the maximal allowed loss of signal-to-noise ratio (SNR) due to the mismatch between real signals and templates. The main result of this analysis is that the fraction of SNR recovered is on average much higher than MM, which dramatically decreases the mean percentage of false dismissals. Indeed, it goes well below its estimated value of 1-MM 3 used as input of the algorithm. Thus, as this feature should be common to any tiling algorithm, it seems possible to reduce the constraint on the value of MM - and indeed the number of templates and the computing power - without losing as many events as expected on average. This should be of great
On the modeling of bubble evolution and transport using coupled level-set/CFD method
International Nuclear Information System (INIS)
Bartlomiej Wierzbicki; Steven P Antal; Michael Z Podowski
2005-01-01
Full text of publication follows: The ability to predict the shape of the gas/liquid/solid interfaces is important for various multiphase flow and heat transfer applications. Specific issues of interest to nuclear reactor thermal-hydraulics, include the evolution of the shape of bubbles attached to solid surfaces during nucleation, bubble surface interactions in complex geometries, etc. Additional problems, making the overall task even more complicated, are associated with the effect of material properties that may be significantly altered by the addition of minute amounts of impurities, such as surfactants or nano-particles. The present paper is concerned with the development of an innovative approach to model time-dependent shape of gas/liquid interfaces in the presence of solid walls. The proposed approach combines a modified level-set method with an advanced CFD code, NPHASE. The coupled numerical solver can be used to simulate the evolution of gas/liquid interfaces in two-phase flows for a variety of geometries and flow conditions, from individual bubbles to free surfaces (stratified flows). The issues discussed in the full paper will include: a description of the novel aspects of the proposed level-set concept based method, an overview of the NPHASE code modeling framework and a description of the coupling method between these two elements of the overall model. A particular attention will be give to the consistency and completeness of model formulation for the interfacial phenomena near the liquid/gas/solid triple line, and to the impact of the proposed numerical approach on the accuracy and consistency of predictions. The accuracy will be measured in terms of both the calculated shape of the interfaces and the gas and liquid velocity fields around the interfaces and in the entire computational domain. The results of model testing and validation will also be shown in the full paper. The situations analyzed will include: bubbles of different sizes and varying
Methods for sampling geographically mobile female traders in an East African market setting
Achiro, Lillian; Kwena, Zachary A.; McFarland, Willi; Neilands, Torsten B.; Cohen, Craig R.; Bukusi, Elizabeth A.; Camlin, Carol S.
2018-01-01
Background The role of migration in the spread of HIV in sub-Saharan Africa is well-documented. Yet migration and HIV research have often focused on HIV risks to male migrants and their partners, or migrants overall, often failing to measure the risks to women via their direct involvement in migration. Inconsistent measures of mobility, gender biases in those measures, and limited data sources for sex-specific population-based estimates of mobility have contributed to a paucity of research on the HIV prevention and care needs of migrant and highly mobile women. This study addresses an urgent need for novel methods for developing probability-based, systematic samples of highly mobile women, focusing on a population of female traders operating out of one of the largest open air markets in East Africa. Our method involves three stages: 1.) identification and mapping of all market stall locations using Global Positioning System (GPS) coordinates; 2.) using female market vendor stall GPS coordinates to build the sampling frame using replicates; and 3.) using maps and GPS data for recruitment of study participants. Results The location of 6,390 vendor stalls were mapped using GPS. Of these, 4,064 stalls occupied by women (63.6%) were used to draw four replicates of 128 stalls each, and a fifth replicate of 15 pre-selected random alternates for a total of 527 stalls assigned to one of five replicates. Staff visited 323 stalls from the first three replicates and from these successfully recruited 306 female vendors into the study for a participation rate of 94.7%. Mobilization strategies and involving traders association representatives in participant recruitment were critical to the study’s success. Conclusion The study’s high participation rate suggests that this geospatial sampling method holds promise for development of probability-based samples in other settings that serve as transport hubs for highly mobile populations. PMID:29324780
Natale, Ruby; Scott, Stephanie Hapeman; Messiah, Sarah E; Schrack, Maria Mesa; Uhlhorn, Susan B; Delamater, Alan
2013-01-28
Many unhealthy dietary and physical activity habits that foster the development of obesity are established by the age of five. Presently, approximately 70 percent of children in the United States are currently enrolled in early childcare facilities, making this an ideal setting to implement and evaluate childhood obesity prevention efforts. We describe here the methods for conducting an obesity prevention randomized trial in the child care setting. A randomized, controlled obesity prevention trial is currently being conducted over a three year period (2010-present). The sample consists of 28 low-income, ethnically diverse child care centers with 1105 children (sample is 60% Hispanic, 15% Haitian, 12% Black, 2% non-Hispanic White and 71% of caregivers were born outside of the US). The purpose is to test the efficacy of a parent and teacher role-modeling intervention on children's nutrition and physical activity behaviors. . The Healthy Caregivers-Healthy Children (HC2) intervention arm schools received a combination of (1) implementing a daily curricula for teachers/parents (the nutritional gatekeepers); (2) implementing a daily curricula for children; (3) technical assistance with meal and snack menu modifications such as including more fresh and less canned produce; and (4) creation of a center policy for dietary requirements for meals and snacks, physical activity and screen time. Control arm schools received an attention control safety curriculum. Major outcome measures include pre-post changes in child body mass index percentile and z score, fruit and vegetable and other nutritious food intake, amount of physical activity, and parental nutrition and physical activity knowledge, attitudes, and beliefs, defined by intentions and behaviors. All measures were administered at the beginning and end of the school year for year one and year two of the study for a total of 4 longitudinal time points for assessment. Although few attempts have been made to prevent obesity
Transition of Care from the Emergency Department to the Outpatient Setting: A Mixed-Methods Analysis
Directory of Open Access Journals (Sweden)
Chad S. Kessler
2018-02-01
Full Text Available Introduction: The goal of this study was to characterize current practices in the transition of care between the emergency department and primary care setting, with an emphasis on the use of the electronic medical record (EMR. Methods: Using literature review and modified Delphi technique, we created and tested a pilot survey to evaluate for face and content validity. The final survey was then administered face-to-face at eight different clinical sites across the country. A total of 52 emergency physicians (EP and 49 primary care physicians (PCP were surveyed and analyzed. We performed quantitative analysis using chi-square test. Two independent coders performed a qualitative analysis, classifying answers by pre-defined themes (inter-rater reliability > 80%. Participants’ answers could cross several pre-defined themes within a given question. Results: EPs were more likely to prefer telephone communication compared with PCPs (30/52 [57.7%] vs. 3/49 [6.1%] P < 0.0001, whereas PCPs were more likely to prefer using the EMR for discharge communication compared with EPs (33/49 [67.4%] vs. 13/52 [25%] p < 0.0001. EPs were more likely to report not needing to communicate with a PCP when a patient had a benign condition (23/52 [44.2%] vs. 2/49 [4.1%] p < 0.0001, but were more likely to communicate if the patient required urgent follow-up prior to discharge from the ED (33/52 [63.5%] vs. 20/49 [40.8%] p = 0.029. When discussing barriers to effective communication, 51/98 (52% stated communication logistics, followed by 49/98 (50% who reported setting/environmental constraints and 32/98 (32% who stated EMR access was a significant barrier. Conclusion: Significant differences exist between EPs and PCPs in the transition of care process. EPs preferred telephone contact synchronous to the encounter whereas PCPs preferred using the EMR asynchronous to the encounter. Providers believe EP-to-PCP contact is important for improving patient care, but report varied
Directory of Open Access Journals (Sweden)
Eulogio Pardo-Igúzquiza
2015-08-01
Full Text Available Many studies have revealed the cyclicity of past ocean/atmosphere dynamics at a wide range of time scales (from decadal to millennial time scales, based on the spectral analysis of time series of climate proxies obtained from deep sea sediment cores. Among the many techniques available for spectral analysis, the maximum entropy method and the Thomson multitaper approach have frequently been used because of their good statistical properties and high resolution with short time series. The novelty of the present study is that we compared the two methods by according to the performance of their statistical tests to assess the statistical significance of their power spectrum estimates. The statistical significance of maximum entropy estimates was assessed by a random permutation test (Pardo-Igúzquiza and Rodríguez-Tovar, 2000, while the statistical significance of the Thomson multitaper method was assessed by an F-test (Thomson, 1982. We compared the results obtained in a case study using simulated data where the spectral content of the time series was known and in a case study with real data. In both cases the results are similar: while the cycles identified as significant by maximum entropy and the permutation test have a clear physical interpretation, the F-test with the Thomson multitaper estimator tends to find as no significant the peaks in the low frequencies and tends to give as significant more spurious peaks in the middle and high frequencies. Nevertheless, the best strategy is to use both techniques and to use the advantages of each of them.
