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American Journal of Business and Operations Research | 2021

The Effect of Big Five Factors of Personality on Compulsive Buying: The Mediating Role of Consumer Negative Emotions

     This study has examined the direct effect of Big Five Factors of personality (BFF) which include (Neuroticism, Agreeableness, Extraversion, Conscientiousness, and Openness to Experience) on Compulsive Buying (CB). Besides, examining the mediating effect of Consumer Negative Emotions (CNE) in the relationship between Big Five Factors of personality (BFF) and Compulsive Buying (CB). The questionnaire for the study was adapted from earlier established scales and measures which were based on five points Likert Scale. The study was concentrated on shopping malls’ customers in North Delta (Egypt). The study used a sample size of 384 and data was collected randomly using systematic random sampling. 314 questionnaires were valid for statistical analysis and free of missing data were retrieved with a response rate of 81.7%. Smart PLS-SEM3 software was used for data analysis. The results showed that there is a significant positive effect of Neuroticism on compulsive buying. While the results indicated that Extraversion has a significant negative effect on compulsive buying. Also, the results found that Conscientiousness has a significant negative effect on compulsive buying. While Agreeableness and Openness to Experience hadn’t had any effect on compulsive buying. As for the mediating effect of Consumer Negative Emotions, the results mentioned that Consumer Negative Emotions has a partial mediation in the relationship between Neuroticism, Extraversion, and Conscientiousness, and Compulsive Buying. While Consumer Negative Emotions fully mediated the relationship between Openness to Experience and Compulsive Buying. But there was no mediation for Consumer Negative Emotions in the relationship between Agreeableness and Compulsive Buying.

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Mohamed Shemeis mail -
Talaat Asad mail -
Samaa Attia mail
link https://doi.org/10.54216/AJBOR.020102

Volume & Issue

Vol. Volume 2 / Iss. Issue 1

Details open_in_new
American Journal of Business and Operations Research | 2021

Classification Models for Bank Marketing Campaign: Towards Smart Bank Marketing

In this paper, we have proposed two models of marketing classification which are Support Vector Machine (SVM) and Linear regression, these two models are the most popular and useful models of classification. In this paper, we represent how these two models are used for a case study of a bank marketing campaign, the dataset is related to a bank marketing campaign, and for Applying the machine learning models of classification, the RapidMiner software was used.

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Ahmad Freij mail
link https://doi.org/10.54216/AJBOR.050102

Volume & Issue

Vol. Volume 5 / Iss. Issue 1

Details open_in_new
Fusion: Practice and Applications | 2021

An Improved Equilibrium Optimizer Algorithm for Tackling Global Optimization Problems

This paper introduces a new, metaheuristic optimization algorithm, named an Improved Metaheuristic Equilibrium Optimizer (IMEO). The algorithm Equilibrium Optimizer (EO), is inspired by its method of estimating both equilibrium and dynamics, based on mass balance models. Studying the EO closely, we find that EO does not have the potential to get closer to the optimal global solution when it solves certain problems. To improve EO efficiency, this paper suggests using an improvement, called an elite opposition learning-based, that increases the speed and accuracy of EO convergence, and helps the algorithm to get a better solution. Falling into local optima is a big problem, EO suffers from the fact that when we look deeply at the standard EO mathematical formula, we found that the algorithm is trying to get out of the local optima, but sometimes it can't, so we're introducing a new mathematical formula based on using cosine trigonometric function. To validate the proposed algorithm efficiency, The IMEO algorithm is evaluated on 23 benchmarks and compared with other common naturalistic heuristic algorithms. The statistical analysis shows that the results of IMEO achieve better performance compared to the standard EO and several well-known algorithms on several benchmark issues.

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Samia Mandour mail -
IBRAHIM EL-HENAWY mail -
Kareem Ahmed mail
link https://doi.org/10.54216/FPA.030101

Volume & Issue

Vol. Volume 3 / Iss. Issue 1

Details open_in_new
Fusion: Practice and Applications | 2021

Ultrasound Medical Images Classification Based on Deep Learning Algorithms: A Review

With the development of technology and smart devices in the medical field, the computer system has become an essential part of this development to learn devices in the medical field. One of the learning methods is deep learning (DL), which is a branch of machine learning (ML). The deep learning approach has been used in this field because it is one of the modern methods of obtaining accurate results through its algorithms, and among these algorithms that are used in this field are convolutional neural networks (CNN) and recurrent neural networks (RNN). In this paper we reviewed what have researchers have done in their researches to solve fetal problems, then summarize and carefully discuss the applications in different tasks identified for segmentation and classification of ultrasound images. Finally, this study discussed the potential challenges and directions for applying deep learning in ultrasound image analysis.  

