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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
Sun Jul 01 2012
Journal Name
2012 International Symposium On Innovations In Intelligent Systems And Applications
Edge detection for fast block-matching motion estimation to enhance Mean Predictive Block Matching algorithm
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Publication Date
Fri Nov 01 2019
Journal Name
Sensors And Actuators B: Chemical
Sensor and sensor microtiterplate with expanded pH detection range and their use in real samples
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Publication Date
Sat Jun 15 2019
Journal Name
Journal Of Baghdad College Of Dentistry
Taste Detection Thresholds in Relation to Salivary and Serum Zinc in Patients on Simvastatin Treatment
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Background: Hyperlipidemia is an elevated fat (lipids), mostly cholesterol and triglycerides, in the blood. These lipids usually bind to proteins to remain circulated so-called lipoprotein. Aims of the study: To determine taste detection threshold and estimate the trace elements (zinc) in serum and saliva of those patients and compare all of these with healthy control subjects. Methods: Eighty subjects were incorporated in this study, thy were divided into two groups: forty patients on simvastatin treatment age between (35-60) years, and forty healthy control of age range between (35-60) years. Saliva was collected by non-stimulated technique within 10 minutes. Serum was obtained from each subject. Zinc was estimated in serum and saliva

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Publication Date
Fri Aug 21 2026
Journal Name
Knowledge And Information Systems
Enhanced community detection in social networks via topic-sentiment integration and content-enriched Leiden clustering
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Online social networks play a central role in information diffusion and opinion formation, making the identification of meaningful communities essential for understanding collective behavior. However, most community detection methods rely primarily on network topology and remain insensitive to the semantic and affective information embedded in user-generated content. To address this limitation, this study proposes a content-enriched community detection framework that integrates structural interactions (retweets and mentions) with topic- and sentiment-based attributes. The proposed approach includes two core methodological components: a learnable edge-weighting mechanism that infers interaction strengths from structural, topical, and sentime

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Publication Date
Fri Dec 01 2023
Journal Name
Iraqi Journal Of Physics
Surface Plasmon Resonance (SPR)-Based Multimode Optical Fiber Sensors for Electrical Transformer Oil Aging Detection
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In this study, optical fibers were designed and implemented as a chemical sensor based on surface plasmon resonance (SPR) to estimate the age of the oil used in electrical transformers. The study depends on the refractive indices of the oil. The sensor was created by embedding the center portion of the optical fiber in a resin block, followed by polishing, and tapering to create the optical fiber sensor. The tapering time was 50 min. The multi-mode optical fiber was coated with 60 nm thickness gold metal. The deposition length was 4 cm. The sensor's resonance wavelength was 415 nm. The primary sensor parameters were calculated, including sensitivity (6.25), signal-to-noise ratio (2.38), figure of merit (4.88), and accuracy (3.2)

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Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
An Adaptive Harmony Search Part-of-Speech tagger for Square Hmong Corpus
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Data-driven models perform poorly on part-of-speech tagging problems with the square Hmong language, a low-resource corpus. This paper designs a weight evaluation function to reduce the influence of unknown words. It proposes an improved harmony search algorithm utilizing the roulette and local evaluation strategies for handling the square Hmong part-of-speech tagging problem. The experiment shows that the average accuracy of the proposed model is 6%, 8% more than HMM and BiLSTM-CRF models, respectively. Meanwhile, the average F1 of the proposed model is also 6%, 3% more than HMM and BiLSTM-CRF models, respectively.

