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Genre-Based Analysis of Selected Political Debates: A Discourse Analysis Study
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The researchers of the present study have conducted a genre analysis of two political debates between American presidential nominees in the 2016 and 2020 elections. The current study seeks to analyze the cognitive construction of political debates to evaluate the typical moves and strategies politicians use to express their communicative intentions and to reveal the language manifestations of those moves and strategies. To achieve the study’s aims, the researchers adopt Bhatia’s (1993) framework of cognitive construction supported by van Emeren’s (2010) pragma-dialectic framework. The study demonstrates that both presidents adhere to this genre structuring to further their political agendas. For a positive and promising image, presidents focus on highlighting domestic and international issues to reflect leadership. On the other hand, highlighting controversies and defense strategies appear to be prominent in debate in consensus with the contemplative nature of this genre. Discoursal devices like polarized lexicalization and actor description are vital in orienting the controversies and influence with the aid of in-group pronouns, representative speech acts, and national/self-glorification.

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Publication Date
Thu Nov 17 2022
Journal Name
Journal Of Information And Optimization Sciences
Hybrid deep learning model for Arabic text classification based on mutual information
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Publication Date
Mon Nov 21 2022
Journal Name
Sensors
Deep Learning-Based Computer-Aided Diagnosis (CAD): Applications for Medical Image Datasets
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Computer-aided diagnosis (CAD) has proved to be an effective and accurate method for diagnostic prediction over the years. This article focuses on the development of an automated CAD system with the intent to perform diagnosis as accurately as possible. Deep learning methods have been able to produce impressive results on medical image datasets. This study employs deep learning methods in conjunction with meta-heuristic algorithms and supervised machine-learning algorithms to perform an accurate diagnosis. Pre-trained convolutional neural networks (CNNs) or auto-encoder are used for feature extraction, whereas feature selection is performed using an ant colony optimization (ACO) algorithm. Ant colony optimization helps to search for the bes

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Publication Date
Fri Jan 01 2021
Journal Name
Ieee Access
IFFT-Based Microwave Non-Destructive Testing for Delamination Detection and Thickness Estimation
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Publication Date
Sun Oct 01 2023
Journal Name
Ieee Transactions On Industrial Electronics
Singular Perturbation-Based Adaptive Integral Sliding Mode Control for Flexible Joint Robots
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The flexible joint robot (FJR) typically experiences parametric variations, nonlinearities, underactuation, noise propagation, and external disturbances which seriously degrade the FJR tracking. This article proposes an adaptive integral sliding mode controller (AISMC) based on a singular perturbation method and two state observers for the FJR to achieve high performance. First, the underactuated FJR is modeled into two simple second-order fast and slow subsystems by using Olfati transformation and singular perturbation method, which handles underactuation while reducing noise amplification. Then, the AISMC is proposed to effectively accomplish the desired tracking performance, in which the integral sliding surface is designed to reduce cha

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Publication Date
Thu Aug 31 2023
Journal Name
Journal Européen Des Systèmes Automatisés​
An IoT and Machine Learning-Based Predictive Maintenance System for Electrical Motors
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The rise of Industry 4.0 and smart manufacturing has highlighted the importance of utilizing intelligent manufacturing techniques, tools, and methods, including predictive maintenance. This feature allows for the early identification of potential issues with machinery, preventing them from reaching critical stages. This paper proposes an intelligent predictive maintenance system for industrial equipment monitoring. The system integrates Industrial IoT, MQTT messaging and machine learning algorithms. Vibration, current and temperature sensors collect real-time data from electrical motors which is analyzed using five ML models to detect anomalies and predict failures, enabling proactive maintenance. The MQTT protocol is used for efficient com

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Publication Date
Fri Jan 01 2021
Journal Name
Ieee Access
Fast Shot Boundary Detection Based on Separable Moments and Support Vector Machine
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Publication Date
Fri Dec 01 2023
Journal Name
Al-khwarizmi Engineering Journal
PDF Comparison based on Various FSO Channel Models under Different Atmospheric Turbulence
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Recently, wireless communication environments with high speeds and low complexity have become increasingly essential. Free-space optics (FSO) has emerged as a promising solution for providing direct connections between devices in such high-spectrum wireless setups. However, FSO communications are susceptible to weather-induced signal fluctuations, leading to fading and signal weakness at the receiver. To mitigate the effects of these challenges, several mathematical models have been proposed to describe the transition from weak to strong atmospheric turbulence, including Rayleigh, lognormal, Málaga, Nakagami-m, K-distribution, Weibull, Negative-Exponential, Inverse-Gaussian, G-G, and Fisher-Snedecor F distributions. This paper extensive

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Publication Date
Sat Jan 01 2022
Journal Name
Computers, Materials & Continua
An Optimal Method for Supply Chain Logistics Management Based on Neural Network
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Publication Date
Thu Oct 17 2024
Journal Name
مجلة ميسان لعلوم التربية البدنية
A historical study of the origins of the sport of polo and its development from the royal court to the stadiums of modern times
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The sport of polo, the game of kings and sultans, is one of the traditional sports that has defied time throughout its long history. It has preserved its historical roots and been able to adapt to contemporary requirements, societal transformations, and temporal and spatial variables. It has moved from an aristocratic sport practiced as a form of entertainment to a professional competitive sport. It attracts many players and millions of viewers, so it is a living model of how sports develop and transform from a local tradition into global sports with organized rules managed by international institutions and with many championships worldwide. Through this, the research objectives were formulated, including exploring sports' origins. Polo in

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Publication Date
Wed Oct 01 2014
Journal Name
Al–bahith Al–a'alami
TV and educating university youth about the challenges of cultural identity in Iraq Field study of a sample of students at University of Baghdad
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The TV plays an active role in building the general culture of the recipients, which calls for emphasizing its contemporary mission in rebuilding the values that support the development and modernization of diverse societies. Such importance is necessary to explore the challenges facing the cultural invasion, The space opening, which had its cultural returns to the societies, produced a space for alternative values and antagonisms in the cultures and traditions of these societies in the midst of a psychological / social conflict behind a clash with the peculiarities of Muslim societies. Cultural Adtha.
From these points of view, and because the universities are an important stage to announce the demands of the advocates of change and

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