Search results for: gradient descent

Authors: Navdeep Goel, Salvador Gabarda

Abstract:

Digital images are widely used in computer applications. To store or transmit the uncompressed images requires considerable storage capacity and transmission bandwidth. Image compression is a means to perform transmission or storage of visual data in the most economical way. This paper explains about how images can be encoded to be transmitted in a multiplexing time-frequency domain channel. Multiplexing involves packing signals together whose representations are compact in the working domain. In order to optimize transmission resources each 4 × 4 pixel block of the image is transformed by a suitable polynomial approximation, into a minimal number of coefficients. Less than 4 × 4 coefficients in one block spares a significant amount of transmitted information, but some information is lost. Different approximations for image transformation have been evaluated as polynomial representation (Vandermonde matrix), least squares + gradient descent, 1-D Chebyshev polynomials, 2-D Chebyshev polynomials or singular value decomposition (SVD). Results have been compared in terms of nominal compression rate (NCR), compression ratio (CR) and peak signal-to-noise ratio (PSNR) in order to minimize the error function defined as the difference between the original pixel gray levels and the approximated polynomial output. Polynomial coefficients have been later encoded and handled for generating chirps in a target rate of about two chirps per 4 × 4 pixel block and then submitted to a transmission multiplexing operation in the time-frequency domain.

Keywords: Chirp signals, Image multiplexing, Image transformation, Linear canonical transform, Polynomial approximation.

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Authors: S. B. Kulkarni, Hasim A. Chikte, V. Murali Mohan

Abstract:

Exact solution of an unsteady MHD flow of elasticoviscous fluid through a porous media in a tube of elliptic cross section under the influence of magnetic field and constant pressure gradient has been obtained in this paper. Initially, the flow is generated by a constant pressure gradient. After attaining the steady state, the pressure gradient is suddenly withdrawn and the resulting fluid motion in a tube of elliptical cross section by taking into account of the porosity factor and magnetic parameter of the bounding surface is investigated. The problem is solved in two-stages the first stage is a steady motion in tube under the influence of a constant pressure gradient, the second stage concern with an unsteady motion. The problem is solved employing separation of variables technique. The results are expressed in terms of a non-dimensional porosity parameter, magnetic parameter and elastico-viscosity parameter, which depends on the Non-Newtonian coefficient. The flow parameters are found to be identical with that of Newtonian case as elastic-viscosity parameter, magnetic parameter tends to zero, and porosity tends to infinity. The numerical results were simulated in MATLAB software to analyze the effect of Elastico-viscous parameter, porosity parameter, and magnetic parameter on velocity profile. Boundary conditions were satisfied. It is seen that the effect of elastico-viscosity parameter, porosity parameter and magnetic parameter of the bounding surface has significant effect on the velocity parameter.

Keywords: Elastico-viscous fluid, Porous media, Elliptic cross-section, Magnetic parameter, Numerical Simulation.

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Authors: Zhijun Ren, Zhang Lin, Zhao Ye, Zuo Xiangyu, Mei Dongxing

Abstract:

As a pretreatment process of ballast water treatment, the performance of high gradient magnetic separation (HGMS) technology for the removal of particulates and microorganisms was studied. The results showed that HGMS process could effectively remove suspended particles larger than 5 µm and had ability to resist impact load. Microorganism could also be effectively removed by HGMS process, and the removal effect increased with increasing magnetic field strength. The maximum removal rates for Escherichia coli (E. coli) and Staphylococcus aureus (S. aureus) were 4016.1% and 9675.3% higher, respectively, than without the magnetic field. In addition, the superoxide dismutase (SOD) activity of the microbes decreased by 32.2% when the magnetic field strength was 15.4 mT for 72 min. The microstructure of the stainless steel wool was investigated, and the results showed that particle removal by HGMS has common function by the magnetic force of the high-strength, high-gradient magnetic field on weakly magnetic particles in the water, and on the stainless steel wool.

Keywords: HGMS, particulates, superoxide dismutase activity, steel wool magnetic medium.

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Authors: Hossein Riazoshams, Midi Habshah, Jr., Mohamad Bakri Adam

Abstract:

The detection of outliers is very essential because of their responsibility for producing huge interpretative problem in linear as well as in nonlinear regression analysis. Much work has been accomplished on the identification of outlier in linear regression, but not in nonlinear regression. In this article we propose several outlier detection techniques for nonlinear regression. The main idea is to use the linear approximation of a nonlinear model and consider the gradient as the design matrix. Subsequently, the detection techniques are formulated. Six detection measures are developed that combined with three estimation techniques such as the Least-Squares, M and MM-estimators. The study shows that among the six measures, only the studentized residual and Cook Distance which combined with the MM estimator, consistently capable of identifying the correct outliers.

