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Artificial Neural Network and Latent Semantic Analysis for Adverse Drug Reaction Detection
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Adverse drug reactions (ADR) are important information for verifying the view of the patient on a particular drug. Regular user comments and reviews have been considered during the data collection process to extract ADR mentions, when the user reported a side effect after taking a specific medication. In the literature, most researchers focused on machine learning techniques to detect ADR. These methods train the classification model using annotated medical review data. Yet, there are still many challenging issues that face ADR extraction, especially the accuracy of detection. The main aim of this study is to propose LSA with ANN classifiers for ADR detection. The findings show the effectiveness of utilizing LSA with ANN in extracting ADR.

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Publication Date
Mon Sep 30 2024
Journal Name
Iraqi Journal Of Science
Molecular and Immunological Detection of Hepatitis C Virus in Patients with Chronic Renal Failure
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Due to its association with hepatocellular carcinoma and being one of the ten most common malignancies worldwide, hepatitis C viral infection has become a severe public health concern. Therefore, establishing an accurate, reliable and sensitive diagnostic test for this infection is strongly advised. Real-time polymerase chain reaction (PCR) has been created to achieve this purpose. The current study was established to investigate the hepatitis C virus among Iraqi patients with chronic renal failure and to detect the virus immunologically by the fourth generation enzyme-linked immunosorbent assay technique and molecularly by real-time PCR. As a result, out of 50 patients with chronic renal failure undergoing dialysis, 39 patients tes

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Publication Date
Sat Oct 04 2025
Journal Name
Mesopotamian Journal Of Computer Science
Enhanced IOT Cyber-Attack Detection Using Grey Wolf Optimized Feature Selection and Adaptive SMOTE
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The Internet of Things (IoT) has significantly transformed modern systems through extensive connectivity but has also concurrently introduced considerable cybersecurity risks. Traditional rule-based methods are becoming increasingly insufficient in the face of evolving cyber threats.  This study proposes an enhanced methodology utilizing a hybrid machine-learning framework for IoT cyber-attack detection. The framework integrates a Grey Wolf Optimizer (GWO) for optimal feature selection, a customized synthetic minority oversampling technique (SMOTE) for data balancing, and a systematic approach to hyperparameter tuning of ensemble algorithms: Random Forest (RF), XGBoost, and CatBoost. Evaluations on the RT-IoT2022 dataset demonstrat

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Publication Date
Tue Jun 03 2025
Journal Name
Journal Of Animal Health And Production
Prevalence of Toxocara spp. in Cats and Detection of Intestinal Helminth Infections in Humans
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This study aimed to investigate the prevalence of intestinal helminth infections in humans and detect Toxocara spp. in cats, with a focus on assessing the impact of age and gender on infection rates. Traditional diagnostic methods have historically limited the accurate identification of helminth infections in humans. Analysis of 450 human stool samples revealed an overall helminth infection rate of 5.7% using conventional techniques. The specific infection rates were 0.4% for Strongyloides stercoralis, 0.6% for Schistosoma mansoni, 1.7% for Hymenolepis nana, and 2.8% for Ascaris lumbricoides. Notably, no infections were recorded in the 30–39 and ≥40-year age groups, while the highest infection rate (16.3%, P≤0.01) was observed in indi

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Publication Date
Tue Oct 16 2018
Journal Name
International Journal Of Pharmaceutical Quality Assurance
Isolation and Detection of Candida tropicalis from Aborted Placenta in Al-Najaf city/Iraq
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Background: Candida tropicalis is one of the most causes of vulvovaginal candidiasis (VVC) in women. Systemic candidiasis and candidemia may also occur in pregnancies. Objective: This study was carried out to detect and isolate of this yeast from aborted placenta, which may cause severe complications such as spontaneous abortion. Materials and methods: Fresh aborted placenta were collected and washed by normal saline to remove the blood. Then, cut it into portions and place it in test tube containing 5 ml of normal saline. Finally, shake for 10 minutes, after that, cultured for microbial isolation. Isolation and detection were done by some conventional methods with Api candida and CHROMagar. Results: The results showed that four iso

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Publication Date
Tue Oct 08 2002
Journal Name
Iraqi Journal Of Laser
Laser Detection and Tracking System Using an Array of Photodiodes with Fuzzy Logic controller
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In this work laser detection and tracking system (LDTS) is designed and implemented using a fuzzy logic controller (FLC). A 5 mW He-Ne laser system and an array of nine PN photodiodes are used in the detection system. The FLC is simulated using MATLAB package and the result is stored in a lock up table to use it in the real time operation of the system. The results give a good system response in the target detection and tracking in the real time operation.

