Search results for: non-linear dynamics features

Authors: Teng Li, Kamran Mohseni

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This paper presents an inviscid regularization technique that is capable of regularizing the shocks and sharp interfaces simultaneously in the shock-interface interaction simulations. The direct numerical simulation of flows involving shocks has been investigated for many years and a lot of numerical methods were developed to capture the shocks. However, most of these methods rely on the numerical dissipation to regularize the shocks. Moreover, in high Reynolds number flows, the nonlinear terms in hyperbolic Partial Differential Equations (PDE) dominates, constantly generating small scale features. This makes direct numerical simulation of shocks even harder. The same difficulty happens in two-phase flow with sharp interfaces where the nonlinear terms in the governing equations keep sharpening the interfaces to discontinuities. The main idea of the proposed technique is to average out the small scales that is below the resolution (observable scale) of the computational grid by filtering the convective velocity in the nonlinear terms in the governing PDE. This technique is named “observable method” and it results in a set of hyperbolic equations called observable equations, namely, observable Navier-Stokes or Euler equations. The observable method has been applied to the flow simulations involving shocks, turbulence, and two-phase flows, and the results are promising. In the current paper, the observable method is examined on the performance of regularizing shocks and interfaces at the same time in shock-interface interaction problems. Bubble-shock interactions and Richtmyer-Meshkov instability are particularly chosen to be studied. Observable Euler equations will be numerically solved with pseudo-spectral discretization in space and third order Total Variation Diminishing (TVD) Runge Kutta method in time. Results are presented and compared with existing publications. The interface acceleration and deformation and shock reflection are particularly examined.

Keywords: compressible flow simulation, inviscid regularization, Richtmyer-Meshkov instability, shock-bubble interactions.

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Authors: Jatin Gupta, Bishakh Bhattacharya

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With the aging process, many people start suffering from the problem of weak limbs resulting in mobility disorders and loss of sensory and motor function of limbs. Wearable robotic devices are viable solutions to help people suffering from these issues by augmenting their strength. These robotic devices, popularly known as exoskeletons aides user by providing external power and controlling the dynamics so as to achieve desired motion. Present work studies a simplified dynamic model of the human gait. A four link open chain kinematic model is developed to describe the dynamics of Single Support Phase (SSP) of the human gait cycle. The dynamic model is developed integrating mathematical models of the motion of inverted and triple pendulums. Stance leg is modeled as inverted pendulum having single degree of freedom and swing leg as triple pendulum having three degrees of freedom viz. thigh, knee, and ankle joints. The kinematic model is formulated using forward kinematics approach. Lagrangian approach is used to formulate governing dynamic equation of the model. For a system of nonlinear differential equations, numerical method is employed to obtain system response. Reference trajectory is generated using human body simulator, LifeMOD. For optimal mechanical design and controller design of exoskeleton system, it is imperative to study parameter sensitivity of the system. Six different parameters viz. thigh, shank, and foot masses and lengths are varied from 85% to 115% of the original value for the present work. It is observed that hip joint of swing leg is the most sensitive and ankle joint of swing leg is the least sensitive one. Changing link lengths causes more deviation in system response than link masses. Also, shank length and thigh mass are most sensitive parameters. Finally, the present study gives an insight on different factors that should be considered while designing a lower extremity exoskeleton.

Keywords: lower limb exoskeleton, multibody dynamics, energy based formulation, optimal design

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Authors: Ju-Young Hwang, Hyo-Gyoung Kwak

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This paper introduces a numerical analysis method for reinforced-concrete (RC) structures exposed to fire and compares the result with experimental results. The proposed analysis method for RC structure under the high temperature consists of two procedures. First step is to decide the temperature distribution across the section through the heat transfer analysis by using the time-temperature curve. After determination of the temperature distribution, the nonlinear analysis is followed. By considering material and geometrical nonlinearity with the temperature distribution, nonlinear analysis predicts the behavior of RC structure under the fire by the exposed time. The proposed method is validated by the comparison with the experimental results. Finally, prediction model to describe the status of after-cooling concrete can also be introduced based on the results of additional experiment. The product of this study is expected to be embedded for smart structure monitoring system against fire in u-City.

