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exponent</title> <meta name="description" content="Search results for: hurst exponent"> <meta name="keywords" content="hurst exponent"> <meta name="viewport" content="width=device-width, initial-scale=1, minimum-scale=1, maximum-scale=1, user-scalable=no"> <meta charset="utf-8"> <link href="https://cdn.waset.org/favicon.ico" type="image/x-icon" rel="shortcut icon"> <link href="https://cdn.waset.org/static/plugins/bootstrap-4.2.1/css/bootstrap.min.css" rel="stylesheet"> <link href="https://cdn.waset.org/static/plugins/fontawesome/css/all.min.css" rel="stylesheet"> <link href="https://cdn.waset.org/static/css/site.css?v=150220211555" rel="stylesheet"> </head> <body> <header> <div class="container"> <nav class="navbar navbar-expand-lg navbar-light"> <a class="navbar-brand" href="https://waset.org"> <img src="https://cdn.waset.org/static/images/wasetc.png" alt="Open Science Research Excellence" title="Open Science Research Excellence" /> </a> <button class="d-block d-lg-none navbar-toggler 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id="custom-search-input"> <div class="input-group"> <i class="fas fa-search"></i> <input type="text" class="search-query" name="q" placeholder="Author, Title, Abstract, Keywords" value="hurst exponent"> <input type="submit" class="btn_search" value="Search"> </div> </div> </form> </div> </div> <div class="row mt-3"> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Commenced</strong> in January 2007</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Frequency:</strong> Monthly</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Edition:</strong> International</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Paper Count:</strong> 91</div> </div> </div> </div> <h1 class="mt-3 mb-3 text-center" style="font-size:1.6rem;">Search results for: hurst exponent</h1> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">91</span> Analysing the Behaviour of Local Hurst Exponent and Lyapunov Exponent for Prediction of Market Crashes</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Shreemoyee%20Sarkar">Shreemoyee Sarkar</a>, <a href="https://publications.waset.org/abstracts/search?q=Vikhyat%20Chadha"> Vikhyat Chadha</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, the local fractal properties and chaotic properties of financial time series are investigated by calculating two exponents, the Local Hurst Exponent: LHE and Lyapunov Exponent in a moving time window of a financial series.y. For the purpose of this paper, the Dow Jones Industrial Average (DIJA) and S&P 500, two of the major indices of United States have been considered. The behaviour of the above-mentioned exponents prior to some major crashes (1998 and 2008 crashes in S&P 500 and 2002 and 2008 crashes in DIJA) is discussed. Also, the optimal length of the window for obtaining the best possible results is decided. Based on the outcomes of the above, an attempt is made to predict the crashes and accuracy of such an algorithm is decided. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=local%20hurst%20exponent" title="local hurst exponent">local hurst exponent</a>, <a href="https://publications.waset.org/abstracts/search?q=lyapunov%20exponent" title=" lyapunov exponent"> lyapunov exponent</a>, <a href="https://publications.waset.org/abstracts/search?q=market%20crash%20prediction" title=" market crash prediction"> market crash prediction</a>, <a href="https://publications.waset.org/abstracts/search?q=time%20series%20chaos" title=" time series chaos"> time series chaos</a>, <a href="https://publications.waset.org/abstracts/search?q=time%20series%20local%20fractal%20properties" title=" time series local fractal properties"> time series local fractal properties</a> </p> <a href="https://publications.waset.org/abstracts/102568/analysing-the-behaviour-of-local-hurst-exponent-and-lyapunov-exponent-for-prediction-of-market-crashes" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/102568.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">152</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">90</span> The Log S-fbm Nested Factor Model</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Othmane%20Zarhali">Othmane Zarhali</a>, <a href="https://publications.waset.org/abstracts/search?q=C%C3%A9cilia%20Aubrun"> Cécilia Aubrun</a>, <a href="https://publications.waset.org/abstracts/search?q=Emmanuel%20Bacry"> Emmanuel Bacry</a>, <a href="https://publications.waset.org/abstracts/search?q=Jean-Philippe%20Bouchaud"> Jean-Philippe Bouchaud</a>, <a href="https://publications.waset.org/abstracts/search?q=Jean-Fran%C3%A7ois%20Muzy"> Jean-François Muzy</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The Nested factor model was introduced by Bouchaud and al., where the asset return fluctuations are explained by common factors representing the market economic sectors and residuals (noises) sharing with the factors a common dominant volatility mode in addition to the idiosyncratic mode proper to each residual. This construction infers that the factors-residuals log volatilities are correlated. Here, we consider the case of a single factor where the only dominant common mode is a S-fbm process (introduced by Peng, Bacry and Muzy) with Hurst exponent H around 0.11 and the residuals having in addition to the previous common mode idiosyncratic components with Hurst exponents H around 0. The reason for considering this configuration is twofold: preserve the Nested factor model’s characteristics introduced by Bouchaud and al. and propose a framework through which the stylized fact reported by Peng and al. is reproduced, where it has been observed that the Hurst exponents of stock indices are large as compared to those of individual stocks. In this work, we show that the Log S-fbm Nested factor model’s construction leads to a Hurst exponent of single stocks being the ones of the idiosyncratic volatility modes and the Hurst exponent of the index being the one of the common volatility modes. Furthermore, we propose a statistical procedure to estimate the Hurst factor exponent from the stock returns dynamics together with theoretical guarantees, with good results in the limit where the number of stocks N goes to infinity. Last but not least, we show that the factor can be seen as an index constructed from the single stocks weighted by specific coefficients. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=hurst%20exponent" title="hurst exponent">hurst exponent</a>, <a href="https://publications.waset.org/abstracts/search?q=log%20S-fbm%20model" title=" log S-fbm model"> log S-fbm model</a>, <a href="https://publications.waset.org/abstracts/search?q=nested%20factor%20model" title=" nested factor model"> nested factor model</a>, <a href="https://publications.waset.org/abstracts/search?q=small%20intermittency%20approximation" title=" small intermittency approximation"> small intermittency approximation</a> </p> <a href="https://publications.waset.org/abstracts/186694/the-log-s-fbm-nested-factor-model" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/186694.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">49</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">89</span> Rescaled Range Analysis of Seismic Time-Series: Example of the Recent Seismic Crisis of Alhoceima</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Marina%20Benito-Parejo">Marina Benito-Parejo</a>, <a href="https://publications.waset.org/abstracts/search?q=Raul%20Perez-Lopez"> Raul Perez-Lopez</a>, <a href="https://publications.waset.org/abstracts/search?q=Miguel%20Herraiz"> Miguel Herraiz</a>, <a href="https://publications.waset.org/abstracts/search?q=Carolina%20Guardiola-Albert"> Carolina Guardiola-Albert</a>, <a href="https://publications.waset.org/abstracts/search?q=Cesar%20Martinez"> Cesar Martinez</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Persistency, long-term memory and randomness are intrinsic properties of time-series of earthquakes. The Rescaled Range Analysis (RS-Analysis) was introduced by Hurst in 1956 and modified by Mandelbrot and Wallis in 1964. This method represents a simple and elegant analysis which determines the range of variation of one natural property (the seismic energy released in this case) in a time interval. Despite the simplicity, there is complexity inherent in the property measured. The cumulative curve of the energy released in time is the well-known fractal geometry of a devil’s staircase. This geometry is used for determining the maximum and minimum value of the range, which is normalized by the standard deviation. The rescaled range obtained obeys a power-law with the time, and the exponent is the Hurst value. Depending on this value, time-series can be classified in long-term or short-term memory. Hence, an algorithm has been developed for compiling the RS-Analysis for time series of earthquakes by days. Completeness time distribution and locally stationarity of the time series are required. The interest of this analysis is their application for a complex seismic crisis where different earthquakes take place in clusters in a short period. Therefore, the Hurst exponent has been obtained for the seismic crisis of Alhoceima (Mediterranean Sea) of January-March, 2016, where at least five medium-sized earthquakes were triggered. According to the values obtained from the Hurst exponent for each cluster, a different mechanical origin can be detected, corroborated by the focal mechanisms calculated by the official institutions. Therefore, this type of analysis not only allows an approach to a greater understanding of a seismic series but also makes possible to discern different types of seismic origins. