Article Per Year (5 Year)
p-Index From 2021 - 2026
0.835
P-Index
This Author published in this journals
All Journal African Multidisciplinary Journal of Sciences and Artificial Intelligence Open Access DRIVERset Kwaghe International Journal of Sciences and Technology Open Access DRIVERset Kwaghe International Journal of Engineering and Information Technology
Aimufua, Gilbert I. O.
Unknown Affiliation
Aerospace Engineering Agriculture, Biological Sciences & Forestry Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Environmental Science Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Social Sciences

Published : 5 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 5 Documents
Search

 1 
Cultural Dimensions and Their Impact on Intelligent Personal Assistant Adoption in African Contexts Shinkafi, Abdullahi A.; Bassey, Steve; Chaku, Shammah Emmanuel; Aimufua, Gilbert I. O.; Joseph, Abraham D.
African Multidisciplinary Journal of Sciences and Artificial Intelligence Vol 2 No 2 (2025): African Multidisciplinary Journal of Sciences and Artificial Intelligence
Publisher : Darul Yasin Al Sys

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58578/amjsai.v2i2.6481

Abstract

This paper investigates the influence of cultural dimensions on the adoption and user satisfaction of Intelligent Personal Assistants (IPAs) across diverse African contexts. Utilizing a sequential explanatory mixed-methods approach, data were gathered from 528 participants across West, Southern, and Central African regions through surveys and in-depth interviews. Hofstede’s cultural dimensions framework comprising power distance, individualism–collectivism, uncertainty avoidance, masculinity–femininity, and long-term orientation was applied to analyze how cultural variability shapes IPA usage behaviors and satisfaction levels. The results reveal significant differences in adoption patterns and interaction preferences, particularly influenced by collectivist values, high power distance, and heightened uncertainty avoidance. These cultural dimensions were found to moderate the relationship between perceived usefulness and user satisfaction, underscoring the importance of context-aware design. The study highlights the critical need for culturally responsive design strategies in the development of IPA interfaces tailored to African markets. This research contributes to the expanding discourse on cross-cultural technology adoption and offers practical guidance for enhancing human-computer interaction in culturally heterogeneous environments.
Cultural Dimensions and Their Impact on Intelligent Personal Assistant Adoption in African Contexts Shinkafi, Abdullahi A.; Bassey, Steve; Chaku, Shammah Emmanuel; Aimufua, Gilbert I. O.; Joseph, Abraham D.
African Multidisciplinary Journal of Sciences and Artificial Intelligence Vol 2 No 2 (2025): African Multidisciplinary Journal of Sciences and Artificial Intelligence
Publisher : Darul Yasin Al Sys

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58578/amjsai.v2i2.6481

Abstract

This paper investigates the influence of cultural dimensions on the adoption and user satisfaction of Intelligent Personal Assistants (IPAs) across diverse African contexts. Utilizing a sequential explanatory mixed-methods approach, data were gathered from 528 participants across West, Southern, and Central African regions through surveys and in-depth interviews. Hofstede’s cultural dimensions framework comprising power distance, individualism–collectivism, uncertainty avoidance, masculinity–femininity, and long-term orientation was applied to analyze how cultural variability shapes IPA usage behaviors and satisfaction levels. The results reveal significant differences in adoption patterns and interaction preferences, particularly influenced by collectivist values, high power distance, and heightened uncertainty avoidance. These cultural dimensions were found to moderate the relationship between perceived usefulness and user satisfaction, underscoring the importance of context-aware design. The study highlights the critical need for culturally responsive design strategies in the development of IPA interfaces tailored to African markets. This research contributes to the expanding discourse on cross-cultural technology adoption and offers practical guidance for enhancing human-computer interaction in culturally heterogeneous environments.
A Framework for IOC-Driven Early Warning Threat Intelligence Raji, Adereti Rasak; O, Adenomon M.; Aimufua, Gilbert I. O.; Bassey, Steven I.
Kwaghe International Journal of Sciences and Technology Vol 2 No 2 (2025): Kwaghe International Journal of Sciences and Technology
Publisher : Darul Yasin Al Sys

