Artificial Neural networks (ANN) are powerful and effective tools in time-series applications. The first aim of this paper is to diagnose better and more efficient ANN models (Back Propagation, Radial Basis Function Neural networks (RBF), and Recurrent neural networks) in solving the linear and nonlinear time-series behavior. The second aim is dealing with finding accurate estimators as the convergence sometimes is stack in the local minima. It is one of the problems that can bias the test of the robustness of the ANN in time series forecasting. To determine the best or the optimal ANN models, forecast Skill (SS) employed to measure the efficiency of the performance of ANN models. The mean square error and

As they are the smallest functional parts of the muscle, motor units (MUs) are considered as the basic building blocks of the neuromuscular system. Monitoring MU recruitment, de-recruitment, and firing rate (by either invasive or surface techniques) leads to the understanding of motor control strategies and of their pathological alterations. EMG signal decomposition is the process of identification and classification of individual motor unit action potentials (MUAPs) in the interference pattern detected with either intramuscular or surface electrodes. Signal processing techniques were used in EMG signal decomposition to understand fundamental and physiological issues. Many techniques have been developed to decompose intramuscularly detec

Android OS is developing very fast, and because of being an open source OS, it is vulnerable to many problems that are manifested to users directly or indirectly. Poor application launch time is one of these problems. In this paper, a set of sixteen experiments is established to distinguish the factors that have the most evident effects on application launch time in Android mobiles. These factors are application, launch and kill, events, and storage. Mann Kendall (MK) test, one way analysis of variance (ANOVA), and Design of Experiment (DOE) are used to prove the influence of factors statistically. As a result of the experiments, the application factor, especially the third party applications level, has the most prominent effects on appl

There are many methods of forecasting, and these methods take data only, analyze it, make a prediction by analyzing, neglect the prior information side and do not considering the fluctuations that occur overtime. The best way to forecast oil prices that takes the fluctuations that occur overtime and is updated by entering prior information is the Bayesian structural time series (BSTS) method. Oil prices fluctuations have an important role in economic so predictions of future oil prices that are crucial for many countries whose economies depend mainly on oil, such as Iraq. Oil prices directly affect the health of the economy. Thus, it is necessary to forecast future oil price with models adapted for emerging events. In this article, we st

The problem of the current paper is embodied in the weakness of the female students
of the department of the Quran sciences in the college of Education for Women in the
University of Baghdad in the subject of reciting and memorizing the Holy Quran. This is what
the professors and the scientific and educational supervisors stress equally through their visits
to the students applicants during the period of their practical application of teaching in the
schools; especially that the subject is thought for four years during their study in the college.
That weakness is so explicit with a quite large number of the students-applicants, who are
supposed to be the future teachers in the subject of the Holy Quran and Islamic Ed

 The financial markets are one of the sectors whose data is characterized by continuous movement in most of the times and it is constantly changing, so it is difficult to predict its trends , and this leads to the need of methods , means and techniques for making decisions, and that pushes investors and analysts in the financial markets to use various and different methods in order to reach at predicting the movement of the direction of the financial markets. In order to reach the goal of making decisions in different investments, where the algorithm of the support vector machine and the CART regression tree algorithm are used to classify the stock data in order to determine

The Synthesis of yttrium oxide nanoparticles have been achieved via calcination
of yttrium hydroxide produced from the reaction of aqueous solutions of yttrium
nitrate and sodium hydroxide at pH = 13 using hydrothermal and hydrothermal
microwave methods. Effect of heat treatment of the resulted yttrium hydroxide
powder on the morphology and crystallinity of the resulting oxide was studied at
calcination 500, 700 and 1000°C to obtain. The resulted products were
characterized by means of X-ray diffraction (XRD), scanning electron microscope
(SEM), atomic force microscope (AFM), Fourier transform infrared spectrometer
(FTIR) and thermal analyses (TG).

The unemployment is considered from the most danger problems that our society face them in current time & in the near future , because it makes prodigality for element of human being , particularly age of youth who have ability to work & producing , that resulted in negative effects forecast to dire consequences social and economical dangers . In the same time as will be stated in our explanation in the following in our research , because the unemployment has ability to help to prepare good environment to grow crime , actions of violence that mostly are main cause to decrease living level of majority of citizens & in increasing numbers who became under poverty , the unemployment is economical problem as it is psycholo