Search results for: gaussian mixture model (GMM)
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 17468

Search results for: gaussian mixture model (GMM)

17378 Non-Universality in Barkhausen Noise Signatures of Thin Iron Films

Authors: Arnab Roy, P. S. Anil Kumar

Abstract:

We discuss angle dependent changes to the Barkhausen noise signatures of thin epitaxial Fe films upon altering the angle of the applied field. We observe a sub-critical to critical phase transition in the hysteresis loop of the sample upon increasing the out-of-plane component of the applied field. The observations are discussed in the light of simulations of a 2D Gaussian Random Field Ising Model with references to a reducible form of the Random Anisotropy Ising Model.

Keywords: Barkhausen noise, Planar Hall effect, Random Field Ising Model, Random Anisotropy Ising Model

Procedia PDF Downloads 359
17377 Study of Proton-9,11Li Elastic Scattering at 60~75 MeV/Nucleon

Authors: Arafa A. Alholaisi, Jamal H. Madani, M. A. Alvi

Abstract:

The radial form of nuclear matter distribution, charge and the shape of nuclei are essential properties of nuclei, and hence, are of great attention for several areas of research in nuclear physics. More than last three decades have witnessed a range of experimental means employing leptonic probes (such as muons, electrons etc.) for exploring nuclear charge distributions, whereas the hadronic probes (for example alpha particles, protons, etc.) have been used to investigate the nuclear matter distributions. In this paper, p-9,11Li elastic scattering differential cross sections in the energy range  to  MeV have been studied by means of Coulomb modified Glauber scattering formalism. By applying the semi-phenomenological Bhagwat-Gambhir-Patil [BGP] nuclear density for loosely bound neutron rich 11Li nucleus, the estimated matter radius is found to be 3.446 fm which is quite large as compared to so known experimental value 3.12 fm. The results of microscopic optical model based calculation by applying Bethe-Brueckner–Hartree–Fock formalism (BHF) have also been compared. It should be noted that in most of phenomenological density model used to reproduce the p-11Li differential elastic scattering cross sections data, the calculated matter radius lies between 2.964 and 3.55 fm. The calculated results with phenomenological BGP model density and with nucleon density calculated in the relativistic mean-field (RMF) reproduces p-9Li and p-11Li experimental data quite nicely as compared to Gaussian- Gaussian or Gaussian-Oscillator densities at all energies under consideration. In the approach described here, no free/adjustable parameter has been employed to reproduce the elastic scattering data as against the well-known optical model based studies that involve at least four to six adjustable parameters to match the experimental data. Calculated reaction cross sections σR for p-11Li at these energies are quite large as compared to estimated values reported by earlier works though so far no experimental studies have been performed to measure it.

Keywords: Bhagwat-Gambhir-Patil density, Coulomb modified Glauber model, halo nucleus, optical limit approximation

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17376 Microstructure Analysis of Biopolymer Mixture (Chia-Gelatin) by Laser Confocal Microscopy

Authors: Emmanuel Flores Huicochea, Guadalupe Borja Mendiola, Jacqueline Flores Lopez, Rodolfo Rendon Villalobos

Abstract:

The usual procedure to investigate the properties of biodegradable films has been to prepare the film, measure the mechanical or transport properties and then decide whether the mixture has better properties than the individual components, instead of investigating whether the mixture has biopolymer-biopolymer interaction, then prepare the film and finally measure the properties of the film. The work investigates the presence of interaction biopolymer-biopolymer in a mixture of chia biopolymer and gelatin using Laser Confocal Microscopy (LCM). Previously, the chia biopolymer was obtained from chia seed. CML analysis of mixtures of chia biopolymer-gelatin without Na⁺ ions exhibited aggregates of different size, in the range of 100-400 μm, of defined color, for the two colors, but no mixing of color was observed. The increased of gelatin in the mixture decreases the size and number of aggregates. The tridimensional microstructure reveled that there are two layers of biopolymers, chia and gelatin well defined. The mixture chia biopolymer-gelatin with 10 mM Na⁺ and with a ratio 75:25 (chia-gelatin) showed lower aggregated size than others mixture with and without ions. This result could be explained because the chia biopolymer is a polyelectrolyte and the added sodium ions reduce the molecular rigidity by neutralizing the negative charges that the chia biopolymer possesses and therefore a better biopolymer-biopolymer interaction is allowed between the biopolymer of chia and gelatin.

Keywords: biopolymer-biopolymer interaction, confocal laser microscopy, CLM, microstructure, mixture chia-gelatin

Procedia PDF Downloads 169
17375 Entropy Generation Analysis of Heat Recovery Vapor Generator for Ammonia-Water Mixture

Authors: Chul Ho Han, Kyoung Hoon Kim

Abstract:

This paper carries out a performance analysis based on the first and second laws of thermodynamics for heat recovery vapor generator (HRVG) of ammonia-water mixture when the heat source is low-temperature energy in the form of sensible heat. In the analysis, effects of the ammonia mass concentration and mass flow ratio of the binary mixture are investigated on the system performance including the effectiveness of heat transfer, entropy generation, and exergy efficiency. The results show that the ammonia concentration and the mass flow ratio of the mixture have significant effects on the system performance of HRVG.

