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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
Tue Apr 16 2019
Journal Name
Proceedings Of The 2019 5th International Conference On Computer And Technology Applications
Four Char DNA Encoding for Anomaly Intrusion Detection System
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Recent research has shown that a Deoxyribonucleic Acid (DNA) has ability to be used to discover diseases in human body as its function can be used for an intrusion-detection system (IDS) to detect attacks against computer system and networks traffics. Three main factor influenced the accuracy of IDS based on DNA sequence, which is DNA encoding method, STR keys and classification method to classify the correctness of proposed method. The pioneer idea on attempt a DNA sequence for intrusion detection system is using a normal signature sequence with alignment threshold value, later used DNA encoding based cryptography, however the detection rate result is very low. Since the network traffic consists of 41 attributes, therefore we proposed the

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Publication Date
Sat Jan 01 2022
Journal Name
Journal Of Cybersecurity And Information Management
Machine Learning-based Information Security Model for Botnet Detection
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Botnet detection develops a challenging problem in numerous fields such as order, cybersecurity, law, finance, healthcare, and so on. The botnet signifies the group of co-operated Internet connected devices controlled by cyber criminals for starting co-ordinated attacks and applying various malicious events. While the botnet is seamlessly dynamic with developing counter-measures projected by both network and host-based detection techniques, the convention techniques are failed to attain sufficient safety to botnet threats. Thus, machine learning approaches are established for detecting and classifying botnets for cybersecurity. This article presents a novel dragonfly algorithm with multi-class support vector machines enabled botnet

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Publication Date
Fri Nov 05 2021
Journal Name
Semiconductor Science And Information Devices
Cladding Modified Fiber Bragg Grating for Copper Ions Detection
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This paper reports a fiber Bragg grating (FBG) as a biosensor. The FBGs were etched using a chemical agent,namely,hydrofluoric acid (HF). This implies the removal of some part of the cladding layer. Consequently, the evanescent field propagating out of the core will be closer to the environment and become more sensitive to the change in the surrounding. The proposed FBG sensor was utilized to detect toxic heavy metal ions aqueous medium namely, copper ions (Cu2+). Two FBG sensors were etched with 20 and 40 μm diameters and fabricated. The sensors were studied towards Cu2+ with different concentrations using wavelength shift as a result of the interaction between the evanescent field and copper ions. The FBG sensors showed

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Publication Date
Thu Dec 01 2022
Journal Name
Iraqi Journal Of Science
PLAGIARISM DETECTION SYSTEM IN SCIENTIFIC PUBLICATION USING LSTM NETWORKS
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Publication Date
Mon Oct 01 2012
Journal Name
International Journal Of Recent Scientific Research
DETECTION OF LTH, FSH AND LH HORMONE LEVEL IN PREGNANT WOMEN INFECTED WITH TOXOPLASMA GONDII
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Infection with the protozoan parasite Toxoplasma gondii is widely prevalent in humans and animals. Infection with Toxoplasma may associate with miscarriage in many pregnant women due to infection. In this study, the level of lutetropic hormone (LTH), folliclestimulating hormone (FSH) and luteinizing hormone (LH) was measured in pregnant women suffering from toxoplasmosis using mini-VIDAS®technique. Results showed that pregnant women have high concentration of both LTH and FSH hormone(10.80 ± 6.53) ng/ml and (9.51 ± 2.40) μIU/ml respectively, while the concentration of LH hormone was lower than normal(4.49 ± 0.56) μIU/ml. Such finding is to suggest that infection with T. gondii is interfering with these hormones in pregnant women.

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Publication Date
Tue Apr 28 2020
Journal Name
Iraqi Journal Of Veterinary Sciences
Detection and pathogenicity of Listeria monocytogenes in common carp (Cyprinus carpio) fish in Baghdad, Iraq
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Publication Date
Thu Jun 29 2023
Journal Name
Journal Of University Of Babylon For Pure And Applied Sciences
Genetic Detection of IMP-1 Gene and its Relationship with Biofilm Formation in Klebsiella pneumonia
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Background: Klebsiella pneumoniae were considered as normal flora of skin, and intestine. It can cause damage to human lungs; the danger of this bacterium is related to exposure to the hospital surroundings. materials and methods: the detection of Klebsiella pneumoniae on morphological and biochemical tests and then assured with VITEK 2 system. Resistance to antibiotics was determined by Kirby-Baeur method. And genotyping of IMP-1 in isolates was done by PCR technique, then biofilm formation was identified by Micro titer plate method. Results: The present study included a collecting of 50 specimens from different clinical specimens, (blood 40%, urine 30%, sputum 20%, wound infection 10%); 10 isolates were identified as K

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Publication Date
Thu Apr 18 2019
Journal Name
Al-kindy College Medical Journal
Basal cell markers:34BE12 and p63, improving detection of basal cells in atypical prostatic lesions
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Background: The diagnosis of prostatic pathology may be of challenging , as some  difficult and suspected, atypical  cases may lack basal cell layer by routine H&E sections . Antibodies against 34BE12(HMW-CK) and p63 aid the diagnosis of such cases , to distinguish benign from  malignant prostatic lesions.

Objective: to identify basal cells in atypical prostatic lesions ,and distinguish benign from malignant prostatic lesions.

Type of the study:  A retro-spective  study.

Methods:  115cases of  paraffin embedded prostatic tissue blocks ,diagnosed as : 76 cases were benign prostatic hy

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Publication Date
Sat Dec 03 2011
Journal Name
Ibn Al-haitham Journal For Pure And Applied Science
Detection of shoreline change in AL-Thirthar Lake using remotely sensed imagery and topography map
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Publication Date
Sun Mar 02 2025
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences (
Detection of Some Virulence Factors, Antibiotics Resistant and esp Gene Expression in Enterococcus faecalis bacteria
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