Keywords: RC, high temperature, after-cooling analysis, nonlinear analysis

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Authors: Nadia el Atlas, Mohammed el Aroussi, Mohammed Wahbi

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In this paper a novel technique of mass characterization based on robust features-fusion is presented. The proposed method consists of mainly four stages: (a) the first phase involves segmenting the masses using edge information’s. (b) The second phase is to calculate and fuse the most relevant morphological features. (c) The last phase is the classification step which allows us to classify the images into benign and malignant masses. In this step we have implemented Support Vectors Machines (SVM) and Artificial Neural Networks (ANN), which were evaluated with the following performance criteria: confusion matrix, accuracy, sensitivity, specificity, receiver operating characteristic ROC, and error histogram. The effectiveness of this new approach was evaluated by a recently developed database: INBREAST database. The fusion of the most appropriate morphological features provided very good results. The SVM gives accuracy to within 64.3%. Whereas the ANN classifier gives better results with an accuracy of 97.5%.

Keywords: breast cancer, mammography, CAD system, features, fusion

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Authors: M. W. Sun, Y. Zhang, L. M. Zhang, Z. H. Wang, Z. Q. Chen

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In the realm of flight control, the Proportional- Derivative (PD) control is still widely used for the attitude control in practice, particularly for the pitch control, and the attitude dynamics using PD controller should be investigated deeply. According to the empirical knowledge about the unstable flight dynamics, the control parameter combination conditions to generate sole or finite number of closed-loop oscillations, which is a quite smooth response and is more preferred by practitioners, are presented in analytical or numerical manners. To analyze the effects of the combination conditions of the control parameters, the roots of several polynomials are sought to obtain feasible solutions. These conditions can also be plotted in a 2-D plane which makes the conditions be more explicit by using multiple interval operations. Finally, numerical examples are used to validate the proposed methods and some comparisons are also performed.

Keywords: attitude control, dynamic performance, numerical solving method, interval, unstable flight dynamics

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Authors: Minh Dong Le, Viet Dung Nguyen, Do Huu Viet, Nguyen Huu Tu

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In this paper, we present a new method for circumscribed masses detection in mammograms. Our method is evaluated on 23 mammographic images of circumscribed masses and 20 normal mammograms from public Mini-MIAS database. The method is quite sanguine with sensitivity (SE) of 95% with only about 1 false positive per image (FPpI). To achieve above results we carry out a progression following: Firstly, the input images are preprocessed with the aim to enhance key information of circumscribed masses; Next, we calculate and evaluate statistically basic features of abnormal regions on training database; Then, mammograms on testing database are divided into equal blocks which calculated corresponding features. Finally, using priority order of basic features to classify blocks as an abnormal or normal regions.

Keywords: mammograms, circumscribed masses, evaluated statistically, priority order of basic features

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Authors: Somayyeh Karimiyan

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To evaluate the seismic vulnerability of vital offshore structures with the highest possible precision, Nonlinear Time History Analyses (NLTHA), is the most reliable method. However, since it is very time-consuming, a quick procedure is greatly desired. This paper presents a quick method by combining the Push Over Analysis (POA) and the NLTHA. The POA is preformed first to recognize the more critical members, and then the NLTHA is performed to evaluate more precisely the critical members’ vulnerability. The proposed method has been applied to jacket type structure. Results show that combining POA and NLTHA is a reliable seismic evaluation method, and also that none of the earthquake characteristics alone, can be a dominant factor in vulnerability evaluation.