Keywords: entropy, exergy, ammonia-water mixture, heat exchanger

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17374 An Association Model to Correlate the Experimentally Determined Mixture Solubilities of Methyl 10-Undecenoate with Methyl Ricinoleate in Supercritical Carbon Dioxide

Authors: V. Mani Rathnam, Giridhar Madras

Abstract:

Fossil fuels are depleting rapidly as the demand for energy, and its allied chemicals are continuously increasing in the modern world. Therefore, sustainable renewable energy sources based on non-edible oils are being explored as a viable option as they do not compete with the food commodities. Oils such as castor oil are rich in fatty acids and thus can be used for the synthesis of biodiesel, bio-lubricants, and many other fine industrial chemicals. There are several processes available for the synthesis of different chemicals obtained from the castor oil. One such process is the transesterification of castor oil, which results in a mixture of fatty acid methyl esters. The main products in the above reaction are methyl ricinoleate and methyl 10-undecenoate. To separate these compounds, supercritical carbon dioxide (SCCO₂) was used as a green solvent. SCCO₂ was chosen as a solvent due to its easy availability, non-toxic, non-flammable, and low cost. In order to design any separation process, the preliminary requirement is the solubility or phase equilibrium data. Therefore, the solubility of a mixture of methyl ricinoleate with methyl 10-undecenoate in SCCO₂ was determined in the present study. The temperature and pressure range selected for the investigation were T = 313 K to 333 K and P = 10 MPa to 18 MPa. It was observed that the solubility (mol·mol⁻¹) of methyl 10-undecenoate varied from 2.44 x 10⁻³ to 8.42 x 10⁻³ whereas it varied from 0.203 x 10⁻³ to 6.28 x 10⁻³ for methyl ricinoleate within the chosen operating conditions. These solubilities followed a retrograde behavior (characterized by the decrease in the solubility values with the increase in temperature) throughout the range of investigated operating conditions. An association theory model, coupled with regular solution theory for activity coefficients, was developed in the present study. The deviation from the experimental data using this model can be quantified using the average absolute relative deviation (AARD). The AARD% for the present compounds is 4.69 and 8.08 for methyl 10-undecenoate and methyl ricinoleate, respectively in a mixture of methyl ricinoleate and methyl 10-undecenoate. The maximum solubility enhancement of 32% was observed for the methyl ricinoleate in a mixture of methyl ricinoleate and methyl 10-undecenoate. The highest selectivity of SCCO₂ was observed to be 12 for methyl 10-undecenoate in a mixture of methyl ricinoleate and methyl 10-undecenoate.

Keywords: association theory, liquid mixtures, solubilities, supercritical carbon dioxide

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17373 Adsorption of Cd2+ from Aqueous Solutions Using Chitosan Obtained from a Mixture of Littorina littorea and Achatinoidea Shells

Authors: E. D. Paul, O. F. Paul, J. E. Toryila, A. J. Salifu, C. E. Gimba

Abstract:

Adsorption of Cd2+ ions from aqueous solution by Chitosan, a natural polymer, obtained from a mixture of the exoskeletons of Littorina littorea (Periwinkle) and Achatinoidea (Snail) was studied at varying adsorbent dose, contact time, metal ion concentrations, temperature and pH using batch adsorption method. The equilibrium adsorption isotherms were determined between 298 K and 345 K. The adsorption data were adjusted to Langmuir, Freundlich and the pseudo second order kinetic models. It was found that the Langmuir isotherm model most fitted the experimental data, with a maximum monolayer adsorption of 35.1 mgkg⁻¹ at 308 K. The entropy and enthalpy of adsorption were -0.1121 kJmol⁻¹K⁻¹ and -11.43 kJmol⁻¹ respectively. The Freundlich adsorption model, gave Kf and n values consistent with good adsorption. The pseudo-second order reaction model gave a straight line plot with rate constant of 1.291x 10⁻³ kgmg⁻¹ min⁻¹. The qe value was 21.98 mgkg⁻¹, indicating that the adsorption of Cadmium ion by the chitosan composite followed the pseudo-second order kinetic model.

