Preferred Language
Articles
/
jcoeduw-1444
Cognitive Implications of Usage-Based Approach: رغد فهمي اعجمي
...Show More Authors

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.

Crossref
View Publication Preview PDF
Quick Preview PDF
Publication Date
Fri Dec 31 2021
Journal Name
International Journal Of Intelligent Engineering And Systems
Airborne Computer System Based Collision-Free Flight Path Finding Strategy Design for Drone Model
...Show More Authors

View Publication
Scopus (9)
Crossref (1)
Scopus Crossref
Publication Date
Mon Jan 04 2021
Journal Name
Multimedia Tools And Applications
Attention enhancement system for college students with brain biofeedback signals based on virtual reality
...Show More Authors

View Publication
Scopus (5)
Crossref (6)
Scopus Clarivate Crossref
Publication Date
Tue Jan 31 2023
Journal Name
International Journal Of Nonlinear Analysis And Applications
Survey on intrusion detection system based on analysis concept drift: Status and future directions
...Show More Authors

Nowadays, internet security is a critical concern; the One of the most difficult study issues in network security is "intrusion detection". Fight against external threats. Intrusion detection is a novel method of securing computers and data networks that are already in use. To boost the efficacy of intrusion detection systems, machine learning and deep learning are widely deployed. While work on intrusion detection systems is already underway, based on data mining and machine learning is effective, it requires to detect intrusions by training static batch classifiers regardless considering the time-varying features of a regular data stream. Real-world problems, on the other hand, rarely fit into models that have such constraints. Furthermor

... Show More
View Publication
Publication Date
Sat Jan 01 2022
Journal Name
Ssrn Electronic Journal
Highly Sensitive Fiber Brag Grating Based Gas Sensor Integrating Polyaniline Nanofiber for Remote Monitoring
...Show More Authors

View Publication
Crossref
Publication Date
Fri Sep 30 2022
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Risk-Based Inspection Due to Corrosion Consequences for Oil and Gas Flowline: A Review
...Show More Authors

   The petroleum industry, which is one of the pillars of the national economy, has the potential to generate vast wealth and employment possibilities. The transportation of petroleum products is complicated and changeable because of the hazards caused by the corrosion consequences. Hazardous chemical leaks caused by natural disasters may harm the environment, resulting in significant economic losses. It significantly threatens the aim for sustainable development. When a result, determining the likelihood of leakage and the potential for environmental harm, it becomes a top priority for decision-makers as they develop maintenance plans. This study aims to provide an in-depth understanding of the risks associated with oil and gas pipeli

... Show More
View Publication Preview PDF
Crossref (3)
Crossref
Publication Date
Mon Oct 02 2023
Journal Name
Journal Of Engineering
Microgrid Integration Based on Deep Learning NARMA-L2 Controller for Maximum Power Point Tracking
...Show More Authors

This paper presents a hybrid energy resources (HER) system consisting of solar PV, storage, and utility grid. It is a challenge in real time to extract maximum power point (MPP) from the PV solar under variations of the irradiance strength.  This work addresses challenges in identifying global MPP, dynamic algorithm behavior, tracking speed, adaptability to changing conditions, and accuracy. Shallow Neural Networks using the deep learning NARMA-L2 controller have been proposed. It is modeled to predict the reference voltage under different irradiance. The dynamic PV solar and nonlinearity have been trained to track the maximum power drawn from the PV solar systems in real time.

Moreover, the proposed controller i

... Show More
View Publication Preview PDF
Crossref
Publication Date
Tue Jan 14 2025
Journal Name
South Eastern European Journal Of Public Health
Deep learning-based threat Intelligence system for IoT Network in Compliance With IEEE Standard
...Show More Authors

The continuous advancement in the use of the IoT has greatly transformed industries, though at the same time it has made the IoT network vulnerable to highly advanced cybercrimes. There are several limitations with traditional security measures for IoT; the protection of distributed and adaptive IoT systems requires new approaches. This research presents novel threat intelligence for IoT networks based on deep learning, which maintains compliance with IEEE standards. Interweaving artificial intelligence with standardization frameworks is the goal of the study and, thus, improves the identification, protection, and reduction of cyber threats impacting IoT environments. The study is systematic and begins by examining IoT-specific thre

... Show More
View Publication
Crossref
Publication Date
Tue Jan 10 2017
Journal Name
International Journal Of Dynamics And Control
On local approximation-based adaptive control with applications to robotic manipulators and biped robots
...Show More Authors

View Publication
Scopus (10)
Crossref (7)
Scopus Crossref
Publication Date
Fri Sep 27 2024
Journal Name
Journal Of Applied Mathematics And Computational Mechanics
Fruit classification by assessing slice hardness based on RGB imaging. Case study: apple slices
...Show More Authors

Correct grading of apple slices can help ensure quality and improve the marketability of the final product, which can impact the overall development of the apple slice industry post-harvest. The study intends to employ the convolutional neural network (CNN) architectures of ResNet-18 and DenseNet-201 and classical machine learning (ML) classifiers such as Wide Neural Networks (WNN), Naïve Bayes (NB), and two kernels of support vector machines (SVM) to classify apple slices into different hardness classes based on their RGB values. Our research data showed that the DenseNet-201 features classified by the SVM-Cubic kernel had the highest accuracy and lowest standard deviation (SD) among all the methods we tested, at 89.51 %  1.66 %. This

... Show More
View Publication
Scopus (2)
Crossref (1)
Scopus Clarivate Crossref
Publication Date
Sat Jul 01 2023
Journal Name
Journal Of Engineering
Silica Fume Modified Cement-Based Mortar Exposed to High Temperatures: Residual Strengths and Microstructure
...Show More Authors

Several previous investigations and studies utilized silica fume (SF) or (micro silica) particles as supplementary cementitious material added as a substitute to cement-based mortars and their effect on the overall properties, especially on physical properties, strength properties, and mechanical properties. This study investigated the impact of the inclusion of silica fume (SF) particles on the residual compressive strengths and microstructure properties of cement-based mortars exposed to severe conditions of elevated temperatures. The prepared specimens were tested and subjected to 25, 250, 450, 600, and 900 °C. Their residual compressive strengths and microstructure were evaluated and compared with control samples (C

... Show More
View Publication Preview PDF
Crossref (3)
Crossref