Keywords: jacket structure, seismic evaluation, push-over and nonlinear time history analyses, critical members

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Authors: Amit Kumar, Archana Gupta, Poonam Tandon, E. D. D’Silva

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Nonlinear optical (NLO) materials are the key materials for the fast processing of information and optical data storage applications. In the last decade, materials showing nonlinear optical properties have been the object of increasing attention by both experimental and computational points of view. Chalcones are one of the most important classes of cross conjugated NLO chromophores that are reported to exhibit good SHG efficiency, ultra fast optical nonlinearities and are easily crystallizable. The basic structure of chalcones is based on the π-conjugated system in which two aromatic rings are connected by a three-carbon α, β-unsaturated carbonyl system. Due to the overlap of π orbitals, delocalization of electronic charge distribution leads to a high mobility of the electron density. On a molecular scale, the extent of charge transfer across the NLO chromophore determines the level of SHG output. Hence, the functionalization of both ends of the π-bond system with appropriate electron donor and acceptor groups can enhance the asymmetric electronic distribution in either or both ground and excited states, leading to an increased optical nonlinearity. In this research, the experimental and theoretical study on the structure and vibrations of (2E)-3-[4-(methylsulfanyl) phenyl]-1-(3-bromophenyl) prop-2-en-1-one (3Br4MSP) is presented. The FT-IR and FT-Raman spectra of the NLO material in the solid phase have been recorded. Density functional theory (DFT) calculations at B3LYP with 6-311++G(d,p) basis set were carried out to study the equilibrium geometry, vibrational wavenumbers, infrared absorbance and Raman scattering activities. The interpretation of vibrational features (normal mode assignments, for instance) has an invaluable aid from DFT calculations that provide a quantum-mechanical description of the electronic energies and forces involved. Perturbation theory allows one to obtain the vibrational normal modes by estimating the derivatives of the Kohn−Sham energy with respect to atomic displacements. The molecular hyperpolarizability β plays a chief role in the NLO properties, and a systematical study on β has been carried out. Furthermore, the first order hyperpolarizability (β) and the related properties such as dipole moment (μ) and polarizability (α) of the title molecule are evaluated by Finite Field (FF) approach. The electronic α and β of the studied molecule are 41.907×10-24 and 79.035×10-24 e.s.u. respectively, indicating that 3Br4MSP can be used as a good nonlinear optical material.

Keywords: DFT, MEP, NLO, vibrational spectra

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Authors: Zhijie Li, Wenhui Peng, Zelong Yuan, Jianchun Wang

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Turbulence is a complex phenomenon that plays a crucial role in various fields, such as engineering, atmospheric science, and fluid dynamics. Predicting and understanding its behavior over long time scales have been challenging tasks. Traditional methods, such as large-eddy simulation (LES), have provided valuable insights but are computationally expensive. In the past few years, machine learning methods have experienced rapid development, leading to significant improvements in computational speed. However, ensuring stable and accurate long-term predictions remains a challenging task for these methods. In this study, we introduce the implicit U-net enhanced Fourier neural operator (IU-FNO) as a solution for stable and efficient long-term predictions of the nonlinear dynamics in three-dimensional (3D) turbulence. The IU-FNO model combines implicit re-current Fourier layers to deepen the network and incorporates the U-Net architecture to accurately capture small-scale flow structures. We evaluate the performance of the IU-FNO model through extensive large-eddy simulations of three types of 3D turbulence: forced homogeneous isotropic turbulence (HIT), temporally evolving turbulent mixing layer, and decaying homogeneous isotropic turbulence. The results demonstrate that the IU-FNO model outperforms other FNO-based models, including vanilla FNO, implicit FNO (IFNO), and U-net enhanced FNO (U-FNO), as well as the dynamic Smagorinsky model (DSM), in predicting various turbulence statistics. Specifically, the IU-FNO model exhibits improved accuracy in predicting the velocity spectrum, probability density functions (PDFs) of vorticity and velocity increments, and instantaneous spatial structures of the flow field. Furthermore, the IU-FNO model addresses the stability issues encountered in long-term predictions, which were limitations of previous FNO models. In addition to its superior performance, the IU-FNO model offers faster computational speed compared to traditional large-eddy simulations using the DSM model. It also demonstrates generalization capabilities to higher Taylor-Reynolds numbers and unseen flow regimes, such as decaying turbulence. Overall, the IU-FNO model presents a promising approach for long-term dynamics prediction in 3D turbulence, providing improved accuracy, stability, and computational efficiency compared to existing methods.