Keywords: Nonlinear Regression, outliers, Gradient, LeastSquare, M-estimate, MM-estimate.

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Authors: Ishtiaq A. Chaudhry, Zia R. Tahir

Abstract:

Experimental investigation has been carried out towards understanding the complex fluid dynamics involved in the interaction of vortical structures with zero pressure gradient boundary layer. A laminar boundary layer is produced on the flat plate placed in the water flume and the synthetic jet actuator is deployed on top of the plate at a definite distance from the leading edge. The synthetic jet actuator has been designed in such a way that the to and fro motion of the diaphragm is maneuvered at will by varying the operating parameters to produce the typical streamwise vortical structures namely hairpin and tilted vortices. PIV measurements are made on the streamwise plane normal to the plate to evaluate their interaction with the near wall fluid.

Keywords: Boundary layer, synthetic jet actuator, flow separation control, vortical structures.

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Authors: Toshinori Nawata

Abstract:

In this paper we consider a nonlinear feedback control called augmented automatic choosing control (AACC) using the automatic choosing functions of gradient optimization type for nonlinear systems. Constant terms which arise from sectionwise linearization of a given nonlinear system are treated as coefficients of a stable zero dynamics. Parameters included in the control are suboptimally selected by minimizing the Hamiltonian with the aid of the genetic algorithm. This approach is applied to a field excitation control problem of power system to demonstrate the splendidness of the AACC. Simulation results show that the new controller can improve performance remarkably well.

Keywords: augmented automatic choosing control, nonlinear control, genetic algorithm, zero dynamics.

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Authors: Vai Kuong Sin

Abstract:

Non-isothermal stagnation-point flow with consideration of thermal radiation is studied numerically. A set of partial differential equations that governing the fluid flow and energy is converted into a set of ordinary differential equations which is solved by Runge-Kutta method with shooting algorithm. Dimensionless wall temperature gradient and temperature boundary layer thickness for different combinaton of values of Prandtl number Pr and radiation parameter NR are presented graphically. Analyses of results show that the presence of thermal radiation in the stagnation-point flow is to increase the temperature boundary layer thickness and decrease the dimensionless wall temperature gradient.

Keywords: Stagnation-point flow, Similarity solution, Thermal radiation.

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Authors: N. Shanmugapriya, R. Nallusamy

Abstract:

Content-based image retrieval (CBIR) uses the contents of images to characterize and contact the images. This paper focus on retrieving the image by separating images into its three color mechanism R, G and B and for that Discrete Wavelet Transformation is applied. Then Wavelet based Generalized Gaussian Density (GGD) is practical which is used for modeling the coefficients from the wavelet transforms. After that it is agreed to Histogram of Oriented Gradient (HOG) for extracting its characteristic vectors with Relevant Feedback technique is used. The performance of this approach is calculated by exactness and it confirms that this method is wellorganized for image retrieval.

Keywords: Content-Based Image Retrieval (CBIR), Relevant Feedback, Histogram of Oriented Gradient (HOG), Generalized Gaussian Density (GGD).

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Authors: M. A. Beisenbi, N. M. Kissikova, S. E. Beisembina, S. T. Suleimenova, S. A. Kaliyeva

Abstract:

The paper proposes a method for constructing a self-organizing control system for unstable and deterministic chaotic processes in the class of catastrophe “hyperbolic umbilic” for objects with m-inputs and n-outputs. The self-organizing control system is investigated by the universal gradient-velocity method of Lyapunov vector-functions. The conditions for self-organization of the control system in the class of catastrophes “hyperbolic umbilic” are shown in the form of a system of algebraic inequalities that characterize the aperiodic robust stability in the stationary states of the system.

Keywords: Gradient-velocity method of Lyapunov vector-functions, hyperbolic umbilic, self-organizing control system, stability.

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Authors: Toshinori Nawata

Abstract:

In this paper we consider a nonlinear feedback control called augmented automatic choosing control (AACC) using the gradient optimization automatic choosing functions for nonlinear systems. Constant terms which arise from sectionwise linearization of a given nonlinear system are treated as coefficients of a stable zero dynamics. Parameters included in the control are suboptimally selected by expanding a stable region in the sense of Lyapunov with the aid of the genetic algorithm. This approach is applied to a field excitation control problem of power system to demonstrate the splendidness of the AACC. Simulation results show that the new controller can improve performance remarkably well.

