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Using Scenarios to Assess Student Learning
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Publication Date
Wed Apr 06 2022
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
The Role Talents Management in Consolidating Organizational Learning Process: An Applied Study at the Yemeni General Telecommunications Corporation
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This study aimed at accounting for the role of talents management in consolidating organizational learning process at the Yemeni General Corporation For telecommunication. To achieve the objective of the study, the researcher designed a questionnaire and administered it. The sample of the study consisted of (166) employees (General Manager, Manager and Department Head). They were selected randomly out of a total Population of (291) employees during the Year 2019. The descriptive analytic approach was used t reach conclusions.

The finding of the study revealed existence of effect of talents management dimensions, all together and alone, (talents polarization, talents development, talents maintenance and ma

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Publication Date
Sun Dec 01 2013
Journal Name
Journal
The Effects Of Pbl On Understanding Of Thermodynamics, Group Work And Self-Directed Learning Skills Among Physics Undergraduates
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The aim of this study is to compare the effects of three methods: problem-based learning (PBL), PBL with lecture method, and conventional teaching on the understanding of thermodynamics, group work and self-directed learning skills among physics undergraduates. The actual sample size comprises of 122 students, who were selected randomly from the Physics Department, College of Education in Iraq, for academic year 2011-2012. In this study, the pre and posttest were done and the instruments were administered to the students for data collection. Inferential statistics were employed to analyze data. The independent variables were the PBL, the PBL with lecture method, and the conventional teaching. Dependent variables of statistical analysis were

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Publication Date
Tue Apr 02 2019
Journal Name
Artificial Intelligence Research
A three-stage learning algorithm for deep multilayer perceptron with effective weight initialisation based on sparse auto-encoder
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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

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Publication Date
Wed Nov 25 2020
Journal Name
Plos One
Impact of the COVID-19 pandemic on medical education: Medical students’ knowledge, attitudes, and practices regarding electronic learning
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The Coronavirus Disease 2019 (COVID-19) pandemic has caused an unprecedented disruption in medical education and healthcare systems worldwide. The disease can cause life-threatening conditions and it presents challenges for medical education, as instructors must deliver lectures safely, while ensuring the integrity and continuity of the medical education process. It is therefore important to assess the usability of online learning methods, and to determine their feasibility and adequacy for medical students. We aimed to provide an overview of the situation experienced by medical students during the COVID-19 pandemic, and to determine the knowledge, attitudes, and practices of medical students regarding electronic medical education.

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Publication Date
Sat Aug 09 2025
Journal Name
Scientific Reports
Machine learning models for predicting morphological traits and optimizing genotype and planting date in roselle (Hibiscus Sabdariffa L.)
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Accurate prediction and optimization of morphological traits in Roselle are essential for enhancing crop productivity and adaptability to diverse environments. In the present study, a machine learning framework was developed using Random Forest and Multi-layer Perceptron algorithms to model and predict key morphological traits, branch number, growth period, boll number, and seed number per plant, based on genotype and planting date. The dataset was generated from a field experiment involving ten Roselle genotypes and five planting dates. Both RF and MLP exhibited robust predictive capabilities; however, RF (R² = 0.84) demonstrated superior performance compared to MLP (R² = 0.80), underscoring its efficacy in capturing the nonlinear genoty

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Publication Date
Fri Aug 13 2021
Journal Name
Neural Computing And Applications
Integration of extreme gradient boosting feature selection approach with machine learning models: application of weather relative humidity prediction
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Publication Date
Wed Oct 01 2025
Journal Name
Journal Of Physical Education
The Effect of Increasing Rehabilitation Program Using Electric Stimulation On Rehabilitating Knee Joint Working Muscles Due to ACL Tear In Athletes
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Publication Date
Mon Sep 28 2020
Journal Name
Journal Of Physical Education
The Effect of Increasing Rehabilitation Program Using Electric Stimulation On Rehabilitating Knee Joint Working Muscles Due to ACL Tear In Athletes
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The research aimed at designing a rehabilitation program using electric stimulation for rehabilitating knee joint working muscles as a result of ACL tear using an apparatus developed by the researchers that stimulate the muscle vibration and work as well as the ability to rehabilitate the join in shorter periods. In addition to that, it aimed at identifying the effect of this program on rehabilitating the knee joint working muscles. The researchers used the experimental method on Baghdad clubs’ players who suffer from complete knee joint ACL tear aged (19 – 24) years old. The results showed that the training program developed the working muscles significantly achieving normal levels of activity.

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Publication Date
Thu May 18 2023
Journal Name
Journal Of Engineering
Design and Implementation of a Generalized N-Digit Binary-To-Decimal Converter on an FPGA Seven-Segment Display Using Verilog Hdl
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It is often needed to have circuits that can display the decimal representation of a binary number and specifically in this paper on a 7-segment display. In this paper a circuit that can display the decimal equivalent of an n-bit binary number is designed and it’s behavior is described using Verilog Hardware Descriptive Language (HDL).
This HDL program is then used to configure an FPGA to implement the designed circuit.

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Publication Date
Sat Sep 28 2024
Journal Name
Journal Of International Dental And Medical Research
Effect of Air–Particle Abrasion of Dentin Surface on Shear Bond Strength of Lithium Disilicate to Dentin Using Three Different Cements
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This study aims to evaluate the influence of the air abrasion of dentin on the shear bond strength of lithium disilicate using three different types of luting cements. Sixty cylindrical specimens were milled from lithium disilicate CAD/CAM blocks (IPSe.max CAD). Sixty sound human maxillary premolar teeth were decoronated to the level of peripheral dentin, then randomly divided into three groups according to the type of luting cement used for the cementation of the lithium disilicate specimens (n = 20); Group A: Glass ionomer cement (Riva Self- Cure); Group B: Adhesive resin cement (Rely X Ultimate); Group C: Self-adhesive resin cement (Rely X U200). Each group was then further subdivided into two subgroups (n=10); Subgroups AI, BI, and CI,

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