Keywords: data-driven, Fourier neural operator, large eddy simulation, fluid dynamics

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Authors: M. H. Korayem, Sh. Ameri, N. Yousefi Lademakhi

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To ensure the stability of closed-loop nonlinear model predictive control (NMPC) within a finite horizon, there is a need for appropriate design terminal ingredients, which can be a time-consuming and challenging effort. Otherwise, in order to ensure the stability of the control system, it is necessary to consider an infinite predictive horizon. Increasing the prediction horizon increases computational demand and slows down the implementation of the method. In this study, a new technique has been proposed to ensure system stability without terminal ingredients. This technique has been employed in the design of the NMPC algorithm, leading to a reduction in the computational complexity of designing terminal ingredients and computational burden. The studied system is a wheeled mobile robot (WMR) subjected to non-holonomic constraints. Simulation has been investigated for two problems: trajectory tracking and adjustment mode.

Keywords: wheeled mobile robot, nonlinear model predictive control, stability, without terminal ingredients

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Authors: Elias Nemer, Greg Vines

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Time-frequency transformation and spectral representations of audio signals are commonly used in various machine learning applications. Training networks on frequency features such as the Mel-Spectrogram or Cochleogram have been proven more effective and convenient than training on-time samples. In practical realizations, these features are created on a different processor and/or pre-computed and stored on disk, requiring additional efforts and making it difficult to experiment with different features. In this paper, we provide a PyTorch framework for creating various spectral features as well as time-frequency transformation and time-domain filter-banks using the built-in trainable conv1d() layer. This allows computing these features on the fly as part of a larger network and enabling easier experimentation with various combinations and parameters. Our work extends the work in the literature developed for that end: First, by adding more of these features and also by allowing the possibility of either starting from initialized kernels or training them from random values. The code is written as a template of classes and scripts that users may integrate into their own PyTorch classes or simply use as is and add more layers for various applications.

Keywords: neural networks Mel-Spectrogram, chromagram, cochleogram, discrete Fourrier transform, PyTorch conv1d()

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Authors: Shyhrete Morina

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This paper deals with morphological features in Mjeda's works. To make such a distinction, these features will be compared to standard Albanian language, considering the linguistic structure in the morphological field, which represent an all-important segment of Albanian language. Therefore, the study will focus mainly on the description and construction of these paradigms, which will give a linguistic insight into the entire work of Mjeda as the author who wrote in the dialect of northwestern Geg. Therefore, we have tried to distinguish different parts of the author's language, as well as the distinctive features or even the similarities of these paradigms that arise in the literary work of Mjeda. By constructing the corpus of this phonetic and grammar segment from the whole of Mjeda's work, we have seen that in these fields has built a variety of grammar structures, which for the history of Albanian are of special importance, that in the full variant of the work, as far as we can investigate, we will point out in all the distinctive features. Therefore, our study aims to highlight the linguistic features, namely the author's deep knowledge toward the language, the authenticity of its use, and its mutual relationship with it.

Keywords: distinctive morpholgy, nouns, adjetives, pronouns, Albanian standard language

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Authors: A. Bahmanpour, I. Eames, C. Klettner, A. Dimakopoulos

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We develop a new set of diagnostic tools to analyze inundation into a model district using three-dimensional CFD simulations, with a view to generating a database against which to test simpler models. A three-dimensional model of Oregon city with different-sized groups of building next to the coastline is used to run calculations of the movement of a long period wave on the shore. The initial and boundary conditions of the off-shore water are set using a nonlinear inverse method based on Eulerian spatial information matching experimental Eulerian time series measurements of water height. The water movement is followed in time, and this enables the pressure distribution on every surface of each building to be followed in a temporal manner. The three-dimensional numerical data set is validated against published experimental work. In the first instance, we use the dataset as a basis to understand the success of reduced models - including 2D shallow water model and reduced 1D models - to predict water heights, flow velocity and forces. This is because models based on the shallow water equations are known to underestimate drag forces after the initial surge of water. The second component is to identify critical flow features, such as hydraulic jumps and choked states, which are flow regions where dissipation occurs and drag forces are large. Finally, we describe how future tsunami inundation models should be modified to account for the complex effects of buildings through drag and blocking.Financial support from UCL and HR Wallingford is greatly appreciated. The authors would like to thank Professor Daniel Cox and Dr. Hyoungsu Park for providing the data on the Seaside Oregon experiment.

