Interface bonding between asphalt layers has been a topic of international investigation over the last thirty years. In this condition, a number of researchers have made their own techniques and used them to examine the characteristics of pavement interfaces. It is obvious that test findings won't always be comparable to the lack of a globally standard methodology for interface bonding. Also, several kinds of research have shown that factors like temperature, loading conditions, materials, and others have an impact on surface qualities. This study aims to solve this problem by thoroughly investigating interface bond testing that might serve as a basis for a uniform strategy. First, a general explanation of how the bonding strength

This study involves the design of 24 mixtures of fiber reinforced magnetic reactive powder concrete containing nano Silica. Tap water has been used in mixing 12 of these mixtures, while the other 12 have been mixed using magnetic water. Nano Silica (NS) with ratios (1, 1.5, 2, 2.5 and 3) % were used. The results showed that the mixture containing 2.5%NS gives the highest compressive strength at age 7 days. Many different other tests were carried out, the results showed that the fiber reinforced magnetic reactive powder concrete containing 2.5% NS (FRMRPCCNS)  has the higher bulk density, dynamic modulus of elasticity, ultrasonic pulse velocity  electrical resistivity and lesser absorption than fiber reinforced

A non-polynomial spline (NPS) is an approximation method that relies on the triangular and polynomial parts, so the method has infinite derivatives of the triangular part of the NPS to compensate for the loss of smoothness inherited by the polynomial. In this paper, we propose polynomial-free linear and quadratic spline types to solve fuzzy Volterra integral equations (FVIE) of the 2nd kind with the weakly singular kernel (FVIEWSK) and Abel's type kernel. The linear type algorithm gives four parameters to form a linear spline. In comparison, the quadratic type algorithm gives five parameters to create a quadratic spline, which is more of a credit for the exact solution. These algorithms process kernel singularities with a simple techniqu

Interface bonding between asphalt layers has been a topic of international investigation over the last thirty years. In this condition, a number of researchers have made their own techniques and used them to examine the characteristics of pavement interfaces. It is obvious that test findings won't always be comparable to the lack of a globally standard methodology for interface bonding. Also, several kinds of research have shown that factors like temperature, loading conditions, materials, and others have an impact on surface qualities. This study aims to solve this problem by thoroughly investigating interface bond testing that might serve as a basis for a uniform strategy. First, a general explanation of how

In this paper the effect of nonthermal atmospheric argon plasma on the optical properties of the cadmium oxide CdO thin films prepared by chemical spray pyrolysis was studied. The prepared films were exposed to different time intervals (0, 5, 10, 15, 20) min. For every sample, the transmittance, Absorbance, absorption coefficient, energy gap, extinction coefficient and dielectric constant were studied. It is found that the transmittance and the energy gap increased with exposure time, and absorption. Absorption coefficient, extinction coefficient, dielectric constant decreased with time of exposure to the argon plasma

Ziegler and Nichols proposed the well-known Ziegler-Nichols method to tune the coefficients of PID controller. This tuning method is simple and gives fixed values for the coefficients which make PID controller have weak adaptabilities for the model parameters variation and changing in operating conditions. In order to achieve adaptive controller, the Neural Network (NN) self-tuning PID control is proposed in this paper which combines conventional PID controller and Neural Network learning capabilities. The proportional, integral and derivative (K_P, K_I, K_D) gains are self tuned on-line by the NN output which is obtained due to the error value on the desired output of the system under control. The conventio

In this paper, Bayes estimators of Poisson distribution have been derived by using two loss functions: the squared error loss function and the proposed exponential loss function in this study, based on different priors classified as the two different informative prior distributions represented by erlang and inverse levy prior distributions and non-informative prior for the shape parameter of Poisson distribution. The maximum likelihood estimator (MLE) of the Poisson distribution has also been derived. A simulation study has been fulfilled to compare the accuracy of the Bayes estimates with the corresponding maximum likelihood estimate (MLE) of the Poisson distribution based on the root mean squared error (RMSE) for different cases of the

A low-cost reverse flow plasma system powered by argon gas pumping was built using homemade materials in this paper. The length of the resulting arc change was directly proportional to the flow rate, while using the thermal camera to examine the thermal intensity distribution and demonstrating that it is concentrated in the centre, away from the walls at various flow rates, the resulting arc's spectra were also measured. The results show that as the gas flow rate increased, so did the ambient temperature. The results show that the medium containing the arc has a maximum temperature of 34.1 ˚C at a flow rate of 14 L/min and a minimum temperature of 22.6 ˚C at a flow rate of 6 L/min.

The nonlinear optical properties for polymeric (PMMA) doping with dye Rhodmine (R3Go) has been studied .The samples are prepared by normal polymerization method with concentrations of 5x10^-5mol/l and a thickness of 272.5µm.

                         Plasma effect was studied on samples prepared before and after exposure to the Nd: YAG laser for three times 5, 10 and 15 minutes. Z-Scan technique is used to determine the nonlinear optical properties such as; refractive index (n₂) and the coefficient of nonlinear absorption (β). It was found that the nonlinear properties is change by increasi

The evolution in the field of Artificial Intelligent (AI) with its training algorithms make AI very important in different aspect of the life. The prediction problem of behavior of dynamical control system is one of the most important issue that the AI can be employed to solve it. In this paper, a Convolutional Multi-Spike Neural Network (CMSNN) is proposed as smart system to predict the response of nonlinear dynamical systems. The proposed structure mixed the advantages of Convolutional Neural Network (CNN) with Multi -Spike Neural Network (MSNN) to generate the smart structure. The CMSNN has the capability of training weights based on a proposed training algorithm. The simulation results demonstrated that the proposed