Scaling Analysis Method Research Articles

Arrhythmia detection from heart rate variability by SDFA method

The smoothed detrended fluctuation analysis (SDFA) based on DFA and the principal of wavelet shrinkage procedures is a scaling analysis method to represent the correlation properties of a time series. Since there is not a specific rule for the choice of the numbers of regressors in SDFA Method, we present here an asymptotic optimal choice. We carried out some Monte Carlo simulations on fractional Gaussian noise (FGN) models, to investigate the effect of the numbers of regressors in SDFA Method. We analyze the long dependence property in view of the SDFA method to compare 10 healthy and 10 unhealthy (with cardiac arrhythimia) RR time series randomly selected from databases of the PhysioBank. It is proposed that utilizing Hurst estimator by SDFA method, as an additional diagnostic tool may provide an indication of cardiac arrhythmia.

Time and frequency domain characteristics of detrending-operation-based scaling analysis: Exact DFA and DMA frequency responses

We develop a general framework to study the time and frequency domain characteristics of detrending-operation-based scaling analysis methods, such as detrended fluctuation analysis (DFA) and detrending moving average (DMA) analysis. In this framework, using either the time or frequency domain approach, the frequency responses of detrending operations are calculated analytically. Although the frequency domain approach based on conventional linear analysis techniques is only applicable to linear detrending operations, the time domain approach presented here is applicable to both linear and nonlinear detrending operations. Furthermore, using the relationship between the time and frequency domain representations of the frequency responses, the frequency domain characteristics of nonlinear detrending operations can be obtained. Based on the calculated frequency responses, it is possible to establish a direct connection between the root-mean-square deviation of the detrending-operation-based scaling analysis and the power spectrum for linear stochastic processes. Here, by applying our methods to DFA and DMA, including higher-order cases, exact frequency responses are calculated. In addition, we analytically investigate the cutoff frequencies of DFA and DMA detrending operations and show that these frequencies are not optimally adjusted to coincide with the corresponding time scale.

Fast algorithm for scaling analysis with higher-order detrending moving average method.

Among scaling analysis methods based on the root-mean-square deviation from the estimated trend, it has been demonstrated that centered detrending moving average (DMA) analysis with a simple moving average has good performance when characterizing long-range correlation or fractal scaling behavior. Furthermore, higher-order DMA has also been proposed; it is shown to have better detrending capabilities, removing higher-order polynomial trends than original DMA. However, a straightforward implementation of higher-order DMA requires a very high computational cost, which would prevent practical use of this method. To solve this issue, in this study, we introduce a fast algorithm for higher-order DMA, which consists of two techniques: (1) parallel translation of moving averaging windows by a fixed interval; (2) recurrence formulas for the calculation of summations. Our algorithm can significantly reduce computational cost. Monte Carlo experiments show that the computational time of our algorithm is approximately proportional to the data length, although that of the conventional algorithm is proportional to the square of the data length. The efficiency of our algorithm is also shown by a systematic study of the performance of higher-order DMA, such as the range of detectable scaling exponents and detrending capability for removing polynomial trends. In addition, through the analysis of heart-rate variability time series, we discuss possible applications of higher-order DMA.

A Theoretical Analysis of the Interaction Between Pores and Inclusions During the Continuous Casting of Steel

A mathematical model is derived to predict the trajectories of pores and inclusions that are nucleated in the interdendritic region during the continuous casting of steel. Using basic fluid mechanics and heat transfer, scaling analysis, and asymptotic methods, the model accounts for the possible lateral drift of the pores as a result of the dependence of the surface tension on temperature and sulfur concentration. Moreover, the soluto–thermocapillary drift of such pores prior to final solidification, coupled to the fact that any inclusions present can only have a vertical trajectory, can help interpret recent experimental observations of pore-inclusion clusters in solidified steel castings.

