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jcoeduw-1444
Cognitive Implications of Usage-Based Approach: رغد فهمي اعجمي
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Tremendous efforts have been exerted to understand first language acquisition to facilitate second language learning. The problem lies in the difficulty of mastering English language and adapting a theory that helps in overcoming the difficulties facing students. This study aims to apply Thomasello's theory of language mastery through usage. It assumes that adults can learn faster than children and can learn the language separately, and far from academic education. Tomasello (2003) studied the stages of language acquisition for children, and developed his theory accordingly. Some studies, such as: (Ghalebi and Sadighi, 2015, Arvidsson, 2019; Munoz, 2019; Verspoor and Hong, 2013) used this theory when examining language acquisition. Thus, the present study implies adopting Tomasello's approach represented by his usage-based theory when examining Iraqi adults’ English language acquisition. The participants, who were (20) in number, were asked to watch series and show what they learn through re-enacting scenes. The Data were collected qualitatively through observations, focus group discussion, peer review, and interviews. Results have shown that:  a remarkable progress in the participants' performance, the participants' responses to using English through increasing their language stock, the ability to use language during the development of their linguistic repertoire increased their self-confidence to participate in conversations they were trying to avoid. As a result, the experiment achieved its objectives by finding that use-based theory is a cognitive linguistic approach that can facilitate the learning tasks.

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Publication Date
Sat Aug 25 2012
Journal Name
Wireless Personal Communications
Multi-Objective Evolutionary Algorithm Based on Decomposition for Energy Efficient Coverage in Wireless Sensor Networks
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Publication Date
Wed Aug 28 2019
Journal Name
Journal Of Engineering
     Influent Flow Rate Effect On Sewage Pump Station Performance Based On Organic And Sediment Loading
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The performance of sewage pumps stations affected by many factors through its work time which produce undesired transportation efficiency. This paper is focus on the use of artificial neural network and multiple linear regression (MLR) models for prediction the major sewage pump station in Baghdad city. The data used in this work were obtained from Al-Habibia sewage pump station during specified records- three years in Al-Karkh district, Baghdad. Pumping capability of the stations was recognized by considering the influent input importance of discharge, total suspended solids (TSS) and biological oxygen demand (BOD).  In addition, the chemical oxygen demands (COD), pH and chloride (Cl). The proposed model performanc

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Publication Date
Thu Dec 01 2022
Journal Name
Ieee Transactions On Human-machine Systems
Myoelectric Control With Fixed Convolution-Based Time-Domain Feature Extraction: Exploring the Spatio–Temporal Interaction
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Publication Date
Sat Dec 30 2023
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Enhancing Nitrate Ion Removal from Water using Fixed Bed Columns with Composite Chitosan-based Beads
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    Water contamination is a pressing global concern, especially regarding the presence of nitrate ions. This research focuses on addressing this issue by developing an effective adsorbent for removing nitrate ions from aqueous solutions. two adsorbents Chitosan-Zeolite-Zirconium (Cs-Ze-Zr composite beads and Chitosan-Bentonite-Zirconium Cs-Bn-Zr composite beads were prepared. The study involved continuous experimentation using a fixed bed column with varying bed heights (1.5 and 3 cm) and inlet flow rates (1 and 3 ml/min). The results showed that the breakthrough time increased with higher bed heights for both Cs-Ze-Zr and Cs-Bn-Zr composite beads. Conversely, an increase in flow rate led to a decrease in breakthrough time. Notab

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Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
Early Diagnose Alzheimer's Disease by Convolution Neural Network-based Histogram Features Extracting and Canny Edge
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Alzheimer's disease (AD) increasingly affects the elderly and is a major killer of those 65 and over. Different deep-learning methods are used for automatic diagnosis, yet they have some limitations. Deep Learning is one of the modern methods that were used to detect and classify a medical image because of the ability of deep Learning to extract the features of images automatically. However, there are still limitations to using deep learning to accurately classify medical images because extracting the fine edges of medical images is sometimes considered difficult, and some distortion in the images. Therefore, this research aims to develop A Computer-Aided Brain Diagnosis (CABD) system that can tell if a brain scan exhibits indications of

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Publication Date
Fri Dec 01 2017
Journal Name
2017 11th Asian Control Conference (ascc)
Super-twisting based integral sliding mode control applied to a rotary flexible joint robot manipulator
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In this paper, a single link flexible joint robot is used to evaluate a tracking trajectory control and vibration reduction by a super-twisting integral sliding mode (ST-ISMC). Normally, the system with joint flexibility has inevitably some uncertainties and external disturbances. In conventional sliding mode control, the robustness property is not guaranteed during the reaching phase. This disadvantage is addressed by applying ISMC that eliminates a reaching phase to ensure the robustness from the beginning of a process. To design this controller, the linear quadratic regulator (LQR) controller is first designed as the nominal control to decide a desired performance for both tracking and vibration responses. Subsequently, discontinuous con

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Publication Date
Tue Jun 14 2022
Journal Name
Chemical Papers
Nile red based dye D–π–A as a promising material for solar cell applications
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A recently reported Nile red (NR) dye conjugated with benzothiadiazole species paves the way for the development of novel organic-based sensitizers used in solar cells whose structures are susceptible to modifications. Thus, six novel NR structures were derived from two previously developed structures in laboratories. In this study, density functional theory (DFT) calculations and time-dependent DFT (TD-DFT) were used to determine the optoelectronic properties of the NR-derived moieties such as absorption spectra. Various linkers were investigated in an attempt to understand the impact of π-linkers on the optoelectronic properties. According to the findings, the presence of furan species led to the planarity of the molecule and a reduction

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Publication Date
Thu Dec 28 2023
Journal Name
Farmacia
LASMIDITAN NANOEMULSION BASED IN SITU GEL INTRANASAL DOSAGE FORM: FORMULATION, CHARACTERIZATION AND IN VIVO STUDY
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Publication Date
Thu Oct 21 2021
Journal Name
Physical Review E
Lattice Boltzmann method with moment-based boundary conditions for rarefied flow in the slip regime
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Publication Date
Mon Dec 08 2025
Journal Name
Pigment & Resin Technology
Sustainable automotive interior trim components based on SBR-expanded polystyrene composites reinforced with biomass fibers
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Purpose

The purpose of this paper is to apply styrene butadiene rubber (SBR) as virgin alongside expanded polystyrene (EPS) resin as a recycled polymer after consumption in the presence of bagasse fibers (BF) as biomass source derived from sugarcane in different concentrations to reinforce this polymeric matrix to form affordable composites that can be used in manufacturing low-cost and sustainable car interior-trim constituents.

Design/methodology/approach

SBR and EPS represent an example for thermoplastic elastomers (

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