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Deep Classifier Structures with Autoencoder for Higher-level Feature Extraction
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Publication Date
Mon Jul 10 2023
Journal Name
Journal Of Engineering
Experimental Study of Pre-Cast Reinforced Concrete Deep Beams (Hallow Core section) Retrofitting with Carbon Fiber Reinforced Polymer (CFRP)
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Experimental programs based test results has been used as a means to find out the response of individual elements of structure. In the present study involves investigated behavior of five reinforced concrete deep beams of dimension (length 1200 x height 300 x width150mm) under two points concentrated load with shear span to depth ratio of (1.52), four of these beams with hallow core and
retrofit with carbon fiber reinforced polymer CFRP (with single or double or sides Strips). Two shapes of hallow are investigated (circle and square section) to evaluated the response of beams in case experimental behavior. Test on simply supported beam was performed in the laboratory & loaddeflection, strain of concrete data and crack pattern of

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Publication Date
Sat Jul 06 2024
Journal Name
Multimedia Tools And Applications
Text classification based on optimization feature selection methods: a review and future directions
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A substantial portion of today’s multimedia data exists in the form of unstructured text. However, the unstructured nature of text poses a significant task in meeting users’ information requirements. Text classification (TC) has been extensively employed in text mining to facilitate multimedia data processing. However, accurately categorizing texts becomes challenging due to the increasing presence of non-informative features within the corpus. Several reviews on TC, encompassing various feature selection (FS) approaches to eliminate non-informative features, have been previously published. However, these reviews do not adequately cover the recently explored approaches to TC problem-solving utilizing FS, such as optimization techniques.

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Publication Date
Mon Jul 01 2024
Journal Name
Journal Of Engineering
Efficient Intrusion Detection Through the Fusion of AI Algorithms and Feature Selection Methods
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With the proliferation of both Internet access and data traffic, recent breaches have brought into sharp focus the need for Network Intrusion Detection Systems (NIDS) to protect networks from more complex cyberattacks. To differentiate between normal network processes and possible attacks, Intrusion Detection Systems (IDS) often employ pattern recognition and data mining techniques. Network and host system intrusions, assaults, and policy violations can be automatically detected and classified by an Intrusion Detection System (IDS). Using Python Scikit-Learn the results of this study show that Machine Learning (ML) techniques like Decision Tree (DT), Naïve Bayes (NB), and K-Nearest Neighbor (KNN) can enhance the effectiveness of an Intrusi

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Publication Date
Mon Dec 20 2021
Journal Name
Baghdad Science Journal
Anemia and The Level of IL-6 in Children Infected with Entamoeba histolytica and Giardia lamblia
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The relation between anemia and inflammatory immune response has lately had much attention. This research was conducted from October 2018 until April 2019, including  (110) children below 12 years from both gender in some Hospitals, Primary Health care centers, Public Primary Schools and Kindergarten in Baghdad, Iraq. The objective of this study is to determine the possible correlation between iron deficiency anemia and inflammatory immune response  among children infected with Entamoeba  histolytica or Giardia  lamblia. Blood samples were taken from all groups to measure  hemoglobin level, serum iron, total iron binding capacity (TIBC), mean corpuscular volume (MCV), and mean corpuscular  hemoglobin concentration

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Publication Date
Sun Jan 01 2023
Journal Name
Iraqi Journal Of Hematology
Evaluation of angiopoietin-2 level in patients with multiple myeloma at presentation and in remission state
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The study aimed to assess the level of ANG‑2 in MM patients at diagnosis and in remission state and elaborate on its correlation with interleukin‑6 (IL‑6) and beta‑2 microglobulin (B2M) levels. Sixty MM patients; 20 newly diagnosed (ND), and 40 patients in remission were included. Twenty healthy individuals were included as a control group. Plasma levels of ANG‑2, B2M, and IL‑6 were tested by enzyme‑lin ked immunosorbent assay. There are significant statistical differences between ND patients and those in remission in hemoglobin, neutrophil count, blood urea, serum creatinine, glomerular filtration rate, B2M, IL6, and ANG‑2 (P = 0.001, 0.033, 0.005, 0.001, 0.001, 0.001, 0.004, and 0.001, respectively). ANG‑2 showed signifi

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Publication Date
Wed Aug 30 2023
Journal Name
Al-kindy College Medical Journal
Salivary Interleukin-6 Level in Iraqi Patients with Oral Lichen Planus receiving Platelet-Rich Plasma Injections
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Background: Interleukin-6 (IL-6) is a cytokine that has several functions, including stimulating growth and inhibiting cell death. It has the potential to operate as a biomarker for the accurate prediction of disease severity and activity, platelets-rich plasma was used in the treatment of oral lichen planus and can change the salivary IL-6 level.

Objectives: To study the clinical outcome of intralesional platelets-rich plasma in patients with oral lichen planus and to measure salivary IL-6 levels before and after the treatment with platelets-rich plasma were the aims of this study.

Subjects and Methods: In this clinical trial, for each patient a standardi

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Publication Date
Sun Jul 07 2013
Journal Name
Journal Of Educational And Psychological Researches
Vocational stresses and their relation with the level of ambition among the lecturers of the university
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Vocational stresses and their relation with the level of ambition among the lecturers of the university In general , vocational stresses affect the attention and the process of focusing making individual busy with solving of his daily problems instead of his job. The vocational stresses , anxiety and tension are factors effecting the physical and psychological ability of the individual. This study aims to measure the vocational stresses among the lecturers of the university , to measure the level of ambition among them, to identify the statistical differences significant among them according to sex variable, to identify the differences significant in level of ambition among them according to sex variable and to identify the correlation r

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Publication Date
Tue Mar 28 2017
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Association of Admission Serum Resistin Level with Acute ST-Segment Elevation Myocardial Infarction in Iraqi Patients
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Human resistin is an adipokine, with a possible link to coronary heart disease.A few studies were done about resistin in acute phase of ST-segment elevation myocardial infarction (STEMI) especially in Iraqi patients. Accordingly we design a study to investigate the association between resistin concentration and acute phase of STEMI in Iraqi patients.

The present study was carried out at Al-Yarmouk Teaching Hospital from December 2011 until June 2012. Serum resistin levels were measured in 50 patients with acute STEMI (mean age: 58.16 ± 11.73 years) at the first 12 hours of admission and 34 normal controls (mean age: 53.98 ± 15.46 years) matched for age, sex and other risk factors.

 Resistin level in patients wi

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Publication Date
Tue Mar 01 2016
Journal Name
Minerals Engineering
The application of deep eutectic solvent ionic liquids for environmentally-friendly dissolution and recovery of precious metals
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Publication Date
Thu May 01 2025
Journal Name
2025 3rd International Conference On Business Analytics For Technology And Security (icbats)
Comparison of Deep Neural Network Models (LSTM, Bi-LSTM, GRU and Bi-GRU) for Gold Price Prediction
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This research studies the comparison of deep neural network models and performance evaluation to predict the gold prices of time series, where the gold prices contain high fluctuations and non-linear patterns that are difficult to capture using traditional models, which makes predicting them a significant challenge. Therefore, the focus was on using deep learning models represented by (LSTM), (Bi-LSTM), (GRU) and (Bi-GRU). The results showed the superiority of the (Bi-GRU) model according to comparison criteria (MSE), (RMSE), (MAE), and (R∧2) compared to other models because it was able to understand the time patterns better by processing the data in both directions and provided superior performance, which indicates its effectiveness, eff

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