In the last few years, the literature conferred a great interest in studying the feasibility of using memristive devices for computing. Memristive devices are important in structure, dynamics, as well as functionalities of artificial neural networks (ANNs) because of their resemblance to biological learning in synapses and neurons regarding switching characteristics of their resistance. Memristive architecture consists of a number of metastable switches (MSSs). Although the literature covered a variety of memristive applications for general purpose computations, the effect of low or high conductance of each MSS was unclear. This paper focuses on finding a potential criterion to calculate the conductance of each MMS rather t

The most significant function in oil exploration is determining the reservoir facies, which are based mostly on the primary features of rocks. Porosity, water saturation, and shale volume as well as sonic log and Bulk density are the types of input data utilized in Interactive Petrophysics software to compute rock facies. These data are used to create 15 clusters and four groups of rock facies. Furthermore, the accurate matching between core and well-log data is established by the neural network technique. In the current study, to evaluate the applicability of the cluster analysis approach, the result of rock facies from 29 wells derived from cluster analysis were utilized to redistribute the petrophysical properties for six units of Mishri

The problem of research was to identify after the use of cost technology based on specifications in the validity of determining and measuring the costs of the implementation of contracting, by applying to al-Mansour General Construction Contracting Company as an appropriate alternative to the traditional costing system currently adopted, which is characterized by many shortcomings and weaknesses Which has been reflected in the validity and integrity of the calculations. To solve this problem, the research was based on the premise that: (The application of cost technology based on specifications will result in calculating the cost of the product according to the specification required by the customer, to meet his wishes properly and witho

Wireless Body Area Sensor Network (WBASN) is gaining significant attention due to its applications in smart health offering cost-effective, efficient, ubiquitous, and unobtrusive telemedicine. WBASNs face challenges including interference, Quality of Service, transmit power, and resource constraints. Recognizing these challenges, this paper presents an energy and Quality of Service-aware routing algorithm. The proposed algorithm is based on each node's Collaboratively Evaluated Value (CEV) to select the most suitable cluster head (CH). The Collaborative Value (CV) is derived from three factors, the node's residual energy, the distance vector between nodes and personal device, and the sensor's density in each CH. The CEV algorithm operates i

The research aims to identify the academic problems of family counseling diploma students at Saudi Universities. In addition, to identify the differences in these problems according to gender, marital status, place of study, academic specialization, and GPA. The sample consisted of (491) students. The researcher has used one questionnaire for academic problems prepared by the researcher.  The research revealed the following results: There were academic problems among family counseling diploma students at Saudi Universities, the most problems were related to the systems and administrations of the university, then the field training, the buildings, classrooms and campus facilities, then the academic courses, after that the exams, then

Symmetric cryptography forms the backbone of secure data communication and storage by relying on the strength and randomness of cryptographic keys. This increases complexity, enhances cryptographic systems' overall robustness, and is immune to various attacks. The present work proposes a hybrid model based on the Latin square matrix (LSM) and subtractive random number generator (SRNG) algorithms for producing random keys. The hybrid model enhances the security of the cipher key against different attacks and increases the degree of diffusion. Different key lengths can also be generated based on the algorithm without compromising security. It comprises two phases. The first phase generates a seed value that depends on producing a rand

The research aims to know the effectiveness of a training program based on multiple intelligence theory in developing literary thinking among students of the Arabic Language Department at Ibn Rushd School of Humanities and to achieve the goal of research, the Safaris Research Institute, and the research community of Arabic language students in the Faculty of Education the third section of Arabic Language: The research sample consists of (71) students. Divided into (35) students in the experimental group and (36) students in the control group, the researcher balanced between the two groups with variables (intelligence, testing of tribal literary thinking, and time age in months), and after using the T-test for two independent samples, the

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

This paper presents a new design of a nonlinear multi-input multi-output PID neural controller of the active brake steering force and the active front steering angle for a 2-DOF vehicle model based on modified Elman recurrent neural. The goal of this work is to achieve the stability and to improve the vehicle dynamic’s performance through achieving the desired yaw rate and reducing the lateral velocity of the vehicle in a minimum time period for preventing the vehicle from slipping out the road curvature by using two active control actions: the front steering angle and the brake steering force. Bacterial forging optimization algorithm is used to adjust the parameters weights of the proposed controller. Simulation resul