1991-03-21
discussion of spectral factorability and motivations for broadband analysis, the report is subdivided into four main sections. In Section 1.0, we...estimates. The motivation for developing our multi-channel deconvolution method was to gain information about seismic sources, most notably, nuclear...with complex constraints for estimating the rupture history. Such methods (applied mostly to data sets that also include strong rmotion data), were
Şenol, Mehmet; Alquran, Marwan; Kasmaei, Hamed Daei
2018-06-01
In this paper, we present analytic-approximate solution of time-fractional Zakharov-Kuznetsov equation. This model demonstrates the behavior of weakly nonlinear ion acoustic waves in a plasma bearing cold ions and hot isothermal electrons in the presence of a uniform magnetic field. Basic definitions of fractional derivatives are described in the Caputo sense. Perturbation-iteration algorithm (PIA) and residual power series method (RPSM) are applied to solve this equation with success. The convergence analysis is also presented for both methods. Numerical results are given and then they are compared with the exact solutions. Comparison of the results reveal that both methods are competitive, powerful, reliable, simple to use and ready to apply to wide range of fractional partial differential equations.
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Saeed Dinarvand
2012-01-01
Full Text Available The steady three-dimensional flow of condensation or spraying on inclined spinning disk is studied analytically. The governing nonlinear equations and their associated boundary conditions are transformed into the system of nonlinear ordinary differential equations. The series solution of the problem is obtained by utilizing the homotopy perturbation method (HPM. The velocity and temperature profiles are shown and the influence of Prandtl number on the heat transfer and Nusselt number is discussed in detail. The validity of our solutions is verified by the numerical results. Unlike free surface flows on an incline, this through flow is highly affected by the spray rate and the rotation of the disk.
International Nuclear Information System (INIS)
Sakai, Shiro; Arita, Ryotaro; Aoki, Hideo
2006-01-01
We propose a new quantum Monte Carlo method especially intended to couple with the dynamical mean-field theory. The algorithm is not only much more efficient than the conventional Hirsch-Fye algorithm, but is applicable to multiorbital systems having an SU(2)-symmetric Hund's coupling as well
A robust method for generating separate catch time-series for each ...
African Journals Online (AJOL)
Here, species-separated data from an observer programme and scientific surveys are used to model the spatio-temporal overlap of the two species, which are then used to predict the catch by species in each commercial trawl. The study presents a method that compensates for both the escapement and codend retention ...
The Gift Box Open Achilles Tendon Repair Method: A Retrospective Clinical Series.
Labib, Sameh A; Hoffler, C Edward; Shah, Jay N; Rolf, Robert H; Tingan, Alexis
2016-01-01
Previous biomechanical studies have shown that the gift box technique for open Achilles tendon repair is twice as strong as a Krackow repair. The technique incorporates a paramedian skin incision with a midline paratenon incision, and a modification of the Krackow stitch is used to reinforce the repair. The wound is closed in layers such that the paratenon repair is offset from paramedian skin incision, further protecting the repair. The present study retrospectively reviews the clinical results for a series of patients who underwent the gift box technique for treatment of acute Achilles tendon ruptures from March 2002 to April 2007. The patients completed the Foot Function Index and the American Orthopaedic Foot and Ankle Society ankle-hindfoot scale. The tendon width and calf circumference were measured bilaterally and compared using paired t tests with a 5% α level. A total of 44 subjects, mean age 37.5 ± 8.6 years, underwent surgery approximately 10.8 ± 6.5 days after injury. The response rate was 35 (79.54%) patients for the questionnaire and 20 (45.45%) for the examination. The mean follow-up period was 35.7 ± 20.1 months. The complications included one stitch abscess, persistent pain, and keloid formation. One (2.86%) respondent reported significant weakness. Five (14.29%) respondents indicated persistent peri-incisional numbness. The range of motion was full or adequate. The mean American Orthopaedic Foot and Ankle Society ankle-hindfoot scale score was 93.2 ± 6.8) and the mean Foot Function Index score was 7.0 ± 10.5. The calf girth and tendon width differences were statistically significantly between the limbs. The patients reported no repeat ruptures, sural nerve injuries, dehiscence, or infections. We present the outcomes data from patients who had undergone this alternative technique for Achilles tendon repair. The technique is reproducible, with good patient satisfaction and return to activity. The results compared well with the historical
Directory of Open Access Journals (Sweden)
Loktev Aleksey Alekseevich
2015-03-01
geometrical parameters by analyzing a series of images. This is the issue and the subject of this work, which developed the computational algorithms to detect external defects. At the stage of preliminary image processing there is the delineation of characteristic points in the image and the calculation of the optical flow in the area of these points. When determining the defect position, the characteristic points of the image are determined using the detector of Harris-Laplace, which are located in the central part of the image. The characteristic points outside the frame are considered to be background. There is an identification of the changes in characteristic points in the frame in relation to the background by using a pyramidal iterative scheme. In the second stage servo frame focuses on a specific point with the greatest change in relation to the background in the current time. The algorithm for object detection and determination of its parameters includes three procedures: detection procedure start; the procedure of the next image processing; stop procedure for determining the parameters of the object. The method described here can be used to create information-measuring system of monitoring based on the use of photodetectors with high-definition and recognition of defects (color differences and differences in the form compared to the background. Since almost each examination of a building or structure begins with a visual examination and determination of the most probable places of occurrence and presence of the defects, the proposed method can be combined with this stage and it will simplify the process of diagnosing, screening for the development of projects on reconstruction and placement of additional equipment on the existing infrastructure.
