This study aims to identify the amount of the effect of the ability to learn the individuals within the organization on the accumulation of intellectual capital and the role it plays in improving the performance of the organization, and to achieve that, the researcher designed a questionnaire to collect data and information from the surveyed respondents and analyzed using SPSS software, the study concluded after testing hypotheses to have a direct impact between the capacity for organizational learning and the accumulation of intellectual capital, which in turn affects the accumulation of intellectual capital as a positive and direct impact on the performance of the organization, al

     In this article, the lattice Boltzmann method with two relaxation time  (TRT)  for the  D2Q9 model is used to investigate numerical results for 2D flow. The problem is performed to show the dissipation of the kinetic energy rate and its relationship with the enstrophy growth for 2D dipole wall collision. The investigation is carried out for normal collision and oblique incidents at an angle of . We prove the accuracy of moment -based boundary conditions with slip and Navier-Maxwell slip conditions to simulate this flow. These conditions are under the effect of Burnett-order stress conditions that are consistent with the discrete Boltzmann equation. Stable results are found by using this kind of boundary condition where d

Dust is a frequent contributor to health risks and changes in the climate, one of the most dangerous issues facing people today. Desertification, drought, agricultural practices, and sand and dust storms from neighboring regions bring on this issue. Deep learning (DL) long short-term memory (LSTM) based regression was a proposed solution to increase the forecasting accuracy of dust and monitoring. The proposed system has two parts to detect and monitor the dust; at the first step, the LSTM and dense layers are used to build a system using to detect the dust, while at the second step, the proposed Wireless Sensor Networks (WSN) and Internet of Things (IoT) model is used as a forecasting and monitoring model. The experiment DL system

Emotion recognition has important applications in human-computer interaction. Various sources such as facial expressions and speech have been considered for interpreting human emotions. The aim of this paper is to develop an emotion recognition system from facial expressions and speech using a hybrid of machine-learning algorithms in order to enhance the overall performance of human computer communication. For facial emotion recognition, a deep convolutional neural network is used for feature extraction and classification, whereas for speech emotion recognition, the zero-crossing rate, mean, standard deviation and mel frequency cepstral coefficient features are extracted. The extracted features are then fed to a random forest classifier. In

The purpose of the study is to identify the teaching techniques that mathematics' teachers use due to the Brain-based learning theory. The sample is composed of (90) teacher: (50) male, (40) female. The results have shown no significant differences between male and female responses' mean. Additionally, through the observation of author, he found a lack of using Brain-based learning techniques. Thus, the researcher recommend that it is necessary to involve teachers in remedial courses to enhance their ability to create a classroom that raise up brain-based learning skills.  

The optical energy gap(Eopt) and the width of the tails of localized states in the band gap (?E) for Se:2%Sb thin films prepared by thermal co-evaporation method as a function of annealing temperature are studied in the photon energy range ( 1 to 5.4)eV.Se2%Sb film was found to be indirect transition with energy gap of (1.973,2.077, 2.096, 2.17) eV at annealing temperature (295,370,445,520)K respectively. The Eopt and ?E of Se:2%Sb films as a function of annealing temperature showed an increase in Eopt and a decrease in ?E with increasing the annealing temperature. This behavior may be related to structural defects and dangling bonds.