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Early Detection of Autism Spectrum Disorder in Children Using Different Machine Learning Algorithms
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Abstract<p>Autism spectrum disorder(ASD) is a neurological condition marked by impaired communication abilities, social detachment, and repetitive behaviors in individuals. Global health organization facing difficulties in establishing an effective ASD diagnostic system that facilitates precise analysis and early autism prediction. It is a scientific issue that necessitates resolution. This research presents an approach for the early prediction of children with ASD utilizing significant variables through machine learning (ML) methods. Three stages comprise the suggested technique. First, a 1250-case ASD dataset was identified and preprocessed. Five extremely effective traits with high Pearson correlation coefficient (PCC) are chosen from 10: Sex, Speech delay, Jaundice, Genetic disorders, and family history. Next, chosen ASD feature dataset through its paces using five ML techniques: Naive Bayes (NB), K-Nearest Neighbor (k-NN), Decision Tree (DT), Support Vector Machine (SVM), and AdaBoostM1 (ABM1). The proposed framework is assessed in the third phase utilizing five measurements such as accuracy, precision, predicting time, recall, and F1-score,. The findings revealed that: The NB and K-NN approaches exhibit superior accuracy rates of 99.2% and 97.2%, with minimal prediction times of approximately 0.3 seconds and 0.45 seconds, correspondingly. Conversely, the DT and AdBM1 methods demonstrate a minor decline in accuracy, achieving 94.8% and 87.6%, respectively, along with increased prediction times. Nonetheless, the SVM approach exhibits the least performance, achieving an accuracy of 80.4% with a highest prediction time of 0.84 seconds.</p>
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Publication Date
Wed Apr 01 2020
Journal Name
Plant Archives
Land cover change detection using satellite images based on modified spectral angle mapper method
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This research depends on the relationship between the reflected spectrum, the nature of each target, area and the percentage of its presence with other targets in the unity of the target area. The changes occur in Land cover have been detected for different years using satellite images based on the Modified Spectral Angle Mapper (MSAM) processing, where Landsat satellite images are utilized using two software programming (MATLAB 7.11 and ERDAS imagine 2014). The proposed supervised classification method (MSAM) using a MATLAB program with supervised classification method (Maximum likelihood Classifier) by ERDAS imagine have been used to get farthest precise results and detect environmental changes for periods. Despite using two classificatio

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Publication Date
Mon Jul 15 2024
Journal Name
2024 46th Annual International Conference Of The Ieee Engineering In Medicine And Biology Society (embc)
Automatic COVID-19 Detection from Chest X-ray using Deep MobileNet Convolutional Neural Network
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Publication Date
Fri May 31 2019
Journal Name
Journal Of Engineering
A Comparative Study of Various Intelligent Algorithms based Path Planning for Mobile Robots
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In general, path-planning problem is one of most important task in the field of robotics. This paper describes the path-planning problem of mobile robot based on various metaheuristic algorithms. The suitable collision free path of a robot must satisfies certain optimization criteria such as feasibility, minimum path length, safety and smoothness and so on. In this research, various three approaches namely, PSO, Firefly and proposed hybrid FFCPSO are applied in static, known environment to solve the global path-planning problem in three cases. The first case used single mobile robot, the second case used three independent mobile robots and the third case applied three follow up mobile robot.  Simulation results, whi

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Publication Date
Wed Mar 18 2020
Journal Name
Baghdad Science Journal
A Software Defined Network of Video Surveillance System Based on Enhanced Routing Algorithms
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Software Defined Network (SDN) is a new technology that separate the ‎control plane from the data plane. SDN provides a choice in automation and ‎programmability faster than traditional network. It supports the ‎Quality of Service (QoS) for video surveillance application. One of most ‎significant issues in video surveillance is how to find the best path for routing the packets ‎between the source (IP cameras) and destination (monitoring center). The ‎video surveillance system requires fast transmission and reliable delivery ‎and high QoS. To improve the QoS and to achieve the optimal path, the ‎SDN architecture is used in this paper. In addition, different routing algorithms are ‎used with different steps. First, we eva