Directory of Open Access Journals (Sweden)
Stefan eSchinkel
2012-11-01
Full Text Available Complex networks provide an excellent framework for studying the functionof the human brain activity. Yet estimating functional networks from mea-sured signals is not trivial, especially if the data is non-stationary and noisyas it is often the case with physiological recordings. In this article we proposea method that uses the local rank structure of the data to deﬁne functionallinks in terms of identical rank structures. The method yields temporal se-quences of networks which permits to trace the evolution of the functionalconnectivity during the time course of the observation. We demonstrate thepotentials of this approach with model data as well as with experimentaldata from an electrophysiological study on language processing.
Solution of systems of linear algebraic equations by the method of summation of divergent series
International Nuclear Information System (INIS)
Kirichenko, G.A.; Korovin, Ya.S.; Khisamutdinov, M.V.; Shmojlov, V.I.
2015-01-01
A method for solving systems of linear algebraic equations has been proposed on the basis on the summation of the corresponding continued fractions. The proposed algorithm for solving systems of linear algebraic equations is classified as direct algorithms providing an exact solution in a finite number of operations. Examples of solving systems of linear algebraic equations have been presented and the effectiveness of the algorithm has been estimated [ru
International Nuclear Information System (INIS)
Zedgenidze, G.A.; Narkevich, K.Ya.
1987-01-01
To substantiate the expediency of choosing either vizualization method, a comparative analysis of advantages and disadvantages of roentgen computerized tomography (CT) and ultrasonic investigation (UI) has been performed. Conditions of using CT and UI in developing countries emphasising on organizational and technical and esepecially clinical-diagnostic aspects of this problem have been analysed as well. A manual on clinical indications and correct CT and UI use from the point of view of methodology has been compiled
"Rehabilitation schools for scoliosis" thematic series: describing the methods and results
Rigo, Manuel D; Grivas, Theodoros B
2010-01-01
Abstract The Scoliosis Rehabilitation model begins with the correct diagnosis and evaluation of the patient, to make treatment decisions oriented to the patient. The treatment is based on observation, education, scoliosis specific exercises, and bracing. The state of research in the field of conservative treatment is insufficient. There is some evidence supporting scoliosis specific exercises as a part of the rehabilitation treatment, however, the evidence is poor and the different methods ar...
Directory of Open Access Journals (Sweden)
Shu-Huai Zhang
2017-05-01
Full Text Available Considering the effects of isolation and high efficiency, a series-resonant DC-DC converter (L-L-C type, with two inductors and a capacitor has been introduced into a residential photovoltaic (PV generation and storage system in this work, and a voltage gain curve upwarp drifting problem was found. In this paper, the reason of upwarp drifting in the voltage gain curve is given, and a new changing topological control method to solve the voltage regulation problem under light load conditions is proposed. Firstly, the ideal and actual first harmonic approximation (FHA models are given, and this drifting problem is ascribed to the multiple peaks of higher-order resonance between resonant tank and parasitic capacitors. Then the paper presents the pulse-frequency-modulation (PFM driver signals control method to translate the full-bridge LLC into a half-bridge LLC converter, and with this method the voltage gain could easily be reduced by half. Based on this method, the whole voltage and resonant current sharing control methods in on-line and off-line mode are proposed. The parameters design and optimization methods are also discussed in detail. Finally, a residential PV system platform based on the proposed parallel 7-kW full-bridge LLC converter is built to verify the proposed control method and theoretical analysis.
Zeman, Antonín; Šmíd, Michal; Havelcová, Martina; Coufalová, Lucie; Kučková, Štěpánka; Velčovská, Martina; Hynek, Radovan
2013-11-01
Degenerative aortic stenosis has become a common and dangerous disease in recent decades. This disease leads to the mineralization of aortic valves, their gradual thickening and loss of functionality. We studied the detailed assessment of the proportion and composition of inorganic and organic components in the ossified aortic valve, using a set of analytical methods applied in science: polarized light microscopy, scanning electron microscopy, X-ray fluorescence, X-ray diffraction, gas chromatography/mass spectrometry and liquid chromatography-tandem mass spectrometry. The sample valves showed the occurrence of phosphorus and calcium in the form of phosphate and calcium carbonate, hydroxyapatite, fluorapatite and hydroxy-fluorapatite, with varying content of inorganic components from 65 to 90 wt%, and with phased development of degenerative disability. The outer layers of the plaque contained an organic component with peptide bonds, fatty acids, proteins and cholesterol. The results show a correlation between the formation of fluorapatite in aortic valves and in other parts of the human bodies, associated with the formation of bones.
Governance of professional nursing practice in a hospital setting: a mixed methods study.
dos Santos, José Luís Guedes; Erdmann, Alacoque Lorenzini
2015-01-01
To elaborate an interpretative model for the governance of professional nursing practice in a hospital setting. A mixed methods study with concurrent triangulation strategy, using data from a cross-sectional study with 106 nurses and a Grounded Theory study with 63 participants. The quantitative data were collected through the Brazilian Nursing Work Index - Revised and underwent descriptive statistical analysis. Qualitative data were obtained from interviews and analyzed through initial, selective and focused coding. Based on the results obtained with the Brazilian Nursing Work Index - Revised, it is possible to state that nurses perceived that they had autonomy, control over the environment, good relationships with physicians and organizational support for nursing governance. The governance of the professional nursing practice is based on the management of nursing care and services carried out by the nurses. To perform these tasks, nurses aim to get around the constraints of the organizational support and develop management knowledge and skills. It is important to reorganize the structures and processes of nursing governance, especially the support provided by the organization for the management practices of nurses.
Fang, Xin; Li, Runkui; Kan, Haidong; Bottai, Matteo; Fang, Fang; Cao, Yang
2016-08-16
To demonstrate an application of Bayesian model averaging (BMA) with generalised additive mixed models (GAMM) and provide a novel modelling technique to assess the association between inhalable coarse particles (PM10) and respiratory mortality in time-series studies. A time-series study using regional death registry between 2009 and 2010. 8 districts in a large metropolitan area in Northern China. 9559 permanent residents of the 8 districts who died of respiratory diseases between 2009 and 2010. Per cent increase in daily respiratory mortality rate (MR) per interquartile range (IQR) increase of PM10 concentration and corresponding 95% confidence interval (CI) in single-pollutant and multipollutant (including NOx, CO) models. The Bayesian model averaged GAMM (GAMM+BMA) and the optimal GAMM of PM10, multipollutants and principal components (PCs) of multipollutants showed comparable results for the effect of PM10 on daily respiratory MR, that is, one IQR increase in PM10 concentration corresponded to 1.38% vs 1.39%, 1.81% vs 1.83% and 0.87% vs 0.88% increase, respectively, in daily respiratory MR. However, GAMM+BMA gave slightly but noticeable wider CIs for the single-pollutant model (-1.09 to 4.28 vs -1.08 to 3.93) and the PCs-based model (-2.23 to 4.07 vs -2.03 vs 3.88). The CIs of the multiple-pollutant model from two methods are similar, that is, -1.12 to 4.85 versus -1.11 versus 4.83. The BMA method may represent a useful tool for modelling uncertainty in time-series studies when evaluating the effect of air pollution on fatal health outcomes. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/
Gensler, S.; Leeflang, P.S.H.; Skiera, B.
The literature discusses several methods to control for self-selection effects but provides little guidance on which method to use in a setting with a limited number of variables. The authors theoretically compare and empirically assess the performance of different matching methods and instrumental
Different methods and settings for glucose monitoring for gestational diabetes during pregnancy.