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Alhoceima%20crisis" title="Alhoceima crisis">Alhoceima crisis</a>, <a href="https://publications.waset.org/abstracts/search?q=earthquake%20time%20series" title=" earthquake time series"> earthquake time series</a>, <a href="https://publications.waset.org/abstracts/search?q=Hurst%20exponent" title=" Hurst exponent"> Hurst exponent</a>, <a href="https://publications.waset.org/abstracts/search?q=rescaled%20range%20analysis" title=" rescaled range analysis"> rescaled range analysis</a> </p> <a href="https://publications.waset.org/abstracts/73744/rescaled-range-analysis-of-seismic-time-series-example-of-the-recent-seismic-crisis-of-alhoceima" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/73744.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">321</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">88</span> The Volume–Volatility Relationship Conditional to Market Efficiency</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Massimiliano%20Frezza">Massimiliano Frezza</a>, <a href="https://publications.waset.org/abstracts/search?q=Sergio%20Bianchi"> Sergio Bianchi</a>, <a href="https://publications.waset.org/abstracts/search?q=Augusto%20Pianese"> Augusto Pianese</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The relation between stock price volatility and trading volume represents a controversial issue which has received a remarkable attention over the past decades. In fact, an extensive literature shows a positive relation between price volatility and trading volume in the financial markets, but the causal relationship which originates such association is an open question, from both a theoretical and empirical point of view. In this regard, various models, which can be considered as complementary rather than competitive, have been introduced to explain this relationship. They include the long debated Mixture of Distributions Hypothesis (MDH); the Sequential Arrival of Information Hypothesis (SAIH); the Dispersion of Beliefs Hypothesis (DBH); the Noise Trader Hypothesis (NTH). In this work, we analyze whether stock market efficiency can explain the diversity of results achieved during the years. For this purpose, we propose an alternative measure of market efficiency, based on the pointwise regularity of a stochastic process, which is the Hurst–H¨older dynamic exponent. In particular, we model the stock market by means of the multifractional Brownian motion (mBm) that displays the property of a time-changing regularity. Mostly, such models have in common the fact that they locally behave as a fractional Brownian motion, in the sense that their local regularity at time t0 (measured by the local Hurst–H¨older exponent in a neighborhood of t0 equals the exponent of a fractional Brownian motion of parameter H(t0)). Assuming that the stock price follows an mBm, we introduce and theoretically justify the Hurst–H¨older dynamical exponent as a measure of market efficiency. This allows to measure, at any time t, markets’ departures from the martingale property, i.e. from efficiency as stated by the Efficient Market Hypothesis. This approach is applied to financial markets; using data for the SP500 index from 1978 to 2017, on the one hand we find that when efficiency is not accounted for, a positive contemporaneous relationship emerges and is stable over time. Conversely, it disappears as soon as efficiency is taken into account. In particular, this association is more pronounced during time frames of high volatility and tends to disappear when market becomes fully efficient. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=volume%E2%80%93volatility%20relationship" title="volume–volatility relationship">volume–volatility relationship</a>, <a href="https://publications.waset.org/abstracts/search?q=efficient%20market%20hypothesis" title=" efficient market hypothesis"> efficient market hypothesis</a>, <a href="https://publications.waset.org/abstracts/search?q=martingale%20model" title=" martingale model"> martingale model</a>, <a href="https://publications.waset.org/abstracts/search?q=Hurst%E2%80%93H%C3%B6lder%20exponent" title=" Hurst–Hölder exponent"> Hurst–Hölder exponent</a> </p> <a href="https://publications.waset.org/abstracts/165930/the-volume-volatility-relationship-conditional-to-market-efficiency" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/165930.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">78</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">87</span> FRATSAN: A New Software for Fractal Analysis of Signals</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Hamidreza%20Namazi">Hamidreza Namazi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Fractal analysis is assessing fractal characteristics of data. It consists of several methods to assign fractal characteristics to a dataset which may be a theoretical dataset or a pattern or signal extracted from phenomena including natural geometric objects, sound, market fluctuations, heart rates, digital images, molecular motion, networks, etc. Fractal analysis is now widely used in all areas of science. An important limitation of fractal analysis is that arriving at an empirically determined fractal dimension does not necessarily prove that a pattern is fractal; rather, other essential characteristics have to be considered. For this purpose a Visual C++ based software called FRATSAN (FRActal Time Series ANalyser) was developed which extract information from signals through three measures. These measures are Fractal Dimensions, Jeﬀrey’s Measure and Hurst Exponent. After computing these measures, the software plots the graphs for each measure. Besides computing three measures the software can classify whether the signal is fractal or no. In fact, the software uses a dynamic method of analysis for all the measures. A sliding window is selected with a value equal to 10% of the total number of data entries. This sliding window is moved one data entry at a time to obtain all the measures. This makes the computation very sensitive to slight changes in data, thereby giving the user an acute analysis of the data. In order to test the performance of this software a set of EEG signals was given as input and the results were computed and plotted. This software is useful not only for fundamental fractal analysis of signals but can be used for other purposes. For instance by analyzing the Hurst exponent plot of a given EEG signal in patients with epilepsy the onset of seizure can be predicted by noticing the sudden changes in the plot. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=EEG%20signals" title="EEG signals">EEG signals</a>, <a href="https://publications.waset.org/abstracts/search?q=fractal%20analysis" title=" fractal analysis"> fractal analysis</a>, <a href="https://publications.waset.org/abstracts/search?q=fractal%20dimension" title=" fractal dimension"> fractal dimension</a>, <a href="https://publications.waset.org/abstracts/search?q=hurst%20exponent" title=" hurst exponent"> hurst exponent</a>, <a href="https://publications.waset.org/abstracts/search?q=Je%EF%AC%80rey%E2%80%99s%20measure" title=" Jeﬀrey’s measure"> Jeﬀrey’s measure</a> </p> <a href="https://publications.waset.org/abstracts/18806/fratsan-a-new-software-for-fractal-analysis-of-signals" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/18806.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">467</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">86</span> The Non-Linear Analysis of Brain Response to Visual Stimuli</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=H.%20Namazi">H. Namazi</a>, <a href="https://publications.waset.org/abstracts/search?q=H.%20T.%20N.%20Kuan"> H. T. N. Kuan</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Brain activity can be measured by acquiring and analyzing EEG signals from an individual. In fact, the human brain response to external and internal stimuli is mapped in his EEG signals. During years some methods such as Fourier transform, wavelet transform, empirical mode decomposition, etc. have been used to analyze the EEG signals in order to find the effect of stimuli, especially external stimuli. But each of these methods has some weak points in analysis of EEG signals. For instance, Fourier transform and wavelet transform methods are linear signal analysis methods which are not good to be used for analysis of EEG signals as nonlinear signals. In this research we analyze the brain response to visual stimuli by extracting information in the form of various measures from EEG signals using a software developed by our research group. The used measures are Jeﬀrey’s measure, Fractal dimension and Hurst exponent. The results of these analyses are useful not only for fundamental understanding of brain response to visual stimuli but provide us with very good recommendations for clinical purposes. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=visual%20stimuli" title="visual stimuli">visual stimuli</a>, <a href="https://publications.waset.org/abstracts/search?q=brain%20response" title=" brain response"> brain response</a>, <a href="https://publications.waset.org/abstracts/search?q=EEG%20signal" title=" EEG signal"> EEG signal</a>, <a href="https://publications.waset.org/abstracts/search?q=fractal%20dimension" title=" fractal dimension"> fractal dimension</a>, <a href="https://publications.waset.org/abstracts/search?q=hurst%20exponent" title=" hurst exponent"> hurst exponent</a>, <a href="https://publications.waset.org/abstracts/search?q=Je%EF%AC%80rey%E2%80%99s%20measure" title=" Jeﬀrey’s measure"> Jeﬀrey’s measure</a> </p> <a href="https://publications.waset.org/abstracts/19758/the-non-linear-analysis-of-brain-response-to-visual-stimuli" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/19758.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">561</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">85</span> The Analysis of Brain Response to Auditory Stimuli through EEG Signals’ Non-Linear Analysis</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=H.