Keywords: augmented automatic choosing control, nonlinear control, genetic algorithm, zero dynamics.

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Authors: Z. Zainuddin, N. Mahat, Y. Abu Hassan

Abstract:

Since the presentation of the backpropagation algorithm, a vast variety of improvements of the technique for training a feed forward neural networks have been proposed. This article focuses on two classes of acceleration techniques, one is known as Local Adaptive Techniques that are based on weightspecific only, such as the temporal behavior of the partial derivative of the current weight. The other, known as Dynamic Adaptation Methods, which dynamically adapts the momentum factors, α, and learning rate, η, with respect to the iteration number or gradient. Some of most popular learning algorithms are described. These techniques have been implemented and tested on several problems and measured in terms of gradient and error function evaluation, and percentage of success. Numerical evidence shows that these techniques improve the convergence of the Backpropagation algorithm.

Keywords: Backpropagation, Dynamic Adaptation Methods, Local Adaptive Techniques, Neural networks.

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Authors: Hadi Sadoghi Yazdi, Mehri Sadoghi Yazdi, Mohammad Reza Mohammadi

Abstract:

This paper is concerned with studying the forgetting factor of the recursive least square (RLS). A new dynamic forgetting factor (DFF) for RLS algorithm is presented. The proposed DFF-RLS is compared to other methods. Better performance at convergence and tracking of noisy chirp sinusoid is achieved. The control of the forgetting factor at DFF-RLS is based on the gradient of inverse correlation matrix. Compared with the gradient of mean square error algorithm, the proposed approach provides faster tracking and smaller mean square error. In low signal-to-noise ratios, the performance of the proposed method is superior to other approaches.

Keywords: Forgetting factor, RLS, Inverse correlation matrix, human motion analysis.

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Authors: F. Bendahma, M. Mana, B. Bestani, S. Bentata

Abstract:

This study deals with the structural and electronic properties of ternary PdMnGe Half-Heusler alloy using the full potential linearized augmented plane wave (FP-LAPW) method based on the density functional theory (DFT) as implemented in the WIEN2k package, within the framework of generalized gradient approximation (GGA). Structural parameters, total and partial densities of states were also analyzed. The obtained result shows that the studied material is metallic in GGA treatment. The elastic constants (Cij) show that our compound is ductile, stiff and anisotropic.

Keywords: Full potential linearized augmented plane wave, generalized gradient approximation treatment, Half-Heusler, structural and electronic properties.

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Authors: Toshinori Nawata

Abstract:

In this paper we consider a nonlinear feedback control called augmented automatic choosing control (AACC) for nonlinear systems with constrained input using weighted gradient optimization automatic choosing functions. Constant term which arises from linearization of a given nonlinear system is treated as a coefficient of a stable zero dynamics. Parameters of the control are suboptimally selected by maximizing the stable region in the sense of Lyapunov with the aid of a genetic algorithm. This approach is applied to a field excitation control problem of power system to demonstrate the splendidness of the AACC. Simulation results show that the new controller can improve performance remarkably well.

Keywords: Augmented automatic choosing control, nonlinear control, genetic algorithm, zero dynamics.

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Authors: N. K. Singh, S. Sarkar

Abstract:

Direct numerical simulation (DNS) is used to study the evolution of a boundary layer that was laminar initially followed by separation and then reattachment owing to generation of turbulence. This creates a closed region of recirculation, known as the laminar-separation bubble. The present simulation emulates the flow environment encountered in a modern LP turbine blade, where a laminar separation bubble may occur on the suction surface. The unsteady, incompressible three-dimensional (3-D) Navier-Stokes (NS) equations have been solved over a flat plate in the Cartesian coordinates. The adverse pressure gradient, which causes the flow to separate, is created by a boundary condition. The separated shear layer undergoes transition through appearance of ╬ø vortices, stretching of these create longitudinal streaks. Breakdown of the streaks into small and irregular structures makes the flow turbulent downstream.

Keywords: Adverse pressure gradient, direct numerical simulation, laminar separation bubble.

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Authors: Mostafa Raki, Mahdi Hamzehei

Abstract:

Equilibrium and stability equations of a thin rectangular plate with length a, width b, and thickness h(x)=C1x+C2, made of functionally graded materials under thermal loads are derived based on the first order shear deformation theory. It is assumed that the material properties vary as a power form of thickness coordinate variable z. The derived equilibrium and buckling equations are then solved analytically for a plate with simply supported boundary conditions. One type of thermal loading, uniform temperature rise and gradient through the thickness are considered, and the buckling temperatures are derived. The influences of the plate aspect ratio, the relative thickness, the gradient index and the transverse shear on buckling temperature difference are all discussed.