Keywords: adsorption, chitosan, littorina littorea, achatinoidea, natural polymer

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17372 Modeling and Simulation of Organic Solar Cells Based on P3HT:PCBM using SCAPS 1-D (Influence of Defects and Temperature on the Performance of the Solar Cell)

Authors: Souhila Boukli Hacene, Djamila Kherbouche, Abdelhak Chikhaoui

Abstract:

In this work, we elucidate theoretically the effect of defects and temperature on the performance of the organic bulk heterojunction solar cell (BHJ) P3HT: PCBM. We have studied the influence of their parameters on cell characteristics. For this purpose, we used the effective medium model and the solar cell simulator (SCAPS) to model the characteristics of the solar cell. We also explore the transport of charge carriers in the device. It was assumed that the mixture is lightly p-type doped and that the band gap contains acceptor defects near the HOMO level with a Gaussian distribution of energy states at 100 and 50 meV. We varied defects density between 1012-1017 cm-3, from 1016 cm-3, a total decrease of the photovoltaic characteristics due to the increase of the non-radiative recombination can be noticed. Then we studied the effect of variation of the electron and the hole capture cross-section on the cell’s performance, we noticed that the cell obtains a better efficiency of about 3.6% for an electron capture cross section ≤ 10-15 cm2 and a hole capture cross section ≤ 10-19 cm2. On the other hand, we also varied the temperature between 120K and 400K. We observed that the temperature of the solar cell induces a noticeable effect on its voltage. While the effect of temperature on the solar cell current is negligible.

Keywords: organic solar cell, P3HT:PCBM, defects, temperature, SCAPS

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17371 Valorization of Local Materials in the Waterproofing Technique of Landfills Site "TLS"

Authors: M. Debieche, F. Kaoua

Abstract:

This paper deals with the use two locals materials abundant in our country, with the view to use a mixture in the waterproofing the landfills. Our interest comes from the necessity to the environment protection, which has recently considerably grown. The site's waterproofing technique, in the landfills sites, is nowadays a very necessary condition to protect the environment, which requires the use of appropriate materials. To this end, an optimal mixture ensuring good performance in terms of hydraulic conductivity, durability and shear strength, mixtures based of sand at different concentrations of sodium bentonite, at compact state are prepared and studied. This study showed that a low permeability of mixture (sand / bentonite) can be achieved 6% of sodium bentonite. This mixture confers also good mechanical behavior, expressed by the recorded, reduction of friction (φ) and the increase of the cohesion (C). Thus, the selected formulation represents an optimal mixture for waterproofing systems. It guarantees an economical and ecological advantages.

Keywords: hydraulic conductivity, sand, sodium bentonite, sustainability

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17370 Numerical Modeling the Cavitating Flow in Injection Nozzle Holes

Authors: Ridha Zgolli, Hatem Kanfoudi

Abstract:

Cavitating flows inside a diesel injection nozzle hole were simulated using a mixture model. A 2D numerical model is proposed in this paper to simulate steady cavitating flows. The Reynolds-averaged Navier-Stokes equations are solved for the liquid and vapor mixture, which is considered as a single fluid with variable density which is expressed as function of the vapor volume fraction. The closure of this variable is provided by the transport equation with a source term TEM. The processes of evaporation and condensation are governed by changes in pressure within the flow. The source term is implanted in the CFD code ANSYS CFX. The influence of numerical and physical parameters is presented in details. The numerical simulations are in good agreement with the experimental data for steady flow.

Keywords: cavitation, injection nozzle, numerical simulation, k–ω

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17369 Analysis of Financial Time Series by Using Ornstein-Uhlenbeck Type Models

Authors: Md Al Masum Bhuiyan, Maria C. Mariani, Osei K. Tweneboah

Abstract:

In the present work, we develop a technique for estimating the volatility of financial time series by using stochastic differential equation. Taking the daily closing prices from developed and emergent stock markets as the basis, we argue that the incorporation of stochastic volatility into the time-varying parameter estimation significantly improves the forecasting performance via Maximum Likelihood Estimation. While using the technique, we see the long-memory behavior of data sets and one-step-ahead-predicted log-volatility with ±2 standard errors despite the variation of the observed noise from a Normal mixture distribution, because the financial data studied is not fully Gaussian. Also, the Ornstein-Uhlenbeck process followed in this work simulates well the financial time series, which aligns our estimation algorithm with large data sets due to the fact that this algorithm has good convergence properties.

Keywords: financial time series, maximum likelihood estimation, Ornstein-Uhlenbeck type models, stochastic volatility model

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17368 Powder Flow with Normalized Powder Particles Size Distribution and Temperature Analyses in Laser Melting Deposition: Analytical Modelling and Experimental Validation

Authors: Muhammad Arif Mahmood, Andrei C. Popescu, Mihai Oane, Diana Chioibascu, Carmen Ristoscu, Ion N. Mihailescu

Abstract:

Powder flow and temperature distributions are recognized as influencing factors during laser melting deposition (LMD) process, that not only affect the consolidation rate but also characteristics of the deposited layers. Herewith, two simplified analytical models will be presented to simulate the powder flow with the inclusion of powder particles size distribution in Gaussian form, under three powder jet nozzles, and temperature analyses during LMD process. The output of the 1st model will serve as the input in the 2nd model. The models will be validated with experimental data, i.e., weight measurement method for powder particles distribution and infrared imaging for temperature analyses. This study will increase the cost-efficiency of the LMD process by adjustment of the operating parameters for reaching optimal powder debit and energy. This research has received funds under the Marie Sklodowska-Curie grant agreement No. 764935, from the European Union’s Horizon 2020 research and innovation program.

