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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 CNNs have shown improved accuracy in the classification of ASD compared to traditional machine learning algorithms, on all these datasets with higher accuracy of 99.45%, 98.66%, and 90% for Autistic Spectrum Disorder Screening in Data for Adults, Children, and Adolescents respectively as they are better suited for the analysis of time series data commonly used in the diagnosis of this disorder

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Publication Date
Sat Dec 31 2022
Journal Name
Iraqi Journal Of Market Research And Consumer Protection
PREPARATION AND STUDY OF THE PHYSICAL PROPERTIES OF SOME COMPLEXES WITH SCHIFF BASE LIGAND FOR CEFDINIR DERIVATIVE : PREPARATION AND STUDY OF THE PHYSICAL PROPERTIES OF SOME COMPLEXES WITH SCHIFF BASE LIGAND FOR CEFDINIR DERIVATIVE
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ABSTRACT

Metal (II) complexes of Co, Ni, Cu and Zn with cefdinir C14H13N5O5S2 derivative (L) were synthesized and identification by elemental analysis CHNS Uv-Vis, FTIR, TGA, metal analysis AA, magnetic susceptibility and conduct metric measurement. by analysis the ligand behaves as a bidentate. For the cobalt complex, Tetrahedral geometry shape was suggested, while other complexes that have nickel, copper and zinc ions were proposed as octahedral geometry shape. The experimental method was studied for prevention of corrosion carbon steel in 3.5% NaCl by using a novel Cefdinir derivations drugs. The results showed that metal complex was a strong corro

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Publication Date
Sun Apr 30 2023
Journal Name
Al-kindy College Medical Journal
Comparison between Quantitative Computed Tomography and Dual-Energy X-Ray Absorptiometry in the Detection of Osteoporosis in Postmenopausal Women
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Background: Osteoporosis is denoted by low bone mass and microarchitectural breakdown of bone tissue, directing to increased fracture risk and bone fragility. Fractures may lead to a decreased quality of life and increased medical costs. Thus, osteoporosis is widely considered a significant health concern.

Objective. This study aimed to compare quantitative computed tomography (QCT) and dual-energy X-Ray absorptiometry (DXA) to detect osteoporosis in postmenopausal women.

Subjects and Methods. We measured spinal volumetric bone mineral density (BMD) with QCT and areal spinal and hip BMD with DXA in 164 postmenopausal women. We calculated the osteo

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Publication Date
Sat Apr 30 2022
Journal Name
Revue D'intelligence Artificielle
Performance Evaluation of SDN DDoS Attack Detection and Mitigation Based Random Forest and K-Nearest Neighbors Machine Learning Algorithms
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Software-defined networks (SDN) have a centralized control architecture that makes them a tempting target for cyber attackers. One of the major threats is distributed denial of service (DDoS) attacks. It aims to exhaust network resources to make its services unavailable to legitimate users. DDoS attack detection based on machine learning algorithms is considered one of the most used techniques in SDN security. In this paper, four machine learning techniques (Random Forest, K-nearest neighbors, Naive Bayes, and Logistic Regression) have been tested to detect DDoS attacks. Also, a mitigation technique has been used to eliminate the attack effect on SDN. RF and KNN were selected because of their high accuracy results. Three types of ne

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Publication Date
Wed Sep 20 2023
Journal Name
Journal Of Applied And Natural Science
Detection of some virulence genes (esp, agg, gelE, CylA) in Enterococcus faecalis isolated from different clinical cases at Baghdad
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The virulent genes are the key players in the ability of the bacterium to cause disease. The products of such genes that facilitate the successful colonization and survival of the bacterium in or cause damage to the host are pathogenicity determinants. This study aimed to investigate the prevalence of virulence factors (esp, agg, gelE, CylA) in E. faecalis isolated from diverse human clinical collected in Iraqi patient , as well as to assess their ability to form biofilm and to determine their haemolytic and gelatinase activities. Thirty-two isolates of bacteria Enterococcus faecalis were obtained, including 15 isolates (46.87%) of the urine, 6 isolates (18.75%) for each of the stool and uterine secretions, and 5 isolates (15.62%) of the wo