Identification of Chaos-Periodic Transitions, Band Merging, and Internal Crisis Using Wavelet-DFA Method

Detrended Fluctuation Analysis (DFA) is a scaling analysis method that can identify intrinsic self-similarity in any nonstationary time series. In contrast, Wavelet Transform (WT) method is widely used to investigate the self-similar processes, as the self-similarity properties exist within the subbands. Therefore, a combination of these two approaches, DFA and WPT, is promising for rigorous investigation of such a system. In this paper a new methodology, so-called wavelet DFA, is introduced and interpreted to evaluate this idea. This approach, further than identifying self-similarity properties, enable us to detect and capture the chaos-periodic transitions, band merging, and internal crisis in systems that become chaotic through period-doubling phenomena. Changes of wavelet DFA exponent have been compared with that of Lyapunov and DFA through Logistic, Sine, Gaussian, Cubic, and Quartic Maps. Furthermore, the potential capabilities of this new exponent have been presented.

International research trends of pharmacognosy on molecular level --based on analysis of SCI literature

The techniques and methods of molecular biology have been widely applied in pharmacognosy fields. International development trends of pharmacognosy studies on molecular level were analyzed by bibliometric methods using the SCIE database on Web of Science, the literature distribution, national distribution, agency distribution, periodicals distribution, and hot research topics were described using multivariate statistical analysis and multidimensional scaling analysis method,etc. The number of international pharmacognosy literature on molecular level is increasing year by year. USA, China and Japan have close cooperation, and focus on molecular identification and genetic diversity. Chinese scientists issued high-impact factor journals papers and high citations amount in the international forefront. The international pharmacognosy research on molecular level has developed rapidly. Chinese research has a significant influence.The molecular mechanism of the formation of Dao-di Herbs may become the next hotspot.

Direct Scaling Analysis of Fermionic Multiparticle Correlated Anderson Models with Infinite-Range Interaction

We adapt the method of direct scaling analysis developed earlier for single-particle Anderson models, to the fermionic multiparticle models with finite or infinite interaction on graphs. Combined with a recent eigenvalue concentration bound for multiparticle systems, the new method leads to a simpler proof of the multiparticle dynamical localization with optimal decay bounds in a natural distance in the multiparticle configuration space, for a large class of strongly mixing random external potentials. Earlier results required the random potential to be IID.

Singularity analysis based on wavelet transform of fractal measures for identifying geochemical anomaly in mineral exploration

Multi-resolution and scale-invariance have been increasingly recognized as two closely related intrinsic properties endowed in geofields such as geochemical and geophysical anomalies, and they are commonly investigated by using multiscale- and scaling-analysis methods. In this paper, the wavelet-based multiscale decomposition (WMD) method was proposed to investigate the multiscale natures of geochemical pattern from large scale to small scale. In the light of the wavelet transformation of fractal measures, we demonstrated that the wavelet approximation operator provides a generalization of box-counting method for scaling analysis of geochemical patterns. Specifically, the approximation coefficient acts as the generalized density-value in density–area fractal modeling of singular geochemical distributions. Accordingly, we presented a novel local singularity analysis (LSA) using the WMD algorithm which extends the conventional moving averaging to a kernel-based operator for implementing LSA. Finally, the novel LSA was validated using a case study dealing with geochemical data (Fe2O3) in stream sediments for mineral exploration in Inner Mongolia, China. In comparison with the LSA implemented using the moving averaging method the novel LSA using WMD identified improved weak geochemical anomalies associated with mineralization in covered area.