Raman, Puvaneswary; Shepherd, Emily; Dowswell, Therese; Middleton, Philippa; Crowther, Caroline A
2017-10-29
Incidence of gestational diabetes mellitus (GDM) is increasing worldwide. Blood glucose monitoring plays a crucial part in maintaining glycaemic control in women with GDM and is generally recommended by healthcare professionals. There are several different methods for monitoring blood glucose which can be carried out in different settings (e.g. at home versus in hospital). The objective of this review is to compare the effects of different methods and settings for glucose monitoring for women with GDM on maternal and fetal, neonatal, child and adult outcomes, and use and costs of health care. We searched the Cochrane Pregnancy and Childbirth Group Trials Register (30 September 2016) and reference lists of retrieved studies. Randomised controlled trials (RCTs) or quasi-randomised controlled trials (qRCTs) comparing different methods (such as timings and frequencies) or settings, or both, for blood glucose monitoring for women with GDM. Two authors independently assessed study eligibility, risk of bias, and extracted data. Data were checked for accuracy.We assessed the quality of the evidence for the main comparisons using GRADE, for:- primary outcomes for mothers: that is, hypertensive disorders of pregnancy; caesarean section; type 2 diabetes; and- primary outcomes for children: that is, large-for-gestational age; perinatal mortality; death or serious morbidity composite; childhood/adulthood neurosensory disability;- secondary outcomes for mothers: that is, induction of labour; perineal trauma; postnatal depression; postnatal weight retention or return to pre-pregnancy weight; and- secondary outcomes for children: that is, neonatal hypoglycaemia; childhood/adulthood adiposity; childhood/adulthood type 2 diabetes. We included 11 RCTs (10 RCTs; one qRCT) that randomised 1272 women with GDM in upper-middle or high-income countries; we considered these to be at a moderate to high risk of bias. We assessed the RCTs under five comparisons. For outcomes assessed using
Closed Tibial shaft fractures treated with the Ilizarov method: A ten year case series.
May, Jonathan David; Paavana, Thumri; McGregor-Riley, Jonathan; Royston, Simon
2017-07-01
To review the outcomes of patients treated with the Ilizarov method for an isolated, closed, simple diaphyseal, Tibial fracture at our institution over the last decade. The Ilizarov frame database was used to identify 76 skeletally mature patients who sustained an isolated, closed, extra-articular, simple, diaphyseal Tibial fracture; the injury also known as a "nail-able Tibial fracture." The average age of the patient was 38 (17-70). All 76 patients progressed to union. The average time until union was 148 (55-398) days. The coronal and sagittal alignment was 3° (0-17°) and 4° (0-14°) respectively. No patient suffered from compartment syndrome. No patient developed septic arthritis. No patient had documented anterior knee pain or secondary knee specialist input post frame removal. On average, there were 9(4-29) follow up appointments and 10(5-26) radiographs post frame application. There is a 59% chance of a patient having a difficulty post frame application. The malunion rate was 5%. Persisting pinsite infection post frame removal occurred in 5 patients (6.5%). Drilling of the pinsite sequestrum resolved the infection in four of these patients, giving a deep infection rate of 1.3%. The Ilizarov method has a role to play in the treatment of simple closed Tibial shaft fractures in patients who need to kneel. Patient education is a priority however; the patient must be made aware of the difficulty rate associated with the Ilizarov method when compared to the complication profile of alternative treatments. Crown Copyright © 2017. Published by Elsevier Ltd. All rights reserved.
International Nuclear Information System (INIS)
1975-12-01
A tentative reference method for the measurement of tritium in potable and nonpotable environmental water is described. Water samples are treated with sodium hydroxide and potassium permanganate and then a water fraction is separated from interferences by distillation. Two distillation procedures are described, a simple aqueous distillation for samples from potable water sources, and an aqueous-azeotropic-benzene distillation for nonpotable water sources. Alliquots of a designated distillate fraction are measured for tritium activity by liquid scintillation detection. Distillation recovery and counting efficiency factors are determined with tritium standards. Results are reported in picocuries per milliliter
Measuring Group Synchrony: A Cluster-Phase Method for Analyzing Multivariate Movement Time-Series
Directory of Open Access Journals (Sweden)
Michael eRichardson
2012-10-01
Full Text Available A new method for assessing group synchrony is introduced as being potentially useful for objectively determining degree of group cohesiveness or entitativity. The cluster-phase method of Frank and Richardson (2010 was used to analyze movement data from the rocking chair movements of six-member groups who rocked their chairs while seated in a circle facing the center. In some trials group members had no information about others’ movements (their eyes were shut or they had their eyes open and gazed at a marker in the center of the group. As predicted, the group level synchrony measure was able to distinguish between situations where synchrony would have been possible and situations where it would be impossible. Moreover, other aspects of the analysis illustrated how the cluster phase measures can be used to determine the type of patterning of group synchrony, and, when integrated with multi-level modeling, can be used to examine individual-level differences in synchrony and dyadic level synchrony as well.
International Nuclear Information System (INIS)
Liu Yongkuo; Xia Hong; Xie Chunli; Chen Zhihui; Chen Hongxia
2007-01-01
Rough set theory and fuzzy neural network are combined, to take full advantages of the two of them. Based on the reduction technology to knowledge of Rough set method, and by drawing the simple rule from a large number of initial data, the fuzzy neural network was set up, which was with better topological structure, improved study speed, accurate judgment, strong fault-tolerant ability, and more practical. In order to test the validity of the method, the inverted U-tubes break accident of Steam Generator and etc are used as examples, and many simulation experiments are performed. The test result shows that it is feasible to incorporate the fault intelligence diagnosis method based on rough set and fuzzy neural network in the nuclear power plant equipment, and the method is simple and convenience, with small calculation amount and reliable result. (authors)
International Nuclear Information System (INIS)
Huskey, D.R.
1991-01-01
The arrival of Generic Letter 89-10 came as no surprise to many in the industry. The surprise was the apparent focus of the letter in light of the past history and experiences of the industry. Indeed, even the Attachment 1 list of '33' deficiencies reflects the true picture more accurately than the letter itself. From reviewing the 'GL-33', one can see that the vast majority of problems are maintenance or training related, or some combination of both. Hence, the bulk of solutions to these problems should also be focused on maintenance and training of maintenance and operations personnel. The one or two problems associated with 'stem thrust' or torque, however, are what the apparent bulk of the efforts to respond to the generic letter will ultimately entail. The reasons for this focus by the NRC seems to stem from some limited blow-down tests, which are still under review and are not necessarily representative of the majority of valves in the industry; coupled with repeated claims by certain diagnostic vendors as to the extent of the stem thrust problem based on their test results at the time. Hindsight now reflects that the problems were largely in methodology and interpretations errors of the data as opposed to real problems with the motor operated valves (MOVs) themselves. As a result however, the letter was issued, and many utilities have been put in a rather awkward position at the timing. First generation stem thrust measuring technology has proven to be full of pitfalls and methodology problems and is expensive on top of it all. State-of-the-art equipment is still undergoing growing pains. The purpose of this paper is to describe briefly a technique in use at a number of stations to set and maintain torque switch set points, i.e. use of a torque wrench combined with an ohmmeter to determine torque switch trip point. At least one station is utilizing the method to trend the spring pack relaxation phenomenon which Limitorque has been investigating
Passive Rn dose meters - measuring methods appropriate for large measurement series
International Nuclear Information System (INIS)
Urban, M.; Kiefer, H.