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Fairoz Q. Kareem mail -
Adnan Mohsin Abdulazeez mail
link https://doi.org/10.54216/FPA.030102

Volume & Issue

Vol. Volume 3 / Iss. Issue 1

Details open_in_new
Fusion: Practice and Applications | 2021

Electrocardiogram Classification Based on Deep Convolutional Neural Networks: A Review

Due to many new medical uses, the value of ECG classification is very demanding. There are some Machine Learning (ML) algorithms currently available that can be used for ECG data processing and classification. The key limitations of these ML studies, however, are the use of heuristic hand-crafted or engineered characteristics of shallow learning architectures. The difficulty lies in the probability of not having the most suitable functionality that will provide this ECG problem with good classification accuracy. One choice suggested is to use deep learning algorithms in which the first layer of CNN acts as a feature. This paper summarizes some of the key approaches of ECG classification in machine learning, assessing them in terms of the characteristics they use, the precision of classification important physiological keys ECG biomarkers derived from machine learning techniques, and statistical modeling and supported simulation.

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Rozin Majeed Abdullah mail -
Adnan Mohsin Abdulazeez mail
link https://doi.org/10.54216/FPA.030103

Volume & Issue

Vol. Volume 3 / Iss. Issue 1

Details open_in_new
Journal of Cybersecurity and Information Management | 2021

A Study of Internet of Medical Things (IoMT) Used in Pandemic Covid-19 For Healthcare Monitoring Services

 Before Internet of things, visit or meet a doctor is based on the appointments, by tele and text communication and also interaction with patient and doctors are limited. IoMT enables medical devices remote monitoring, unleash the possibility for patients to keep safe and healthy, also made easy for physicians to deliver excellent care for patients. The capability of IoT or IoMT in infectious disease control a network of interconnected systems and Artificial intelligence, Data analytics and using omnipresent connectivity in all these networks based upon real time data can help to provide an early warning system to restraint the spread of Pandemic like situation (Covid-19 corona virus, Ebola virus, Hanta Virus etc.) and it also help in healthcare monitoring and treatment services.

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Mandeep Singh Heer mail -
Harikrishna Chavhan mail -
Vikas Chumber mail -
Vikrant Sharma mail
link https://doi.org/10.54216/JCIM.050201

Volume & Issue

Vol. Volume 5 / Iss. Issue 2 : Special Issue CITCOVID-19

Details open_in_new
Journal of Cybersecurity and Information Management | 2021

Analysis of Various Credit Card Fraud Detection Techniques

Data mining is a technique that is applied to mine valuable information from the rough data. A prediction analysis is an approach that has the potential for forecasting future possibilities based on the recent data. The CCFD is the challenge of prediction in which fraudulent transactions are predicted based on certain rules. There are several stages included in the detection of fraud in credit cards. Various classification algorithms are reviewed with respect to the performance analysis in order to detect fraud in the credit card. The performance is measured with regard to precision.

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Heena Kochhar1
link https://doi.org/10.54216/JCIM.050202

Volume & Issue

Vol. Volume 5 / Iss. Issue 2 : Special Issue CITCOVID-19

Details open_in_new
Journal of Cybersecurity and Information Management | 2021

A Novel Artificial Face Mask based Nanofibers with Special Intelligent Engineered Nanocomposite Against Covid-19

We introduce our idea about a new face mask against Covid-19. Herein our novel face mask is a polymeric matrix of nanofibers. These nanofibers are decorated with special engineered nanocomposite. The later possesses antiviral, antimicrobial. Awell-established IR temperature biosensor will be implanted in the face mask and connected to the mobile phone using App (Seek thermal) to allow temperature monitoring. Artificial Intelligence can play a vital role in the fight against COVID-19. AI is being successfully used in the identification of disease clusters, monitoring of cases, prediction of the future outbreaks, mortality risk, diagnosis of COVID-19, disease management by resource allocation, facilitating training, record maintenance and pattern recognition for studying the disease trend. Therefore, AI is used as a type of alarm which be connected through Global Position System (GPS) to a central networking system to monitor the crowded areas of probable infections. In this case, the hospital in this neighborhood will be charged to let a mobile unit of assessment travel quickly to the infected people areas.

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Ahmed A. Elngar mail -
S.I. El-Dek mail
link https://doi.org/10.54216/JCIM.050203

Volume & Issue

Vol. Volume 5 / Iss. Issue 2 : Special Issue CITCOVID-19

Details open_in_new