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Improve Memory for Alzheimer Patient by Employing Mind Wave on Virtual Reality with Deep Learning
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Publication Date
Sun Nov 01 2015
Journal Name
Journal Of Engineering
Enhancement Solution to Improve Remediation of Soil Contaminated with Lead by Electrical Field
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A laboratory investigation of six different tests were conducted on silty clay soil spiked with lead in concentrations of 1500 mg/kg. A constant DC voltage gradient of 1 V/cm was applied for all these tests with duration of 7 days remediation process for each test. Different purging solutions and addition configurations, i.e. injection wells, were investigated experimentally to enhance the removal of lead from Iraqi soil during electro-kinetic remediation process. The experimental results showed that the overall removal efficiency of lead for tests conducted with distilled water, 0.1 M acetic acid, 0.2 M EDTA and 1 M  ammonium citrate as the purging solutions were equal to 18 %, 37 %, 42 %, and 29 %, respectively. H

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Publication Date
Wed Nov 06 2024
Journal Name
2024 17th International Conference On Development In Esystem Engineering (dese)
Speech Enhancement Algorithm using Deep Learning and Hahn Polynomials
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Publication Date
Mon Jan 01 2024
Journal Name
Computers, Materials & Continua
Credit Card Fraud Detection Using Improved Deep Learning Models
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Publication Date
Mon Mar 09 2026
Journal Name
International Journal Of Inventions In Engineering & Science Technology
Sentiment Analysis of Twitter Users Using Deep Learning Models
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This research suggests a robust and systematic way for Arabic Sentiment Analysis using a vast dataset of 66,666 text reviews. One of the main advantages of this study is that the dataset was perfectly balanced (33,333 positive samples and 33,333 negative samples). In machine learning, this 50/50 split is important because it eliminates class bias and enables the predictive model to treat both sentiment classes equally. As shown in the values of the metrics — overall accuracy, weighted precision, weighted recall, and F1 score — there is great similarity among them, indicating a stable and reliable assessment of the model's real potential throughout the Arabic dataset. Based on data profile, the average word count per review is 42.3

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Publication Date
Mon Mar 02 2026
Journal Name
International Journal Of Inventions In Engineering & Science Technology
A Review: Campus Violence Detection Using Deep Learning Models
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This paper offers a systemic review of the deep learning methods to detect violence on campus, which is a critical issue in intelligent surveillance to improve the student safety and prompt cut off of violent accidents. The review reviews studies published 2018-2025, concentrating on model structure to detect fights, bullying, vandalism, and aggressive behavior on problematic campuses due to occlusion and light variations and complicated human interactions. The research design includes a comparative study of different deep learning networks, such as CNNs, RNNs, 3D CNNs, attention-based networks, transformers, graph neural networks, neuro-fuzzy, and multimodal systems and federated learning methods. The paper also assesses benchmark

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Publication Date
Sun Nov 01 2020
Journal Name
Iop Conference Series: Materials Science And Engineering
3D scenes semantic segmentation using deep learning based Survey
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Abstract<p>Semantic segmentation realization and understanding is a stringent task not just for computer vision but also in the researches of the sciences of earth, semantic segmentation decompose compound architectures in one elements, the most mutual object in a civil outside or inside senses must classified then reinforced with information meaning of all object, it’s a method for labeling and clustering point cloud automatically. Three dimensions natural scenes classification need a point cloud dataset to representation data format as input, many challenge appeared with working of 3d data like: little number, resolution and accurate of three Dimensional dataset . Deep learning now is the po</p> ... Show More
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Publication Date
Sat Dec 02 2023
Journal Name
Journal Of Engineering
Deep Learning of Diabetic Retinopathy Classification in Fundus Images
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Diabetic retinopathy is an eye disease in diabetic patients due to damage to the small blood vessels in the retina due to high and low blood sugar levels. Accurate detection and classification of Diabetic Retinopathy is an important task in computer-aided diagnosis, especially when planning for diabetic retinopathy surgery. Therefore, this study aims to design an automated model based on deep learning, which helps ophthalmologists detect and classify diabetic retinopathy severity through fundus images. In this work, a deep convolutional neural network (CNN) with transfer learning and fine tunes has been proposed by using pre-trained networks known as Residual Network-50 (ResNet-50). The overall framework of the proposed

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Publication Date
Mon Jan 09 2023
Journal Name
2023 15th International Conference On Developments In Esystems Engineering (dese)
Deep Learning-Based Speech Enhancement Algorithm Using Charlier Transform
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Publication Date
Wed Jan 01 2025
Journal Name
Lecture Notes In Networks And Systems
Automated Detection of Dubas Bug Infestation in Palm Trees Using Deep Learning with Residual Neural Networks
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Automated detection of Dubas palm infestation by image processing techniques has practical significance as it can improve agricultural efficiency, increase crop yield and quality, protect the environment, and provide data-driven insights. It also reduces the human effort required for pest control and enhances sustainability. In this study, we aimed to automate the detection of Dubas bug infestation in palm trees using deep learning with transfer learning residual neural networks. Based on four models: InceptionResNetV2, ResNet18, ResNet50, and ResNet101, the data used in this study were obtained by drone photography, many images were taken, and then the infected area was extracted. Using two types of data, 185 infected images and 185 health

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Publication Date
Mon May 12 2025
Journal Name
Boundary Value Problems
Minimal wave speed and traveling wave in nonlocal dispersion SIS epidemic model with delay
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This study examines traveling wave solutions of the SIS epidemic model with nonlocal dispersion and delay. The research shows that a key factor in determining whether traveling waves exist is the basic reproduction number R0. In particular, the system permits nontrivial traveling wave solutions for σ≥σ∗ for R0>1, whereas there are no such solutions for σ<σ∗. This is because there is a minimal wave speed σ∗>0. On the other hand, there are no traveling wave solutions when R0≤1. In conclusion, we provide several numerical simulations that illustrate the existence of TWS.

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