Comprehensive analysis of the socioeconomic conditions of regions with use of the grid-technology

Ranking of the socioeconomic conditions of districts of Rivne region on statistical indicators of economic activity in the first half of 2015 was held based on Data Mining using Grid-technologies. System evaluation using the elements of methods of scaling, factor and cluster analysis was performed. Flexible and scalable module that extends the capabilities of the standard web-services and simplifies the procedures of collection and processing of data was designed

The Sedimentation of Slim Flexible Particles in Stokes Flow

Background/Objectives: The dynamics of elastic slim particles (filaments) surrounded by fluid flow is a noteworthy topic of study because of its application in natural sciences and industrial processes. When deformation of elastic particle is large many complications arise which needs specific consideration in order to develop an efficient method for modeling the solid-fluid interaction accurately and with acceptable computational cost. Method: In order to study the sedimentation process of filament which is immersed in a quiescent fluid flow, we constitute related governing equations based on nonlocal solid-fluid interaction coupling with slender body theory. The fluid flow governed by Stokes assumptions which allow us to use superposition principle. Also, the extracted equations rearrange by two controller parameters Elasto-gravitation, β, and Slenderness-parameter, ϵ. Findings: A Highly Flexible filament (HF-filament) and a Moderately Flexible filament (MF-filament) have examined by mentioned method. The results show that the HF-filament fall on a periodic motion during the sedimentation process. This periodic motion leads to a set of unbalance forces along the filament which causes a permanent lateral drift. In the other side the MF-filament meets an equilibrium point with a final constant U-shape. Also, in order to validation we compare the outcome data with the results obtained by local and multiple scale analysis methods. Application/Improvements: The approach have been presented by this paper can be used in different fields which there are any necessity to simulating slim particles motion more simple and with less computational cost in compare with conventional methods.

Assessment of the relative ratio of correlated and uncorrelated waiting times in the Southern California earthquakes catalogue

In the present study, we investigated the interevent time interval distribution of earthquakes in Southern California. We analyzed and compared datasets of waiting times between consecutive earthquakes and time structure-distorted datasets. The aim of this study was to determine the proportion of waiting time values in the original catalogue that can be regarded as statistically distinguishable or indistinguishable from the baseline time intervals datasets where the original structure of the temporal distribution of earthquakes was disrupted. We compiled two types of time structure-distorted baseline sequences, which comprised mean values of: (a) shuffled original interevent data and (b) interevent times data from time-randomized catalogues. To compare the dynamical characteristics of the original and time structure-distorted baseline sequences, we used several data analysis methods such as power spectrum regression, detrended fluctuation, and multifractal detrended fluctuation analysis. We also tested the nonlinear structure of the original and baseline sequences using the magnitude and sign scaling analysis method. We calculated theZscore in order to assess whether the interevent time values in the original dataset shared statistical similarity or dissimilarity with the time structure-distorted baseline interevent data sequence. We compared the interevent time values in the original dataset with the mean baseline interevent times computed for two types of time structure-distorted sequences. The results showed that about 30% of the original interevent times were statistically indistinguishable from the mean of the shuffled dataset and 10% from the mean of the time structure-distorted baseline interevent dataset. We performed similar analyses for other catalogues obtained from different parts of the world. According to the results of this analysis, the proportion of events in the original catalogues that were indistinguishable from sequences with disturbed time structure did not contradict the results obtained for the Southern California catalogue.

Numerical simulation of heat and moisture transfer through bulky PAN nanofiber mats

In this study, the coupled heat and moisture transfer of polyacrylonitril nanofiber mats were investigated by theoretical and experimental methods. A mathematical model was used to describe and predict the coupled heat and moisture transfer of nanofiber mats. Based on the results obtained by scale analysis method, order of magnitude of heat transfer by radiation is negligible for nanofiber mats but heat transfer by convection is important. In this investigation, the coupled heat and moisture transfer including convection heat transfer was solved numerically by finite difference method. Comparison between numerical results and experimental data shows good agreement, which indicates the high accuracy of the numerical results.

Effects of Exponential Trends on Correlations of Stock Markets

Detrended fluctuation analysis (DFA) is a scaling analysis method used to estimate long-range power-law correlation exponents in time series. In this paper, DFA is employed to discuss the long-range correlations of stock market. The effects of exponential trends on correlations of Hang Seng Index (HSI) are investigated with emphasis. We find that the long-range correlations and the positions of the crossovers of lower order DFA appear to have no immunity to the additive exponential trends. Further, our analysis suggests that an increase in the DFA order increases the efficiency of eliminating on exponential trends. In addition, the empirical study shows that the correlations and crossovers are associated with DFA order and magnitude of exponential trends.