Keywords: computational fluid dynamics, extreme events, loading, tsunami

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Authors: Rui Mao, Heming Ji, Xiaoyu Wang

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Keystroke dynamics are widely used in identity recognition. It has the advantage that the individual typing rhythm is difficult to imitate. It also supports continuous authentication through the keyboard without extra devices. The existing keystroke dynamics authentication methods based on machine learning have a drawback in supporting relatively complex scenarios with massive data. There are drawbacks to both feature extraction and model optimization in these methods. To overcome the above weakness, an authentication model of keystroke dynamics based on deep learning is proposed. The model uses feature vectors formed by keystroke content and keystroke time. It ensures efficient continuous authentication by cooperating attention mechanisms with the combination of CNN and Bi-LSTM. The model has been tested with Open Data Buffalo dataset, and the result shows that the FRR is 3.09%, FAR is 3.03%, and EER is 4.23%. This proves that the model is efficient and accurate on continuous authentication.

Keywords: keystroke dynamics, identity authentication, deep learning, CNN, LSTM

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Authors: Sabyasachi Mukhopadhyay, Joseph Ogutu, Hans-Peter Piepho

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We aim to model dynamics of wildlife or pastoral livestock population for understanding of their population change and hence for wildlife conservation and promoting human welfare. The study is motivated by an age-sex structured population counts in different regions of Serengeti-Mara during the period 1989-2003. Developing reliable and realistic models for population dynamics of large herbivore population can be a very complex and challenging exercise. However, the Bayesian statistical domain offers some flexible computational methods that enable the development and efficient implementation of complex population dynamics models. In this work, we have used a novel Bayesian state-space model to analyse the dynamics of topi and hartebeest populations in the Serengeti-Mara Ecosystem of East Africa. The state-space model involves survival probabilities of the animals which further depend on various factors like monthly rainfall, size of habitat, etc. that cause recent declines in numbers of the herbivore populations and potentially threaten their future population viability in the ecosystem. Our study shows that seasonal rainfall is the most important factors shaping the population size of animals and indicates the age-class which most severely affected by any change in weather conditions.

Keywords: bayesian state-space model, Markov Chain Monte Carlo, population dynamics, conservation

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Authors: S. N. Derrar, M. Sekkal-Rahal

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The Nonlinear optics (NLO) technique is widely used in the field of biological imaging. In fact, grafting biological entities with a high NLO response on tissues and cells enhances the NLO responses of these latter, and ameliorates, consequently, their biological imaging quality. In this optics, we carried out a theoretical study, in the aim of analyzing the peptide bonds created between alanine amino acid and both unnatural amino acids: L-Dopa and Azatryptophan, respectively. Ramachandran plots have been performed for these systems, and their structural parameters have been analyzed. The NLO responses of these peptides have been reported by calculating the first hyperpolarizability values of all the minima found on the plots. The use of such unnatural amino acids as endogenous probing molecules has been investigated through this study. The Density Functional Theory (DFT) has been used for structural properties, while the Second-order Møller-Plesset Perturbation Theory (MP2) has been employed for the NLO calculations.

Keywords: biological imaging, hyperpolarizability, nonlinear optics, probing molecule

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Authors: Yuri V. Kim

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This article presents a new approach to the Functional Testing of Space Systems (SS). It can be considered as a generic test and used for a wide class of SS that from the point of view of System Dynamics and Control may be described by the ordinary differential equations. Suggested methodology is based on using semi-natural experiment- laboratory stand that doesn’t require complicated, precise and expensive technological control-verification equipment. However, it allows for testing system as a whole totally assembled unit during Assembling, Integration and Testing (AIT) activities, involving system hardware (HW) and software (SW). The test physically activates system input (sensors) and output (actuators) and requires recording their outputs in real time. The data is then inserted in laboratory PC where it is post-experiment processed by Matlab/Simulink Identification Toolbox. It allows for estimating system dynamics in form of estimation of system differential equations by the experimental way and comparing them with expected mathematical model prematurely verified by mathematical simulation during the design process.

