The aim of the research is to find out the availability of the requirements of applying the indicators of school performance system in the public schools in  Mahayel Asir educational directorate through the school planning indicator, the safety and security indicator, the active learning indicator, the student guidance indicator and determining the existence of statistically significant differences between the responses of the research community according to the variable of (scientific qualification - years of work as a principal - training courses). The questionnaire was used as a tool for data collection from the research community, which consists of all the public schools’ principals (n=180) Mahayel Asir educational directorate

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

In this paper, the system of the power plant has been investigated as a special type of industrial systems, which has a significant role in improving societies since the electrical energy has entered all kinds of industries, and it is considered as the artery of modern life.

   The aim of this research is to construct a programming system, which could be used to identify the most important failure modes that are occur in a steam type of power plants. Also the effects and reasons of each failure mode could be analyzed through the usage of this programming system reaching to the basic events (main reasons) that causing each failure mode. The construction of this system for FMEA is dependi

In this paper we generalize Jacobsons results by proving that any integer  in   is a square-free integer), belong to . All units of  are generated by the fundamental unit  having the forms

Our generalization build on using the conditions

This leads us to classify the real quadratic fields  into the sets  Jacobsons results shows that  and Sliwa confirm that  and  are the only real quadratic fields in .

This paper proposes an on-line adaptive digital Proportional Integral Derivative (PID) control algorithm based on Field Programmable Gate Array (FPGA) for Proton Exchange Membrane Fuel Cell (PEMFC) Model. This research aims to design and implement Neural Network like a digital PID using FPGA in order to generate the best value of the hydrogen partial pressure action (PH₂) to control the stack terminal output voltage of the (PEMFC) model during a variable load current applied. The on-line Particle Swarm Optimization (PSO) algorithm is used for finding and tuning the optimal value of the digital PID-NN controller (kp, ki, and kd) parameters that improve the dynamic behavior of the closed-loop digital control fue

In this paper the effect of thermal annealing on the structural and optical properties of Antimony Selenide (Sb2Se3) is investigated. Sb2Se3 powder is evaporated on clean amorphous glass substrates at room temperature under high vacuum pressure (4.5×10-6 mbar) to form thin films. The structural investigation was done with the aid of X-ray diffraction (XRD) and atomic force microscopy (AFM). The amorphous to polycrystalline transformation of these thin films was shown by X-ray diffraction analysis after thermal annealing. These films' morphology is explained. (UV-Vis ) spectra in ranges from 300 to 1100 nm was used to examine the optical properties of the films .The absorption coefficient and optical energy gap of the investigated films are

The unconventional techniques called “the quick look techniques”, have been developed to present well log data calculations, so that they may be scanned easily to identify the zones that warrant a more detailed analysis, these techniques have been generated by service companies at the well site which are among the useful, they provide the elements of information needed for making decisions quickly when time is of essence^. The techniques used in this paper are:

• Apparent resistivity R_wa
• R_xo /R_t

   The above two methods had been used to evaluate Nasiriyah oil field formations (well-NS-3) to discover the hydrocarbon bearing formations. A compu

الخلاصة لقد شكل المحافظون الجدد وهم بالأساس نخبة من المثقفين ومن السياسيين الأمريكيين كتلة ضغط كبيرة التأثير على الإدارة في عهد الجمهوريين. حمل هؤلاء المحافظون مشروعاً إيديولوجياً البسوه لسلطة الجمهوريين وهو يهدف إلى جعل أمريكا سيدة العالم من دون منازع خاصة بعد انهيار الاتحاد السوفييتي ونهاية الحرب الباردة. واكب هذا الحدث التاريخي الكثير من الأفكار ومنها (نهاية التاريخ)، وصراع الحضارات، وكذ