%20Namazi">H. Namazi</a>, <a href="https://publications.waset.org/abstracts/search?q=H.%20T.%20N.%20Kuan"> H. T. N. Kuan</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Brain activity can be measured by acquiring and analyzing EEG signals from an individual. In fact, the human brain response to external and internal stimuli is mapped in his EEG signals. During years some methods such as Fourier transform, wavelet transform, empirical mode decomposition, etc. have been used to analyze the EEG signals in order to find the effect of stimuli, especially external stimuli. But each of these methods has some weak points in analysis of EEG signals. For instance, Fourier transform and wavelet transform methods are linear signal analysis methods which are not good to be used for analysis of EEG signals as nonlinear signals. In this research we analyze the brain response to auditory stimuli by extracting information in the form of various measures from EEG signals using a software developed by our research group. The used measures are Jeﬀrey’s measure, Fractal dimension and Hurst exponent. The results of these analyses are useful not only for fundamental understanding of brain response to auditory stimuli but provide us with very good recommendations for clinical purposes. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=auditory%20stimuli" title="auditory stimuli">auditory stimuli</a>, <a href="https://publications.waset.org/abstracts/search?q=brain%20response" title=" brain response"> brain response</a>, <a href="https://publications.waset.org/abstracts/search?q=EEG%20signal" title=" EEG signal"> EEG signal</a>, <a href="https://publications.waset.org/abstracts/search?q=fractal%20dimension" title=" fractal dimension"> fractal dimension</a>, <a href="https://publications.waset.org/abstracts/search?q=hurst%20exponent" title=" hurst exponent"> hurst exponent</a>, <a href="https://publications.waset.org/abstracts/search?q=Je%EF%AC%80rey%E2%80%99s%20measure" title=" Jeﬀrey’s measure"> Jeﬀrey’s measure</a> </p> <a href="https://publications.waset.org/abstracts/18990/the-analysis-of-brain-response-to-auditory-stimuli-through-eeg-signals-non-linear-analysis" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/18990.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">534</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">84</span> Signal Processing Approach to Study Multifractality and Singularity of Solar Wind Speed Time Series</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Tushnik%20Sarkar">Tushnik Sarkar</a>, <a href="https://publications.waset.org/abstracts/search?q=Mofazzal%20H.%20Khondekar"> Mofazzal H. Khondekar</a>, <a href="https://publications.waset.org/abstracts/search?q=Subrata%20Banerjee"> Subrata Banerjee</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper investigates the nature of the fluctuation of the daily average Solar wind speed time series collected over a period of 2492 days, from 1<sup>st </sup>January, 1997 to 28<sup>th</sup> October, 2003. The degree of self-similarity and scalability of the Solar Wind Speed signal has been explored to characterise the signal fluctuation. Multi-fractal Detrended Fluctuation Analysis (MFDFA) method has been implemented on the signal which is under investigation to perform this task. Furthermore, the singularity spectra of the signals have been also obtained to gauge the extent of the multifractality of the time series signal. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=detrended%20fluctuation%20analysis" title="detrended fluctuation analysis">detrended fluctuation analysis</a>, <a href="https://publications.waset.org/abstracts/search?q=generalized%20hurst%20exponent" title=" generalized hurst exponent"> generalized hurst exponent</a>, <a href="https://publications.waset.org/abstracts/search?q=holder%20exponents" title=" holder exponents"> holder exponents</a>, <a href="https://publications.waset.org/abstracts/search?q=multifractal%20exponent" title=" multifractal exponent"> multifractal exponent</a>, <a href="https://publications.waset.org/abstracts/search?q=multifractal%20spectrum" title=" multifractal spectrum"> multifractal spectrum</a>, <a href="https://publications.waset.org/abstracts/search?q=singularity%20spectrum" title=" singularity spectrum"> singularity spectrum</a>, <a href="https://publications.waset.org/abstracts/search?q=time%20series%20analysis" title=" time series analysis"> time series analysis</a> </p> <a href="https://publications.waset.org/abstracts/62350/signal-processing-approach-to-study-multifractality-and-singularity-of-solar-wind-speed-time-series" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/62350.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">393</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">83</span> Behavior of Clay effect on Electrical Parameter of Reservoir Rock Using Global Hydraulic Elements (GHEs) Approach </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Noreddin%20Mousa">Noreddin Mousa</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The main objective of this study is to estimate which type of clay minerals that more effect on saturation exponent using Global Hydraulic Elements (GHEs) approach to estimating the distribution of saturation exponent factor. Two wells and seven core samples have been selected from various (GHEs) for detailed study. There are many factors affecting saturation exponent such as wettability, grain pattern pressure of certain authigenic clays, which may promote oil wet characteristics of history of fluid displacement. The saturation exponent is related to the texture and affected by wettability and clay minerals. Capillary pressure (mercury injection) has been used to confirm GHEs which are selected to define rock types; the porous plate method is used to derive the saturation exponent in the laboratory. The petrography is very important in order to study the mineralogy and texture. In this study the results showing excellent relation between saturation exponent and the type of clay minerals which was observed that the Global Hydraulic Elements GHE-2 and GHE-5 which are containing Chlorite is more affect on saturation exponent comparing with the other GHE’s. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=GHEs" title="GHEs">GHEs</a>, <a href="https://publications.waset.org/abstracts/search?q=wettability" title=" wettability"> wettability</a>, <a href="https://publications.waset.org/abstracts/search?q=global%20hydraulic%20elements" title=" global hydraulic elements"> global hydraulic elements</a>, <a href="https://publications.waset.org/abstracts/search?q=petrography" title=" petrography "> petrography </a> </p> <a href="https://publications.waset.org/abstracts/3162/behavior-of-clay-effect-on-electrical-parameter-of-reservoir-rock-using-global-hydraulic-elements-ghes-approach" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/3162.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">301</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">82</span> Approximation of the Time Series by Fractal Brownian Motion</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Valeria%20Bondarenko">Valeria Bondarenko</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, we propose two problems related to fractal Brownian motion. First problem is simultaneous estimation of two parameters, Hurst exponent and the volatility, that describe this random process. Numerical tests for the simulated fBm provided an efficient method. Second problem is approximation of the increments of the observed time series by a power function by increments from the fractional Brownian motion. Approximation and estimation are shown on the example of real data, daily deposit interest rates. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=fractional%20Brownian%20motion" title="fractional Brownian motion">fractional Brownian motion</a>, <a href="https://publications.waset.org/abstracts/search?q=Gausssian%20processes" title=" Gausssian processes"> Gausssian processes</a>, <a href="https://publications.waset.org/abstracts/search?q=approximation" title=" approximation"> approximation</a>, <a href="https://publications.waset.org/abstracts/search?q=time%20series" title=" time series"> time series</a>, <a href="https://publications.waset.org/abstracts/search?q=estimation%20of%20properties%20of%20the%20model" title=" estimation of properties of the model"> estimation of properties of the model</a> </p> <a href="https://publications.waset.org/abstracts/4285/approximation-of-the-time-series-by-fractal-brownian-motion" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/4285.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">376</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">81</span> The Modelling of Real Time Series Data</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Valeria%20Bondarenko">Valeria Bondarenko</a> </p> <p class="card-text"><strong>Abstract:</strong></p> We proposed algorithms for: estimation of parameters fBm (volatility and Hurst exponent) and for the approximation of random time series by functional of fBm. We proved the consistency of the estimators, which constitute the above algorithms, and proved the optimal forecast of approximated time series. The adequacy of estimation algorithms, approximation, and forecasting is proved by numerical experiment. During the process of creating software, the system has been created, which is displayed by the hierarchical structure. The comparative analysis of proposed algorithms with the other methods gives evidence of the advantage of approximation method. The results can be used to develop methods for the analysis and modeling of time series describing the economic, physical, biological and other processes. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=mathematical%20model" title="mathematical model">mathematical model</a>, <a href="https://publications.waset.org/abstracts/search?q=random%20process" title=" random process"> random process</a>, <a href="https://publications.waset.org/abstracts/search?q=Wiener%20process" title=" Wiener process"> Wiener process</a>, <a href="https://publications.waset.org/abstracts/search?q=fractional%20Brownian%20motion" title=" fractional Brownian motion"> fractional Brownian motion</a> </p> <a href="https://publications.waset.org/abstracts/49210/the-modelling-of-real-time-series-data" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/49210.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">357</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">80</span> Assessment of Petrophysical Parameters Using Well Log and Core Data</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Khulud%20M.%20Rahuma">Khulud M. Rahuma</a>, <a href="https://publications.waset.org/abstracts/search?q=Ibrahim%20B.%20Younis"> Ibrahim B. Younis</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Assessment of petrophysical parameters are very essential for reservoir engineer. Three techniques can be used to predict reservoir properties: well logging, well testing, and core analysis. Cementation factor and saturation exponent are very required for calculation, and their values role a great effect on water saturation estimation. In this study a sensitive analysis was performed to investigate the influence of cementation factor and saturation exponent variation applying logs, and core analysis. Measurements of water saturation resulted in a maximum difference around fifteen percent. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=porosity" title="porosity">porosity</a>, <a href="https://publications.waset.org/abstracts/search?q=cementation%20factor" title=" cementation factor"> cementation factor</a>, <a href="https://publications.waset.org/abstracts/search?q=saturation%20exponent" title=" saturation exponent"> saturation exponent</a>, <a href="https://publications.waset.org/abstracts/search?q=formation%20factor" title=" formation factor"> formation factor</a>, <a href="https://publications.waset.org/abstracts/search?q=water%20saturation" title=" water saturation"> water saturation</a> </p> <a href="https://publications.waset.org/abstracts/11077/assessment-of-petrophysical-parameters-using-well-log-and-core-data" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/11077.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">693</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">79</span> Informational Efficiency and Integration: Evidence from Gulf Cooperation Council (GCC) Shariah Equity Market</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Sania%20Ashraf">Sania Ashraf</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The paper focuses on the prevalence of informational efficiency and integration of GCC Shariah Equity market for the period of 01st January 2010 to 31st June 2015 with daily equity returns of Kuwait, Oman, Qatar, Bahrain, Saudi Arabia and United Arab Emirates. The study employs traditional as well as the modern approach of tracing out the efficiency and integration in the return series. From the results of efficiency it was observed that the market lacked efficiency in terms of its past information. The results of integration test clearly indicates that there was a long memory in the returns of GCC Shariah during the study period. Hence it was concluded and proved that the returns of all GCC Equity Shariah were not informationally efficient but fractionally integrated during the study period. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=efficiency" title="efficiency">efficiency</a>, <a href="https://publications.waset.org/abstracts/search?q=Fama" title=" Fama"> Fama</a>, <a href="https://publications.waset.org/abstracts/search?q=GCC%20shariah" title=" GCC shariah"> GCC shariah</a>, <a href="https://publications.waset.org/abstracts/search?q=hurst%20exponent" title=" hurst exponent"> hurst exponent</a>, <a href="https://publications.waset.org/abstracts/search?q=integration" title=" integration"> integration</a>, <a href="https://publications.waset.org/abstracts/search?q=serial%20correlation" title=" serial correlation"> serial correlation</a> </p> <a href="https://publications.waset.org/abstracts/50792/informational-efficiency-and-integration-evidence-from-gulf-cooperation-council-gcc-shariah-equity-market" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/50792.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">362</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">78</span> Factors Affecting Special Core Analysis Resistivity Parameters</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Hassan%20Sbiga">Hassan Sbiga</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Laboratory measurements methods were undertaken on core samples selected from three different fields (A, B, and C) from the Nubian Sandstone Formation of the central graben reservoirs in Libya. These measurements were conducted in order to determine the factors which affect resistivity parameters, and to investigate the effect of rock heterogeneity and wettability on these parameters. This included determining the saturation exponent (n) in the laboratory at two stages. The first stage was before wettability measurements were conducted on the samples, and the second stage was after the wettability measurements in order to find any effect on the saturation exponent. Another objective of this work was to quantify experimentally pores and porosity types (macro- and micro-porosity), which have an affect on the electrical properties, by integrating capillary pressure curves with other routine and special core analysis. These experiments were made for the first time to obtain a relation between pore size distribution and saturation exponent n. Changes were observed in the formation resistivity factor and cementation exponent due to ambient conditions and changes of overburden pressure. The cementation exponent also decreased from GHE-5 to GHE-8. Changes were also observed in the saturation exponent (n) and water saturation (Sw) before and after wettability measurement. Samples with an oil-wet tendency have higher irreducible brine saturation and higher Archie saturation exponent values than samples with an uniform water-wet surface. The experimental results indicate that there is a good relation between resistivity and pore type depending on the pore size. When oil begins to penetrate micro-pore systems in measurements of resistivity index versus brine saturation (after wettability measurement), a significant change in slope of the resistivity index relationship occurs. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=part%20of%20thesis" title="part of thesis">part of thesis</a>, <a href="https://publications.waset.org/abstracts/search?q=cementation" title=" cementation"> cementation</a>, <a href="https://publications.waset.org/abstracts/search?q=wettability" title=" wettability"> wettability</a>, <a href="https://publications.waset.org/abstracts/search?q=resistivity" title=" resistivity"> resistivity</a> </p> <a href="https://publications.waset.org/abstracts/3160/factors-affecting-special-core-analysis-resistivity-parameters" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/3160.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">246</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">77</span> An Efficient Discrete Chaos in Generalized Logistic Maps with Applications in Image Encryption </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ashish%20Ashish">Ashish Ashish</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In the last few decades, the discrete chaos of difference equations has gained a massive attention of academicians and scholars due to its tremendous applications in each and every branch of science, such as cryptography, traffic control models, secure communications, weather forecasting, and engineering. In this article, a generalized logistic discrete map is established and discrete chaos is reported through period doubling bifurcation, period three orbit and Lyapunov exponent. It is interesting to see that the generalized logistic map exhibits superior chaos due to the presence of an extra degree of freedom of an ordered parameter. The period doubling bifurcation and Lyapunov exponent are demonstrated for some particular values of parameter and the discrete chaos is determined in the sense of Devaney's definition of chaos theoretically as well as numerically. Moreover, the study discusses an extended chaos based image encryption and decryption scheme in cryptography using this novel system. Surprisingly, a larger key space for coding and more sensitive dependence on initial conditions are examined for encryption and decryption of text messages, images and videos which secure the system strongly from external cyber attacks, coding attacks, statistic attacks and differential attacks. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=chaos" title="chaos">chaos</a>, <a href="https://publications.waset.org/abstracts/search?q=period-doubling" title=" period-doubling"> period-doubling</a>, <a href="https://publications.waset.org/abstracts/search?q=logistic%20map" title=" logistic map"> logistic map</a>, <a href="https://publications.waset.org/abstracts/search?q=Lyapunov%20exponent" title=" Lyapunov exponent"> Lyapunov exponent</a>, <a href="https://publications.waset.org/abstracts/search?q=image%20encryption" title=" image encryption"> image encryption</a> </p> <a href="https://publications.waset.org/abstracts/112408/an-efficient-discrete-chaos-in-generalized-logistic-maps-with-applications-in-image-encryption" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/112408.