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Publication Date
Tue Dec 01 2020
Journal Name
Baghdad Science Journal
Association between Allelic Variations of -174G/C Polymorphism of Interleukin-6 Gene and Chronic Kidney Disease-Mineral and Bone Disorder in Iraqi Patients
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This study designed to examine association between-174G/C polymorphism of interleukin-6 gene and phosphate, calcium, vitamin D3, and parathyroid hormone levels in Iraqi patient with chronic kidney disease on maintenance hemodialysis. Seventy chronic renal failure patients (patients group) and 20 healthy subjects (control group) were genotyped for interleukin-6 polymorphism and genotyping was performed by conventional polymerase chain reaction-restriction fragment length polymorphism. No significant differences in phosphate levels were observed in patients and control with different interleukin-6 genotypes. Control had non-significant differences in calcium levels, while patients with GG and CG genotypes displayed significant e

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Publication Date
Tue Dec 11 2018
Journal Name
Iraqi National Journal Of Nursing Specialties
Prevalence of Posttraumatic Stress Disorder (PTSD) among the Iraqi Repatriated Prisoners of the Iran-Iraq War, 1980-1988
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Objective: To determine the prevalence of Posttraumatic Stress Disorder (PTSD) among Iraqi repatriated
prisoners of Iran-Iraq war, and the relationship with demographic factors.
Methodology: A descriptive study was carried out from Oct. 18th, 2009 through Jan. 10th, 2010. A nonprobability
based snowball sampling technique was used to recruit 92 Iraqi repatriated prisoners of war
(IRPOWs) who had visited Ministry of Human Rights. A data collection instrument was constructed that
consisted of six demographic characteristics, and eight items to measure the level of PTSD in POWs. Data were
collected with the constructed instrument during a brief interview. Data were analyzed through the application of
descriptive statist

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Publication Date
Sat Feb 18 2023
Journal Name
Luminescence
Online column preconcentration for speciation and selective determination of Cr(III) in natural water samples using flow injection with chemiluminescence detection
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Abstract<p>A simple, rapid, sensitive and inexpensive approach is described in this work based on a combination of solid‐phase extraction of 8‐hydroxyquinoline (8HQ), for speciation and preconcentration of Cr(III) and Cr(VI) in river water, and the direct determination of these species using a flow injection system with chemiluminescence detection (FI–CL) and a 4‐diethylamino phenyl hydrazine (DEAPH)–hydrogen peroxide system. At different pH, the two forms of chromium [Cr(III) and Cr(VI)] have different exchange capacities for 8HQ, therefore two columns were constructed; the pH of column 1 was adjusted to pH 3 for retaining Cr(III) and column 2 was adjusted to pH 1 for retaining of Cr(VI). The sorbe</p> ... Show More
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Publication Date
Mon Jan 20 2025
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Assessing Landsat Processing Levels and Support Vector Machine Classification
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The availability of different processing levels for satellite images makes it important to measure their suitability for classification tasks. This study investigates the impact of the Landsat data processing level on the accuracy of land cover classification using a support vector machine (SVM) classifier. The classification accuracy values of Landsat 8 (LS8) and Landsat 9 (LS9) data at different processing levels vary notably. For LS9, Collection 2 Level 2 (C2L2) achieved the highest accuracy of (86.55%) with the polynomial kernel of the SVM classifier, surpassing the Fast Line-of-Sight Atmospheric Analysis of Spectral Hypercubes (FLAASH) at (85.31%) and Collection 2 Level 1 (C2L1) at (84.93%). The LS8 data exhibits similar behavior. Conv

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Publication Date
Tue Jul 01 2014
Journal Name
International Journal Of Artificial Intelligence And Mechatronics
Building a Three-Axis CNC Milling Machine Control System
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CNC machines are widely used in production fields since they produce similar parts in a minimum time, at higher speed and with possibly minimum error. A control system is designed, implemented and tested to control the operation of a laboratory CNC milling machine having three axes that are moved by using a stepper motor attached to each axis. The control system includes two parts, hardware part and software part, the hardware part used a PC (works as controller) connected to the CNC machine through its parallel port by using designed interface circuit. The software part includes the algorithms needed to control the CNC. The sample needs to be machined is drawn by using one of the drawing software like AUTOCAD or 3D MAX and is saved in a we

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Publication Date
Sun Jun 15 2008
Journal Name
Al Mustansiriyah Journal Of Pharmaceutical Sciences
The prevalence of Schistosomiasis among children of primary Schools in Balad –Rooz
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Balad –Rooz is considered as one of the endemic foci of Schistosomiasisin Iraq.A survey was performed during the first three months of 2002 in fewprimary schools in Balad –Rooz to assess the prevalence among them.

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