Fintech Mobile Security: Advanced Fraud Detection, Secure Payment Processing, and Regulatory Compliance in Mobile Financial Applications
Android Based Course Learning Materials Application with Embedded Assignment Protocol
Integrating UX Design Principles into SEO Strategies: From Clicks to Conversions
AI Usage in iOS and Android: A Functional Comparison and Performance Analysis
Mobile Communication Systems: Architecture, Technologies, Performance Analysis, and Future Trends
Development of Mobile App for the Soil Classification
Applications of Wearable Technology in Elite Sports
Using the Arduino Platform for Controlling AC Appliances with GSM Module and Relay
Evaluation of Mobile Banking Services Usage in Minna, Niger State
Emerging Technologies in Interaction with Mobile Computing Devices – A Technology Forecast
Smartphone Applications–A Comparative Study BetweenOlder And Younger Users
Technological Diffusion of Near Field Communication (NFC)
Touchscreen and Perceived Usability: A Comparison of Attitudes between Older and Younger Mobile Device Users
A Review on Routing Protocols for Mobile Adhoc Networks
Applications of Wearable Technology in Elite Sports
The rapid rise of mobile financial apps has completely changed the landscape of financial services, opening up amazing opportunities, but also bringing along some serious security challenges. This paper dives into the essential security frameworks that are crucial for Fintech mobile applications, honing in on three main areas: advanced fraud detection methods, secure payment processing protocols, and the requirements for regulatory compliance. By thoroughly analyzing current security technologies and regulatory frameworks, this study assesses how effective machine learning-based fraud detection systems, blockchain-enabled payment security, and multi-layered authentication protocols really are. The research employs a mixed-methods approach, blending a systematic literature review with case studies of top Fintech platforms. The results show that AI-driven fraud detection systems achieve an impressive 94% accuracy in spotting fraudulent transactions, while multifactor authentication cuts down unauthorized access by 87%. However, the landscape of regulatory compliance is still quite fragmented across different jurisdictions, which poses implementation challenges. The findings suggest that integrated security architectures that combine behavioral analytics, biometric authentication, and real-time monitoring offer the strongest protection for mobile financial applications. This research adds to our understanding of the comprehensive security frameworks needed for sustainable growth in Fintech, all while keeping user trust and regulatory compliance in check.
To heighten interaction between students and tutors, an andriod application (app) with inbuilt assignment protocol was carried out in this study. Students can utilize the app to view and download course materials, turn in assignments directly from their mobile devices, after utilizing their matriculation number for registration. Tutors can upload course materials as well as publish assignments, and students can receive real-time notifications. Firebase was utilized for file storage, authentication as well as database management. Major characteristics of the app - notification delivery, file upload and login were evaluated, and the corresponding results obtained affirmed the app's effectiveness and reliability. The developed app offers a digital approach to academic administration, facilitating faster access to educational resources and potentially boosting communication within a university community. Because the architecture of the app was designed with scalability in mind, it can be expanded to incorporate features like automatic grading, student performance data and course registration. This study thus, demonstrates that mobile technology can be utilized in education administration and it serves as a template for schools to follow if they wish to update their academic systems, especially institutions like Bells University of Technology who is on a journey to attain her digital transformation goals.
The growing complexity of search engine algorithms has shifted the focus of Search Engine Optimization (SEO) from keyword manipulation to user-centered experience design. However, a clear methodological framework integrating User Experience (UX) principles with SEO strategies remains underexplored. This study addresses this gap by examining how UX-driven factors—such as intuitive navigation, visual hierarchy, responsive layout, and optimized call-to-actions (CTAs)- influence key SEO performance indicators like dwell time, bounce rate, and conversion rate. The research employs comparative analysis and case-based evaluation (notably Amazon.com) to measure performance variations before and after UX optimization. Results indicate that UX-integrated SEO strategies significantly improve user engagement, organic visibility, and conversion efficiency. The study contributes an evidence-based framework demonstrating how aligning UX design with SEO objectives transforms web interactions from mere clicks to meaningful conversions, offering actionable insights for designers, developers, and digital strategists. This research contributes to bridging design thinking and algorithmic optimization, offering a unified model for future UX-SEO innovations.
Artificial Intelligence (AI) has become a cornerstone of modern smartphone functionality, significantly enhancing user experience, security, and efficiency. This paper presents a functional comparison and performance analysis of AI usage in iOS and Android, focusing on key areas such as voice assistants (Siri (Speech Interpretation and Recognition Interface) vs. Google Assistant), AI-driven security features (Face ID vs. Face Unlock), machine learning frameworks (Core ML vs. TensorFlow Lite), computational photography, battery optimization, and augmented reality (ARKit vs. ARCore). The study highlights how AI-powered advancements improve system responsiveness, personalization, and automation while addressing challenges related to privacy, data security, and computational efficiency. Our analysis demonstrates that Apple's AI approach prioritizes on-device processing and privacy, whereas Google leverages cloud-based AI for broader functionality. As AI continues to evolve, future developments in edge AI, federated learning, and neural processing units (NPUs) will further shape the landscape of mobile intelligence. This comparative study provides insights into the strengths and limitations of AI in both ecosystems, offering a roadmap for future AI-driven innovations in smartphone technology.
Mobile communication systems have become an indispensable component of modern society, enabling ubiquitous connectivity, real-time information exchange, and seamless access to multimedia services. The evolution from first- generation (1G) analog systems to advanced fifth-generation (5G) and emerging sixth-generation (6G) networks reflects continuous innovation driven by the demand for higher data rates, lower latency, massive connectivity, and improved reliability. This review presents a comprehensive, and in-depth study of mobile communication systems, focusing on their fundamental principles, network architectures, multiple access techniques, propagation characteristics, performance metrics, and real-world applications. Detailed discussions on cellular concepts, handoff mechanisms, channel modeling, modulation and coding schemes, and modern technologies such as LTE, 5G New Radio, and mobile edge computing are included. Furthermore, challenges and limitations of existing systems are analyzed, followed by future research directions emphasizing artificial intelligence-driven networks, ultra-reliable low-latency communications, and sustainable mobile communication infrastructures.