1985-01-01
Passive integrating measuring methods can be classified in several groups by their functioning principle, e.g. spray chambers or open chambers with nuclear trace detectors or TL detectors, open detectors, activated carbon dose meters with or without TL detectors. According to the functioning principle, only radon or radon and fission products can be detected. The lecture gives a survey of the present state of development of passive Rn dose meters. By the example of the Ra dose meter developed at Karlsruhe which was used in inquiry measurements carried out in Germany, Switzerland, the Netherlands, Belgium and Austria, etching technology, estimation of measuring uncertainties, reproducibility and fading behaviour shall be discussed. (orig./HP) [de
Evaluation of a Consistent LES/PDF Method Using a Series of Experimental Spray Flames
Heye, Colin; Raman, Venkat
2012-11-01
A consistent method for the evolution of the joint-scalar probability density function (PDF) transport equation is proposed for application to large eddy simulation (LES) of turbulent reacting flows containing evaporating spray droplets. PDF transport equations provide the benefit of including the chemical source term in closed form, however, additional terms describing LES subfilter mixing must be modeled. The recent availability of detailed experimental measurements provide model validation data for a wide range of evaporation rates and combustion regimes, as is well-known to occur in spray flames. In this work, the experimental data will used to investigate the impact of droplet mass loading and evaporation rates on the subfilter scalar PDF shape in comparison with conventional flamelet models. In addition, existing model term closures in the PDF transport equations are evaluated with a focus on their validity in the presence of regime changes.
A comparative study of time series modeling methods for reactor noise analysis
International Nuclear Information System (INIS)
Kitamura, Masaharu; Shigeno, Kei; Sugiyama, Kazusuke
1978-01-01
Two modeling algorithms were developed to study at-power reactor noise as a multi-input, multi-output process. A class of linear, discrete time description named autoregressive-moving average model was used as a compact mathematical expression of the objective process. One of the model estimation (modeling) algorithms is based on the theory of Kalman filtering, and the other on a conjugate gradient method. By introducing some modifications in the formulation of the problem, realization of the practically usable algorithms was made feasible. Through the testing with several simulation models, reliability and effectiveness of these algorithms were confirmed. By applying these algorithms to experimental data obtained from a nuclear power plant, interesting knowledge about the at-power reactor noise was found out. (author)
International Nuclear Information System (INIS)
Lafuma, J.; Nenot, J.C.; Morin, M.
1968-01-01
We followed the biological fate of a complex formed on one side with either a rare earth (cerium-144) or a transuranium element (plutonium-239), and on the other side with a chelating agent of the polyamino acid series (EDTA, BAETA, DTPA, TTHA). This method allowed to study: 1 - the in vivo stability of the various complexes and to compare them; 2 - the stability of the complexes as a function of the isotope - chelating agent weight relationships; 3 - the metabolism of the chelating agents resulting in stable complexes, i. e. DTPA and TTHA mainly. This simple method brought out the higher efficiency, of DTPA in chelating rare earths and plutonium and for therapeutic purposes. (authors) [fr
Directory of Open Access Journals (Sweden)
Pelin Yüksel
2015-01-01
Full Text Available The main purposes of phenomenological research are to seek reality from individuals’ narratives of their experiences and feelings, and to produce in-depth descriptions of the phenomenon. Phenomenological research studies in educational settings generally embody lived experience, perception, and feelings of participants about a phenomenon. This study aims to provide a general framework for researchers who are interested in phenomenological studies especially in educational setting. Additionally, the study provides a guide for researchers on how to conduct a phenomenological research and how to collect and analyze phenomenal data. The first part of the paper explains the underpinnings of the research methodology consisting of methodological framework and key phenomenological concepts. The second part provides guidance for a phenomenological research in education settings, focusing particularly on phenomenological data collection procedure and phenomenological data analysis methods.Keywords: Phenomenology, phenomenological inquiry, phenomenological data analysis Eğitim Ortamlarında Fenomenal Çalışmaları Yürütmek İçin Teorik Çerçeveler, Yöntemler ve ProsedürlerÖzFenomenolojik araştırmaların temel amacı, bireyin deneyimlerinden ve duygularından yola çıkarak belli bir fenomenan üzerinde yaptığı anlatılarında gerçeği aramak ve bu fenomenana yönelik derinlemesine açıklamalar üretmektir. Eğitim ortamlarında fenomenolojik araştırmalar genellikle araştırmaya katılanların belli bir fenomenan hakkında yaşantıları, deneyimleri, algıları ve duyguları somutlaştırmak için kullanılır. Bu çalışma, özellikle eğitim ortamlarında fenomenolojik çalışmalarla ilgilenen araştırmacılar için genel bir çerçeve sunmayı amaçlamaktadır. Ayrıca, çalışmada fenomenolojik araştırmalar için veri toplamak ve bu fenomenal verileri analiz yapmak için araştırmacılara yön gösterici bir k
Che, Chengjian; Rocha, Roberto A.
2006-01-01
In order to compare order sets discovered using a data mining algorithm with existing order sets, we developed an order matching tool based on Oracle Text. The tool includes both automated searching and manual review processes. The comparison between the automated process and the manual review process indicates that the sensitivity of the automated matching is 81% and the specificity is 84%.
van der Burg, Eeke; de Leeuw, Jan; Verdegaal, Renée
1988-01-01
Homogeneity analysis, or multiple correspondence analysis, is usually applied tok separate variables. In this paper we apply it to sets of variables by using sums within sets. The resulting technique is called OVERALS. It uses the notion of optimal scaling, with transformations that can be multiple
Dimitrakopoulou, Konstantina; Vrahatis, Aristidis G; Wilk, Esther; Tsakalidis, Athanasios K; Bezerianos, Anastasios
2013-09-01
The increasing flow of short time series microarray experiments for the study of dynamic cellular processes poses the need for efficient clustering tools. These tools must deal with three primary issues: first, to consider the multi-functionality of genes; second, to evaluate the similarity of the relative change of amplitude in the time domain rather than the absolute values; third, to cope with the constraints of conventional clustering algorithms such as the assignment of the appropriate cluster number. To address these, we propose OLYMPUS, a novel unsupervised clustering algorithm that integrates Differential Evolution (DE) method into Fuzzy Short Time Series (FSTS) algorithm with the scope to utilize efficiently the information of population of the first and enhance the performance of the latter. Our hybrid approach provides sets of genes that enable the deciphering of distinct phases in dynamic cellular processes. We proved the efficiency of OLYMPUS on synthetic as well as on experimental data. The discriminative power of OLYMPUS provided clusters, which refined the so far perspective of the dynamics of host response mechanisms to Influenza A (H1N1). Our kinetic model sets a timeline for several pathways and cell populations, implicated to participate in host response; yet no timeline was assigned to them (e.g. cell cycle, homeostasis). Regarding the activity of B cells, our approach revealed that some antibody-related mechanisms remain activated until day 60 post infection. The Matlab codes for implementing OLYMPUS, as well as example datasets, are freely accessible via the Web (http://biosignal.med.upatras.gr/wordpress/biosignal/). Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.