Keywords: Stability of plate, thermal buckling, rectangularplate, functionally graded material, first order shear deformationtheory.

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Authors: Hu Haibo, Zhao Hong

Abstract:

Gaussian mixture background model is widely used in moving target detection of the image sequences. However, traditional Gaussian mixture background model usually considers the time continuity of the pixels, and establishes background through statistical distribution of pixels without taking into account the pixels- spatial similarity, which will cause noise, imperfection and other problems. This paper proposes a new Gaussian mixture modeling approach, which combines the color and gradient of the spatial information, and integrates the spatial information of the pixel sequences to establish Gaussian mixture background. The experimental results show that the movement background can be extracted accurately and efficiently, and the algorithm is more robust, and can work in real time in tracking applications.

Keywords: Gaussian mixture model, real-time tracking, sequence image, gradient.

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Authors: A. Kurşun, E. Kara, E. Çetin, Ş. Aksoy, A. Kesimli

Abstract:

In this study, thermal elastic stress distribution occurred on long hollow cylinders made of functionally graded material (FGM) was analytically defined under thermal, mechanical and thermo mechanical loads. In closed form solutions for elastic stresses and displacements are obtained analytically by using the infinitesimal deformation theory of elasticity. It was assumed that elasticity modulus, thermal expansion coefficient and density of cylinder materials could change in terms of an exponential function as for that Poisson’s ratio was constant. A gradient parameter n is chosen between - 1 and 1. When n equals to zero, the disc becomes isotropic. Circumferential, radial and longitudinal stresses in the FGMs cylinders are depicted in the figures. As a result, the gradient parameters have great effects on the stress systems of FGMs cylinders.

Keywords: Functionally graded materials, hollow cylinder, thermoelasticity, thermomechanical load.

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Authors: V. Azadeh Ranjbar

Abstract:

Rarefied gas flows are often occurred in micro electro mechanical systems and classical CFD could not precisely anticipate the flow and thermal behavior due to the high Knudsen number. Therefore, the heat transfer and the fluid dynamics characteristics of rarefied gas flows in both a two-dimensional simple microchannel and geometry similar to single Knudsen compressor have been investigated with a goal of increasing performance of a actual Knudsen compressor by using a particle simulation method. Thermal transpiration and thermal creep, which are rarefied gas dynamic phenomena, that cause movement of the flow from less to higher temperature is generated by using two different longitude temperature gradients (Linear, Step) along the walls of the flow microchannel. In this study the influence of amount of temperature gradient and governing pressure in various Knudsen numbers and length-to-height ratios have been examined.

Keywords: DSMC, Thermal transpiration, Thermal creep, MEMS, Knudsen Compressor.

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Authors: C. Y. Chen

Abstract:

As the global climate changes, the threat from landslides and debris flows increases. Learning how a watershed initiates landslides under abnormal rainfall conditions and predicting landslide magnitude and frequency distribution is thus important. Landslides show a power-law distribution in the frequency-area distribution. The distribution curve shows an exponent gradient 1.0 in the Sandpile model test. Will the landslide frequency-area statistics show a distribution similar to the Sandpile model under extreme rainfall conditions? The purpose of the study is to identify the extreme rainfall-induced landslide frequency-area distribution in the Laonong River Basin in southern Taiwan. Results of the analysis show that a lower gradient of landslide frequency-area distribution could be attributed to the transportation and deposition of debris flow areas that are included in the landslide area.

Keywords: Landslide, power-law distribution, GIS.

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Authors: Cafer Görkem Pınar, İlker Coşar, Serkan Uzun, Atahan Çelebi, Mehmet Ali Ersoy, Ali Pınarbaşı

Abstract:

In this study, it was numerically investigated that a 1:1 scale model of the Renault Clio MK4 SW brand vehicle aerodynamic analysis was performed in the commercial computational fluid dynamics (CFD) package program of ANSYS CFX 2021 R1 under steady, subsonic, and 3-D conditions. The model of vehicle used for the analysis was made independent of the number of mesh elements and the k-epsilon turbulence model was applied during the analysis. Results were interpreted as streamlines, pressure gradient, and turbulent kinetic energy contours around the vehicle at 50 km/h and 100 km/h speeds. In addition, the validity of the analysis was decided by comparing the drag coefficient of the vehicle with the values in the literature. As a result, the pressure gradient contours of the taillight of the Renault Clio MK4 SW vehicle were examined and the behavior of the total force at speeds of 50 km/h and 100 km/h was interpreted.

