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Shadow Detection and Elimination for Robot and Machine Vision Applications
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Shadow removal is crucial for robot and machine vision as the accuracy of object detection is greatly influenced by the uncertainty and ambiguity of the visual scene. In this paper, we introduce a new algorithm for shadow detection and removal based on different shapes, orientations, and spatial extents of Gaussian equations. Here, the contrast information of the visual scene is utilized for shadow detection and removal through five consecutive processing stages. In the first stage, contrast filtering is performed to obtain the contrast information of the image. The second stage involves a normalization process that suppresses noise and generates a balanced intensity at a specific position compared to the neighboring intensities. In the third stage, the boundary of the target object is extracted, and in the fourth and fifth stages, respectively, the region of interest (ROI) is highlighted and reconstructed. Our model was tested and evaluated using realistic scenarios which include outdoor and indoor scenes. The results reflect the ability of our approach to detect and remove shadows and reconstruct a shadow free image with a small error of approximately 6%.

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Publication Date
Wed Jan 01 2025
Journal Name
Fusion: Practice And Applications
Enhanced EEG Signal Classification Using Machine Learning and Optimization Algorithm
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This paper proposes a better solution for EEG-based brain language signals classification, it is using machine learning and optimization algorithms. This project aims to replace the brain signal classification for language processing tasks by achieving the higher accuracy and speed process. Features extraction is performed using a modified Discrete Wavelet Transform (DWT) in this study which increases the capability of capturing signal characteristics appropriately by decomposing EEG signals into significant frequency components. A Gray Wolf Optimization (GWO) algorithm method is applied to improve the results and select the optimal features which achieves more accurate results by selecting impactful features with maximum relevance

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Publication Date
Mon Jan 01 2024
Journal Name
Bio Web Of Conferences
Forecasting Cryptocurrency Market Trends with Machine Learning and Deep Learning
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Cryptocurrency became an important participant on the financial market as it attracts large investments and interests. With this vibrant setting, the proposed cryptocurrency price prediction tool stands as a pivotal element providing direction to both enthusiasts and investors in a market that presents itself grounded on numerous complexities of digital currency. Employing feature selection enchantment and dynamic trio of ARIMA, LSTM, Linear Regression techniques the tool creates a mosaic for users to analyze data using artificial intelligence towards forecasts in real-time crypto universe. While users navigate the algorithmic labyrinth, they are offered a vast and glittering selection of high-quality cryptocurrencies to select. The

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Publication Date
Sat Sep 30 2017
Journal Name
Al-khwarizmi Engineering Journal
A Cognitive Hybrid Tuning Control Algorithm Design for Nonlinear Path-Tracking Controller for Wheeled Mobile Robot
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Abstract

This research presents a on-line cognitive tuning control algorithm for the nonlinear controller of path-tracking for dynamic wheeled mobile robot to stabilize and follow a continuous reference path with minimum tracking pose error. The goal of the proposed structure of a hybrid (Bees-PSO) algorithm is to find and tune the values of the control gains of the nonlinear (neural and back-stepping method) controllers as a simple on-line with fast tuning techniques in order to obtain the best torques actions of the wheels for the cart mobile robot from the proposed two controllers. Simulation results (Matlab Package 2012a) show that the nonlinear neural controller with hybrid Bees-PSO cognitive algorithm is m

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Publication Date
Wed Jun 01 2011
Journal Name
Journal Of Economics And Administrative Sciences
The reality and dilemmas of higher education in IraqAnalytical vision in knowledge economies
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The subject of education, and since time immemorial, gripe the attention of the religious, intellectual, political, social and economic elites. This attention not only in Iraq, but in different countries in the world. There is a close correlation between the educational level of the societies and the edginess of its rising and advancement in all fields.

In order to achieve the research objectives, the research has   been divided into three sections: section I include the historical, scientific, humanitarian evolution of education, starting from the first economic revolution (The Agricultural revolution) through the second economic revolution (The Industrial Revolution) and till the Third Economi

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Publication Date
Fri Dec 01 2023
Journal Name
Political Sciences Journal
Societal awareness and its role in building the Arab state: an intellectual vision:
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It is no secret to everyone that the Arab individual suffers from poor self-awareness and political awareness, which made the state and the importance of its existence and preserving its institutions not among his interests, which made researchers wonder about the possibility of strengthening it and the extent of its impact on the future of building the contemporary Arab state, so the study attempted Addressing the issue of community awareness and its impact on building the state through a clear intellectual vision that blended what is social and political to define the concept of community awareness and highlight its importance and role as a basic pillar in shaping and building modern Arab countries. In the Arab world and ways to enhanc

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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
Mon Jan 01 2024
Journal Name
Baghdad Science Journal
Artificial Neural Network and Latent Semantic Analysis for Adverse Drug Reaction Detection
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Adverse drug reactions (ADR) are important information for verifying the view of the patient on a particular drug. Regular user comments and reviews have been considered during the data collection process to extract ADR mentions, when the user reported a side effect after taking a specific medication. In the literature, most researchers focused on machine learning techniques to detect ADR. These methods train the classification model using annotated medical review data. Yet, there are still many challenging issues that face ADR extraction, especially the accuracy of detection. The main aim of this study is to propose LSA with ANN classifiers for ADR detection. The findings show the effectiveness of utilizing LSA with ANN in extracting AD

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Publication Date
Wed Oct 20 2021
Journal Name
Ibn Al- Haitham Journal For Pure And Applied Sciences
Polymer Chain Reaction (PCR): Principle and Applications
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The new, standard molecular biologic system for duplicating DNA enzymatically devoid of employing a living organism, like E. coli or yeast, represents polymerases chain reaction (PCR). This technology allows an exponential intensification of a minor quantity of DNA molecule several times. Analysis can be straightforward with more DNA available. A thermal heat cycler performs a polymerization chain reaction that involves repeated cycles of heating and cooling the reactant tubes at the desired temperature for each reaction step. A heated deck is positioned on the upper reaction tube to avoid evaporating the reaction mixture (normally volumes range from 15 to 100 l per tube), or an oil layer can be placed on a reaction mixture su

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Publication Date
Tue Mar 07 2017
Journal Name
The First International Conference For Engineering Research
Colony Counting Using iPad and iPhone Applications
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Publication Date
Wed Jun 01 2022
Journal Name
Innovations
Proteolytics, Their Functional Role and Practical Applications
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RMK Al-Zaid, AT Al-Musawi, SJ Mohammad

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