In this research, the nonparametric technique has been presented to estimate the time-varying coefficients functions for the longitudinal balanced data that characterized by observations obtained through (n) from the independent subjects, each one of them is measured repeatedly by group of  specific time points (m). Although the measurements are independent among the different subjects; they are mostly connected within each subject and the applied techniques is the Local Linear kernel LLPK technique. To avoid the problems of dimensionality, and thick computation, the two-steps method has been used to estimate the coefficients functions by using the two former technique. Since, the two-

This paper presents a cognition path planning with control algorithm design for a nonholonomic wheeled mobile robot based on Particle Swarm Optimization (PSO) algorithm. The aim of this work is to propose the circular roadmap (CRM) method to plan and generate optimal path with free navigation as well as to propose a nonlinear MIMO-PID-MENN controller in order to track the wheeled mobile robot on the reference path. The PSO is used to find an online tune the control parameters of the proposed controller to get the best torques actions for the wheeled mobile robot. The numerical simulation results based on the Matlab package show that the proposed structure has a precise and highly accurate distance of the generated refere

Maximum power point tracking (MPPT) is used in photovoltaic (PV) systems to enhance efficiency and maximize the output power of PV module, regardless the variation of temperature, irradiation, and the electrical characteristics of the load. A new MPPT system has been presented in this research, consisting of a synchronous DC-DC step-down Buck converter controlled by an Arduino microcontroller based unit. The MPPT process with Perturb and Observe method is performed with a DC-DC converter circuit to overcome the problem of voltage mismatch between the PV modules and the loads. The proposing system has high efficiency, lower cost and can be easily modified to handle more energy sources. The test results indicate that the u

New Schiff-base ligands bearing tetrazole moiety and their polymeric metal complexes with Co(II), Ni(II) and Cd(II) ions are reported. Ligands were prepared in a multiple-step reaction. The reaction of sodium 2,6- diformylphenolate and cyclohexane-1,3-dione with 5-amino-2-fluorobenzonitrile resulted in the isolation of two precursors sodium 2,6-bis((E)-(3-cyano-4-fluorophenylimino)methyl)-4-methylphenolate 1 and 5,5'- (1E,1'E)-cyclohexane-1,3-diylidenebis- (azan-1-yl-1-ylidene)bis(2-fluorobenzonitrile) 2, respectively. The reaction of precursors with azide gave the required ligands; sodium 2,6-bis((E)-(4-fluoro-3-(1H-tetrazol-5- yl)phenylimino)methyl)-4-methylphenolate (NaL) and (N,N'E,N,N'E)-N,N'-(cyclohexane-1,3-diylidene)bis(4- fluoro-3-

The problem of slow learning in primary schools’ pupils is not a local or private one. It is also not related to a certain society other than others or has any relation to a particular culture, it is rather an international problem of global nature. It is one of the well-recognized issues in education field. Additionally, it is regarded as one of the old difficulties to which ancient people gave attention. It is discovered through the process of observing human behaviour and attempting to explain and predict it.
Through the work of the two researchers via frequent visits to primary schools that include special classes for slow learning pupils, in addition to the fact that one of the researcher has a child with slow learning issue, t

A three-stage learning algorithm for deep multilayer perceptron (DMLP) with effective weight initialisation based on sparse auto-encoder is proposed in this paper, which aims to overcome difficulties in training deep neural networks with limited training data in high-dimensional feature space. At the first stage, unsupervised learning is adopted using sparse auto-encoder to obtain the initial weights of the feature extraction layers of the DMLP. At the second stage, error back-propagation is used to train the DMLP by fixing the weights obtained at the first stage for its feature extraction layers. At the third stage, all the weights of the DMLP obtained at the second stage are refined by error back-propagation. Network structures an

New Schiff-base ligands bearing tetrazole moiety and their polymeric metal complexes with Co(II), Ni(II) and Cd(II) ions are reported. Ligands were prepared in a multiple-step reaction. The reaction of sodium 2,6- diformylphenolate and cyclohexane-1,3-dione with 5-amino-2-fluorobenzonitrile resulted in the isolation of two precursors sodium 2,6-bis((E)-(3-cyano-4-fluorophenylimino)methyl)-4-methylphenolate 1 and 5,5'- (1E,1'E)-cyclohexane-1,3-diylidenebis- (azan-1-yl-1-ylidene)bis(2-fluorobenzonitrile) 2, respectively. The reaction of precursors with azide gave the required ligands; sodium 2,6-bis((E)-(4-fluoro-3-(1H-tetrazol-5- yl)phenylimino)methyl)-4-methylphenolate (NaL) and (N, N'E, N, N'E)-N, N'-(cyclohexane-1,3-diylidene)bis(4- fluor