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Publication Date
Wed Jan 11 2017
Journal Name
Journal: Ibn Al-haitham Journal For Pure And Applied Sciences
Synthesis and Characterization of some Metal Complexes with (3Z ,5Z, 8Z)-2-azido-8-[azido(3Z,5Z)-2-azido-2,6- bis(azidocarbonyl)-8,9-dihydro-2H-1,7-dioxa-3,4,5- triazonine-9-yl]methyl]-9-[(1-azido-1-hydroxy)methyl]-2H1,7-dioxa-3,4,5-triazonine – 2,6 – dicarbonylazide(L-AZ) .
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The reaction of LAs-Cl8 : [ (2,2- (1-(3,4-bis(carboxylicdichloromethoxy)-5-oxo-2,5- dihydrofuran-2-yl)ethane – 1,2-diyl)bis(2,2-dichloroacetic acid)]with sodium azide in ethanol with drops of distilled water has been investigated . The new product L-AZ :(3Z ,5Z,8Z)-2- azido-8-[azido(3Z,5Z)-2-azido-2,6-bis(azidocarbonyl)-8,9-dihydro-2H-1,7-dioxa-3,4,5- triazonine-9-yl]methyl]-9-[(1-azido-1-hydroxy)methyl]-2H-1,7-dioxa-3,4,5-triazonine – 2,6 – dicarbonylazide was isolated and characterized by elemental analysis (C.H.N) , 1H-NMR , Mass spectrum and Fourier transform infrared spectrophotometer (FT-IR) . The reaction of the L-AZ withM+n: [ ( VO(II) , Cr(III) ,Mn(II) , Co(II) , Ni(II) , Cu(II) , Zn(II) , Cd(II) and Hg(II)] has been i

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Publication Date
Thu Jun 30 2016
Journal Name
Al-kindy College Medical Journal
Detection of Thrombi in Left Atrial chamber by Transoesophageal Ecchocardiography in patients suffer from Non-rheumatic Atrial Fibrillation
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Background: Background : Patients with non-rheumatic atrial fibrillation have high risk of thromboembolism especially ischemic stroke usually arising from left atrial appendage .Transoesophageal echocardiography provides useful information for risk stratification in these patients as it detects thrombus in the left atrial or left atrial appendage. Objective : This study was conducted at Al-Kadhimiya Teaching Hospital to assess the prevalence of left atrial chamber thrombi in patients with chronic non-rheumatic atrial fibrillation using transoesophageal echocardiography and its clinical significance as well as to verify the superiority of transoesophageal over transthoracic echocardiography in the detection of these abnormalities. Type of

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Publication Date
Sun Sep 01 2019
Journal Name
Baghdad Science Journal
Detection of 16S rRNA Methylases and Co-Resistance with β-lactams among Klebsiella pneumoniae Isolates from Iraqi Patients
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Out of 150 clinical samples, 50 isolates of Klebsiella pneumoniae were identified according to morphological and biochemical properties. These isolates were collected from different clinical samples, including 15 (30%) urine, 12 (24%) blood, 9 (18%) sputum, 9 (18%) wound, and 5 (10%) burn. The minimum inhibitory concentrations (MICs) assay revealed that 25 (50%) of isolates were resistant to gentamicin (≥16µg/ml), 22 (44%) of isolates were resistant to amikacin (≥64 µg/ml), 21 (42%) of isolates were resistant to ertapenem (≥8 µg/ml), 18 (36%) of isolates were resistant to imipenem (4- ≥16µg/ml), 43 (86%) of isolates were resistant to ceftriaxone (4- ≥64 µg/ml), 42 (84%) of isolates were resistant to ceftazidime (1

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Publication Date
Sun Mar 05 2017
Journal Name
Baghdad Science Journal
Detection of wheat damping off and root rot disease pathogenic fungi and it bio control by pseudomonas fluorescens
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This study was conducted to determine the fungal cause and bio control of damping off and root rot of wheat plants by using pseudomonas fluorescens under greenhouse and field conditions. Results showed isolation of eight species from the soil and roots to deferent region of Baghdad government. Rhizoctonia solani (Rs) and Fusarium solani (Fs) were the predominant damping off fungus with frequency 60 and 52% respectively. Led the using of bacteria formulations such as crud suspension , pure bacteria filtration and pure living cells in culture medium inhibit all type fungi with rates ranging from 84-96% , 80- 93% and 75-88% respectively. Rs and Fs were more pathogenesis under greenhouse conditions, with incidence of 80 and 68% and disease s

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