Keywords: CFD, k-epsilon, aerodynamics, drag coefficient, taillight.

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Authors: Mostafa Ghayour, Mohammad Sadegh Golabi

Abstract:

In the recent years, functionally gradient materials (FGMs) have gained considerable attention in the high temperature environment applications. In this paper, free vibration of thin functionally graded cylindrical shell with hole composed of stainless steel and zirconia is studied. The mechanical properties vary smoothly and continuously from one surface to the other according to a volume fraction power-law distribution. The Influence of shell geometrical parameters, variations of volume fractions and boundary conditions on natural frequency is considered. The equations of motion are based on strains-displacement relations from Love-s shell theory and Rayleigh method. The results have been obtained for natural frequencies of cylindrical shell with holes for different shape, number and location in this paper.

Keywords: Functionally gradient material, Vibration, various boundary conditions, cylindrical shells.

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Authors: Karina Zaccari, Ernesto Cordeiro Marujo

Abstract:

This paper presents a Machine Learning (ML) approach to support Meningitis diagnosis in patients at a children’s hospital in Sao Paulo, Brazil. The aim is to use ML techniques to reduce the use of invasive procedures, such as cerebrospinal fluid (CSF) collection, as much as possible. In this study, we focus on predicting the probability of Meningitis given the results of a blood and urine laboratory tests, together with the analysis of pain or other complaints from the patient. We tested a number of different ML algorithms, including: Adaptative Boosting (AdaBoost), Decision Tree, Gradient Boosting, K-Nearest Neighbors (KNN), Logistic Regression, Random Forest and Support Vector Machines (SVM). Decision Tree algorithm performed best, with 94.56% and 96.18% accuracy for training and testing data, respectively. These results represent a significant aid to doctors in diagnosing Meningitis as early as possible and in preventing expensive and painful procedures on some children.

Keywords: Machine learning, medical diagnosis, meningitis detection, gradient boosting.

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Authors: B. J. C. Horsten, L. L. M. Veldhuis

Abstract:

Because support interference corrections are not properly understood, engineers mostly rely on expensive dummy measurements or CFD calculations. This paper presents a method based on uncorrected wind tunnel measurements and fast calculation techniques (it is a hybrid method) to calculate wall interference, support interference and residual interference (when e.g. a support member closely approaches the wind tunnel walls) for any type of wind tunnel and support configuration. The method provides with a simple formula for the calculation of the interference gradient. This gradient is based on the uncorrected measurements and a successive calculation of the slopes of the interference-free aerodynamic coefficients. For the latter purpose a new vortex-lattice routine is developed that corrects the slopes for viscous effects. A test case of a measurement on a wing proves the value of this hybrid method as trends and orders of magnitudes of the interference are correctly determined.

Keywords: Hybrid method, support interference, wall interference, wind tunnel corrections.

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Authors: Satish Kumar Dewangan, Santosh Kumar Senapati

Abstract:

The present work focuses on the investigation of the effect of non-Newtonian behavior on the oil-water stratified flow in a horizontal channel using ANSYS Fluent. Coupled level set and volume of fluid (CLSVOF) has been used to capture the evolving interface assuming unsteady, coaxial flow with constant fluid properties. The diametric variation of oil volume fraction, mixture velocity, total pressure and pressure gradient has been studied. Non-Newtonian behavior of oil has been represented by the power law model in order to investigate the effect of flow behavior index. Stratified flow pattern tends to assume dispersed flow pattern with the change in the behavior of oil to non-Newtonian. The pressure gradient is found to be very much sensitive to the flow behavior index. The findings could be useful in designing the transportation pipe line in petroleum industries.

Keywords: Oil-water stratified flow, horizontal channel, CLSVOF, non–Newtonian behavior.