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">151</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">76</span> Analysis of Epileptic Electroencephalogram Using Detrended Fluctuation and Recurrence Plots</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mrinalini%20Ranjan">Mrinalini Ranjan</a>, <a href="https://publications.waset.org/abstracts/search?q=Sudheesh%20Chethil"> Sudheesh Chethil</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Epilepsy is a common neurological disorder characterised by the recurrence of seizures. Electroencephalogram (EEG) signals are complex biomedical signals which exhibit nonlinear and nonstationary behavior. We use two methods 1) Detrended Fluctuation Analysis (DFA) and 2) Recurrence Plots (RP) to capture this complex behavior of EEG signals. DFA considers fluctuation from local linear trends. Scale invariance of these signals is well captured in the multifractal characterisation using detrended fluctuation analysis (DFA). Analysis of long-range correlations is vital for understanding the dynamics of EEG signals. Correlation properties in the EEG signal are quantified by the calculation of a scaling exponent. We report the existence of two scaling behaviours in the epileptic EEG signals which quantify short and long-range correlations. To illustrate this, we perform DFA on extant ictal (seizure) and interictal (seizure free) datasets of different patients in different channels. We compute the short term and long scaling exponents and report a decrease in short range scaling exponent during seizure as compared to pre-seizure and a subsequent increase during post-seizure period, while the long-term scaling exponent shows an increase during seizure activity. Our calculation of long-term scaling exponent yields a value between 0.5 and 1, thus pointing to power law behaviour of long-range temporal correlations (LRTC). We perform this analysis for multiple channels and report similar behaviour. We find an increase in the long-term scaling exponent during seizure in all channels, which we attribute to an increase in persistent LRTC during seizure. The magnitude of the scaling exponent and its distribution in different channels can help in better identification of areas in brain most affected during seizure activity. The nature of epileptic seizures varies from patient-to-patient. To illustrate this, we report an increase in long-term scaling exponent for some patients which is also complemented by the recurrence plots (RP). RP is a graph that shows the time index of recurrence of a dynamical state. We perform Recurrence Quantitative analysis (RQA) and calculate RQA parameters like diagonal length, entropy, recurrence, determinism, etc. for ictal and interictal datasets. We find that the RQA parameters increase during seizure activity, indicating a transition. We observe that RQA parameters are higher during seizure period as compared to post seizure values, whereas for some patients post seizure values exceeded those during seizure. We attribute this to varying nature of seizure in different patients indicating a different route or mechanism during the transition. Our results can help in better understanding of the characterisation of epileptic EEG signals from a nonlinear analysis. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=detrended%20fluctuation" title="detrended fluctuation">detrended fluctuation</a>, <a href="https://publications.waset.org/abstracts/search?q=epilepsy" title=" epilepsy"> epilepsy</a>, <a href="https://publications.waset.org/abstracts/search?q=long%20range%20correlations" title=" long range correlations"> long range correlations</a>, <a href="https://publications.waset.org/abstracts/search?q=recurrence%20plots" title=" recurrence plots"> recurrence plots</a> </p> <a href="https://publications.waset.org/abstracts/84822/analysis-of-epileptic-electroencephalogram-using-detrended-fluctuation-and-recurrence-plots" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/84822.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">176</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">75</span> 2D Monte Carlo Simulation of Grain Growth under Transient Conditions</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=K.%20R.%20Phaneesh">K. R. Phaneesh</a>, <a href="https://publications.waset.org/abstracts/search?q=Anirudh%20Bhat"> Anirudh Bhat</a>, <a href="https://publications.waset.org/abstracts/search?q=G.%20Mukherjee"> G. Mukherjee</a>, <a href="https://publications.waset.org/abstracts/search?q=K.%20T.%20Kashyap"> K. T. Kashyap</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Extensive Monte Carlo Potts model simulations were performed on 2D square lattice to investigate the effects of simulated higher temperatures effects on grain growth kinetics. A range of simulation temperatures (KTs) were applied on a matrix of size 10002 with Q-state 64, dispersed with a wide range of second phase particles, ranging from 0.001 to 0.1, and then run to 100,000 Monte Carlo steps. The average grain size, the largest grain size and the grain growth exponent were evaluated for all particle fractions and simulated temperatures. After evaluating several growth parameters, the critical temperature for a square lattice, with eight nearest neighbors, was found to be KTs = 0.4. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=average%20grain%20size" title="average grain size">average grain size</a>, <a href="https://publications.waset.org/abstracts/search?q=critical%20temperature" title=" critical temperature"> critical temperature</a>, <a href="https://publications.waset.org/abstracts/search?q=grain%20growth%20exponent" title=" grain growth exponent"> grain growth exponent</a>, <a href="https://publications.waset.org/abstracts/search?q=Monte%20Carlo%20steps" title=" Monte Carlo steps"> Monte Carlo steps</a> </p> <a href="https://publications.waset.org/abstracts/26332/2d-monte-carlo-simulation-of-grain-growth-under-transient-conditions" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/26332.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">523</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">74</span> The Shannon Entropy and Multifractional Markets</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Massimiliano%20Frezza">Massimiliano Frezza</a>, <a href="https://publications.waset.org/abstracts/search?q=Sergio%20Bianchi"> Sergio Bianchi</a>, <a href="https://publications.waset.org/abstracts/search?q=Augusto%20Pianese"> Augusto Pianese</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Introduced by Shannon in 1948 in the field of information theory as the average rate at which information is produced by a stochastic set of data, the concept of entropy has gained much attention as a measure of uncertainty and unpredictability associated with a dynamical system, eventually depicted by a stochastic process. In particular, the Shannon entropy measures the degree of order/disorder of a given signal and provides useful information about the underlying dynamical process. It has found widespread application in a variety of fields, such as, for example, cryptography, statistical physics and finance. In this regard, many contributions have employed different measures of entropy in an attempt to characterize the financial time series in terms of market efficiency, market crashes and/or financial crises. The Shannon entropy has also been considered as a measure of the risk of a portfolio or as a tool in asset pricing. This work investigates the theoretical link between the Shannon entropy and the multifractional Brownian motion (mBm), stochastic process which recently is the focus of a renewed interest in finance as a driving model of stochastic volatility. In particular, after exploring the current state of research in this area and highlighting some of the key results and open questions that remain, we show a well-defined relationship between the Shannon (log)entropy and the memory function H(t) of the mBm. In details, we allow both the length of time series and time scale to change over analysis to study how the relation modify itself. On the one hand, applications are developed after generating surrogates of mBm trajectories based on different memory functions; on the other hand, an empirical analysis of several international stock indexes, which confirms the previous results, concludes the work. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Shannon%20entropy" title="Shannon entropy">Shannon entropy</a>, <a href="https://publications.waset.org/abstracts/search?q=multifractional%20Brownian%20motion" title=" multifractional Brownian motion"> multifractional Brownian motion</a>, <a href="https://publications.waset.org/abstracts/search?q=Hurst%E2%80%93Holder%20exponent" title=" Hurst–Holder exponent"> Hurst–Holder exponent</a>, <a href="https://publications.waset.org/abstracts/search?q=stock%20indexes" title=" stock indexes"> stock indexes</a> </p> <a href="https://publications.waset.org/abstracts/166023/the-shannon-entropy-and-multifractional-markets" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/166023.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">110</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">73</span> Lyapunov Exponents in the Restricted Three Body Problem under the Influence of Perturbations</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ram%20Kishor">Ram Kishor</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The Lyapunov characteristic exponent (LCE) is an important tool to describe behavior of a dynamical system, which measures the average rate of divergence (or convergence) of a trajectory emanating in the vicinity of initial point. To analyze the behavior of nearby trajectory emanating in the neighborhood of an equilibrium point in the restricted three-body problem under the influence of perturbations in the form of radiation pressure and oblateness, we compute LCEs of first order with the help of slandered method which is based on variational equation of the system. It is observed that trajectories are chaotic in nature due positive LCEs. Also, we analyze the effect of radiation pressure and oblateness on the LCEs. Results are applicable to study the behavior of more generalized RTBP in the presence of perturbations such as PR drag, solar wind drag etc. