
Biomedical image encryption based on double-humped and fractional logistic maps
This paper presents a secured highly sensitive image encryption system suitable for biomedical applications. The pseudo random number generator of the presented system is based on two discrete logistic maps. The employed maps are: the double humped logistic map as well as the fractional order logistic map. The mixing of the map parameters and the initial conditions x0, offers a great variety for constructing more efficient encryption keys. Different analyses are introduced to measure the performance of the proposed encryption system such as: histogram analysis, correlation coefficients, MAE

Design of a generalized bidirectional tent map suitable for encryption applications
The discrete tent map is one of the most famous discrete chaotic maps that has widely-spread applications. This paper investigates a set of four generalized tent maps where the conventional map is a special case. The proposed maps have extra degrees of freedom which provide different chaotic characteristics and increase the design flexibility required for many applications. Mathematical analyses for generalized positive and mostly positive tent maps include: bifurcation diagrams relative to all parameters, effective range of parameters, bifurcation points. The maximum Lyapunov exponent (MLE)
Fractional derivative modeling of double-diffusive free convection with von Neumann stability analysis
This paper focuses on the problem of fractional time derivative of fluid flow and convective heat and mass transfer from a heated semi-infinite wall immersed. We provided two cases of study, one is free convective heat transfer and the other is a free double-convective heat and mass transfer. The time-derivative terms in the equations of momentum, energy and concentration are assumed to be fractional using the Grunwald-Letnikov (GL) model. A finite difference scheme has been developed for each case of study and followed by a von Neumann stability analysis. Therefore, a stability condition has

Design of low-voltage FO-[PD] controller for motion systems
Fractional-order controllers have gained significant research interest in various practical applications due to the additional degrees of freedom offered in their tuning process. The main contribution of this work is the analog implementation, for the first time in the literature, of a fractional-order controller with a transfer function that is not directly constructed from terms of the fractional-order Laplacian operator. This is achieved using Padé approximation, and the resulting integer-order transfer function is implemented using operational transconductance amplifiers as active elements

Design of fopid controller for a dc motor using approximation techniques
This paper introduces a study of fractional-order PID (FOPID) controller applied to a DC motor. The idea is to control the motor speed using the FOPID and compare it with the conventional PID controller. Two approximation techniques are employed to realize the FOPID, which are Matsuda and Oustaloup, each with order four. Different responses are depicted for various fractional orders. A specific case study for controlling the speed of a DC motor is investigated with selected fractional-orders. A comparison between the two applied techniques is proposed on the case study to determine which

Modelling and implementation of soft bio-mimetic turtle using echo state network and soft pneumatic actuators
Advances of soft robotics enabled better mimicking of biological creatures and closer realization of animals’ motion in the robotics field. The biological creature’s movement has morphology and flexibility that is problematic deportation to a bio-inspired robot. This paper aims to study the ability to mimic turtle motion using a soft pneumatic actuator (SPA) as a turtle flipper limb. SPA’s behavior is simulated using finite element analysis to design turtle flipper at 22 different geometrical configurations, and the simulations are conducted on a large pressure range (0.11–0.4 Mpa). The
Atmospheric pressure air microplasma current time series for true random bit generation
Generating true random bits of high quality at high data rates is usually viewed as a challenging task. To do so, physical sources of entropy with wide bandwidth are required which are able to provide truly random bits and not pseudorandom bits, as it is the case with deterministic algorithms and chaotic systems. In this work we demonstrate a reliable high-speed true random bit generator (TRBG) device based on the unpredictable electrical current time series of atmospheric pressure air microplasma (APAMP). After binarization of the sampled current time series, no further post-processing was

A Digital Hardware Implementation for A new Mixed-Order Nonlinear 3-D Chaotic System
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
Fractional-order edge detection masks for diabetic retinopathy diagnosis as a case study
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

A Grunwald–Letnikov based Manta ray foraging optimizer for global optimization and image segmentation
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
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