Article Per Year (5 Year)
p-Index From 2021 - 2026
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This Author published in this journals
All Journal Emerging Science Journal
Mohanaad Shakir, Mohanaad
Unknown Affiliation
Environmental Science

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Gender Differences in Academic Staff Performance: An Advanced Analysis Using PLS-SEM in Higher Education Taufiq Hail, Ghilan Al-Madhagy; Yusof, Shafiz Affendi Mohd; Shakir, Mohanaad; Al Farsi, Maryam Juma; Al-Shamsi, Ibrahim R.; Sarea, Adel
Emerging Science Journal Vol 8 (2024): Special Issue "Current Issues, Trends, and New Ideas in Education"
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/ESJ-2024-SIED1-09

Abstract

This study aims to comprehensively explore the intricate dynamics among positive and negative emotions, self-efficacy, and task performance within the unique context of the Covid-19 pandemic in Bahrain, specifically placing emphasis on potential gender-related distinctions within the proposed relationships. The ongoing pandemic accentuates the need to investigate the interplay between emotional states, self-efficacy beliefs, and task performance in academic and teaching domains, especially considering potential gender variations within the framework of a society promoting gender equality. Employing a quantitative survey instrument and rigorous statistical techniques, the study validates its proposed model through indicators such as the coefficient of determination (R²) and predictive relevance (Q²). The diverse sample comprises academic and teaching staff of both genders from Bahrain. Advanced statistical methodologies, including Measurement Invariance (MICOM) and Multigroup Analysis (MGA) facilitated by SmartPLS PLS-SEM, provide deeper insights into gender disparities. Significantly contributing to existing knowledge, this paper elucidates the complex relationships among emotions, self-efficacy, and task performance amid a crisis, with a distinctive focus on meticulously investigating gender differences. The study underscores the consistent positive impact of positive emotions on task performance across genders in Bahrain. Recommendations advocate for prioritizing support for academic and teaching staff during crises, emphasizing the positive impact on academic outcomes. Future research should explore demographic intricacies and potential mediating or moderating factors, deepening the comprehension of these complex dynamics. Highlighting the cascading impact of prioritizing the well-being and morale of academic and teaching staff, the study envisions a positive transformation resonating across various facets of society, extending beyond the confines of academia. Doi: 10.28991/ESJ-2024-SIED1-09 Full Text: PDF
Enhancing User Differentiation in the Electronic Personal Synthesis Behavior (EPSBV01) Algorithm by Adopting the Time Series Analysis Shakir, Mohanaad
Emerging Science Journal Vol 9, No 1 (2025): February
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/ESJ-2025-09-01-014

Abstract

The progress of contemporary technology has rendered information systems essential in our everyday existence, underscoring the crucial necessity to safeguard information security and privacy. In password authentication, the Electronic Personal Synthesis Behaviour (EPSB) heightens the accuracy of authorizing an authenticated user based on three parameters: EPSBERROR, EPSBTime, and EPSBStyle. EPSBTime suffers from a lack of indicators associated with the legitimate user; containing only six indicators, there arose the need to adopt methods for generating additional reliable indicators by analyzing old indicators and generating new indicators related to the legitimate user. Therefore, this study aims to test the impact of adopting time series analysis in the EPSB time indicator on improving the differentiation of user legitimacy in the case of password-stolen attacks. The research methodology, which involves analyzing and evaluating existing authentication methods in web-based systems, is a key component of this study. The study is divided into stages, with the first phase focusing on enhancing the existing EPSB model, the second phase implementing EPSBalgorithmV01, and the final stage ensuring validation. Thus, two preliminary experiments were conducted with 22 users from January 13 to February 1, 2024. The final phase involved comparing EPSBV01's accuracy in determining unauthorized users before and after using the ARIMA method. Thus, the EPSBV01algorithm successfully identified 17 unauthorized users during a stolen password attack simulation, outperforming the normal EPSB by 22.73%. Doi: 10.28991/ESJ-2025-09-01-014 Full Text: PDF
Co-Authors Al Farsi, Maryam Juma Al-Shamsi, Ibrahim R. Sarea, Adel Shafiz Affendi Mohd Yusof, Shafiz Affendi Mohd Taufiq Hail, Ghilan Al-Madhagy