ABSTRACT

Learning vocabulary is a challenging task for female English as a foreign language (EFL) students. Thus, improving students’ knowledge of vocabulary is critical if they are to make progress in learning a new language. The current study aimed at exploring the vocabulary learning strategies used by EFL students at Northern Border University (NBU). It also aimed to identify the mechanisms applied by EFL students at NBU University to learn vocabulary. It also aimed at evaluating the approaches adopted by EFL female students at Northern Border University (NBU) to learn a language. The study adopted the descriptive-analytical method. Two research instruments were developed to collect data namely, a survey qu

This study aims to identify both the importance of using (LinkedIn) and its drawbacks for researchers and specialists in the field of information and knowledge technologies. The study relied mainly on the statistical method (analytical method) from the collection of data tools (questionnaire) that was distributed electronically (Google Forms) to the sample community of (55) instructors. The feedback received illustrates that (46) instructors among those who participated in the questionnaire subscribed to (LinkedIn) and the rest did not. Their data was analyzed statistically, and the general arithmetic mean and the hypothetical mean was extracted for them to achieve the objectives of the study and prove their hypotheses. The site positively

This study deals with the elimination of methyl orange (MO) from an aqueous solution by utilizing the 3D electroFenton process in a batch reactor with an anode of porous graphite and a cathode of copper foam in the presence of granular activated carbon (GAC) as a third pole, besides, employing response surface methodology (RSM) in combination with Box-Behnk Design (BBD) for studying the effects of operational conditions, such as current density (3–8 mA/cm2), electrolysis time (10–20 min), and the amount of GAC (1–3 g) on the removal efficiency beside to their interaction. The model was veiled since the value of R2 was high (>0.98) and the current density had the greatest influence on the response. The best removal efficiency (MO Re%)

Sensing insole systems are a promising technology for various applications in healthcare and sports. They can provide valuable information about the foot pressure distribution and gait patterns of different individuals. However, designing and implementing such systems poses several challenges, such as sensor selection, calibration, data processing, and interpretation. This paper proposes a sensing insole system that uses force-sensitive resistors (FSRs) to measure the pressure exerted by the foot on different regions of the insole. This system classifies four types of foot deformities: normal, flat, over-pronation, and excessive supination. The classification stage uses the differential values of pressure points as input for a feedforwar

This paper presents a modified training method for Recurrent Neural Networks. This method depends on the Non linear Auto Regressive (NARX) model with Modified Wavelet Function as activation function (MSLOG) in the hidden layer. The modified model is known as Modified Recurrent Neural (MRN). It is used for identification Forward dynamics of four Degrees of Freedom (4-DOF) Selective Compliance Assembly Robot Arm (SCARA) manipulator robot. This model is also used in the design of Direct Inverse Control (DIC). This method is compared with Recurrent Neural Networks that used Sigmoid activation function (RS) in the hidden layer and Recurrent Neural Networks with Wavelet activation function (RW). Simulation results shows that the MRN model is bett

This paper proposes improving the structure of the neural controller based on the identification model for nonlinear systems. The goal of this work is to employ the structure of the Modified Elman Neural Network (MENN) model into the NARMA-L2 structure instead of Multi-Layer Perceptron (MLP) model in order to construct a new hybrid neural structure that can be used as an identifier model and a nonlinear controller for the SISO linear or nonlinear systems. Two learning algorithms are used to adjust the parameters weight of the hybrid neural structure with its serial-parallel configuration; the first one is supervised learning algorithm based Back Propagation Algorithm (BPA) and the second one is an intelligent algorithm n

An adaptive nonlinear neural controller to reduce the nonlinear flutter in 2-D wing is proposed in the paper. The nonlinearities in the system come from the quasi steady aerodynamic model and torsional spring in pitch direction. Time domain simulations are used to examine the dynamic aero elastic instabilities of the system (e.g. the onset of flutter and limit cycle oscillation, LCO). The structure of the controller consists of two models :the modified Elman neural network (MENN) and the feed forward multi-layer Perceptron (MLP). The MENN model is trained with off-line and on-line stages to guarantee that the outputs of the model accurately represent the plunge and pitch motion of the wing and this neural model acts as the identifier. Th

 

This work implements the face recognition system based on two stages, the first stage is feature extraction stage and the second stage is the classification stage. The feature extraction stage consists of Self-Organizing Maps (SOM) in a hierarchical format in conjunction with Gabor Filters and local image sampling. Different types of SOM’s were used and a comparison between the results from these SOM’s was given.

The next stage is the classification stage, and consists of self-organizing map neural network; the goal of this stage is to find the similar image to the input image. The proposal method algorithm implemented by using C++ packages, this work is successful classifier for a face database consist of 20

The study aimed to determine the effect of the flipped learning model in improving the acquisition of the overhand serve skill in volleyball among second-year students at the College of Physical Education and Sport Sciences, University of Baghdad, for the academic year 2024/2025. The study used an experimental design with a control group and pre-post testing, on a purposive sample consisting of 12 students. The model relied on watching short videos before class via the SGS application, and practical application in class at a rate of three sessions per week. The results showed a significant improvement in performance, as the calculated value (t = 5.356) exceeded the tabulated value (2.042) at a significance level of 0.05. The percentage of s