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Credit Card Fraud Detection Challenges and Solutions: A Review
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     Credit card fraud has become an increasing problem due to the growing reliance on electronic payment systems and technological advances that have improved fraud techniques. Numerous financial institutions are looking for the best ways to leverage technological advancements to provide better services to their end users, and researchers used various protection methods to provide security and privacy for credit cards. Therefore, it is necessary to identify the challenges and the proposed solutions to address them.  This review provides an overview of the most recent research on the detection of fraudulent credit card transactions to protect those transactions from tampering or improper use, which includes imbalance classes, concept drift, and verification latency problems using machine learning and deep learning. It also provides valuable information for academic and industrial researchers and opens new avenues for research aimed at developing robust fraud detection systems.

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Publication Date
Wed Nov 07 2018
Journal Name
Iraqi National Journal Of Nursing Specialties
Early detection of first degree relatives to type-II diabetes mellitus
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Objective(s): The study aims to assess the early detection of early detection of first degree relatives to type-II
diabetes mellitus throughout the diagnostic tests of Glycated Hemoglobin A1C. (HgbA1C), Oral Glucose Tolerance
Test (OGTT) and to find out the relationship between demographic data and early detection of first degree
relatives to type-II diabetes mellitus.
Methodology: A purposive "non-probability" sample of (200) subjects first degree relatives to type-II diabetes
mellitus was selected from National Center for Diabetes Mellitus/Al-Mustansria University and Specialist Center
for Diabetes Mellitus and Endocrine Diseases/Al-kindy. These related persons have presented the age of (40-70)
years old. A questio

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Publication Date
Mon Aug 17 2020
Journal Name
Current Pharmaceutical Analysis
Hydrophilic Interaction Chromatography Analysis of Esculin in Ointments with UV Detection
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Background:

Esculin (ESCN) is used in the pharmaceutical industry with intravenous effect, stimulant and anti-inflammatory capillaries, like vitamin P. It is a significant component of many anti-inflammatory remedies such as esqusan, esflazid and anavenol [14]. It is also found in numerous other remedies available in the market such as proctosone, anustat, and ariproct.

Objective:

To determine experimental conditions, to elucidate retention behavior of esculin in HILIC mode. Moreover, to suggest new ways to separate and determinate esculin in ointments.

Methods:

Two hydrophilic c

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Publication Date
Sun May 01 2022
Journal Name
Journal Of Engineering
Performance Analysis of different Machine Learning Models for Intrusion Detection Systems
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In recent years, the world witnessed a rapid growth in attacks on the internet which resulted in deficiencies in networks performances. The growth was in both quantity and versatility of the attacks. To cope with this, new detection techniques are required especially the ones that use Artificial Intelligence techniques such as machine learning based intrusion detection and prevention systems. Many machine learning models are used to deal with intrusion detection and each has its own pros and cons and this is where this paper falls in, performance analysis of different Machine Learning Models for Intrusion Detection Systems based on supervised machine learning algorithms. Using Python Scikit-Learn library KNN, Support Ve

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Publication Date
Tue Sep 23 2025
Journal Name
Journal Of Plant Protection Research
Smart sprayer for weed control using an object detection algorithm (yolov5)
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Spraying pesticides is one of the most common procedures that is conducted to control pests. However, excessive use of these chemicals inversely affects the surrounding environments including the soil, plants, animals, and the operator itself. Therefore, researchers have been encouraged to...

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Publication Date
Tue Aug 01 2023
Journal Name
Baghdad Science Journal
An Effective Hybrid Deep Neural Network for Arabic Fake News Detection
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Recently, the phenomenon of the spread of fake news or misinformation in most fields has taken on a wide resonance in societies. Combating this phenomenon and detecting misleading information manually is rather boring, takes a long time, and impractical. It is therefore necessary to rely on the fields of artificial intelligence to solve this problem. As such, this study aims to use deep learning techniques to detect Arabic fake news based on Arabic dataset called the AraNews dataset. This dataset contains news articles covering multiple fields such as politics, economy, culture, sports and others. A Hybrid Deep Neural Network has been proposed to improve accuracy. This network focuses on the properties of both the Text-Convolution Neural