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Publication Date
Fri Jul 21 2023
Journal Name
Journal Of Engineering
GENERATION AND TOOTH CONTACT ANALYSIS (TCA) OF HYPOID GEAR DRIVE
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The present work covers the Face-Hobbing method for generation and simulation of meshing of Face hobbed hypoid gear drive. In this work the generation process of hobbed hypoid gear has been achieved by determination of the generation function of blade cutter. The teeth surfaces have been drawn depending on the simulation of the cutting process and the head cutter motion. Tooth contact analysis (TCA) of such gear drive is presented to evaluate analytically the transmission error function for concave and convex tooth side due to misalignment errors. TCA results show that the gear is very sensitive to misalignment errors and
the increasing of the gear teeth number decrease the transmission error for both concave and convex tooth sides a

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Publication Date
Thu Apr 30 2020
Journal Name
Journal Of Economics And Administrative Sciences
Role of System Strategic Learning Smart In Sustainability Success of Managing Network e-Business
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Purpose: Determining and identifying the relationships of smart strategic education systems and their potential effects on sustainable success in managing clouding electronic business networks according to green, economic and environmental logic based on vigilance and awareness of the strategic mind.

Design: Designing a hypothetical model that reveals the role and investigating audit and cloud electronic governance according to a philosophy that highlights smart strategic learning processes, identifying its assumptions in cloud spaces, choosing its tools, what it costs to devise expert minds, and strategic intelligence.

Methodology:

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Publication Date
Thu Sep 02 2010
Journal Name
Journal Of Kerbala University
N3O3 Hexanuclear Complexes type are Synthesized and Characterised from the reaction of Diphenylmonoxime with (Mn(II) ,Co(II) ,Ni(II) ,Cu(II) ,Zn(II) , and Hg(II) ) ions.
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The new Hexadentate complexes type [M(H3L3)]K were prepared from the condensation reaction of Diphenylmonoxime and KOH with (Mn(II), Co(II), Ni(II), Cu(II), Zn(II), and Hg(II)) in methanol with 3:1 ligand : metal ratio to give a series of new complexes of the general formula [M(H3L3)]K (where: M(II) = Mn ,Co ,N ,Cu ,Zn and Hg).All compounds have been Characterized by spectroscopic methods [I.R, U.v-Vis, atomic absorption and microanalysis (C.H.N) along with conductivity measurements. The stability constant K and Gibbs free energy ∆G were calculated for [Co (H3L3)] K, [Ni (H3L3)] K and [Cu (H3L3)] K and complexes using spectrophotometer method. The obtained values indicate that these complexes stable in their solution. From the above data

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Publication Date
Wed May 31 2023
Journal Name
Iraqi Geological Journal
Studying the Effect of Permeability Prediction on Reservoir History Matching by Using Artificial Intelligence and Flow Zone Indicator Methods
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The map of permeability distribution in the reservoirs is considered one of the most essential steps of the geologic model building due to its governing the fluid flow through the reservoir which makes it the most influential parameter on the history matching than other parameters. For that, it is the most petrophysical properties that are tuned during the history matching. Unfortunately, the prediction of the relationship between static petrophysics (porosity) and dynamic petrophysics (permeability) from conventional wells logs has a sophisticated problem to solve by conventional statistical methods for heterogeneous formations. For that, this paper examines the ability and performance of the artificial intelligence method in perme

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Publication Date
Wed Jan 28 2026
Journal Name
Journal Of Baghdad College Of Dentistry
Effect of surface treatments and thermocycling on shear bond strength of various artificial teeth with different denture base materials
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Background: Separation and deboning of artificial teeth from denture bases present a major clinical and labortory problem which affect both the patient and the dentist. The optimal bond strength of artificial teeth with denture base reinforced with nanofillers and flexible denture bases and the effect of thermo cycling should be evaluated. This study was conducted to evaluate and compare the shear bond strength of artificial teeth (acrylic and porcelain) with denture bases reinforced by 5% Zirconium oxide nanofillers and flexible bases under the effect of different surface treatments and thermo cycling and comparing the results with conventional water bath cured denture bases. Material and methods: Two types of artificial teeth; acrylic and

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