Comparative study of four time series methods in forecasting typhoid fever incidence in China.
Directory of Open Access Journals (Sweden)
Xingyu Zhang
Full Text Available Accurate incidence forecasting of infectious disease is critical for early prevention and for better government strategic planning. In this paper, we present a comprehensive study of different forecasting methods based on the monthly incidence of typhoid fever. The seasonal autoregressive integrated moving average (SARIMA model and three different models inspired by neural networks, namely, back propagation neural networks (BPNN, radial basis function neural networks (RBFNN, and Elman recurrent neural networks (ERNN were compared. The differences as well as the advantages and disadvantages, among the SARIMA model and the neural networks were summarized and discussed. The data obtained for 2005 to 2009 and for 2010 from the Chinese Center for Disease Control and Prevention were used as modeling and forecasting samples, respectively. The performances were evaluated based on three metrics: mean absolute error (MAE, mean absolute percentage error (MAPE, and mean square error (MSE. The results showed that RBFNN obtained the smallest MAE, MAPE and MSE in both the modeling and forecasting processes. The performances of the four models ranked in descending order were: RBFNN, ERNN, BPNN and the SARIMA model.
Comparative study of four time series methods in forecasting typhoid fever incidence in China.
Zhang, Xingyu; Liu, Yuanyuan; Yang, Min; Zhang, Tao; Young, Alistair A; Li, Xiaosong
2013-01-01
Accurate incidence forecasting of infectious disease is critical for early prevention and for better government strategic planning. In this paper, we present a comprehensive study of different forecasting methods based on the monthly incidence of typhoid fever. The seasonal autoregressive integrated moving average (SARIMA) model and three different models inspired by neural networks, namely, back propagation neural networks (BPNN), radial basis function neural networks (RBFNN), and Elman recurrent neural networks (ERNN) were compared. The differences as well as the advantages and disadvantages, among the SARIMA model and the neural networks were summarized and discussed. The data obtained for 2005 to 2009 and for 2010 from the Chinese Center for Disease Control and Prevention were used as modeling and forecasting samples, respectively. The performances were evaluated based on three metrics: mean absolute error (MAE), mean absolute percentage error (MAPE), and mean square error (MSE). The results showed that RBFNN obtained the smallest MAE, MAPE and MSE in both the modeling and forecasting processes. The performances of the four models ranked in descending order were: RBFNN, ERNN, BPNN and the SARIMA model.
On tight multiparty Bell inequalities for many settings
Zukowski, Marek
2006-01-01
A derivation method is given which leads to a series of tight Bell inequalities for experiments involving N parties, with binary observables, and three possible local settings. The approach can be generalized to more settings. Ramifications are presented.
International Nuclear Information System (INIS)
Meng, Dan; Yang, Liu; Shen, Fu; Yang, Yi; Ma, Yinghao; Ma, Tao; Zhang, Zhilong; Fu, Cuiming
2016-01-01
Airborne radioactive particulate in many important nuclear facilities (particularly nuclear power plants) will have a strong impact on the relative public dose if they are released into the corresponding environment traversing the stack or vents. The radiation protection researchers have regarded the relative environment assessing and estimation of public doses. And the model of assessing impact of discharges radioactive substance to the environment have been recommended by many international organizations (e.g. IAEA) with the nuclear energy safety and radiation protection. This paper introduced the generic models that were suggested by International Atomic Energy Agency (IAEA), for use in assessing the impact of discharges of radioactive substances to the environment (e.g. IAEA Safety Report Series No.19). The writers of this paper, based on the recommend methods, assessed the discharge limits in some airborne radioactive substances discharging standards. The reasons that IAEA method are introduced are mainly the following considerations: IAEA is one of international organizations with some authorities in the nuclear energy safety and radiation protection; and, more important, the recommend modes are operational methods rather than the methods having little operations such as that have used by some researchers. It is wish that the introduced methods in this paper can be referenced in draft or revise of the standards related to discharges of radioactive substances to the environment
Energy Technology Data Exchange (ETDEWEB)
Meng, Dan; Yang, Liu; Shen, Fu; Yang, Yi; Ma, Yinghao; Ma, Tao; Zhang, Zhilong; Fu, Cuiming [China Institute for Radiation Protection, Taiyuan (China)
2016-12-15
Airborne radioactive particulate in many important nuclear facilities (particularly nuclear power plants) will have a strong impact on the relative public dose if they are released into the corresponding environment traversing the stack or vents. The radiation protection researchers have regarded the relative environment assessing and estimation of public doses. And the model of assessing impact of discharges radioactive substance to the environment have been recommended by many international organizations (e.g. IAEA) with the nuclear energy safety and radiation protection. This paper introduced the generic models that were suggested by International Atomic Energy Agency (IAEA), for use in assessing the impact of discharges of radioactive substances to the environment (e.g. IAEA Safety Report Series No.19). The writers of this paper, based on the recommend methods, assessed the discharge limits in some airborne radioactive substances discharging standards. The reasons that IAEA method are introduced are mainly the following considerations: IAEA is one of international organizations with some authorities in the nuclear energy safety and radiation protection; and, more important, the recommend modes are operational methods rather than the methods having little operations such as that have used by some researchers. It is wish that the introduced methods in this paper can be referenced in draft or revise of the standards related to discharges of radioactive substances to the environment.
DEFF Research Database (Denmark)
Folkvardsen, Dorte Bek; Norman, Anders; Andersen, Åse Bengård
2017-01-01
cases belonging to this outbreak via routine MIRU-VNTR typing. Here, we present a retrospective analysis of the C2/1112-15 dataset, based on whole-genome data from a sparse time-series consisting of five randomly selected isolates from each of the 23 years. Even if these data are derived from only 12...
Teleexercise for Persons With Spinal Cord Injury: A Mixed-Methods Feasibility Case Series.