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Publication Date
Sat Mar 01 2025
Journal Name
Radiology Case Reports
Intradural extra-medullary spinal cord tumor after dorso-lumbar spine fixation following 12th dorsal vertebra burst fracture: A case report with literature review
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Publication Date
Thu Jan 01 2026
Journal Name
Egyptian Journal Of Aquatic Biology And Fisheries
Study of the Effect of Redbelly Tilapia (Coptodon zillii (Gervais, 1848)) (Cichliformes: Cichlidae) on the Sustainability of the Iraqi Aquatic Environment: A Review
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This research reviews studies that identify the habitats of the redbelly tilapia, Coptodon zillii, in Iraq, the environmental conditions favorable to this species distribution and proliferation, as well as its economic and social significance as a food source. Additonally, the study examines its effects on biodiversity through competition with native fish species for resources, as well as its role as reservoirs of pathogens, its adverse effect on human health due to the tendency to retain oil crude inside the tissues, and its impact on environmental and water quality by increasing water turbidity. Finally, the review exhibits recommendations for strategies to mitigate its detrimental effects on biodiversity as well as environment.

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Publication Date
Mon Jan 01 2018
Journal Name
Biochemical Cellular Archive
Immunological and molecular detection of herpes simplex virus type 1 and 2 in patients clinically diagnosed with parkinson’s disease and multiple sclerosis
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To determine the relationship between herpes simplex virus 1, 2 and neurological disorders, sixty samples from patients with neurological diseases were collected (40 patients with Multiple sclerosis and 20 patients with Parkinson’s disease) all of whom attended both the Neurological science Hospital as well as the Neuropathology consultation Department in Baghdad Hospital In Iraq. The samples were collected in the time frame between November 2017 and April 2018. The ages of the patients that were investigated were between (17-76) years and compared to a control group consisting of 25 samples collected from apparently healthy individuals. All the studied groups were subjected to the measurement of anti-HSV 1, 2 IgG antibodies by the means

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Publication Date
Sun Dec 01 2013
Journal Name
Baghdad Science Journal
Detection of Anti-Helicopacter pylori IgG Antibody, Anti-GAD antibody, Anti-Beta islets cell in a sample of serum with type-2 Diabetes mellitus patients
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We have investigated twenty five patients with type-2 diabetes mellitus aged (35-60) years and fifteen healthy persons as control group to detect Anti-Helicobacter pylori IgG antibody. All studied groups were carried out to measure fasting blood sugar, anti- Glutamic acid decarboxylase (GAD), anti-? islets cells antibody by IFAT, Anti-H. pylori IgG antibody by ELISA technique. There was significant elevation in the concentration of fasting blood sugar than in control group (P < 0.05), the patients had negative results for anti-GAD antibody and anti- ? islets cells antibody, there were significant differences (P < 0.05) of anti-H. pylori IgG antibody in 28 % of patients had type-2 diabetes than control group. This lead to suggestion that typ

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Publication Date
Sun Jun 01 2014
Journal Name
Baghdad Science Journal
Using the molecular methods in detection of antibiotics resistance genes in bacteria of Typhoi (Salmonella typhi): Batool A. Shihab|Sahira Y. Rwayah|Ashna J. Faik
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This study was carried out for direct detection of typhi and some of its multidrug resistance genes(tem,capt,gyrA&sul2)which encode for resistance to (Ampicillin, Chloramphenicol,Ciprofioxacin,Co-trimoxazole)by using Polymerase Chain Reaction technique .(71)blood samples for people suffering from typhoid fever symptoms depending on the clinical examination and (25)for control were collected. The results investigation for flic gene which encode for flagellin protein indicated that only (19)with percentage of (26,76%)gave appositive results while all control had a negative ones. Investigation for antibiotic resistance drug in samples which show positive results for flic gene showed that there is a multidrug for all antibiotics with (94.7

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