Survival analysis is widely applied in data describing for the life time of item until the occurrence of an event of interest such as death or another event of understudy . The purpose of this paper is to use the dynamic approach in the deep learning neural network method, where in this method a dynamic neural network that suits the nature of discrete survival data and time varying effect. This neural network is based on the Levenberg-Marquardt (L-M) algorithm in training, and the method is called Proposed Dynamic Artificial Neural Network (PDANN). Then a comparison was made with another method that depends entirely on the Bayes methodology is called Maximum A Posterior (MAP) method. This method was carried out using numerical algorithms represented by Iteratively Weighted Kalman Filter Smoothing (IWKFS) algorithm and in combination with the Expectation Maximization (EM) algorithm. Average Mean Square Error (AMSE) and Cross Entropy Error (CEE) were used as comparison’s criteria. The methods and procedures were applied to data generated by simulation using a different combination of sample sizes and the number of intervals.
In this paper, a new technique is offered for solving three types of linear integral equations of the 2nd kind including Volterra-Fredholm integral equations (LVFIE) (as a general case), Volterra integral equations (LVIE) and Fredholm integral equations (LFIE) (as special cases). The new technique depends on approximating the solution to a polynomial of degree and therefore reducing the problem to a linear programming problem(LPP), which will be solved to find the approximate solution of LVFIE. Moreover, quadrature methods including trapezoidal rule (TR), Simpson 1/3 rule (SR), Boole rule (BR), and Romberg integration formula (RI) are used to approximate the integrals that exist in LVFIE. Also, a comparison between those methods i
... Show MoreMost of drinking water consuming all over the world has been treated at the water treatment plant (WTP) where raw water is abstracted from reservoirs and rivers. The turbidity removal efficiency is very important to supply safe drinking water. This study is focusing on the use of multiple linear regression (MLR) and artificial neural network (ANN) models to predict the turbidity removal efficiency of Al-Wahda WTP in Baghdad city. The measured physico-chemical parameters were used to determine their effect on turbidity removal efficiency in various processes. The suitable formulation of the ANN model is examined throughout many preparations, trials, and steps of evaluation. The predict
The root-mean square-radius of proton, neutron, matter and charge radii, energy level, inelastic longitudinal form factors, reduced transition probability from the ground state to first-excited 2+ state of even-even isotopes, quadrupole moments, quadrupole deformation parameter, and the occupation numbers for some calcium isotopes for A=42,44,46,48,50 are computed using fp-model space and FPBM interaction. 40Ca nucleus is regarded as the inert core for all isotopes under this model space with valence nucleons are moving throughout the fp-shell model space involving 1f7/2, 2p3/2, 1f5/2, and 2p1/2 orbits. Model space is used to present calculations using FPBM intera
... Show MoreThe effect of electrolysis operating parameters on the removal efficiency of cadmium from a simulated wastewater was studied by adopting response surface methodology combined with Box–Behnken Design. As a new electrode design, spiral-wound woven wire mesh rotating cylinder electrode was used for cadmium removal. Current (240–400 mA), rotation speed (200–1000 rpm), initial cadmium concentration (200–600ppm), and cathode mesh number (30–60) were chosen as independent variables while the removal efficiency of cadmium was considered as a response function. The results revealed that the rotation speed has the major effect on the removal efficiency of cadmium. Regression analysis showed good fit of the experimental data to the second-or
... Show MoreThe current study aimed to standardize the multi-position suicidal tendency scale MAST in the Saudi environment as well as to assess suicidal tendencies in adolescents. Moreover, the study aimed to test the psychometric characteristics of the scale among a sample of (490) high school and undergraduate students, in the adolescence who ranging in age from (16-21) years. The scale demonstrated satisfactory internal consistency in terms of validity and reliability tests. as the results showed of exploratory factor analysis to the four dimensions of suicidal tendencies loading on two factors that accommodate 74.60% of the overall variance of the scale (1) the attitude toward life, and absorbs 43, 20% of the total variance of the scale,
... Show MoreThe present study aimed to investigate the acetamiprid effects on biochemical aspects in albino mice. Thirty albino mice at the age of 6-8 weeks and average weight 25±5 g were divided into three groups each having ten (10) healthy mice. The first group was orally administrated with distilled water while the second and third groups were orally administrated with 50 mg/mL and 100 mg/mL respectively of acetamprid (0.1 mL) daily for one week. LD50 of acetamiprid was measured and found to be 200 mg/kg. The parameters of evaluations included liver function using Aspartate Aminotransferase (AST), Alanine Aminotransferase (ALT) and Alkaline Phosphatase (ALP). Lipid profile was anal
... Show MoreHeat transfer around a flat plate fin integrated with piezoelectric actuator used as oscillated fin in laminar flow has been studied experimentally utilizing thermal image camera. This study is performed
for fixed and oscillated single and triple fins. Different substrate-fin models have been tested, using fins of (35mm and 50mm) height, two sets of triple fins of (3mm and 6mm) spacing and three frequencies
applied to piezoelectric actuator (5, 30 and 50HZ). All tests are carried out for (0.5 m/s and 3m/s) in subsonic open type wind tunnel to evaluate temperature distribution, local and average Nusselt number (Nu) along the fin. It is observed, that the heat transfer enhancement with oscillation is significant compared to without o
The need to create the optimal water quality management process has motivated researchers to pursue prediction modeling development. One of the widely important forecasting models is the sessional autoregressive integrated moving average (SARIMA) model. In the present study, a SARIMA model was developed in R software to fit a time series data of monthly fluoride content collected from six stations on Tigris River for the period from 2004 to 2014. The adequate SARIMA model that has the least Akaike's information criterion (AIC) and mean squared error (MSE) was found to be SARIMA (2,0,0) (0,1,1). The model parameters were identified and diagnosed to derive the forecasting equations at each selected location. The correlation coefficien
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