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Lyapunov%20characteristic%20exponent" title="Lyapunov characteristic exponent">Lyapunov characteristic exponent</a>, <a href="https://publications.waset.org/abstracts/search?q=RTBP" title=" RTBP"> RTBP</a>, <a href="https://publications.waset.org/abstracts/search?q=radiation%20pressure" title=" radiation pressure"> radiation pressure</a>, <a href="https://publications.waset.org/abstracts/search?q=oblateness" title=" oblateness"> oblateness</a> </p> <a href="https://publications.waset.org/abstracts/49916/lyapunov-exponents-in-the-restricted-three-body-problem-under-the-influence-of-perturbations" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/49916.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">443</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">72</span> Reconsidering Taylor’s Law with Chaotic Population Dynamical Systems</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Yuzuru%20Mitsui">Yuzuru Mitsui</a>, <a href="https://publications.waset.org/abstracts/search?q=Takashi%20Ikegami"> Takashi Ikegami</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The exponents of Taylor’s law in deterministic chaotic systems are computed, and their meanings are intensively discussed. Taylor’s law is the scaling relationship between the mean and variance (in both space and time) of population abundance, and this law is known to hold in a variety of ecological time series. The exponents found in the temporal Taylor’s law are different from those of the spatial Taylor’s law. The temporal Taylor’s law is calculated on the time series from the same locations (or the same initial states) of different temporal phases. However, with the spatial Taylor’s law, the mean and variance are calculated from the same temporal phase sampled from different places. Most previous studies were done with stochastic models, but we computed the temporal and spatial Taylor’s law in deterministic systems. The temporal Taylor’s law evaluated using the same initial state, and the spatial Taylor’s law was evaluated using the ensemble average and variance. There were two main discoveries from this work. First, it is often stated that deterministic systems tend to have the value two for Taylor’s exponent. However, most of the calculated exponents here were not two. Second, we investigated the relationships between chaotic features measured by the Lyapunov exponent, the correlation dimension, and other indexes with Taylor’s exponents. No strong correlations were found; however, there is some relationship in the same model, but with different parameter values, and we will discuss the meaning of those results at the end of this paper. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=chaos" title="chaos">chaos</a>, <a href="https://publications.waset.org/abstracts/search?q=density%20effect" title=" density effect"> density effect</a>, <a href="https://publications.waset.org/abstracts/search?q=population%20dynamics" title=" population dynamics"> population dynamics</a>, <a href="https://publications.waset.org/abstracts/search?q=Taylor%E2%80%99s%20law" title=" Taylor’s law"> Taylor’s law</a> </p> <a href="https://publications.waset.org/abstracts/109945/reconsidering-taylors-law-with-chaotic-population-dynamical-systems" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/109945.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">174</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">71</span> Modelling of Creep in a Thick-Walled Cylindrical Vessel Subjected to Internal Pressure</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Tejeet%20Singh">Tejeet Singh</a>, <a href="https://publications.waset.org/abstracts/search?q=Ishvneet%20Singh"> Ishvneet Singh</a>, <a href="https://publications.waset.org/abstracts/search?q=Vinay%20Gupta"> Vinay Gupta</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The present study focussed on carrying out the creep analysis in an isotropic thick-walled composite cylindrical pressure vessel composed of aluminium matrix reinforced with silicon-carbide in particulate form. The creep behaviour of the composite material has been described by the threshold stress based creep law. The value of stress exponent appearing in the creep law was selected as 3, 5 and 8. The constitutive equations were developed using well known von-Mises yield criteria. Models were developed to find out the distributions of creep stresses and strain rate in thick-walled composite cylindrical pressure vessels under internal pressure. In order to obtain the stress distributions in the cylinder, the equilibrium equation of the continuum mechanics and the constitutive equations are solved together. It was observed that the radial stress, tangential stress and axial stress increases along with the radial distance. The cross-over was also obtained almost at the middle region of cylindrical vessel for tangential and axial stress for different values of stress exponent. The strain rates were also decreasing in nature along the entire radius. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=creep" title="creep">creep</a>, <a href="https://publications.waset.org/abstracts/search?q=composite" title=" composite"> composite</a>, <a href="https://publications.waset.org/abstracts/search?q=cylindrical%20vessel" title=" cylindrical vessel"> cylindrical vessel</a>, <a href="https://publications.waset.org/abstracts/search?q=internal%20pressure" title=" internal pressure"> internal pressure</a> </p> <a href="https://publications.waset.org/abstracts/23762/modelling-of-creep-in-a-thick-walled-cylindrical-vessel-subjected-to-internal-pressure" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/23762.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">576</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">70</span> Modeling of Steady State Creep in Thick-Walled Cylinders under Internal Pressure</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Tejeet%20Singh">Tejeet Singh</a>, <a href="https://publications.waset.org/abstracts/search?q=Ishavneet%20Singh"> Ishavneet Singh</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The present study focused on carrying out the creep analysis in an isotropic thick-walled composite cylindrical pressure vessel composed of aluminum matrix reinforced with silicon-carbide in particulate form. The creep behavior of the composite material has been described by the threshold stress based creep law. The values of stress exponent appearing in the creep law were selected as 3, 5 and 8. The constitutive equations were developed using well known von-Mises yield criteria. Models were developed to find out the distributions of creep stress and strain rate in thick-walled composite cylindrical pressure vessels under internal pressure. In order to obtain the stress distributions in the cylinder, the equilibrium equation of the continuum mechanics and the constitutive equations are solved together. It was observed that the radial stress, tangential stress and axial stress increases along with the radial distance. The cross-over was also obtained almost at the middle region of cylindrical vessel for tangential and axial stress for different values of stress exponent. The strain rates were also decreasing in nature along the entire radius. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=steady%20state%20creep" title="steady state creep">steady state creep</a>, <a href="https://publications.waset.org/abstracts/search?q=composite" title=" composite"> composite</a>, <a href="https://publications.waset.org/abstracts/search?q=cylinder" title=" cylinder"> cylinder</a>, <a href="https://publications.waset.org/abstracts/search?q=pressure" title=" pressure"> pressure</a> </p> <a href="https://publications.waset.org/abstracts/44079/modeling-of-steady-state-creep-in-thick-walled-cylinders-under-internal-pressure" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/44079.