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A Critical Review of Remote Sensing Approaches and Deep Learning Techniques in Archaeology
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To date, comprehensive reviews and discussions of the strengths and limitations of Remote Sensing (RS) standalone and combination approaches, and Deep Learning (DL)-based RS datasets in archaeology have been limited. The objective of this paper is, therefore, to review and critically discuss existing studies that have applied these advanced approaches in archaeology, with a specific focus on digital preservation and object detection. RS standalone approaches including range-based and image-based modelling (e.g., laser scanning and SfM photogrammetry) have several disadvantages in terms of spatial resolution, penetrations, textures, colours, and accuracy. These limitations have led some archaeological studies to fuse/integrate multiple RS datasets to overcome limitations and produce comparatively detailed outcomes. However, there are still knowledge gaps in examining the effectiveness of these RS approaches in enhancing the detection of archaeological remains/areas. Thus, this review paper is likely to deliver valuable comprehension for archaeological studies to fill knowledge gaps and further advance exploration of archaeological areas/features using RS along with DL approaches.

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Publication Date
Mon Jan 01 2024
Journal Name
Ieee Access
Transfer Learning and Hybrid Deep Convolutional Neural Networks Models for Autism Spectrum Disorder Classification From EEG Signals
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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
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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

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Publication Date
Fri Jan 01 2021
Journal Name
Artificial Intelligence For Covid-19
An Efficient Mixture of Deep and Machine Learning Models for COVID-19 and Tuberculosis Detection Using X-Ray Images in Resource Limited Settings
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Publication Date
Mon Oct 30 2023
Journal Name
Aro-the Scientific Journal Of Koya University
Enhancing Upper Limb Prosthetic Control in Amputees Using Non-invasive EEG and EMG Signals with Machine Learning Techniques
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Amputation of the upper limb significantly hinders the ability of patients to perform activities of daily living. To address this challenge, this paper introduces a novel approach that combines non-invasive methods, specifically Electroencephalography (EEG) and Electromyography (EMG) signals, with advanced machine learning techniques to recognize upper limb movements. The objective is to improve the control and functionality of prosthetic upper limbs through effective pattern recognition. The proposed methodology involves the fusion of EMG and EEG signals, which are processed using time-frequency domain feature extraction techniques. This enables the classification of seven distinct hand and wrist movements. The experiments conducte

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Publication Date
Fri Dec 01 2023
Journal Name
Applied Energy
Deep clustering of Lagrangian trajectory for multi-task learning to energy saving in intelligent buildings using cooperative multi-agent
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The intelligent buildings provided various incentives to get highly inefficient energy-saving caused by the non-stationary building environments. In the presence of such dynamic excitation with higher levels of nonlinearity and coupling effect of temperature and humidity, the HVAC system transitions from underdamped to overdamped indoor conditions. This led to the promotion of highly inefficient energy use and fluctuating indoor thermal comfort. To address these concerns, this study develops a novel framework based on deep clustering of lagrangian trajectories for multi-task learning (DCLTML) and adding a pre-cooling coil in the air handling unit (AHU) to alleviate a coupling issue. The proposed DCLTML exhibits great overall control and is

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Publication Date
Sat Jun 24 2023
Journal Name
Arab World English Journal
The Construction of Racism in Cartoon Films: A Critical Discourse Analysis
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Animation is an industry that is expanding more quickly than ever. Every child’s favorite activity is watching cartoons. Therefore, it is essential to be cautious of the kinds of cartoon films children and teenagers tend. Because children and teenagers are the target audience for these films. This study aims at exposing a hidden enactment, namely racism, in a well-known cartoon film, Lion King, which has been selected accurately by the researchers because it shapes a set of ideas about black people and constructs prejudiced beliefs in their minds. This study is to answer the inquiry ‘Is the ideology of racism imposed in Lion King? And how?’ The significance of the present paper lies in highlighting the educational function of

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Publication Date
Tue Jan 02 2018
Journal Name
Journal Of Educational And Psychological Researches
Teaching techniques due to the Brain-based learning theory among math teachers
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The purpose of the study is to identify the teaching techniques that mathematics' teachers use due to the Brain-based learning theory. The sample is composed of (90) teacher: (50) male, (40) female. The results have shown no significant differences between male and female responses' mean. Additionally, through the observation of author, he found a lack of using Brain-based learning techniques. Thus, the researcher recommend that it is necessary to involve teachers in remedial courses to enhance their ability to create a classroom that raise up brain-based learning skills.  

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Publication Date
Wed Sep 28 2022
Journal Name
Journal Of The College Of Education For Women
Women's Rape in Iraq between Legislation and Social Norms: A Critical Discourse Analysis
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Recently, women's rape has been a pervasive problem in the Iraqi society. Thus, it has become necessary to consider the role of language and its influence on the common beliefs and opinions about rape in the Iraqi society. Thus, taking into consideration the critical role of language and its impact on the perception of human reality and the social development based on people's beliefs and principles of life has become highly indispensable. Therefore. The aim of this article is to address this problem critically from legislation and social norms in NGOs' reports (2015; 2019) with reference to some provisions from the Iraqi Panel Code (1969; 2010). Therefore, the researchers examine the discursive strategies and ideological viewpoints in t

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Publication Date
Tue Aug 01 2023
Journal Name
Journal Of Engineering
An Extensive Literature Review on Risk Assessment Models (Techniques and Methodology) for Construction Industry
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This study looks into the many methods that are used in the risk assessment procedure that is used in the construction industry nowadays. As a result of the slow adoption of novel assessment methods, professionals frequently resort to strategies that have previously been validated as being successful. When it comes to risk assessment, having a precise analytical tool that uses the cost of risk as a measurement and draws on the knowledge of professionals could potentially assist bridge the gap between theory and practice. This step will examine relevant literature, sort articles according to their published year, and identify domains and qualities. Consequently, the most significant findings have been presented in a manne

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Publication Date
Fri Jun 30 2023
Journal Name
Journal Of The College Of Education For Women
Investigating The Ideology of Bullying in Hunt’s Fish in a Tree: A Critical Stylistic Approach
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         Language always conveys ideologies that represent an essential aspect of the world we live in. The beliefs and opinions of an individual or community can be organized, interacted with, and negotiated via the use of language. Recent researches have paid attention to bullying as a social issue. They have focused on the psychological aspect of bullying rather than the linguistic one. To bridge this gap, the current study is intended to investigate the ideology of bullying from a critical stylistic perspective. The researchers adopt Jeffries' (2010) critical stylistics model to analyze the data which is five extracts taken from Hunt’s Fish in a Tree (2015). The analysis demonstrates

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