Keywords: laser additive manufacturing, powder particles size distribution in Gaussian form, powder stream distribution, temperature analyses

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17367 Hydro-Mechanical Behavior of a Tuff and Calcareous Sand Mixture for Use in Pavement in Arid Region

Authors: I. Goual, M. S. Goual, M. K. Gueddouda, Taïbi Saïd, Abou-Bekr Nabil, A. Ferhat

Abstract:

The aim of the paper is to study the hydro-mechanical behavior of a tuff and calcareous sand mixture. A first experimental phase was carried out in order to find the optimal mixture. This showed that the material composed of 80% tuff and 20% calcareous sand provides the maximum mechanical strength. The second experimental phase concerns the study of the drying-wetting behavior of the optimal mixture was carried out on slurry samples and compacted samples at the MPO. Experimental results let to deduce the parameters necessary for the prediction of the hydro-mechanical behavior of pavement formulated from tuff and calcareous sand mixtures, related to moisture. This optimal mixture satisfies the regulation rules and hence constitutes a good local eco-material, abundantly available, for the conception of pavements.

Keywords: tuff, sandy calcareous, road engineering, hydro mechanical behaviour, suction

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17366 Cyclostationary Gaussian Linearization for Analyzing Nonlinear System Response Under Sinusoidal Signal and White Noise Excitation

Authors: R. J. Chang

Abstract:

A cyclostationary Gaussian linearization method is formulated for investigating the time average response of nonlinear system under sinusoidal signal and white noise excitation. The quantitative measure of cyclostationary mean, variance, spectrum of mean amplitude, and mean power spectral density of noise is analyzed. The qualitative response behavior of stochastic jump and bifurcation are investigated. The validity of the present approach in predicting the quantitative and qualitative statistical responses is supported by utilizing Monte Carlo simulations. The present analysis without imposing restrictive analytical conditions can be directly derived by solving non-linear algebraic equations. The analytical solution gives reliable quantitative and qualitative prediction of mean and noise response for the Duffing system subjected to both sinusoidal signal and white noise excitation.

Keywords: cyclostationary, duffing system, Gaussian linearization, sinusoidal, white noise

Procedia PDF Downloads 458
17365 Investigation of Droplet Size Produced in Two-Phase Gravity Separators

Authors: Kul Pun, F. A. Hamad, T. Ahmed, J. O. Ugwu, J. Eyers, G. Lawson, P. A. Russell

Abstract:

Determining droplet size and distribution is essential when determining the separation efficiency of a two/three-phase separator. This paper investigates the effect of liquid flow and oil pad thickness on the droplet size at the lab scale. The findings show that increasing the inlet flow rates of the oil and water results in size reduction of the droplets and increasing the thickness of the oil pad increases the size of the droplets. The data were fitted with a simple Gaussian model, and the parameters of mean, standard deviation, and amplitude were determined. Trends have been obtained for the fitted parameters as a function of the Reynolds number, which suggest a way forward to better predict the starting parameters for population models when simulating separation using CFD packages. The key parameter to predict to fix the position of the Gaussian distribution was found to be the mean droplet size.

Keywords: two-phase separator, average bubble droplet, bubble size distribution, liquid-liquid phase

Procedia PDF Downloads 143
17364 BER Estimate of WCDMA Systems with MATLAB Simulation Model

Authors: Suyeb Ahmed Khan, Mahmood Mian

Abstract:

Simulation plays an important role during all phases of the design and engineering of communications systems, from early stages of conceptual design through the various stages of implementation, testing, and fielding of the system. In the present paper, a simulation model has been constructed for the WCDMA system in order to evaluate the performance. This model describes multiusers effects and calculation of BER (Bit Error Rate) in 3G mobile systems using Simulink MATLAB 7.1. Gaussian Approximation defines the multi-user effect on system performance. BER has been analyzed with comparison between transmitting data and receiving data.

Keywords: WCDMA, simulations, BER, MATLAB

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17363 Confidence Envelopes for Parametric Model Selection Inference and Post-Model Selection Inference

Authors: I. M. L. Nadeesha Jayaweera, Adao Alex Trindade

Abstract:

In choosing a candidate model in likelihood-based modeling via an information criterion, the practitioner is often faced with the difficult task of deciding just how far up the ranked list to look. Motivated by this pragmatic necessity, we construct an uncertainty band for a generalized (model selection) information criterion (GIC), defined as a criterion for which the limit in probability is identical to that of the normalized log-likelihood. This includes common special cases such as AIC & BIC. The method starts from the asymptotic normality of the GIC for the joint distribution of the candidate models in an independent and identically distributed (IID) data framework and proceeds by deriving the (asymptotically) exact distribution of the minimum. The calculation of an upper quantile for its distribution then involves the computation of multivariate Gaussian integrals, which is amenable to efficient implementation via the R package "mvtnorm". The performance of the methodology is tested on simulated data by checking the coverage probability of nominal upper quantiles and compared to the bootstrap. Both methods give coverages close to nominal for large samples, but the bootstrap is two orders of magnitude slower. The methodology is subsequently extended to two other commonly used model structures: regression and time series. In the regression case, we derive the corresponding asymptotically exact distribution of the minimum GIC invoking Lindeberg-Feller type conditions for triangular arrays and are thus able to similarly calculate upper quantiles for its distribution via multivariate Gaussian integration. The bootstrap once again provides a default competing procedure, and we find that similar comparison performance metrics hold as for the IID case. The time series case is complicated by far more intricate asymptotic regime for the joint distribution of the model GIC statistics. Under a Gaussian likelihood, the default in most packages, one needs to derive the limiting distribution of a normalized quadratic form for a realization from a stationary series. Under conditions on the process satisfied by ARMA models, a multivariate normal limit is once again achieved. The bootstrap can, however, be employed for its computation, whence we are once again in the multivariate Gaussian integration paradigm for upper quantile evaluation. Comparisons of this bootstrap-aided semi-exact method with the full-blown bootstrap once again reveal a similar performance but faster computation speeds. One of the most difficult problems in contemporary statistical methodological research is to be able to account for the extra variability introduced by model selection uncertainty, the so-called post-model selection inference (PMSI). We explore ways in which the GIC uncertainty band can be inverted to make inferences on the parameters. This is being attempted in the IID case by pivoting the CDF of the asymptotically exact distribution of the minimum GIC. For inference one parameter at a time and a small number of candidate models, this works well, whence the attained PMSI confidence intervals are wider than the MLE-based Wald, as expected.

Keywords: model selection inference, generalized information criteria, post model selection, Asymptotic Theory

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17362 Enhancing Predictive Accuracy in Pharmaceutical Sales through an Ensemble Kernel Gaussian Process Regression Approach

Authors: Shahin Mirshekari, Mohammadreza Moradi, Hossein Jafari, Mehdi Jafari, Mohammad Ensaf

Abstract:

This research employs Gaussian Process Regression (GPR) with an ensemble kernel, integrating Exponential Squared, Revised Matern, and Rational Quadratic kernels to analyze pharmaceutical sales data. Bayesian optimization was used to identify optimal kernel weights: 0.76 for Exponential Squared, 0.21 for Revised Matern, and 0.13 for Rational Quadratic. The ensemble kernel demonstrated superior performance in predictive accuracy, achieving an R² score near 1.0, and significantly lower values in MSE, MAE, and RMSE. These findings highlight the efficacy of ensemble kernels in GPR for predictive analytics in complex pharmaceutical sales datasets.

Keywords: Gaussian process regression, ensemble kernels, bayesian optimization, pharmaceutical sales analysis, time series forecasting, data analysis

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17361 The Determinants of Country Corruption: Unobserved Heterogeneity and Individual Choice- An empirical Application with Finite Mixture Models

Authors: Alessandra Marcelletti, Giovanni Trovato

Abstract:

Corruption in public offices is found to be the reflection of country-specific features, however, the exact magnitude and the statistical significance of its determinants effect has not yet been identified. The paper aims to propose an estimation method to measure the impact of country fundamentals on corruption, showing that covariates could differently affect the extent of corruption across countries. Thus, we exploit a model able to take into account different factors affecting the incentive to ask or to be asked for a bribe, coherently with the use of the Corruption Perception Index. We assume that discordant results achieved in literature may be explained by omitted hidden factors affecting the agents' decision process. Moreover, assuming homogeneous covariates effect may lead to unreliable conclusions since the country-specific environment is not accounted for. We apply a Finite Mixture Model with concomitant variables to 129 countries from 1995 to 2006, accounting for the impact of the initial conditions in the socio-economic structure on the corruption patterns. Our findings confirm the hypothesis of the decision process of accepting or asking for a bribe varies with specific country fundamental features.

Keywords: Corruption, Finite Mixture Models, Concomitant Variables, Countries Classification

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17360 Covariance of the Queue Process Fed by Isonormal Gaussian Input Process

Authors: Samaneh Rahimirshnani, Hossein Jafari

Abstract:

In this paper, we consider fluid queueing processes fed by an isonormal Gaussian process. We study the correlation structure of the queueing process and the rate of convergence of the running supremum in the queueing process. The Malliavin calculus techniques are applied to obtain relations that show the workload process inherits the dependence properties of the input process. As examples, we consider two isonormal Gaussian processes, the sub-fractional Brownian motion (SFBM) and the fractional Brownian motion (FBM). For these examples, we obtain upper bounds for the covariance function of the queueing process and its rate of convergence to zero. We also discover that the rate of convergence of the queueing process is related to the structure of the covariance function of the input process.

