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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
Fri May 17 2019
Journal Name
Lecture Notes In Networks And Systems
Features Selection for Intrusion Detection System Based on DNA Encoding
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Intrusion detection systems detect attacks inside computers and networks, where the detection of the attacks must be in fast time and high rate. Various methods proposed achieved high detection rate, this was done either by improving the algorithm or hybridizing with another algorithm. However, they are suffering from the time, especially after the improvement of the algorithm and dealing with large traffic data. On the other hand, past researches have been successfully applied to the DNA sequences detection approaches for intrusion detection system; the achieved detection rate results were very low, on other hand, the processing time was fast. Also, feature selection used to reduce the computation and complexity lead to speed up the system

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Scopus
Publication Date
Sat Apr 05 2025
Journal Name
2025 Ieee 4th International Conference On Computing And Machine Intelligence (icmi)
From Pixels to Diagnosis: AI-Powered CNN for Pneumonia Detection
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Publication Date
Mon Jan 01 2024
Journal Name
Iraqi Journal Of Hematology
Detection of active human cytomegalovirus in patients with multiple myeloma
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Abstract:<sec><title>BACKGROUND:

Human cytomegalovirus (HCMV) infection is ubiquitous and successfully reactivated in patients with immune dysfunction as in patient with multiple myeloma (MM), causing a wide range of life-threatening diseases. Early detection of HCMV and significant advances in MM management has amended patient outcomes and prolonged survival rates.

OBJECTIVES:

The aim of the study was to estimate the frequency of active HCMV in MM patients.

MATERIALS AND METHODS:

This is a case–control study involved 50 MM patients attending Hematology Center, Bag

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Publication Date
Fri Feb 08 2019
Journal Name
Iraqi Journal Of Laser
Photoacoustic Imaging for Tumor Detection: An in vitro Simulation Study
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Photoacoustic is a unique imaging method that combines the absorption contrast of light or radio frequency waves with ultrasound resolution. When the deposition of this energy is sufficiently short, a thermo-elastic expansion takes place whereby acoustic waves are generated. These waves can be recorded and stored to construct an image. This work presents experimental procedure of laser photoacoustic two dimensional imaging to detect tumor embedded within normal tissue. The experimental work is accomplished using phantoms that are sandwiched from fish heart or blood sac (simulating a tumor) 1-14mm mean diameter embedded within chicken breast to simulate a real tissue. Nd: YAG laser of 1.064μm and 532nm wavelengths, 10ns pulse duration, 4

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Publication Date
Sun Feb 28 2021
Journal Name
International Journal Of Intelligent Engineering And Systems
Intelligent System for Parasitized Malaria Infection Detection Using Local Descriptors
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Malaria is a curative disease, with therapeutics available for patients, such as drugs that can prevent future malaria infections in countries vulnerable to malaria. Though, there is no effective malaria vaccine until now, although it is an interesting research area in medicine. Local descriptors of blood smear image are exploited in this paper to solve parasitized malaria infection detection problem. Swarm intelligence is used to separate the red blood cells from the background of the blood slide image in adaptive manner. After that, the effective corner points are detected and localized using Harris corner detection method. Two types of local descriptors are generated from the local regions of the effective corners which are Gabor based f

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Publication Date
Sat Dec 01 2012
Journal Name
Journal Of Engineering
Development an Anomaly Network Intrusion Detection System Using Neural Network
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Most intrusion detection systems are signature based that work similar to anti-virus but they are unable to detect the zero-day attacks. The importance of the anomaly based IDS has raised because of its ability to deal with the unknown attacks. However smart attacks are appeared to compromise the detection ability of the anomaly based IDS. By considering these weak points the proposed
system is developed to overcome them. The proposed system is a development to the well-known payload anomaly detector (PAYL). By
combining two stages with the PAYL detector, it gives good detection ability and acceptable ratio of false positive. The proposed system improve the models recognition ability in the PAYL detector, for a filtered unencrypt

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Publication Date
Fri Nov 15 2024
Journal Name
Scientific Reports
Ag@WO3 core–shell nanocomposite for wide range photo detection
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This study successfully synthesized high-performance photodetectors based on Ag-WO3 core–shell heterostructures using a simple and economical two-step pulsed laser ablation in water method and has investigated the electrical characteristics of the Ag@WO3 nanocomposite heterojunction. The Hall effect tests indicate that the synthesized Ag@WO3 exhibits n-type conduction with a Hall mobility of 1.25 × 103 cm2V-1S-1. Dark current–voltage properties indicated that the created heterojunctions displayed rectification capabilities, with the highest rectification factor of around 1.71 seen at a 5 V bias. A photodetector’s responsivity reveals the existence of two response peaks, which are situated in the ultraviolet and visible region. The ph

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Publication Date
Thu Dec 01 2022
Journal Name
Neuroscience Informatics
Epileptic EEG activity detection for children using entropy-based biomarkers
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Publication Date
Fri Sep 16 2022
Journal Name
Asian Journal Of Water, Environment And Pollution
Comparative of Green-Synthesis of Bimetallic Nanoparticles Iron/Nickel (Fe/Ni) and Supported on Zeolite 5A: Heterogeneous Fenton-like For Dye Removal From Aqueous Solutions
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Green synthesis of bimetallic nanoparticles of Fe/Ni (G-Fe/Ni-NPs) and zeolite-5A supported (G-Z-Fe/Ni-NPs) as heterogeneous Fenton-like oxidation for the decolourisation of reactive red 120-dye (RR120) from the aqueous medium using green tea extract as a reducing agent. Zeolite-5A from local kaolin is prepared and characterised using the hydrothermal method and is used as a supporting material for Fe/Ni-NPs. (SEM), (EDX), (AFM), (XRD), (FT-IR), (BET). Its zeta potential were used to characterise G-Fe/Ni-NPs and G-Z-Fe/Ni-NPs. The decolourisation efficiency (Ed) of the RR120-dye using a heterogeneous Fenton-like for G-Fe/Ni-NPs and G-Z-Fe/Ni-NPs is 99.8% and 99.9%, respectively, under the optimum conditions: [H2O2] = 20 and 1 mmol/L

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Publication Date
Sat Nov 13 2021
Journal Name
International Journal Of Pharmacy Practice
A comprehensive review of drivers influencing flu vaccine acceptance in the Middle East over the last six years: using Health Belief Model
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Abstract<sec> <title>Objectives

The objectives of this study were to review the literature covering the perceptions about influenza vaccines in the Middle East and to determine factors influencing the acceptance of vaccination using Health Belief Model (HBM).

Methods

A comprehensive literature search was performed utilizing PubMed and Google Scholar databases. Three keywords were used: Influenza vaccine, perceptions and Middle East. Empirical studies that dealt with people/healthcare worker (HCW) perceptio

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