Lai, Byron; Rimmer, James; Barstow, Beth; Jovanov, Emil; Bickel, C Scott
2016-07-14
Spinal cord injury (SCI) results in significant loss of function below the level of injury, often leading to restricted participation in community exercise programs. To overcome commonly experienced barriers to these programs, innovations in technology hold promise for remotely delivering safe and effective bouts of exercise in the home. To test the feasibility of a remotely delivered home exercise program for individuals with SCI as determined by (1) implementation of the intervention in the home; (2) exploration of the potential intervention effects on aerobic fitness, physical activity behavior, and subjective well-being; and (3) acceptability of the program through participant self-report. Four adults with SCI (mean age 43.5 [SD 5.3] years; 3 males, 1 female; postinjury 25.8 [SD 4.3] years) completed a mixed-methods sequential design with two phases: an 8-week intervention followed by a 3-week nonintervention period. The intervention was a remotely delivered aerobic exercise training program (30-45 minutes, 3 times per week). Instrumentation included an upper body ergometer, tablet, physiological monitor, and custom application that delivered video feed to a remote trainer and monitored and recorded exercise data in real time. Implementation outcomes included adherence, rescheduled sessions, minutes of moderate exercise, and successful recording of exercise data. Pre/post-outcomes included aerobic capacity (VO 2 peak), the Physical Activity Scale for Individuals with Physical Disabilities (PASIPD), the Satisfaction with Life Scale (SWLS), and the Quality of Life Index modified for spinal cord injury (QLI-SCI). Acceptability was determined by participant perceptions of the program features and impact, assessed via qualitative interview at the end of the nonintervention phase. Participants completed all 24 intervention sessions with 100% adherence. Out of 96 scheduled training sessions for the four participants, only 8 (8%) were makeup sessions. The teleexercise
International Nuclear Information System (INIS)
Kuwazuru, Junpei; Magome, Taiki; Arimura, Hidetaka; Yamashita, Yasuo; Oki, Masafumi; Toyofuku, Fukai; Kakeda, Shingo; Yamamoto, Daisuke
2010-01-01
Yamamoto et al. developed the system for computer-aided detection of multiple sclerosis (MS) candidate regions. In a level set method in their proposed method, they employed the constant threshold value for the edge indicator function related to a speed function of the level set method. However, it would be appropriate to adjust the threshold value to each MS candidate region, because the edge magnitudes in MS candidates differ from each other. Our purpose of this study was to develop a computerized detection of MS candidate regions in MR images based on a level set method using an artificial neural network (ANN). To adjust the threshold value for the edge indicator function in the level set method to each true positive (TP) and false positive (FP) region, we constructed the ANN. The ANN could provide the suitable threshold value for each candidate region in the proposed level set method so that TP regions can be segmented and FP regions can be removed. Our proposed method detected MS regions at a sensitivity of 82.1% with 0.204 FPs per slice and similarity index of MS candidate regions was 0.717 on average. (author)
Zimovets, Artem; Matviychuk, Alexander; Ushakov, Vladimir
2016-12-01
The paper presents two different approaches to reduce the time of computer calculation of reachability sets. First of these two approaches use different data structures for storing the reachability sets in the computer memory for calculation in single-threaded mode. Second approach is based on using parallel algorithms with reference to the data structures from the first approach. Within the framework of this paper parallel algorithm of approximate reachability set calculation on computer with SMP-architecture is proposed. The results of numerical modelling are presented in the form of tables which demonstrate high efficiency of parallel computing technology and also show how computing time depends on the used data structure.
Rivera, V. A.; Amaya, L. F.
2017-12-01
In 2016, graduate students from Northwestern University's Center for Interdisciplinary Exploration and Research in Astrophysics (CIERA) initiated the Science Sonification and Composition Project, which pairs scientists with student composers to create original music inspired by and utilizing the products of scientific research. In 2017, these pieces were performed at Northwestern for a mixed audience of scientists, musicians, and community members. Sonification of data, or the representation of data as sound, is an increasingly popular method of examining data in the geosciences, especially in astrophysics, where sonification of gravitational waves has recently made major news. Numerical time-series data are often excellent candidates for sonification, as the data can be modified by simple algorithmic means to convert numerical values which represent physical measurements to numerical values representing musical "variables" like volume, pitch, or timbre. Our collaboration, a result of the CIERA initiative, explores methods of sonification that do not involve a simple conversion of data to sound, instead attempting to create sound from data by analog methods. The piece uses both time-series groundwater elevation data and physical soil samples from the locations where the water table measurements were collected. The field site from which both data and samples were collected is Gensburg Markham Prairie, an urban nature preserve on Chicago's south side which hosts a long-term study on the collateral benefits of urban greenspace for stormwater management and storage. Our aim was to combine physical, living elements with technology to mirror the research, where we examine flows and cycles in nature by "taking the pulse" of the landscape using sensing networks. Soil samples were placed in metal vessels outfitted with contact microphones and manipulated by hand and with water, using time-series data as a guide, much like sheet music. This was repeated for samples and
Local and global recoding methods for anonymizing set-valued data
Terrovitis, Manolis; Mamoulis, Nikos; Kalnis, Panos
2010-01-01
In this paper, we study the problem of protecting privacy in the publication of set-valued data. Consider a collection of supermarket transactions that contains detailed information about items bought together by individuals. Even after removing all
Gulmans, J.; Gulmans, J.; Vollenbroek-Hutten, Miriam Marie Rosé; van Gemert-Pijnen, Julia E.W.C.; van Harten, Willem H.
2007-01-01
Background. Owing to the involvement of multiple professionals from various institutions, integrated care settings are prone to suboptimal patient care communication. To assure continuity, communication gaps should be identified for targeted improvement initiatives. However, available assessment
Pelin Yüksel; Soner Yıldırım
2015-01-01
The main purposes of phenomenological research are to seek reality from individuals’ narratives of their experiences and feelings, and to produce in-depth descriptions of the phenomenon. Phenomenological research studies in educational settings generally embody lived experience, perception, and feelings of participants about a phenomenon. This study aims to provide a general framework for researchers who are interested in phenomenological studies especially in educational setting. Additionall...
Composites Similarity Analysis Method Based on Knowledge Set in Composites Quality Control
Li Haifeng
2016-01-01
Composites similarity analysis is an important link of composites review, it can not only to declare composites review rechecking, still help composites applicants promptly have the research content relevant progress and avoid duplication. This paper mainly studies the composites similarity model in composites review. With the actual experience of composites management, based on the author’s knowledge set theory, paper analyzes deeply knowledge set representation of composites knowledge, impr...
A New 3D Object Pose Detection Method Using LIDAR Shape Set.
Kim, Jung-Un; Kang, Hang-Bong
2018-03-16
In object detection systems for autonomous driving, LIDAR sensors provide very useful information. However, problems occur because the object representation is greatly distorted by changes in distance. To solve this problem, we propose a LIDAR shape set that reconstructs the shape surrounding the object more clearly by using the LIDAR point information projected on the object. The LIDAR shape set restores object shape edges from a bird's eye view by filtering LIDAR points projected on a 2D pixel-based front view. In this study, we use this shape set for two purposes. The first is to supplement the shape set with a LIDAR Feature map, and the second is to divide the entire shape set according to the gradient of the depth and density to create a 2D and 3D bounding box proposal for each object. We present a multimodal fusion framework that classifies objects and restores the 3D pose of each object using enhanced feature maps and shape-based proposals. The network structure consists of a VGG -based object classifier that receives multiple inputs and a LIDAR-based Region Proposal Networks (RPN) that identifies object poses. It works in a very intuitive and efficient manner and can be extended to other classes other than vehicles. Our research has outperformed object classification accuracy (Average Precision, AP) and 3D pose restoration accuracy (3D bounding box recall rate) based on the latest studies conducted with KITTI data sets.
Wang, Tongtong; Xiao, Zhiqiang; Liu, Zhigang
2017-01-01
Leaf area index (LAI) is an important biophysical parameter and the retrieval of LAI from remote sensing data is the only feasible method for generating LAI products at regional and global scales. However, most LAI retrieval methods use satellite observations at a specific time to retrieve LAI. Because of the impacts of clouds and aerosols, the LAI products generated by these methods are spatially incomplete and temporally discontinuous, and thus they cannot meet the needs of practical applications. To generate high-quality LAI products, four machine learning algorithms, including back-propagation neutral network (BPNN), radial basis function networks (RBFNs), general regression neutral networks (GRNNs), and multi-output support vector regression (MSVR) are proposed to retrieve LAI from time-series Moderate Resolution Imaging Spectroradiometer (MODIS) reflectance data in this study and performance of these machine learning algorithms is evaluated. The results demonstrated that GRNNs, RBFNs, and MSVR exhibited low sensitivity to training sample size, whereas BPNN had high sensitivity. The four algorithms performed slightly better with red, near infrared (NIR), and short wave infrared (SWIR) bands than red and NIR bands, and the results were significantly better than those obtained using single band reflectance data (red or NIR). Regardless of band composition, GRNNs performed better than the other three methods. Among the four algorithms, BPNN required the least training time, whereas MSVR needed the most for any sample size. PMID:28045443
Directory of Open Access Journals (Sweden)
Dumitru Baleanu
2014-01-01
Full Text Available We perform a comparison between the fractional iteration and decomposition methods applied to the wave equation on Cantor set. The operators are taken in the local sense. The results illustrate the significant features of the two methods which are both very effective and straightforward for solving the differential equations with local fractional derivative.