Keywords: queue length process, Malliavin calculus, covariance function, fractional Brownian motion, sub-fractional Brownian motion

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17359 Business Process Mashup

Authors: Fethia Zenak, Salima Benbernou, Linda Zaoui

Abstract:

Recently, many companies are based on process development from scratch to achieve their business goals. The process development is not trivial and the main objective of enterprise managing processes is to decrease the software development time. Several concepts have been proposed in the field of business process-based reused development, known as BP Mashup. This concept consists of reusing existing business processes which have been modeled in order to respond to a particular goal. To meet user process requirements, our contribution is to mix parts of processes as 'processes fragments' components to build a new process (i.e. process mashup). The main idea of our paper is to offer graphical framework tool for both creating and running processes mashup. Allow users to perform a mixture of fragments, using a simple interface with set of graphical mixture operators based on a proposed formal model. A process mashup and mixture behavior are described within a new specification of a high-level language, language for process mashup (BPML).

Keywords: business process, mashup, fragments, bp mashup

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17358 Nonlinear Interaction of Free Surface Sloshing of Gaussian Hump with Its Container

Authors: Mohammad R. Jalali

Abstract:

Movement of liquid with a free surface in a container is known as slosh. For instance, slosh occurs when water in a closed tank is set in motion by a free surface displacement, or when liquid natural gas in a container is vibrated by an external driving force, such as an earthquake or movement induced by transport. Slosh is also derived from resonant switching of a natural basin. During sloshing, different types of motion are produced by energy exchange between the liquid and its container. In present study, a numerical model is developed to simulate the nonlinear even harmonic oscillations of free surface sloshing of an initial disturbance to the free surface of a liquid in a closed square basin. The response of the liquid free surface is affected by amplitude and motion frequencies of its container; therefore, sloshing involves complex fluid-structure interactions. In the present study, nonlinear interaction of free surface sloshing of an initial Gaussian hump with its uneven container is predicted numerically. For this purpose, Green-Naghdi (GN) equations are applied as governing equation of fluid field to produce nonlinear second-order and higher-order wave interactions. These equations reduce the dimensions from three to two, yielding equations that can be solved efficiently. The GN approach assumes a particular flow kinematic structure in the vertical direction for shallow and deep-water problems. The fluid velocity profile is finite sum of coefficients depending on space and time multiplied by a weighting function. It should be noted that in GN theory, the flow is rotational. In this study, GN numerical simulations of initial Gaussian hump are compared with Fourier series semi-analytical solutions of the linearized shallow water equations. The comparison reveals that satisfactory agreement exists between the numerical simulation and the analytical solution of the overall free surface sloshing patterns. The resonant free surface motions driven by an initial Gaussian disturbance are obtained by Fast Fourier Transform (FFT) of the free surface elevation time history components. Numerically predicted velocity vectors and magnitude contours for the free surface patterns indicate that interaction of Gaussian hump with its container has localized effect. The result of this sloshing is applicable to the design of stable liquefied oil containers in tankers and offshore platforms.

Keywords: fluid-structure interactions, free surface sloshing, Gaussian hump, Green-Naghdi equations, numerical predictions

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17357 Response of Pavement under Temperature and Vehicle Coupled Loading

Authors: Yang Zhong, Mei-Jie Xu

Abstract:

To study the dynamic mechanics response of asphalt pavement under the temperature load and vehicle loading, asphalt pavement was regarded as multilayered elastic half-space system, and theory analysis was conducted by regarding dynamic modulus of asphalt mixture as the parameter. Firstly, based on the dynamic modulus test of asphalt mixture, function relationship between the dynamic modulus of representative asphalt mixture and temperature was obtained. In addition, the analytical solution for thermal stress in the single layer was derived by using Laplace integral transformation and Hankel integral transformation respectively by using thermal equations of equilibrium. The analytical solution of calculation model of thermal stress in asphalt pavement was derived by transfer matrix of thermal stress in multilayer elastic system. Finally, the variation of thermal stress in pavement structure was analyzed. The result shows that there is an obvious difference between the thermal stress based on dynamic modulus and the solution based on static modulus. Therefore, the dynamic change of parameter in asphalt mixture should be taken into consideration when the theoretical analysis is taken out.

Keywords: asphalt pavement, dynamic modulus, integral transformation, transfer matrix, thermal stress

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17356 Linear Quadratic Gaussian/Loop Transfer Recover Control Flight Control on a Nonlinear Model

Authors: T. Sanches, K. Bousson

Abstract:

As part of the development of a 4D autopilot system for unmanned aerial vehicles (UAVs), i.e. a time-dependent robust trajectory generation and control algorithm, this work addresses the problem of optimal path control based on the flight sensors data output that may be unreliable due to noise on data acquisition and/or transmission under certain circumstances. Although several filtering methods, such as the Kalman-Bucy filter or the Linear Quadratic Gaussian/Loop Transfer Recover Control (LQG/LTR), are available, the utter complexity of the control system, together with the robustness and reliability required of such a system on a UAV for airworthiness certifiable autonomous flight, required the development of a proper robust filter for a nonlinear system, as a way of further mitigate errors propagation to the control system and improve its ,performance. As such, a nonlinear algorithm based upon the LQG/LTR, is validated through computational simulation testing, is proposed on this paper.

