We present a reliable algorithm for solving, homogeneous or inhomogeneous, nonlinear ordinary delay differential equations with initial conditions. The form of the solution is calculated as a series with easily computable components. Four examples are considered for the numerical illustrations of this method. The results reveal that the semi analytic iterative method (SAIM) is very effective, simple and very close to the exact solution demonstrate reliability and efficiency of this method for such problems.

This paper deals with the thirteenth order differential equations linear and nonlinear in boundary value problems by using the Modified Adomian Decomposition Method (MADM), the analytical results of the equations have been obtained in terms of convergent series with easily computable components. Two numerical examples results show that this method is a promising and powerful tool for solving this problems.

The main purpose of this paper, is to characterize new admissible classes of linear operator in terms of seven-parameter Mittag-Leffler function, and discuss sufficient conditions in order to achieve certain third-order differential subordination and superordination results. In addition, some linked sandwich theorems involving these classes had been obtained.  

Abstract Background: The daily usage of maxillofacial prostheses causes them to mechanically deteriorate with time. This study was aimed to evaluate the reinforcement of VST50F maxillofacial silicone by using yttrium oxide (Y2O3) nanoparticles (NPs) to resist aging and mechanical deterioration. Materials and Method: Y2O3 NPs (30–45nm) were loaded into VST50F maxillofacial silicone in two weight percentages (1 and 1.5 wt%), which were predetermined in a pilot study as the best rates for improving tear strength with minimum increase in hardness values. A total of 120 specimens were prepared and divided into the control and experimental groups (with 1 and 1.5 wt% Y2O3 addition). Each group included 40 specimens, 10 specimens for each paramet

This paper experimentally investigates the heating process of a hot water supply using a neural network implementation of a self-tuning PID controller on a microcontroller system. The Particle Swarm Optimization (PSO) algorithm employed in system tuning proved very effective, as it is simple and fast optimization algorithm. The PSO method for the PID parameters is executed on the Matlab platform in order to put these parameters in the real-time digital PID controller, which was experimented with in a pilot study on a microcontroller platform. Instead of the traditional phase angle power control (PAPC) method, the Cycle by Cycle Power Control (CBCPC) method is implemented because it yields better power factor and eliminates harmonics

Aim: To evaluate the effect of ultrasonic agitation for retrograde biodceramic root repair, MTA and biodentine filling materials on push-out bond strength to dentine walls. Materials and Methods: Ninety extracted human teeth with single straight roots were selected randomly. After disinfection and cleaning, the coronal portions were sectioned to standardize the root canal length at 15mm. following root canal shaping, obturation and apical roots resection, retrograde cavities were prepared. Teeth were categorized depending on the filling material used into three groups, 30 teeth each. Group A filled with bioceramic root repair material, B with MTA and C with Biodentine material. These groups were divided in to three subgroup (n= 10). Subgrou

Objectives: This study aimed to evaluate and compare the effect of plasma treatment versus conventional treatment on the micro shear bond strength (μSBS), surface roughness, and wettability of three different CAD/CAM materials. Materials and methods: Sixty cylindrical specimens (5 mm diameter ×3 mm height) were prepared from three different CAD/CAM materials: Group A: Zirconia, Group B: Lithium disilicate, and Group C: Resin nano-ceramic. Each group was subdivided into two subgroups according to surface treatment used: Subgroup I: Conventional treatment, zirconia was sandblasted with Al2O3, while lithium disilicate and resin nano-ceramic were etched with hydrofluoric acid. Subgroup II: Plasma treatment, the surface of each material was tr

Support vector machines (SVMs) are supervised learning models that analyze data for classification or regression. For classification, SVM is widely used by selecting an optimal hyperplane that separates two classes. SVM has very good accuracy and extremally robust comparing with some other classification methods such as logistics linear regression, random forest, k-nearest neighbor and naïve model. However, working with large datasets can cause many problems such as time-consuming and inefficient results. In this paper, the SVM has been modified by using a stochastic Gradient descent process. The modified method, stochastic gradient descent SVM (SGD-SVM), checked by using two simulation datasets. Since the classification of different ca