This study presents a practical method for solving fractional order delay variational problems. The fractional derivative is given in the Caputo sense. The suggested approach is based on the Laplace transform and the shifted Legendre polynomials by approximating the candidate function by the shifted Legendre series with unknown coefficients yet to be determined. The proposed method converts the fractional order delay variational problem into a set of (n + 1) algebraic equations, where the solution to the resultant equation provides us the unknown coefficients of the terminated series that have been utilized to approximate the solution to the considered variational problem. Illustrative examples are given to show that the recommended approach is applicable and accurate for solving such kinds of problems.
Image segmentation can be defined as a cutting or segmenting process of the digital image into many useful points which are called segmentation, that includes image elements contribute with certain attributes different form Pixel that constitute other parts. Two phases were followed in image processing by the researcher in this paper. At the beginning, pre-processing image on images was made before the segmentation process through statistical confidence intervals that can be used for estimate of unknown remarks suggested by Acho & Buenestado in 2018. Then, the second phase includes image segmentation process by using "Bernsen's Thresholding Technique" in the first phase. The researcher drew a conclusion that in case of utilizing
... Show MoreThe natural polyphenolic compound that cinnamon contains is well known for its various biological activities, a broad variety of pharmacological and therapeutic properties. Diversified biomedical and pharmacological applications benefit from organic nanoparticles with controlled properties. Bioactive and non-toxic, cinnamon nanoparticles (CNPs) can be effective antibacterial agents. Driven by this idea, we prepared spherical CNPs using liquid (PLAL) pulse laser ablation technique and defined those NPs. Using Q-switched Nd : YAG With a wavelength of 1064 nm pulse laser of constant energy 500 mj , And different laser pulses ( 250 , 500 , 750 , 1000 ) pulse /sec a pure cinnamon target submerged in
... Show MoreThe objective of the study to develop an amorphous solid dispersion for poorly soluble raltegravir by hot melt extrusion (HME) technique. A novel solubility improving agent plasdone s630 was utilized. The HME raltegravir was formulated into tablet by direct compression method. The prepared tablets were assessed for all pre and post-compression parameters. The drug- excipients interaction was examined by FTIR and DSC. All formulas displayed complying with pharmacopoeial measures. The study reveals that formula prepared by utilizing drug and plasdone S630 at 1:1.5 proportion and span 20 at concentration about 30mg (trail-6) has given highest dissolution rate than contrasted with various formulas of raltegravir.
Keywor
... Show MoreThe present study include a new developed method of analysis for determination of drug Spironolaction (SP) in some Pharmaceuticals by Spectrofluorometric method. Spironolaction was determined under optimal experimental condition that follows :- The excitation spectrum was (l=351 nm), the emmetion spectrum was (l=518 nm), pH=1, the suitable temperature for reaction 60oC and the optimal time less than (3) minute. The analysis and rang statistical data was:-Linear dynamic rang (1-10) ?g.ml-1, the detection limit (D.L = 0.023 ?g.ml-1), Molar absorptivity (? = 29875 liter mole-1 cm-1), Relative standard deviation (%RSD = 0.78), (%Erel = 3.3) and recovery (Rec = 96.6) percentage. Determination of Spironolactone was accomplished by two methods
... Show MoreMonaural source separation is a challenging issue due to the fact that there is only a single channel available; however, there is an unlimited range of possible solutions. In this paper, a monaural source separation model based hybrid deep learning model, which consists of convolution neural network (CNN), dense neural network (DNN) and recurrent neural network (RNN), will be presented. A trial and error method will be used to optimize the number of layers in the proposed model. Moreover, the effects of the learning rate, optimization algorithms, and the number of epochs on the separation performance will be explored. Our model was evaluated using the MIR-1K dataset for singing voice separation. Moreover, the proposed approach achi
... Show MoreAbstract
For sparse system identification,recent suggested algorithms are
-norm Least Mean Square (
-LMS), Zero-Attracting LMS (ZA-LMS), Reweighted Zero-Attracting LMS (RZA-LMS), and p-norm LMS (p-LMS) algorithms, that have modified the cost function of the conventional LMS algorithm by adding a constraint of coefficients sparsity. And so, the proposed algorithms are named
-ZA-LMS,
This paper introduces a non-conventional approach with multi-dimensional random sampling to solve a cocaine abuse model with statistical probability. The mean Latin hypercube finite difference (MLHFD) method is proposed for the first time via hybrid integration of the classical numerical finite difference (FD) formula with Latin hypercube sampling (LHS) technique to create a random distribution for the model parameters which are dependent on time [Formula: see text]. The LHS technique gives advantage to MLHFD method to produce fast variation of the parameters’ values via number of multidimensional simulations (100, 1000 and 5000). The generated Latin hypercube sample which is random or non-deterministic in nature is further integ
... Show MoreFeature selection (FS) constitutes a series of processes used to decide which relevant features/attributes to include and which irrelevant features to exclude for predictive modeling. It is a crucial task that aids machine learning classifiers in reducing error rates, computation time, overfitting, and improving classification accuracy. It has demonstrated its efficacy in myriads of domains, ranging from its use for text classification (TC), text mining, and image recognition. While there are many traditional FS methods, recent research efforts have been devoted to applying metaheuristic algorithms as FS techniques for the TC task. However, there are few literature reviews concerning TC. Therefore, a comprehensive overview was systematicall
... Show MoreThe increased use of hybrid PET /CT scanners combining detailed anatomical information along withfunctional data has benefits for both diagnostic and therapeutic purposes. This presented study is to makecomparison of cross sections to produce 18F , 82Sr and68Ge via different reactions with particle incident energy up to 60 MeV as a part of systematic studies on particle-induced activations on enriched natNe, natRb, natGa 18O,85Rb, and 69Ga targets, theoretical calculation of production yield, calculation of requiredtarget and suggestion of optimum reaction to produce: Fluorine-18 , Strontium-82 andGermanium-68 touse in Hybrid Machines PET/CT Scanners.