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Publication Date
Mon Dec 29 2025
Journal Name
Acta Microbiologica Bulgarica
Molecular detection of fimH, gipA, and ibeA genes in adherent invasive Escherichia coli isolated from patients with ulcerative colitis
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Recently, there has been an increase in the prevalence of ulcerative colitis (UC), and inflammatory bowel diseases (IBD) worldwide, especially in certain recently industrialized countries like China and In¬dia. Globally, the prevalence of UC, a chronic illness that affects the large intestine, is rising. Fifty adherent invasive Escherichia coli (AIEC) isolates were identified from ulcerative colitis biopsy samples originating from the Gastrointestinal tract (GIT) and Hepatology teaching hospitals/medical city in Baghdad City. The test’s results demonstrated that the AIEC isolates had a high level of resistance to the majority of the an-tibiotics under investigation. Enterobacterial Repetitive Intergenic Consensus (ERIC-PCR) and m

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Publication Date
Mon Jan 07 2019
Journal Name
Arab Science Heritage Journal
التحري عن الجراثيم المرضية في بيض المائدة المتوافر في الأسواق المحلية
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     أجري البحث لمعرفة الملوثات الميكروبية الموجودة على قشرة وفي صفار وبياض بيض الدجاج المحلي ، السوري ، التركي ، الاوكراني ، حيث جمعت العينات بمعدل 10 بيضة من الاسواق الشعبية في محافظة  بغداد . أظهرت النتائج أن بكتريا السالمونيلا واضحة في صفار البيض التركي .  وفي قشرة وبياض وصفار البيض الاوكراني . كما أظهرت نتائج فحص البيض

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Publication Date
Sat Dec 01 2018
Journal Name
Nano Hybrids And Composites
Specific NH<sub>3</sub> Gas Sensor Worked at Room Temperature Based on MWCNTs-OH Network
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Functionalized Multi-Walled Carbon Nanotubes (MWCNTs-OH) network with thickness 4μm was made by the vacuum filtration from suspension (FFS) method. The morphology, structure and optical properties of the MWCNTs film were characterized by SEM and UV-Vis. spectra techniques. The SEM images reflected highly ordered network in the form of ropes or bundles with close-packing which looks like spaghetti. The absorbance spectrum revealed that the network has a good absorbance in the UV-Vis. region. The gas sensor system was used to test the MWCNT-OH network to detect NH3gas at room temperature. The resistance of the sensor was increased when exposed to the NH3gas. The sensitivities of the network w

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Publication Date
Tue Jan 01 2019
Journal Name
Chemical Industry And Chemical Engineering Quarterly
Optimization of dye adsorption process for Albizia lebbeck pods as a biomass using central composite rotatable design model
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Albizia lebbeck biomass was used as an adsorbent material in the present study to remove methyl red dye from an aqueous solution. A central composite rotatable design model was used to predict the dye removal efficiency. The optimization was accomplished under a temperature and mixing control system (37?C) with different particle size of 300 and 600 ?m. Highest adsorption efficiencies were obtained at lower dye concentrations and lower weight of adsorbent. The adsorption time, more than 48 h, was found to have a negative effect on the removal efficiency due to secondary metabolites compounds. However, the adsorption time was found to have a positive effect at high dye concentrations and high adsorbent weight. The colour removal effi

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Publication Date
Mon May 04 2020
Journal Name
Environmental Engineering Research
Experimental and modeling study of water defluoridation using waste granular brick in a continuous up-flow fixed bed
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Contamination of surface and groundwater with excessive concentrations of fluoride is of significant health hazard. Adsorption of fluoride onto waste materials of no economic value could be a potential approach for the treatment of fluoride-bearing water. This experimental and modeling study was devoted to investigate for the first the fluoride removal using unmodified waste granular brick (WGB) in a fixed bed running in continuous mode. Characterization of WGB was carried out by FT-IR, SEM, and EDX analysis. The batch mode experiments showed that they were affected by several parameters including contact time, initial pH, and sorbent dosage. The best values of these parameters that provided maximum removal percent (82%) with the in

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Publication Date
Tue Jan 01 2019
Journal Name
Chemical Industry And Chemical Engineering Quarterly
Optimization of dye adsorption process for Albizia lebbeck pods as a biomass using central composite rotatable design model
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Albizia lebbeck biomass was used as an adsorbent material in the present study to remove methyl red dye from an aqueous solution. A central composite rotatable design model was used to predict the dye removal efficiency. The optimization was accomplished under a temperature and mixing control system (37?C) with different particle size of 300 and 600 ?m. Highest adsorption efficiencies were obtained at lower dye concentrations and lower weight of adsorbent. The adsorption time, more than 48 h, was found to have a negative effect on the removal efficiency due to secondary metabolites compounds. However, the adsorption time was found to have a positive effect at high dye concentrations and high adsorbent weight. The colour removal effi

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Scopus (13)
Crossref (11)
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