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

In this paper, we introduce an analytical solution of the fractional derivative gas transport equation using the power-series technique. We present a new universal transform, namely, generalized Boltzmann change of variable which depends on the fractional order, time and space. This universal transform is employed to transfer the partial differential equation into an ordinary differential equation. Moreover, the convergence of the solution has been investigated and found that solutions are unconditionally converged. Results are introduced and discussed for the universal variable and other

This paper introduces a Fractional-Order Model (FOM) of Up-flow Anaerobic Sludge Blanket (UASB) reactor for wastewater treatment regarding high-strength substrate biodegradation. The model can investigate the biogas production rate as well as the specific growth rate of bacteria with extra degree of freedom. Also, the hereditary effect of resident biomass on substrate degradation is studied on periodically long terms. Moreover, biomass concentration is examined in reactor under the influence of various fractional orders. Several numerical simulation results are introduced based on Grünwald

This paper addresses a modified kinetic-hydraulic model for up-flow anaerobic sludge blanket (UASB) reactor aimed to treat wastewater of biodegradable organic substrates as acetic acid based on Van der Meer model incorporated with biological granules inclusion. This dynamic model illustrates the biomass kinetic reaction rate for both direct and indirect growth of microorganisms coupled with the amount of biogas produced by methanogenic bacteria in bed and blanket zones of reactor. Moreover, the pH value required for substrate degradation at the peak specific growth rate of bacteria is

Large and complex system-on-chip devices consisting of many processor cores, accelerators, DSP functions and many other processing and memory elements are becoming common in the semiconductor industry nowadays. To communicate, these processing and memory elements need to have a network-on-chip (NoC) that is scalable enough to support large number of elements and large bandwidth among other requirements. This paper evaluates the performance of the 2D memory-centric NoC architecture from throughput and latency perspective versus the Mesh topology. We also propose a memory-centric architecture

Mixing carbon-based materials with pseudocapacitive material is a widely used strategy to prepare high-energy, high-power supercapacitors. However, phase separation is inevitable after extended charging/discharging which leads to the degradation of performance metrics of the device. Here, we prepare in a single step cobalt-incorporated carbon nanofibers (CNF) by electrospinning homogeneous solutions of polyacrylonitrile (PAN) with cobalt acetate at different nominal proportions (1:0 to 1:1), and investigate their stability and capacitive behavior in symmetric supercapacitors. The

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Renewable Energy sources are the center of attraction for research and development all over the world nowadays, the demand of a lasting cheap source of energy that is environmental friendly, is the main challenge recently. Energy Harvesting is a new technology that is going to make a revolution in the coming decade. Energy Harvesting is a technique to provide alternative sources of energy that are environmental friendly and low in cost. Radio Frequency Energy Harvesting is one of the methods to provide electrical energy from the ambient Radio Frequency waves that already exists in the