Keywords: system dynamics, space system ground tests and space qualification, system dynamics identification, satellite attitude control, assembling, integration and testing

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Authors: Xiang Yu, Chuntao Feng, Lu Yang, Meiyang Song, Wenhao Zhou

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The existing two-dimensional micro-Doppler features extraction ignores the correlation information between the spatial and temporal dimension features. For the range-Doppler map, the time dimension is introduced, and a frequency modulation continuous wave (FMCW) radar human fall detection algorithm based on time-varying range-Doppler features is proposed. Firstly, the range-Doppler sequence maps are generated from the echo signals of the continuous motion of the human body collected by the radar. Then the three-dimensional data cube composed of multiple frames of range-Doppler maps is input into the three-dimensional Convolutional Neural Network (3D CNN). The spatial and temporal features of time-varying range-Doppler are extracted by the convolution layer and pool layer at the same time. Finally, the extracted spatial and temporal features are input into the fully connected layer for classification. The experimental results show that the proposed fall detection algorithm has a detection accuracy of 95.66%.

Keywords: FMCW radar, fall detection, 3D CNN, time-varying range-doppler features

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Authors: Shangerganesh Lingeshwaran

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In this presentation, we have performed numerical simulations for a reaction-diffusion equation with various nonlinear density-dependent diffusion operators and proliferation functions. The mathematical model represented by parabolic partial differential equation is considered to study the invasion of gliomas (the most common type of brain tumors) and to describe the growth of cancer cells and response to their treatment. The unknown quantity of the given reaction-diffusion equation is the density of cancer cells and the mathematical model based on the proliferation and migration of glioma cells. A standard Galerkin finite element method is used to perform the numerical simulations of the given model. Finally, important observations on the each of nonlinear diffusion functions and proliferation functions are presented with the help of computational results.

Keywords: glioma invasion, nonlinear diffusion, reaction-diffusion, finite eleament method

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Authors: J. A. Gbadeyan, R. A. Kareem

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In this paper, we investigated the effects of unsteady internal heat generation of a two-step exothermic reactive hydromagnetic fluid flow under different chemical kinetics namely: Sensitized, Arrhenius and Bimolecular kinetics through an isothermal wall temperature channel. The resultant modeled nonlinear partial differential equations were simplified and solved using a combined Laplace-Differential Transform Method (LDTM). The solutions obtained were discussed and presented graphically to show the salient features of the fluid flow and heat transfer characteristics.

Keywords: unsteady, reactive, hydromagnetic, couette ow, exothermi creactio

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Authors: David C. Ni

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In the previous efforts, we constructed N-Body Systems by an extended Blaschke product (EBP), which represents a non-temporal and nonlinear extension of Lorentz transformation. In this construction, we rely only on two parameters, nonlinear degree, and relative momentum to characterize the systems. We further explored root computation via iteration with an algorithm extended from Jenkins-Traub method. The solution sets demonstrate a form of σ+ i [-t, t], where σ and t are the real numbers, and the [-t, t] shows various canonical distributions. In this paper, we correlate the convergent sets in the original domain with solution sets, which demonstrating large-deviation distributions in the codomain. We proceed to compare our approach with the formula or principles, such as Donsker-Varadhan and Wentzell-Freidlin theories. The deterministic model based on this construction allows us to explore applications in the areas of finance and statistical mechanics.

Keywords: nonlinear Lorentz transformation, Blaschke equation, iteration solutions, root computation, large deviation distribution, deterministic model

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Authors: Abderraouf Gaaloul, Faouzi Msahli

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The use of standard sliding mode controller, usually, leads to the appearing of an undesirable chattering phenomenon affecting the control signal. Such problem can be overcome using a higher-order sliding mode controller (HOSMC) which preserves the main properties of the standard sliding mode and deliberately increases the control smoothness. In this paper, we propose a new HOSMC for a class of uncertain multi-input multi-output nonlinear systems. Based on high gain and integral sliding mode paradigms, the established control scheme removes theoretically the chattering phenomenon and provides the stability of the control system. Numerical simulations are developed to show the effectiveness of the proposed controller when applied to solve a control problem of two water levels into a quadruple-tank process.