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">417</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">69</span> Gestalt in Music and Brain: A Non-Linear Chaos Based Study with Detrended/Adaptive Fractal Analysis</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Shankha%20Sanyal">Shankha Sanyal</a>, <a href="https://publications.waset.org/abstracts/search?q=Archi%20Banerjee"> Archi Banerjee</a>, <a href="https://publications.waset.org/abstracts/search?q=Sayan%20Biswas"> Sayan Biswas</a>, <a href="https://publications.waset.org/abstracts/search?q=Sourya%20Sengupta"> Sourya Sengupta</a>, <a href="https://publications.waset.org/abstracts/search?q=Sayan%20Nag"> Sayan Nag</a>, <a href="https://publications.waset.org/abstracts/search?q=Ranjan%20Sengupta"> Ranjan Sengupta</a>, <a href="https://publications.waset.org/abstracts/search?q=Dipak%20Ghosh"> Dipak Ghosh</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The term ‘gestalt’ has been widely used in the field of psychology which defined the perception of human mind to group any object not in part but as a 'unified' whole. Music, in general, is polyphonic - i.e. a combination of a number of pure tones (frequencies) mixed together in a manner that sounds harmonious. The study of human brain response due to different frequency groups of the acoustic signal can give us an excellent insight regarding the neural and functional architecture of brain functions. Hence, the study of music cognition using neuro-biosensors is becoming a rapidly emerging field of research. In this work, we have tried to analyze the effect of different frequency bands of music on the various frequency rhythms of human brain obtained from EEG data. Four widely popular Rabindrasangeet clips were subjected to Wavelet Transform method for extracting five resonant frequency bands from the original music signal. These frequency bands were initially analyzed with Detrended/Adaptive Fractal analysis (DFA/AFA) methods. A listening test was conducted on a pool of 100 respondents to assess the frequency band in which the music becomes non-recognizable. Next, these resonant frequency bands were presented to 20 subjects as auditory stimulus and EEG signals recorded simultaneously in 19 different locations of the brain. The recorded EEG signals were noise cleaned and subjected again to DFA/AFA technique on the alpha, theta and gamma frequency range. Thus, we obtained the scaling exponents from the two methods in alpha, theta and gamma EEG rhythms corresponding to different frequency bands of music. From the analysis of music signal, it is seen that loss of recognition is proportional to the loss of long range correlation in the signal. From the EEG signal analysis, we obtain frequency specific arousal based response in different lobes of brain as well as in specific EEG bands corresponding to musical stimuli. In this way, we look to identify a specific frequency band beyond which the music becomes non-recognizable and below which in spite of the absence of other bands the music is perceivable to the audience. This revelation can be of immense importance when it comes to the field of cognitive music therapy and researchers of creativity. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=AFA" title="AFA">AFA</a>, <a href="https://publications.waset.org/abstracts/search?q=DFA" title=" DFA"> DFA</a>, <a href="https://publications.waset.org/abstracts/search?q=EEG" title=" EEG"> EEG</a>, <a href="https://publications.waset.org/abstracts/search?q=gestalt%20in%20music" title=" gestalt in music"> gestalt in music</a>, <a href="https://publications.waset.org/abstracts/search?q=Hurst%20exponent" title=" Hurst exponent"> Hurst exponent</a> </p> <a href="https://publications.waset.org/abstracts/71039/gestalt-in-music-and-brain-a-non-linear-chaos-based-study-with-detrendedadaptive-fractal-analysis" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/71039.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">332</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">68</span> A New Correlation Between SPT-N and SSPT-N values for Various Soil Types in Peninsular Malaysia</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Abdull%20Halim">Abdull Halim</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The Standard Penetration Test (SPT-N) is the most common in situ test for soil investigations. The Shearing Seismic Standard Penetration Test (SSPT-N), on the other hand, is a new method using shearing wave with propagation exponent equation between the shearing wave, Vs., and hardness, N values without any need for borehole data. Due to the fast and accurate results that can be obtained, the SSPT has found many applications such as in the field rectification buried pipe line, the acid tank settlement and foundation design analyses, and the quality control assessment. Many geotechnical regimes and properties have attempted to correlate both the SSPT and the SPT-N values. Various foundation design methods have been developed based on the outcomes of these tests. Hence, it is pertinent to correlate these tests so that either one of the test can be used in the absence of the other, especially for preliminary evaluation and design purposes. The primary purpose of this study was to investigate the relationship between the SSPT-N and SPT-N values for different types of cohesive soil in Peninsular Malaysia. Data were collected from four different sites, and the correlations were established between the hardness N values, principal stress-strain Mohr circle curve, cohesion, friction angle and vertical effective stress. A positive exponent relationship was found between the shearing wave, sVs., and the hardness N values of the soil. In general, the SSPT-N value was slightly lower than the SPT-N value due to the upper limit boundary of the soil layer. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=InsituSoil%20determination%3B%20shearing%20wave%3B%20hardness%3B%20correlation" title="InsituSoil determination; shearing wave; hardness; correlation">InsituSoil determination; shearing wave; hardness; correlation</a>, <a href="https://publications.waset.org/abstracts/search?q=SSPT-N" title=" SSPT-N"> SSPT-N</a>, <a href="https://publications.waset.org/abstracts/search?q=SPT-N" title=" SPT-N"> SPT-N</a> </p> <a href="https://publications.waset.org/abstracts/140327/a-new-correlation-between-spt-n-and-sspt-n-values-for-various-soil-types-in-peninsular-malaysia" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/140327.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">184</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">67</span> A Convergent Interacting Particle Method for Computing Kpp Front Speeds in Random Flows</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Tan%20Zhang">Tan Zhang</a>, <a href="https://publications.waset.org/abstracts/search?q=Zhongjian%20Wang"> Zhongjian Wang</a>, <a href="https://publications.waset.org/abstracts/search?q=Jack%20Xin"> Jack Xin</a>, <a href="https://publications.waset.org/abstracts/search?q=Zhiwen%20Zhang"> Zhiwen Zhang</a> </p> <p class="card-text"><strong>Abstract:</strong></p> We aim to efficiently compute the spreading speeds of reaction-diffusion-advection (RDA) fronts in divergence-free random flows under the Kolmogorov-Petrovsky-Piskunov (KPP) nonlinearity. We study a stochastic interacting particle method (IPM) for the reduced principal eigenvalue (Lyapunov exponent) problem of an associated linear advection-diffusion operator with spatially random coefficients. The Fourier representation of the random advection field and the Feynman-Kac (FK) formula of the principal eigenvalue (Lyapunov exponent) form the foundation of our method implemented as a genetic evolution algorithm. The particles undergo advection-diffusion and mutation/selection through a fitness function originated in the FK semigroup. We analyze the convergence of the algorithm based on operator splitting and present numerical results on representative flows such as 2D cellular flow and 3D Arnold-Beltrami-Childress (ABC) flow under random perturbations. The 2D examples serve as a consistency check with semi-Lagrangian computation. The 3D results demonstrate that IPM, being mesh-free and self-adaptive, is simple to implement and efficient for computing front spreading speeds in the advection-dominated regime for high-dimensional random flows on unbounded domains where no truncation is needed. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=KPP%20front%20speeds" title="KPP front speeds">KPP front speeds</a>, <a href="https://publications.waset.org/abstracts/search?q=random%20flows" title=" random flows"> random flows</a>, <a href="https://publications.waset.org/abstracts/search?q=Feynman-Kac%20semigroups" title=" Feynman-Kac semigroups"> Feynman-Kac semigroups</a>, <a href="https://publications.waset.org/abstracts/search?q=interacting%20particle%20method" title=" interacting particle method"> interacting particle method</a>, <a href="https://publications.waset.org/abstracts/search?q=convergence%20analysis" title=" convergence analysis"> convergence analysis</a> </p> <a href="https://publications.waset.org/abstracts/185128/a-convergent-interacting-particle-method-for-computing-kpp-front-speeds-in-random-flows" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/185128.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">46</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">66</span> Comprehensive Analysis of Electrohysterography Signal Features in Term and Preterm Labor</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Zhihui%20Liu">Zhihui Liu</a>, <a href="https://publications.waset.org/abstracts/search?q=Dongmei%20Hao"> Dongmei Hao</a>, <a href="https://publications.waset.org/abstracts/search?q=Qian%20Qiu"> Qian Qiu</a>, <a href="https://publications.waset.org/abstracts/search?q=Yang%20An"> Yang An</a>, <a href="https://publications.waset.org/abstracts/search?q=Lin%20Yang"> Lin Yang</a>, <a href="https://publications.waset.org/abstracts/search?q=Song%20Zhang"> Song Zhang</a>, <a href="https://publications.waset.org/abstracts/search?q=Yimin%20Yang"> Yimin Yang</a>, <a href="https://publications.waset.org/abstracts/search?q=Xuwen%20Li"> Xuwen Li</a>, <a href="https://publications.waset.org/abstracts/search?q=Dingchang%20Zheng"> Dingchang Zheng</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Premature birth, defined as birth before 37 completed weeks of gestation is a leading cause of neonatal morbidity and mortality and has long-term adverse consequences for health. It has recently been reported that the worldwide preterm birth rate is around 10%. The existing measurement techniques for diagnosing preterm delivery include tocodynamometer, ultrasound and fetal fibronectin. However, they are subjective, or suffer from high measurement variability and inaccurate diagnosis and prediction of preterm labor. Electrohysterography (EHG) method based on recording of uterine electrical activity by electrodes attached to maternal abdomen, is a promising method to assess uterine activity and diagnose preterm labor. The purpose of this study is to analyze the difference of EHG signal features between term labor and preterm labor. Free access database was used with 300 signals acquired in two groups of pregnant women who delivered at term (262 cases) and preterm (38 cases). Among them, EHG signals from 38 term labor and 38 preterm labor were preprocessed with band-pass Butterworth filters of 0.08–4Hz. Then, EHG signal features were extracted, which comprised classical time domain description including root mean square and zero-crossing number, spectral parameters including peak frequency, mean frequency and median frequency, wavelet packet coefficients, autoregression (AR) model coefficients, and nonlinear measures including maximal Lyapunov exponent, sample entropy and correlation dimension. Their statistical significance for recognition of two groups of recordings was provided. The results showed that mean frequency of preterm labor was significantly smaller than term labor (p < 0.05). 