This paper introduces a generic modeling for a 3-D nonlinear chaotic based on fractional-order mathematical rules. Also, a novel modeling for the system using a mixture between integer and fractional-order calculus is proposed. Dynamics of the new realization are illustrated using phase portrait diagrams with complex behavior. Also, a great change in the parameter ranges is investigated using bifurcation diagrams. MATLAB and Xilinx ISE 14.5 are used in system simulations. Furthermore, the digital hardware implementation is done using Xilinx FPGA Virtex-5 kit. The synthesis report shows that

Edge detection is one of the main steps in the image processing field, especially in bio-medical imaging, to diagnose a disease or trace its progress. The transfer of medical images makes them more susceptible to quality degradation due to any imposed noise. Hence, the protection of this data against noise is a persistent need. The efficiency of fractional-order filters to detect fine details and their high noise robustness, unlike the integer-order filters, it renders them an attractive solution for biomedical edge detection. In this work, two novel central fractional-order masks are proposed

This paper presents a modified version of Manta ray foraging optimizer (MRFO) algorithm to deal with global optimization and multilevel image segmentation problems. MRFO is a meta-heuristic technique that simulates the behaviors of manta rays to find the food. MRFO established its ability to find a suitable solution for a variant of optimization problems. However, by analyzing its behaviors during the optimization process, it is observed that its exploitation ability is less than exploration ability, which makes MRFO more sensitive to attractive to a local point. Therefore, we enhanced MRFO by

In this article, different control design approaches for parallel robot manipulators are presented with two distinguished classes of control strategies in the literature. These are the model-free control and the dynamic control strategy, which is mainly a model-based scheme, and is mostly the alternative when the control requirements are more stringent. The authors strongly believe that this paper will be helpful for researchers and engineers in the field of robotic systems. Copyright 2017 Inderscience Enterprises Ltd.

Due to the dispersive porous nature of its material, carbon–carbon supercapacitors have a current–voltage relationship which is modeled by a fractional-order differential equation of the form i(t)=Cα[Formula presented] where α≤1 is a dispersion coefficient and Cα is a pseudo-capacitance not measurable in Farads. Hence, the energy stored in a capacitor, known to equal CV2/2 where C is the capacitance in Farad and V is the voltage applied, does not apply to a supercapacitor. In a recent work (Allagui et al., 2016), a fractional-order energy equation that enables the quantification of the energy

Swarm intelligence represents a meta-heuristic approach to solve a wide variety of problems. Searching for similar patterns of genes is becoming very essential to predict the expression of genes under various conditions. Firefly clustering inspired by the behaviour of fireflies helps in grouping genes that behave alike. Contrasting hard clustering methodology, fuzzy clustering assigns membership values for every gene and predicts the possibility of belonging to every cluster. To distinguish highly expressed and suppressed genes, the research in this paper proposes an efficient fuzzy-firefly

This paper is dedicated to develop a fractional order model of the rate of change of cancerous blood cells in Chronic Myeloid Leukaemia using fractional-order differential equations as well as tackling the factors that affect this rate and compare between them. The simulated cases (using MATLAB) prove that the proposed model is doable in terms of the variables positions in the equations and its effect on the overall population. Also, the effect of the Pactional order is investigated through three parameters sets and it has shown strong influence on the dynamic response. © 2017 IEEE.

This paper presents a comparative study of four fractional order filters used for edge detection. The noise performance of these filters is analyzed upon the addition of random Gaussian noise, as well as the addition of salt and pepper noise. The peak signal to noise ratio (PSNR) of the detected images is numerically compared. The mean square error (MSE) of the detected images as well as the execution time are also adopted as evaluation methods for comparison. The visual comparison of the filters capability in medical image edge detection is presented, that can help in the diagnosis of

Recently, numerous research works in retinal-structure analysis have been performed to analyze retinal images for diagnosing and preventing ocular diseases such as diabetic retinopathy, which is the first most common causes of vision loss in the world. In this paper, an algorithm for vessel detection in fundus images is employed. First, a denoising process using the noise-estimation-based anisotropic diffusion technique is applied to restore connected vessel lines in a retinal image and eliminate noisy lines. Next, a multi-scale line-tracking algorithm is implemented to detect all the blood

Genetic algorithms (GAs) are intended to look for the optimum solution by eliminating the gene strings with the worst fitness. Hence, this paper proposes an optimized edge detection technique based on a genetic algorithm. A training dataset that consists of simple images and their corresponding optimal edge features is employed to obtain the optimum filter coefficients along with the optimum thresholding algorithm. Qualitative and quantitative performance analyses are investigated based on several well-known metrics. The performance of the proposed genetic algorithm-based cost minimization