Keywords: nonlinear systems, sliding mode control, high gain, higher order

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Authors: Dong Sang Yoo

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We consider nonlinear uncertain systems such that a priori information of the uncertainties is not available. For such systems, we assume that the upper bound of the uncertainties is represented as a Fredholm integral equation of the first kind and we propose an adaptation law that is capable of estimating the upper bound and design a continuous robust control which renders nonlinear uncertain systems ultimately bounded.

Keywords: adaptive control, estimation, Fredholm integral, uncertain system

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Authors: Birmohan Singh, V.K.Jain

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Computer aided diagnosis systems provide vital opinion to radiologists in the detection of early signs of breast cancer from mammogram images. Masses and microcalcifications, architectural distortions are the major abnormalities. In this paper, a computer aided diagnosis system has been proposed for distinguishing abnormal mammograms with architectural distortion from normal mammogram. Four types of texture features GLCM texture, GLRLM texture, fractal texture and spectral texture features for the regions of suspicion are extracted. Support Vector Machine has been used as classifier in this study. The proposed system yielded an overall sensitivity of 96.47% and accuracy of 96% for the detection of abnormalities with mammogram images collected from Digital Database for Screening Mammography (DDSM) database.

Keywords: architecture distortion, mammograms, GLCM texture features, GLRLM texture features, support vector machine classifier

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Authors: Shachi Pathak

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We are living in knowledge based economy where firms can gain competitive advantage with the help of managing knowledge within the organization. The purpose the study is to develop a conceptual model to explain the relationship between factors affecting knowledge sharing, called as knowledge enablers, in an organization, knowledge sharing activities and organizational performance, using system dynamics approach. This research is important since it will provide better understandings on what are the key knowledge enablers to support knowledge sharing activities, and how knowledge sharing activities will affect the capability of an organization to enhance the performance of the organization.

Keywords: knowledge management, knowledge sharing, organizational performance, system dynamics

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Authors: Hocine Hammoum, Karima Bouzelha, Lounis Ziani, Lounis Hamitouche

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In this paper, we study a complex structure which is an apartment building surmounted by a reinforced concrete water tank. The tank located on the top floor of the building is a container with capacity of 1000 m³. The building is complex in its design, its calculation and by its behavior under earthquake effect. This structure located in Algiers and aged of 53 years has been subjected to several earthquakes, but the earthquake of May 21^st, 2003 with a magnitude of 6.7 on the Richter scale that struck Boumerdes region at 40 Kms East of Algiers was fatal for it. It was downgraded after an investigation study because the central core sustained serious damage. In this paper, to estimate the degree of its damages, the seismic performance of the structure will be evaluated taking into account the hydrodynamic effect, using a static equivalent nonlinear analysis called pushover.

Keywords: performance analysis, building, reinforced concrete tank, seismic analysis, nonlinear analysis, hydrodynamic, pushover

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Authors: Matej Komanec, Tomas Nemecek, Dmytro Suslov, Petr Chvojka, Stanislav Zvanovec