5 coefficients of AR model showed significant difference between term labor and preterm labor. The maximal Lyapunov exponent of early preterm (time of recording < the 26th week of gestation) was significantly smaller than early term. The sample entropy of late preterm (time of recording > the 26th week of gestation) was significantly smaller than late term. There was no significant difference for other features between the term labor and preterm labor groups. Any future work regarding classification should therefore focus on using multiple techniques, with the mean frequency, AR coefficients, maximal Lyapunov exponent and the sample entropy being among the prime candidates. Even if these methods are not yet useful for clinical practice, they do bring the most promising indicators for the preterm labor. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=electrohysterogram" title="electrohysterogram">electrohysterogram</a>, <a href="https://publications.waset.org/abstracts/search?q=feature" title=" feature"> feature</a>, <a href="https://publications.waset.org/abstracts/search?q=preterm%20labor" title=" preterm labor"> preterm labor</a>, <a href="https://publications.waset.org/abstracts/search?q=term%20labor" title=" term labor "> term labor </a> </p> <a href="https://publications.waset.org/abstracts/68367/comprehensive-analysis-of-electrohysterography-signal-features-in-term-and-preterm-labor" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/68367.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">571</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">65</span> On the Well-Posedness of Darcy–Forchheimer Power Model Equation</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Johnson%20Audu">Johnson Audu</a>, <a href="https://publications.waset.org/abstracts/search?q=Faisal%20Fairag"> Faisal Fairag</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In a bounded subset of R^d, d=2 or 3, we consider the Darcy-Forchheimer power model with the exponent 1 < m ≤ 2 for a single-phase strong-inertia fluid flow in a porous medium. Under necessary compatibility condition, and some mild regularity assumptions on the interior and the boundary data, we prove the existence and uniqueness of solution (u, p) in L^(m+1 ) (Ω)^d X (W^(1,(m+1)/m) (Ω)^d ⋂L_0^2 (Ω)^d) and its stability. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=porous%20media" title="porous media">porous media</a>, <a href="https://publications.waset.org/abstracts/search?q=power%20law" title=" power law"> power law</a>, <a href="https://publications.waset.org/abstracts/search?q=strong%20inertia" title=" strong inertia"> strong inertia</a>, <a href="https://publications.waset.org/abstracts/search?q=nonlinear" title=" nonlinear"> nonlinear</a>, <a href="https://publications.waset.org/abstracts/search?q=monotone%20type" title=" monotone type"> monotone type</a> </p> <a href="https://publications.waset.org/abstracts/62820/on-the-well-posedness-of-darcy-forchheimer-power-model-equation" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/62820.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">317</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">64</span> A Multi-Scale Contact Temperature Model for Dry Sliding Rough Surfaces</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Jamal%20Choudhry">Jamal Choudhry</a>, <a href="https://publications.waset.org/abstracts/search?q=Roland%20Larsson"> Roland Larsson</a>, <a href="https://publications.waset.org/abstracts/search?q=Andreas%20Almqvist"> Andreas Almqvist</a> </p> <p class="card-text"><strong>Abstract:</strong></p> A multi-scale flash temperature model has been developed and validated against existing work. The core strength of the proposed model is that it can be adapted to predict flash contact temperatures occurring in various types of sliding systems. In this paper, it is used to investigate how different surface roughness parameters affect the flash temperatures. The results show that for decreasing Hurst exponents as well as increasing values of the high-frequency cut-off, the maximum flash temperature increases. It was also shown that the effect of surface roughness does not influence the average interface temperature. The model predictions were validated against data from an experiment conducted in a pin-on-disc machine. This also showed the importance of including a wear model when simulating flash temperature development in a sliding system. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=multiscale" title="multiscale">multiscale</a>, <a href="https://publications.waset.org/abstracts/search?q=pin-on-disc" title=" pin-on-disc"> pin-on-disc</a>, <a href="https://publications.waset.org/abstracts/search?q=finite%20element%20method" title=" finite element method"> finite element method</a>, <a href="https://publications.waset.org/abstracts/search?q=flash%20temperature" title=" flash temperature"> flash temperature</a>, <a href="https://publications.waset.org/abstracts/search?q=surface%20roughness" title=" surface roughness"> surface roughness</a> </p> <a href="https://publications.waset.org/abstracts/144393/a-multi-scale-contact-temperature-model-for-dry-sliding-rough-surfaces" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/144393.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">118</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">63</span> Chaotic Behavior in Monetary Systems: Comparison among Different Types of Taylor Rule</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Reza%20Moosavi%20Mohseni">Reza Moosavi Mohseni</a>, <a href="https://publications.waset.org/abstracts/search?q=Wenjun%20Zhang"> Wenjun Zhang</a>, <a href="https://publications.waset.org/abstracts/search?q=Jiling%20Cao"> Jiling Cao</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The aim of the present study is to detect the chaotic behavior in monetary economic relevant dynamical system. The study employs three different forms of Taylor rules: current, forward, and backward looking. The result suggests the existence of the chaotic behavior in all three systems. In addition, the results strongly represent that using expectations especially rational expectation hypothesis can increase complexity of the system and leads to more chaotic behavior. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=taylor%20rule" title="taylor rule">taylor rule</a>, <a href="https://publications.waset.org/abstracts/search?q=monetary%20system" title=" monetary system"> monetary system</a>, <a href="https://publications.waset.org/abstracts/search?q=chaos%20theory" title=" chaos theory"> chaos theory</a>, <a href="https://publications.waset.org/abstracts/search?q=lyapunov%20exponent" title=" lyapunov exponent"> lyapunov exponent</a>, <a href="https://publications.waset.org/abstracts/search?q=GMM%20estimator" title=" GMM estimator"> GMM estimator</a> </p> <a href="https://publications.waset.org/abstracts/27264/chaotic-behavior-in-monetary-systems-comparison-among-different-types-of-taylor-rule" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/27264.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">528</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">62</span> Feigenbaum Universality, Chaos and Fractal Dimensions in Discrete Dynamical Systems</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=T.%20K.%20Dutta">T. K. Dutta</a>, <a href="https://publications.waset.org/abstracts/search?q=K.%20K.%20Das"> K. K. Das</a>, <a href="https://publications.waset.org/abstracts/search?q=N.%20Dutta"> N. Dutta</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The salient feature of this paper is primarily concerned with Ricker’s population model: f(x)=x e^(r(1-x/k)), where r is the control parameter and k is the carrying capacity, and some fruitful results are obtained with the following objectives: 1) Determination of bifurcation values leading to a chaotic region, 2) Development of Statistical Methods and Analysis required for the measure of Fractal dimensions, 3) Calculation of various fractal dimensions. These results also help that the invariant probability distribution on the attractor, when it exists, provides detailed information about the long-term behavior of a dynamical system. At the end, some open problems are posed for further research. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Feigenbaum%20universality" title="Feigenbaum universality">Feigenbaum universality</a>, <a href="https://publications.waset.org/abstracts/search?q=chaos" title=" chaos"> chaos</a>, <a href="https://publications.waset.org/abstracts/search?q=Lyapunov%20exponent" title=" Lyapunov exponent"> Lyapunov exponent</a>, <a href="https://publications.waset.org/abstracts/search?q=fractal%20dimensions" title=" fractal dimensions"> fractal dimensions</a> </p> <a href="https://publications.waset.org/abstracts/4761/feigenbaum-universality-chaos-and-fractal-dimensions-in-discrete-dynamical-systems" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/4761.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span 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