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New Weighted Synthetic Oversampling Method for Improving Credit Card Fraud Detection
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The use of credit cards for online purchases has significantly increased in recent years, but it has also led to an increase in fraudulent activities that cost businesses and consumers billions of dollars annually. Detecting fraudulent transactions is crucial for protecting customers and maintaining the financial system's integrity. However, the number of fraudulent transactions is less than legitimate transactions, which can result in a data imbalance that affects classification performance and bias in the model evaluation results. This paper focuses on processing imbalanced data by proposing a new weighted oversampling method, wADASMO, to generate minor-class data (i.e., fraudulent transactions). The proposed method is based on the Synthetic Minority Over-sampling Technique (SMOTE), Adaptive Synthetic Sampling (ADASYN), and weight adjustment to identify specific minority areas while retaining data generalization and accurately identifying patterns associated with fraudulent transactions. Experimental results obtained from two datasets with Autoencoder (AE), Convolutional Neural Network (CNN), and Long Short-Term Memory (LSTM) learning models show that wADASMO surpasses other oversampling methods in three evaluation metrics: accuracy at 95.6%, 98.8%, and 99.2%; detection rate at 90.4%, 93.38%, and 93.38%; and area under the curve (AUC) at 93%, 96%, and 96.3% for AE, CNN, and LSTM models, respectively.

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Publication Date
Fri Sep 05 2014
Journal Name
Engineering And Technology Journal
New Method to Increase the Ability of the Water for Dissolving Total Salts in Soil by Using the Magnetism
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Publication Date
Fri Jul 02 1999
Journal Name
Iraqi Journal Of Science
A new proposal method for sampling and explosion of the phosphatic rocks in the Akkashat Mine, Western desert, Iraq
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Publication Date
Wed Jan 01 2020
Journal Name
Journal Of Southwest Jiaotong University
Image Segmentation for Skin Detection
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Human skin detection, which usually performed before image processing, is the method of discovering skin-colored pixels and regions that may be of human faces or limbs in videos or photos. Many computer vision approaches have been developed for skin detection. A skin detector usually transforms a given pixel into a suitable color space and then uses a skin classifier to mark the pixel as a skin or a non-skin pixel. A skin classifier explains the decision boundary of the class of a skin color in the color space based on skin-colored pixels. The purpose of this research is to build a skin detection system that will distinguish between skin and non-skin pixels in colored still pictures. This performed by introducing a metric that measu

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Publication Date
Sat Sep 30 2017
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Removal of Dyes from Synthetic Wastewater by Agriculturalwaste
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Adsorption is one of the most important technologies for the treatment of polluted water from dyes. Theaim of this study is to use a low-cost adsorbent for this purpose. A novel and economical adsorbent was used to remove methyl violet dye (MV) from aqueous solutions. This adsorbent was prepared from bean peel, which is an agricultural waste. Batch adsorption experiments were conducted to study the ability of the bean peel adsorbent (BPA) to remove the methyl violet (MV) dye. The effects of different variables, such as weight of the adsorbent, pH of the MV solution, initial concentration of MV, contact time and temperature, on the adsorption behaviour were studied. It was found experimentally that the time required to achieve equilibrium

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Publication Date
Sat Oct 01 2022
Journal Name
Al–bahith Al–a'alami
Trends of journalists and consumers about the phenomenon of food fraud
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Food comes after air and water in terms of importance in the survival of human beings, In addition, it is the support and strength of health and support, if lost or destroyed man would die or get sick and become a heavy burden on himself and his society. Food, like other sources of life, is subject to various risks and corruption comes from countless sources. Among these dangers is the result of spontaneousness, lack of knowledge or compulsion due to the interaction of variables beyond the will of the producer and the consumer, such as pollution of water, air and environment and their reflection on food consumed by people. However, we can’t deny that some reasons of corruption are intentional and resulting from a planning in advance in

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Publication Date
Fri Jan 01 2021
Journal Name
Computers, Materials & Continua
A New Hybrid Feature Selection Method Using T-test and Fitness Function
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Publication Date
Thu Apr 18 2019
Journal Name
Al-kindy College Medical Journal
Demonstration of the value of diffusion weighted MR imaging for differentiation of benign from malignant breast lesions
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Background: Radiologic evaluation of breast lesions is being achieved through several imaging modalities. Mammography has an established role in breast cancer screening and diagnosis. Still however, it shows some limitations particulary in dense breast.

Methods : Magnetic resonance imaging is an attractive tool for the diagnosis of breast tumors1 and the use of magnetic resonance imaging of the breast is rapidly increasing as this technique becomes more widely available.1 As an adjunct to mammography and ultrasound, MRI can be a valuable addition to the work-up of a breast abnormality. MRI has the advantages of providing a three-dimensional view of the breast, performing wit

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Publication Date
Tue Jun 20 2023
Journal Name
Baghdad Science Journal
Numerical Solutions for the Nonlinear PDEs of Fractional Order by Using a New Double Integral Transform with Variational Iteration Method
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This paper considers a new Double Integral transform called Double Sumudu-Elzaki transform DSET. The combining of the DSET with a semi-analytical method, namely the variational iteration method DSETVIM, to arrive numerical solution of nonlinear PDEs of Fractional Order derivatives. The proposed dual method property decreases the number of calculations required, so combining these two methods leads to calculating the solution's speed. The suggested technique is tested on four problems. The results demonstrated that solving these types of equations using the DSETVIM was more advantageous and efficient

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Publication Date
Sun Jan 01 2017
Journal Name
Pertanika Journal Of Science & Technology
Modified Kohonen network algorithm for selection of the initial centres of Gustafson-Kessel algorithm in credit scoring
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Credit risk assessment has become an important topic in financial risk administration. Fuzzy clustering analysis has been applied in credit scoring. Gustafson-Kessel (GK) algorithm has been utilised to cluster creditworthy customers as against non-creditworthy ones. A good clustering analysis implemented by good Initial Centres of clusters should be selected. To overcome this problem of Gustafson-Kessel (GK) algorithm, we proposed a modified version of Kohonen Network (KN) algorithm to select the initial centres. Utilising similar degree between points to get similarity density, and then by means of maximum density points selecting; the modified Kohonen Network method generate clustering initial centres to get more reasonable clustering res

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Scopus (9)
Scopus
Publication Date
Mon Apr 03 2023
Journal Name
Journal Of Educational And Psychological Researches
Fitting Scoring Rubrics for Electronic Portfolio to Partial Credit Model According to the Number of Assumed Dimensions
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Abstract

 

The current research aims to reveal the extent to which all scoring rubrics data for the electronic work file conform to the partial estimation model according to the number of assumed dimensions. The study sample consisted of (356) female students. The study concluded that the list with the one-dimensional assumption is more appropriate than the multi-dimensional assumption, The current research recommends preparing unified correction rules for the different methods of performance evaluation in the basic courses. It also suggests the importance of conducting studies aimed at examining the appropriateness of different evaluation methods for models of response theory to the

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