Determining the Technical Efficiency of Specialty Ophthalmology Hospital Using SFA and DEA: 2009-2011

Introduction: During the last decade, the health sector of many countries in general has been faced significantly with the increase of health care costs and in particular with the growth in hospital costs, that a significant part of it is due to the inefficient use of resources. The present study has been calculated the technical efficiency of the Specialty Ophthalmology Hospital of Tehran University of Medical Sciences by the comprehensive data analysis methods and stochastic frontier analysis. Methods: In this article, the technical efficiency of the Specialty Ophthalmology Hospital of Tehran University of Medical Sciences has been calculated by the years of 2009 to 2011, by the comprehensive data analysis methods and stochastic frontier analysis. For this purpose, the form of input-oriented data envelopment analysis approach was used by assuming the variable Productivity to scale and stochastic frontier analysis method and from the five output, the occupied bed days, outpatient admissions, inpatient admissions, inpatient days and bed occupancy factor, and from the six output, it means active beds, number of doctors, nurses, and other personnel, budget and equipment costs were used for the study. For data analyzing, Deap software, edit 1/2 and Frontier edit 1/4, was used. Result: The results of a comprehensive data analysis method showed: 1) The capacity of improving technical efficiency in the studied sector is 34% (average technical efficiency is 0.663 parts); and 2) some of the sectors are met the excess inputs (factors of production). Technical efficiency using stochastic frontier analysis was equal to 0.937. In fact, the stochastic frontier analysis showed the inefficiency is less than the actual value. Conclusion: Reducing excess capacity factors (factors of production) should be conducted in the form of a comprehensive plan and by considering all regarded aspects, that this reduction plays a major role in the hospital and health sector costs reduction.

Safety Assessment in Installation of Precast Concrete

This study was carried out to identify the safety aspects and the level of safety during the installation process in construction sites. A questionnaire survey and interviews were done to provide data on safety requirements in precast concrete construction. All of the interviews and the research questionnaire survey were conducted among contractors that are registered as class 1 to class 7 with the Construction Industry Development Board (CIDB) and class A to class G with Pusat Khidmat Kontraktor (PKK) in Penang. Returned questionnaires were analysed with the use of simple percentages and the Likert Scale analysis method to identify safety aspects of precast construction. The results indicate that the safety aspect implemented by companies involved in the precast construction process is at a good level in the safety aspect during bracing, propping, welding and grouting processes and at a very good level of safety in general aspects and safety aspects during lifting processes.

On the diet of two endemic and rare species of Trichomycterus (Ostariophysi: Trichomycteridae) in the Jordão River, Iguaçu River basin, southern Brazil

The diet and the eect of body size on the feeding habits of Trichomycterus crassicaudatus and Trichomycterus stawiarski, collected in the Jordão River, an import tributary of the Iguaçu River basin, were investigated. Samples were collected in august 2003 during the Jordão River Energetic Complex Aquatic Fauna Rescue and Monitoring program. Stomach contents were evaluated through the frequency of occurrence, permutational multivariate analysis of variance (PERMANOVA), si-milarity percentage analysis (SIMPER) and non-metric multidimensional scaling analysis (MDS) methods. A total of 86 stomach contents of T. stawiarski and 36 of T. crassicaudatus were assessed. The species presented an insectivorous feeding habit, with differences in the diet composition of the “smallest” and the “largest” individuals. Ephemeroptera nymphs, lar-vae and pupae of Diptera, organic detritus and plant fragments were the most important food items. Both species feeding habits were based mainly in benthic aquatic immature insects.