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Nonlinear phenomena in the near- and mid-infrared region are attracting scientific attention mainly due to the supercontinuum generation possibilities and subsequent utilizations for ultra-wideband applications like e.g. absorption spectroscopy or optical coherence tomography. Thulium-based fiber lasers provide access to high-power ultrashort pump pulses in the vicinity of 2000 nm, which can be easily exploited for various nonlinear applications. The paper presents a simulation and experimental study of a pulsed thulium laser based for near-infrared (NIR) and mid-infrared (MIR) nonlinear applications in specialty optical fibers. In the first part of the paper the thulium laser is discussed. The thulium laser is based on a gain-switched seed-laser and a series of amplification stages for obtaining output peak powers in the order of kilowatts for pulses shorter than 200 ps in full-width at half-maximum. The pulsed thulium laser is first studied in a simulation software, focusing on seed-laser properties. Afterward, a pre-amplification thulium-based stage is discussed, with the focus of low-noise signal amplification, high signal gain and eliminating pulse distortions during pulse propagation in the gain medium. Following the pre-amplification stage a second gain stage is evaluated with incorporating a thulium-fiber of shorter length with increased rare-earth dopant ratio. Last a power-booster stage is analyzed, where the peak power of kilowatts should be achieved. Examples of analytical study are further validated by the experimental campaign. The simulation model is further corrected based on real components – parameters such as real insertion-losses, cross-talks, polarization dependencies, etc. are included. The second part of the paper evaluates the utilization of nonlinear phenomena, their specific features at the vicinity of 2000 nm, compared to e.g. 1550 nm, and presents supercontinuum modelling, based on the thulium laser pulsed output. Supercontinuum generation simulation is performed and provides reasonably accurate results, once fiber dispersion profile is precisely defined and fiber nonlinearity is known, furthermore input pulse shape and peak power must be known, which is assured thanks to the experimental measurement of the studied thulium pulsed laser. The supercontinuum simulation model is put in relation to designed and characterized specialty optical fibers, which are discussed in the third part of the paper. The focus is placed on silica and mainly on non-silica fibers (fluoride, chalcogenide, lead-silicate) in their conventional, microstructured or tapered variants. Parameters such as dispersion profile and nonlinearity of exploited fibers were characterized either with an accurate model, developed in COMSOL software or by direct experimental measurement to achieve even higher precision. The paper then combines all three studied topics and presents a possible application of such a thulium pulsed laser system working with specialty optical fibers.

Keywords: nonlinear phenomena, specialty optical fibers, supercontinuum generation, thulium laser

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Authors: A. Oukaci, R. Toufouti, D. Dib, l. Atarsia

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This article presents a multitude of alternative techniques to control the vector control, namely the nonlinear control and sliding mode control. Moreover, the implementation of their control law applied to the high-performance to the induction motor with the objective to improve the tracking control, ensure stability robustness to parameter variations and disturbance rejection. Tests are performed numerical simulations in the Matlab/Simulink interface, the results demonstrate the efficiency and dynamic performance of the proposed strategy.

Keywords: Induction Motor (IM), Non-linear Control (NLC), Sliding Mode Control (SMC), nonlinear sliding surface

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Authors: Yosra Mefteh Rekik, Younes Boujelbene

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We introduce in this paper a new conceptual model representing the stock market dynamics. This model is essentially based on cognitive behavior of the intelligence investors. In order to validate our model, we build an artificial stock market simulation based on agent-oriented methodologies. The proposed simulator is composed of market supervisor agent essentially responsible for executing transactions via an order book and various kinds of investor agents depending to their profile. The purpose of this simulation is to understand the influence of psychological character of an investor and its neighborhood on its decision-making and their impact on the market in terms of price fluctuations. Therefore, the difficulty of the prediction is due to several features: the complexity, the non-linearity and the dynamism of the financial market system, as well as the investor psychology. The Artificial Neural Networks learning mechanism take on the role of traders, who from their futures return expectations and place orders based on their expectations. The results of intensive analysis indicate that the existence of agents having heterogeneous beliefs and preferences has provided a better understanding of price dynamics in the financial market.

Keywords: artificial intelligence methods, artificial stock market, behavioral modeling, multi-agent based simulation

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Authors: Yosra Baaziz, Moez Labidi

Abstract:

Given limited research on monetary policy rules in revolutionary countries, this paper challenges the suitability of the Taylor rule in characterizing the monetary policy behavior of the Tunisian Central Bank (BCT), especially in turbulent times. More specifically, we investigate the possibility that the Taylor rule should be formulated as a threshold process and examine the validity of such nonlinear Taylor rule as a robust rule for conducting monetary policy in Tunisia. Using quarterly data from 1998:Q4 to 2013:Q4 to analyze the movement of nominal short-term interest rate of the BCT, we find that the nonlinear Taylor rule improves its performance with the advent of special events providing thus a better description of the Tunisian interest rate setting. In particular, our results show that the adoption of an appropriate nonlinear approach leads to a reduction in the errors of 150 basis points in 1999 and 2009, and 60 basis points in 2011, relative to the linear approach.

Keywords: policy rule, central bank, exchange rate, taylor rule, nonlinearity

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