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Authors: Chenxue Yang, Mao Ye, Zijian Liu, Tao Li, Jiao Bao

Abstract:

Non-negative matrix factorization (NMF) is a useful computational method to find basis information of multivariate nonnegative data. A popular approach to solve the NMF problem is the multiplicative update (MU) algorithm. But, it has some defects. So the columnwisely alternating gradient (cAG) algorithm was proposed. In this paper, we analyze convergence of the cAG algorithm and show advantages over the MU algorithm. The stability of the equilibrium point is used to prove the convergence of the cAG algorithm. A classic model is used to obtain the equilibrium point and the invariant sets are constructed to guarantee the integrity of the stability. Finally, the convergence conditions of the cAG algorithm are obtained, which help reducing the evaluation time and is confirmed in the experiments. By using the same method, the MU algorithm has zero divisor and is convergent at zero has been verified. In addition, the convergence conditions of the MU algorithm at zero are similar to that of the cAG algorithm at non-zero. However, it is meaningless to discuss the convergence at zero, which is not always the result that we want for NMF. Thus, we theoretically illustrate the advantages of the cAG algorithm.

Keywords: Non-negative matrix factorizations, convergence, cAG algorithm, equilibrium point, stability.

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Authors: Evangelos G. Karvelas, Christos Liosis, Andreas Theodorakakos, Theodoros E. Karakasidis

Abstract:

In the present work, a numerical method for the estimation of the appropriate gradient magnetic fields for optimum driving of the particles into the desired area inside the human body is presented. The proposed method combines Computational Fluid Dynamics (CFD), Discrete Element Method (DEM) and Covariance Matrix Adaptation (CMA) evolution strategy for the magnetic navigation of nanoparticles. It is based on an iteration procedure that intents to eliminate the deviation of the nanoparticles from a desired path. Hence, the gradient magnetic field is constantly adjusted in a suitable way so that the particles’ follow as close as possible to a desired trajectory. Using the proposed method, it is obvious that the diameter of particles is crucial parameter for an efficient navigation. In addition, increase of particles' diameter decreases their deviation from the desired path. Moreover, the navigation method can navigate nanoparticles into the desired areas with efficiency approximately 99%.

Keywords: CFD, CMA evolution strategy, DEM, magnetic navigation, spherical particles.

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Authors: D. Hişam, S. İkizoğlu

Abstract:

Identifying the problem behind balance disorder is one of the most interesting topics in medical literature. This study has considerably enhanced the development of artificial intelligence (AI) algorithms applying multiple machine learning (ML) models to sensory data on gait collected from humans to classify between normal people and those suffering from Vestibular System (VS) problems. Although AI is widely utilized as a diagnostic tool in medicine, AI models have not been used to perform feature extraction and identify VS disorders through training on raw data. In this study, three ML models, the Random Forest Classifier (RF), Extreme Gradient Boosting (XGB), and K-Nearest Neighbor (KNN), have been trained to detect VS disorder, and the performance comparison of the algorithms has been made using accuracy, recall, precision, and f1-score. With an accuracy of 95.28 %, Random Forest (RF) Classifier was the most accurate model.

Keywords: Vestibular disorder, machine learning, random forest classifier, k-nearest neighbor, extreme gradient boosting.

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Authors: Tejeet Singh, Harmanjit Singh

Abstract:

Creep behavior of thick-walled functionally graded cylinder consisting of AlSiC and subjected to internal pressure and high temperature has been analyzed. The functional relationship between strain rate with stress can be described by the well known threshold stress based creep law with a stress exponent of five. The effect of imposing non-linear particle gradient on the distribution of creep stresses in the thick-walled functionally graded composite cylinder has been investigated. The study revealed that for the assumed non-linear particle distribution, the radial stress decreases throughout the cylinder, whereas the tangential, axial and effective stresses have averaging effect. The strain rates in the functionally graded composite cylinder could be reduced to significant extent by employing non-linear gradient in the distribution of reinforcement.

Keywords: Functionally Graded Material, Pressure, Steady State Creep, Thick-Cylinder.

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Authors: Huda Algharib, Amal Algharib, Hanan Algharib, Ali Mohammad Alqudah

Abstract:

Image registration is an important topic for many imaging systems and computer vision applications. The standard image registration techniques such as Mutual information/ Normalized mutual information -based methods have a limited performance because they do not consider the spatial information or the relationships between the neighbouring pixels or voxels. In addition, the amount of image noise may significantly affect the registration accuracy. Therefore, this paper proposes an efficient method that explicitly considers the relationships between the adjacent pixels, where the gradient information of the reference and scene images is extracted first, and then the cosine similarity of the extracted gradient information is computed and used to improve the accuracy of the standard normalized mutual information measure. Our experimental results on different data types (i.e. CT, MRI and thermal images) show that the proposed method outperforms a number of image registration techniques in terms of the accuracy.

Keywords: Image registration, mutual information, image gradients, Image transformations.

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