Xia, Jie; Jin, Hongwei; Liu, Zhenming; Zhang, Liangren; Wang, Xiang Simon
2014-05-27
Benchmarking data sets have become common in recent years for the purpose of virtual screening, though the main focus had been placed on the structure-based virtual screening (SBVS) approaches. Due to the lack of crystal structures, there is great need for unbiased benchmarking sets to evaluate various ligand-based virtual screening (LBVS) methods for important drug targets such as G protein-coupled receptors (GPCRs). To date these ready-to-apply data sets for LBVS are fairly limited, and the direct usage of benchmarking sets designed for SBVS could bring the biases to the evaluation of LBVS. Herein, we propose an unbiased method to build benchmarking sets for LBVS and validate it on a multitude of GPCRs targets. To be more specific, our methods can (1) ensure chemical diversity of ligands, (2) maintain the physicochemical similarity between ligands and decoys, (3) make the decoys dissimilar in chemical topology to all ligands to avoid false negatives, and (4) maximize spatial random distribution of ligands and decoys. We evaluated the quality of our Unbiased Ligand Set (ULS) and Unbiased Decoy Set (UDS) using three common LBVS approaches, with Leave-One-Out (LOO) Cross-Validation (CV) and a metric of average AUC of the ROC curves. Our method has greatly reduced the "artificial enrichment" and "analogue bias" of a published GPCRs benchmarking set, i.e., GPCR Ligand Library (GLL)/GPCR Decoy Database (GDD). In addition, we addressed an important issue about the ratio of decoys per ligand and found that for a range of 30 to 100 it does not affect the quality of the benchmarking set, so we kept the original ratio of 39 from the GLL/GDD.
Carleton, W Christopher; Campbell, David; Collard, Mark
2018-01-01
Statistical time-series analysis has the potential to improve our understanding of human-environment interaction in deep time. However, radiocarbon dating-the most common chronometric technique in archaeological and palaeoenvironmental research-creates challenges for established statistical methods. The methods assume that observations in a time-series are precisely dated, but this assumption is often violated when calibrated radiocarbon dates are used because they usually have highly irregular uncertainties. As a result, it is unclear whether the methods can be reliably used on radiocarbon-dated time-series. With this in mind, we conducted a large simulation study to investigate the impact of chronological uncertainty on a potentially useful time-series method. The method is a type of regression involving a prediction algorithm called the Poisson Exponentially Weighted Moving Average (PEMWA). It is designed for use with count time-series data, which makes it applicable to a wide range of questions about human-environment interaction in deep time. Our simulations suggest that the PEWMA method can often correctly identify relationships between time-series despite chronological uncertainty. When two time-series are correlated with a coefficient of 0.25, the method is able to identify that relationship correctly 20-30% of the time, providing the time-series contain low noise levels. With correlations of around 0.5, it is capable of correctly identifying correlations despite chronological uncertainty more than 90% of the time. While further testing is desirable, these findings indicate that the method can be used to test hypotheses about long-term human-environment interaction with a reasonable degree of confidence.
Korotcov, Alexandru; Tkachenko, Valery; Russo, Daniel P; Ekins, Sean
2017-12-04
Machine learning methods have been applied to many data sets in pharmaceutical research for several decades. The relative ease and availability of fingerprint type molecular descriptors paired with Bayesian methods resulted in the widespread use of this approach for a diverse array of end points relevant to drug discovery. Deep learning is the latest machine learning algorithm attracting attention for many of pharmaceutical applications from docking to virtual screening. Deep learning is based on an artificial neural network with multiple hidden layers and has found considerable traction for many artificial intelligence applications. We have previously suggested the need for a comparison of different machine learning methods with deep learning across an array of varying data sets that is applicable to pharmaceutical research. End points relevant to pharmaceutical research include absorption, distribution, metabolism, excretion, and toxicity (ADME/Tox) properties, as well as activity against pathogens and drug discovery data sets. In this study, we have used data sets for solubility, probe-likeness, hERG, KCNQ1, bubonic plague, Chagas, tuberculosis, and malaria to compare different machine learning methods using FCFP6 fingerprints. These data sets represent whole cell screens, individual proteins, physicochemical properties as well as a data set with a complex end point. Our aim was to assess whether deep learning offered any improvement in testing when assessed using an array of metrics including AUC, F1 score, Cohen's kappa, Matthews correlation coefficient and others. Based on ranked normalized scores for the metrics or data sets Deep Neural Networks (DNN) ranked higher than SVM, which in turn was ranked higher than all the other machine learning methods. Visualizing these properties for training and test sets using radar type plots indicates when models are inferior or perhaps over trained. These results also suggest the need for assessing deep learning further
Directory of Open Access Journals (Sweden)
Nasrin Jiryaee
2015-01-01
Full Text Available Background: Designing an intervention to increase physical activity is important to be based on the health care settings resources and be acceptable by the subject group. This study was designed to assess and compare the effect of the goal setting strategy with a group education method on increasing the physical activity of mothers of children aged 1 to 5. Materials and Methods: Mothers who had at least one child of 1-5 years were randomized into two groups. The effect of 1 goal-setting strategy and 2 group education method on increasing physical activity was assessed and compared 1 month and 3 months after the intervention. Also, the weight, height, body mass index (BMI, waist and hip circumference, and well-being were compared between the two groups before and after the intervention. Results: Physical activity level increased significantly after the intervention in the goal-setting group and it was significantly different between the two groups after intervention (P < 0.05. BMI, waist circumference, hip circumference, and well-being score were significantly different in the goal-setting group after the intervention. In the group education method, only the well-being score improved significantly (P < 0.05. Conclusion: Our study presented the effects of using the goal-setting strategy to boost physical activity, improving the state of well-being and decreasing BMI, waist, and hip circumference.
Detecting nonlinear structure in time series
International Nuclear Information System (INIS)
Theiler, J.
1991-01-01
We describe an approach for evaluating the statistical significance of evidence for nonlinearity in a time series. The formal application of our method requires the careful statement of a null hypothesis which characterizes a candidate linear process, the generation of an ensemble of ''surrogate'' data sets which are similar to the original time series but consistent with the null hypothesis, and the computation of a discriminating statistic for the original and for each of the surrogate data sets. The idea is to test the original time series against the null hypothesis by checking whether the discriminating statistic computed for the original time series differs significantly from the statistics computed for each of the surrogate sets. While some data sets very cleanly exhibit low-dimensional chaos, there are many cases where the evidence is sketchy and difficult to evaluate. We hope to provide a framework within which such claims of nonlinearity can be evaluated. 5 refs., 4 figs