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58578/kijst.v2i2.6458

Abstract

The increasing sophistication of cyber threats necessitates a strategic transition from reactive defenses to proactive threat mitigation. Although Indicators of Compromise (IoCs) serve as essential forensic artifacts in post-incident analysis, their potential for early threat detection remains underutilized due to issues such as data overload, insufficient contextualization, and rapid obsolescence. This study proposes the IoC-Driven Early Warning (IDEW) framework to address these limitations. The IDEW framework introduces a structured, multi-stage approach that includes multi-source data aggregation, advanced IoC validation and scoring, real-time correlation and pattern detection, and the generation of context-rich early warnings. Through systematic processing, the framework enhances the accuracy and timeliness of threat detection, allowing organizations to identify and respond to emerging cyber threats at earlier stages. Grounded in current literature and operational insights, this framework offers a conceptual foundation for integrating IoCs more effectively into proactive cybersecurity strategies.
A Framework for IOC-Driven Early Warning Threat Intelligence Raji, Adereti Rasak; O, Adenomon M.; Aimufua, Gilbert I. O.; Bassey, Steven I.
Kwaghe International Journal of Sciences and Technology Vol 2 No 2 (2025): Kwaghe International Journal of Sciences and Technology
Publisher : Darul Yasin Al Sys

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58578/kijst.v2i2.6458

Abstract

The increasing sophistication of cyber threats necessitates a strategic transition from reactive defenses to proactive threat mitigation. Although Indicators of Compromise (IoCs) serve as essential forensic artifacts in post-incident analysis, their potential for early threat detection remains underutilized due to issues such as data overload, insufficient contextualization, and rapid obsolescence. This study proposes the IoC-Driven Early Warning (IDEW) framework to address these limitations. The IDEW framework introduces a structured, multi-stage approach that includes multi-source data aggregation, advanced IoC validation and scoring, real-time correlation and pattern detection, and the generation of context-rich early warnings. Through systematic processing, the framework enhances the accuracy and timeliness of threat detection, allowing organizations to identify and respond to emerging cyber threats at earlier stages. Grounded in current literature and operational insights, this framework offers a conceptual foundation for integrating IoCs more effectively into proactive cybersecurity strategies.
AI-Driven Mitigation of Cognitive Biases in Intelligent Personal Assistant Interactions: Evidence from African Contexts Shinkafi, Abdullahi A.; Bassey, Steve; Chaku, Shammah Emmanuel; Aimufua, Gilbert I. O.; Joseph, Abraham D.
Kwaghe International Journal of Engineering and Information Technology Vol 2 No 3 (2025): Kwaghe International Journal of Engineering and Information Technology
Publisher : Darul Yasin Al Sys

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58578/kijeit.v2i3.6480

Abstract

This paper presents a rigorous investigation into how artificial intelligence-driven features in Intelligent Personal Assistants (IPAs) can mitigate cognitive biases within the culturally diverse landscapes of African societies. Positioned at the intersection of cognitive psychology, artificial intelligence, and African cultural studies, the research examines how traditional decision-making patterns in West, Southern, and Central African contexts interact with AI-powered debiasing mechanisms. Grounded in Dual-Process Theory and indigenous knowledge systems, the study explores how IPAs can be culturally calibrated to address confirmation bias, anchoring, and availability heuristics as they uniquely manifest within African socio-cultural frameworks. Employing a sequential explanatory mixed-methods design, the study integrates survey data from 528 participants across eight countries with 40 in-depth interviews. The findings reveal that while AI-driven interventions significantly reduce cognitive biases, their effectiveness is deeply moderated by cultural dimensions such as power distance, uncertainty avoidance, and collectivist orientations—each varying distinctly across regions. Culturally contextualized nudges and interventions aligned with local values and communication norms yielded the strongest debiasing outcomes. This research offers essential empirical insights into the emerging field of culturally responsive AI design, emphasizing the need to recalibrate debiasing techniques to reflect and respect African cultural perspectives rather than applying Western-centric models of cognitive optimization.
Co-Authors Bassey, Steve Bassey, Steven I. Chaku, Shammah Emmanuel Joseph, Abraham D. O, Adenomon M. Raji, Adereti Rasak Shinkafi, Abdullahi A.