Keywords: autonomous flight, LQG/LTR, nonlinear state estimator, robust flight control

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17355 The Application of Video Segmentation Methods for the Purpose of Action Detection in Videos

Authors: Nassima Noufail, Sara Bouhali

Abstract:

In this work, we develop a semi-supervised solution for the purpose of action detection in videos and propose an efficient algorithm for video segmentation. The approach is divided into video segmentation, feature extraction, and classification. In the first part, a video is segmented into clips, and we used the K-means algorithm for this segmentation; our goal is to find groups based on similarity in the video. The application of k-means clustering into all the frames is time-consuming; therefore, we started by the identification of transition frames where the scene in the video changes significantly, and then we applied K-means clustering into these transition frames. We used two image filters, the gaussian filter and the Laplacian of Gaussian. Each filter extracts a set of features from the frames. The Gaussian filter blurs the image and omits the higher frequencies, and the Laplacian of gaussian detects regions of rapid intensity changes; we then used this vector of filter responses as an input to our k-means algorithm. The output is a set of cluster centers. Each video frame pixel is then mapped to the nearest cluster center and painted with a corresponding color to form a visual map. The resulting visual map had similar pixels grouped. We then computed a cluster score indicating how clusters are near each other and plotted a signal representing frame number vs. clustering score. Our hypothesis was that the evolution of the signal would not change if semantically related events were happening in the scene. We marked the breakpoints at which the root mean square level of the signal changes significantly, and each breakpoint is an indication of the beginning of a new video segment. In the second part, for each segment from part 1, we randomly selected a 16-frame clip, then we extracted spatiotemporal features using convolutional 3D network C3D for every 16 frames using a pre-trained model. The C3D final output is a 512-feature vector dimension; hence we used principal component analysis (PCA) for dimensionality reduction. The final part is the classification. The C3D feature vectors are used as input to a multi-class linear support vector machine (SVM) for the training model, and we used a multi-classifier to detect the action. We evaluated our experiment on the UCF101 dataset, which consists of 101 human action categories, and we achieved an accuracy that outperforms the state of art by 1.2%.

Keywords: video segmentation, action detection, classification, Kmeans, C3D

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17354 3D Shape Knitting: Loop Alignment on a Surface with Positive Gaussian Curvature

Authors: C. T. Cheung, R. K. P. Ng, T. Y. Lo, Zhou Jinyun

Abstract:

This paper aims at manipulating loop alignment in knitting a three-dimensional (3D) shape by its geometry. Two loop alignment methods are introduced to handle a surface with positive Gaussian curvature. As weft knitting is a two-dimensional (2D) knitting mechanism that the knitting cam carrying the feeders moves in two directions only, left and right, the knitted fabric generated grows in width and length but not in depth. Therefore, a 3D shape is required to be flattened to a 2D plane with surface area preserved for knitting. On this flattened plane, dimensional measurements are taken for loop alignment. The way these measurements being taken derived two different loop alignment methods. In this paper, only plain knitted structure was considered. Each knitted loop was taken as a basic unit for loop alignment in order to achieve the required geometric dimensions, without the inclusion of other stitches which give textural dimensions to the fabric. Two loop alignment methods were experimented and compared. Only one of these two can successfully preserve the dimensions of the shape.

Keywords: 3D knitting, 3D shape, loop alignment, positive Gaussian curvature

Procedia PDF Downloads 312
17353 Antibacterial Activity of Trans-Cinnamaldehyde and Geraniol and Their Potential as Ingredients of Biocidal Polymers

Authors: Daria Olkiewicz, Maciej Walczak

Abstract:

In this paper, the biocidal effects of trans-cinnamaldehyde (a main component of cinnamon oil) and geraniol (a constituent of Pelargonium graveolens essential oil) are presented. The activity of the combination of trans-cinnamaldehyde and geraniol was tested against 3 bacterial strains: Staphylococcus aureus ATCC6538 (Gramm+), Escherichia coli ATCC8739 (Gramm-, Lac+) and Pseudomonas aeruginosa KKP 991(Gramm-, Lac-). The biocidal activity of trans-cinnamaldehyde-geraniol mixture against bacteria mentioned above was evaluated by disk-diffusion method. The model strains were exposed on 1, 2.5, 5 and 10 mg of trans-cinnamaldehyde-geraniol mixture per disk, and all strains were susceptible to this combination of plant compounds. For all microorganisms, also Minimal Inhibitory Concentration (MIC) and Minimal Bactericidal Concentration (MBC) were estimated. For Staphylococcus aureus MIC was 0.0625 mg/ml of the trans-cinnamaldehyde and geraniol mixture, and MBC was 1.25 mg/ml; For Escherichia coli MIC=0.5 mg/ml, MBC=1 mg/ml, and finally Pseudomonas aeruginosa was inhibited in 0.5 mg/ml, and minimal biocidal concentration of tested mixture for it was 1.25 mg/ml. There are also reports about the synergistic working of trans-cinnamaldehyde and geraniol against microorganisms and the antimicrobial activity of polymers enriched with trans-cinnamaldehyde or geraniol, therefore the successful development and introduction to the today life of biocidal polymer enriched with trans-cinnamaldehyde and geraniol are possible.