Geophysical Fluid Dynamics

The workshop “Geophysical Fluid Dynamics” addressed recent advances in analytical, stochastic, modeling and computational studies of geophysical rotating fluids models. Of particular interest on the analytical and stochastic sides were the contributions concerning dispersive mechanism, regularity verses finite-time formation of singularities of certain viscous and inviscid geostrophic models, the primitive equations, Boussinesq approximation, boundary layers and fast rotating fluids. Model reductions, based on asymptotic, scaling analysis and variational methods, were presented. In addition, computational investigations were provided in support of the claim that three-dimensional geophysical turbulent flows exhibit two-dimensional features, at small Rosby numbers.

Representations of Religious Words: Insights for Religious Priming Research

Researchers often expose participants to a series of words (e.g., religion, God, faith) to activate religious concepts and observe their subsequent effects on people's thoughts, feelings, and behaviors. This research has revealed many important effects of experimentally manipulated religious cognition in domains ranging from prosocial behavior to prejudice. However, it is not exactly clear what constitutes a “religious cognition,” and no research has yet investigated conceptual distinctions between different kinds of religious prime words. In the present research we used a card‐sorting task to examine laypeople's subjective understanding of religious prime words, and the central categories or dimensions of these religious concepts. Using multidimensional scaling, property fitting, and cluster analysis methods to analyze the proximities among the words, we find evidence for the mental representation of three relatively distinct kinds of religious concepts: agents (e.g., God, angel), spiritual/abstract (e.g., faith, belief), and institutional/concrete (e.g., shrine, scripture). Theoretical and methodological impli‐cations for religious priming research are discussed.

A user term visualization analysis based on a social question and answer log

The authors of this paper investigate terms of consumers’ diabetes based on a log from the Yahoo!Answers social question and answers (Q&A) forum, ascertain characteristics and relationships among terms related to diabetes from the consumers’ perspective, and reveal users’ diabetes information seeking patterns. In this study, the log analysis method, data coding method, and visualization multiple-dimensional scaling analysis method were used for analysis. The visual analyses were conducted at two levels: terms analysis within a category and category analysis among the categories in the schema. The findings show that the average number of words per question was 128.63, the average number of sentences per question was 8.23, the average number of words per response was 254.83, and the average number of sentences per response was 16.01. There were 12 categories (Cause & Pathophysiology, Sign & Symptom, Diagnosis & Test, Organ & Body Part, Complication & Related Disease, Medication, Treatment, Education & Info Resource, Affect, Social & Culture, Lifestyle, and Nutrient) in the diabetes related schema which emerged from the data coding analysis. The analyses at the two levels show that terms and categories were clustered and patterns were revealed. Future research directions are also included.

Subjective Evaluation of Directional Properties of Loudspeaker Systems with the Analog and Digital Crossover Networks

The aim of this study was to determine the way in which loudspeaker systems with the analog and digital crossover networks were subjectively evaluated. The object of the study were two loudspeaker systems, di ering in both the position of speakers on the front panel of enclosure and con guration of the crossover networks: 2.5-way and 3-way systems with the slope of frequency response of 12 dB/octave in the cut-o regions. The investigations were conducted for 5 angles from the front hemisphere in the horizontal plane. Test signals were fragments of music and speech. The recordings of these signals were conducted in an anechoic chamber using an arti cial head and then presented to the listeners through headphones. Five normally-hearing listeners aged 18 50 years took part in the experiment. Listening tests were carried out in two stages. In the rst stage listeners were listening to test signals grouped in triads and their task was to identify pairs of signals the most and the least similar to each other. In the second stage a parametric evaluation was performed. It consisted in assigning ve numbers, corresponding to the intensity of the attribute of perception space (evaluated on a scale of 0 10) to each of test signals. The attributes of perception space included: sharpness, clearness, fullness, lack of distortions and loudness. Using the method of multidimensional scaling and correlation analysis it was possible to relate a particular dimension of the multidimensional space to the attributes of the perception space. It was found that the intrinsic attributes responsible for the subjective evaluation of loudspeaker systems with the analog and digital crossover network were sharpness, clearness and loudness.