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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
Tue Jun 20 2023
Journal Name
Baghdad Science Journal
Detection of Autism Spectrum Disorder Using A 1-Dimensional Convolutional Neural Network
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Autism Spectrum Disorder, also known as ASD, is a neurodevelopmental disease that impairs speech, social interaction, and behavior. Machine learning is a field of artificial intelligence that focuses on creating algorithms that can learn patterns and make ASD classification based on input data. The results of using machine learning algorithms to categorize ASD have been inconsistent. More research is needed to improve the accuracy of the classification of ASD. To address this, deep learning such as 1D CNN has been proposed as an alternative for the classification of ASD detection. The proposed techniques are evaluated on publicly available three different ASD datasets (children, Adults, and adolescents). Results strongly suggest that 1D

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Publication Date
Mon Apr 09 2018
Journal Name
Al-khwarizmi Engineering Journal
Experimental Evaluation and Finite Element Simulation to Produce Square Cup by Deep Drawing Process
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Deep drawing process to produce square cup is very complex process due to a lot of process parameters which control on this process, therefore associated with it many of defects such as earing, wrinkling and fracture. Study of the effect of some process parameters to determine the values of these parameters which give the best result, the distributions for the thickness and depths of the cup were used to estimate the effect of the parameters on the cup numerically, in addition to experimental verification just to the conditions which give the best numerical predictions in order to reduce the time, efforts and costs for producing square cup with less defects experimentally is the aim of this study. The numerical analysis is used to study

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Publication Date
Wed Feb 01 2023
Journal Name
Baghdad Science Journal
Breast Cancer MRI Classification Based on Fractional Entropy Image Enhancement and Deep Feature Extraction
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Disease diagnosis with computer-aided methods has been extensively studied and applied in diagnosing and monitoring of several chronic diseases. Early detection and risk assessment of breast diseases based on clinical data is helpful for doctors to make early diagnosis and monitor the disease progression. The purpose of this study is to exploit the Convolutional Neural Network (CNN) in discriminating breast MRI scans into pathological and healthy. In this study, a fully automated and efficient deep features extraction algorithm that exploits the spatial information obtained from both T2W-TSE and STIR MRI sequences to discriminate between pathological and healthy breast MRI scans. The breast MRI scans are preprocessed prior to the feature

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Publication Date
Sun Sep 01 2013
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
Impact of applying the third of basel committee11 conventions(market disciplin) in the efficient of significance components for factors of banking capital risks
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We have focused the research problem through an assessment of the applicability of the third pillar of the decisions of the Basel Committee 11 (market discipline) or not and its impact on both the adequacy of bank capital, supervisory oversight and banking risks and the statement weaknesses commitment banking institutions and which in turn lead to the stability of the financial system as a whole.                         .
The research is important statement on the importance of big capital in the banking business and the attributes of a role in the absorption of losses suffered by the bank, which reflects the willin

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Publication Date
Wed Jan 01 2025
Journal Name
Kuwait Journal Of Science
Detection of the most frequent sources of dust storms in Iraq during 2020–2023 using space tools
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Dust storms are typical in arid and semi-arid regions such as the Middle East; the frequency and severity of dust storms have grown dramatically in Iraq in recent years. This paper identifies the dust storm sources in Iraq using remotely sensed data from Meteosat-spinning enhanced visible and infrared imager (SEVIRI) bands. Extracted combined satellite images and simulated frontal dust storm trajectories, using the Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model, are used to identify the most influential sources in the Middle East and Iraq. Out of 132 dust storms in Iraq during 2020–2023, the most frequent occurred in the spring and summer. A dust source frequency percentage map (DSFPM) is generated using ArcGIS so

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Publication Date
Mon Jun 19 2023
Journal Name
Journal Of Engineering
REVIEW THE ASSESSMENT OF EFFECTS OF LOST TIME INJURIES IN AN INDUSTRIAL SYSTEM BY USING AN EXPLANATORY PROGRAM
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Health and safety problem can be described by statistics it can only be understood by knowing and feeling the pain, suffering, and depression. Health and safety has a legal responsibility to protect it for everyone who can affect in the workplace. This includes manufacturers, suppliers, designers and controllers of work places and employees. Work injury is one of the major problems in manufacturing and production systems industries; it is reduced production efficiency and affects the cost. To gain flexibility from a traditional manufacturing system and production efficiency, this paper is about the application of estimating technology to preview and synthesis of Lost Time of Work Injuries in industry systems aims to provide a safe workin

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Publication Date
Fri Jun 27 2025
Journal Name
Sciences Journal Of Physical Education
Using two types of electronic questions by applying the Quiz Creator program in the method of guided discovery and its effect on learning and maintaining a motor chain on the throat
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Publication Date
Sun Mar 03 2024
Journal Name
Mesopotamian Journal Of Cybersecurity
Using Information Technology for Comprehensive Analysis and Prediction in Forensic Evidence
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With the escalation of cybercriminal activities, the demand for forensic investigations into these crimeshas grown significantly. However, the concept of systematic pre-preparation for potential forensicexaminations during the software design phase, known as forensic readiness, has only recently gainedattention. Against the backdrop of surging urban crime rates, this study aims to conduct a rigorous andprecise analysis and forecast of crime rates in Los Angeles, employing advanced Artificial Intelligence(AI) technologies. This research amalgamates diverse datasets encompassing crime history, varioussocio-economic indicators, and geographical locations to attain a comprehensive understanding of howcrimes manifest within the city. Lev

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Publication Date
Fri Jun 27 2025
Journal Name
Journal Of Baghdad College Of Dentistry
Evaluation of treatment of intra-bony defects with a mixture of ?-tricalcium phosphate - hydroxyapatite granules and oily calcium hydroxide suspension
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Background: An oily calcium hydroxide formulation proved over the last years to be highly efficient in promoting bone regeneration in closed defects as periapical lesions, cysts, or post-extraction defects. The aim of the present study is the assessment of the outcome of treatment of deep intrabony periodontal defects with an Open Flap Debridement) (OFD) + combination of {(30% Hydroxyapatite HAp + 70% ?-Tricalcium Phosphate granules mixed with an Oily Calcium Hydroxide Suspension (OCHS )} and compare the results with {(OFD) alone)}. The combination of OCHS& TCP was used in humans with a sort of positive results, and more conduction of studies was recommended. Material and method: The sample of this study composed of sixteen patients;

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Publication Date
Wed May 16 2018
Journal Name
Asian Journal Of Chemistery
Study of Physical and Spectral Properties of Quaternary System of 2,5-Hexadione+Cyclopentanol+Cyclohexanol+3-Heptanol Mixture at 298 K
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