Keywords: antibacterial activity, biocidal polymers, geraniol, trans-cinnamaldehyde

Procedia PDF Downloads 139
17352 General Purpose Graphic Processing Units Based Real Time Video Tracking System

Authors: Mallikarjuna Rao Gundavarapu, Ch. Mallikarjuna Rao, K. Anuradha Bai

Abstract:

Real Time Video Tracking is a challenging task for computing professionals. The performance of video tracking techniques is greatly affected by background detection and elimination process. Local regions of the image frame contain vital information of background and foreground. However, pixel-level processing of local regions consumes a good amount of computational time and memory space by traditional approaches. In our approach we have explored the concurrent computational ability of General Purpose Graphic Processing Units (GPGPU) to address this problem. The Gaussian Mixture Model (GMM) with adaptive weighted kernels is used for detecting the background. The weights of the kernel are influenced by local regions and are updated by inter-frame variations of these corresponding regions. The proposed system has been tested with GPU devices such as GeForce GTX 280, GeForce GTX 280 and Quadro K2000. The results are encouraging with maximum speed up 10X compared to sequential approach.

Keywords: connected components, embrace threads, local weighted kernel, structuring elements

Procedia PDF Downloads 404
17351 Selection of Variogram Model for Environmental Variables

Authors: Sheikh Samsuzzhan Alam

Abstract:

The present study investigates the selection of variogram model in analyzing spatial variations of environmental variables with the trend. Sometimes, the autofitted theoretical variogram does not really capture the true nature of the empirical semivariogram. So proper exploration and analysis are needed to select the best variogram model. For this study, an open source data collected from California Soil Resource Lab1 is used to explain the problems when fitting a theoretical variogram. Five most commonly used variogram models: Linear, Gaussian, Exponential, Matern, and Spherical were fitted to the experimental semivariogram. Ordinary kriging methods were considered to evaluate the accuracy of the selected variograms through cross-validation. This study is beneficial for selecting an appropriate theoretical variogram model for environmental variables.

Keywords: anisotropy, cross-validation, environmental variables, kriging, variogram models

Procedia PDF Downloads 289
17350 Comparative Study of Sorption of Cr Ions and Dye Bezaktiv Yellow HE-4G with the Use of Adsorbents Natural Mixture of Olive Stone and Date Pits from Aqueous Solution

Authors: H. Aksas, H. Babaci, K. Louhab

Abstract:

In this paper, a comparative study of the adsorption of Chromium and dyes, onto mixture biosorbents, olive stones and date pits at different percentage was investigated in aqueous solution. The study of various parameters: Effect of contact time, pH, temperature and initial concentration shows that these materials possess a high affinity for the adsorption of chromium for the adsorption of dye bezaktiv yellow HE-4G. To deepen the comparative study of the adsorption of chromium and dye with the use of different blends of olive stones and date pits, the following models are studied: Langmuir, Freundlich isotherms and Dubinin- Radushkvich (D-R) were used as the adsorption equilibrium data model. Langmuir isotherm model was the most suitable for the adsorption of the dye bezaktiv HE-4G and the D-R model is most suitable for adsorption Chrome. The pseudo-first-order model, pseudo-second order and intraparticle diffusion were used to describe the adsorption kinetics. The apparent activation energy was found to be less than 8KJ/mol, which is characteristic of a controlled chemical reaction for the adsorption of two materials. t was noticed that adsorption of chromium and dye BEZAKTIV HE-YELLOW 4G follows the kinetics of the pseudo second order. The study of the effect of temperature was quantified by calculating various thermodynamic parameters such as Gibbs free energy, enthalpy and entropy changes. The resulting thermodynamic parameters indicate the endothermic nature of the adsorption of Cr (VI) ions and the dye Bezaktiv HE-4G. But these materials are very good adsorbents, as they represent a low cost. in addition, it has been noticed that the greater the quantity of olive stone in the mixture increases, the adsorption ability of the dye or chromium increases.

Keywords: chromium ions, anions dye, sorption, mixed adsorbents, olive stone, date pits

Procedia PDF Downloads 198
17349 Adaptive CFAR Analysis for Non-Gaussian Distribution

Authors: Bouchemha Amel, Chachoui Takieddine, H. Maalem

Abstract:

Automatic detection of targets in a modern communication system RADAR is based primarily on the concept of adaptive CFAR detector. To have an effective detection, we must minimize the influence of disturbances due to the clutter. The detection algorithm adapts the CFAR detection threshold which is proportional to the average power of the clutter, maintaining a constant probability of false alarm. In this article, we analyze the performance of two variants of adaptive algorithms CA-CFAR and OS-CFAR and we compare the thresholds of these detectors in the marine environment (no-Gaussian) with a Weibull distribution.

Keywords: CFAR, threshold, clutter, distribution, Weibull, detection

Procedia PDF Downloads 545