Journal Press India®
It is with great pleasure that we present this issue of Computology: Journal of Applied Computer Science and Intelligent Technologies, which brings together six diverse and timely contributions reflecting the intersection of technology, innovation, and applied research across multiple domains. Each article offers unique insights while collectively highlighting how computational intelligence, data-driven systems, and digital transformations are reshaping industries, education, and governance.
The issue opens with “GENDroid: An Optimized Hybrid Android Malware Detection Framework via Multimodal Feature Fusion and Genetic Algorithm” by Ankit Singh. Addressing the urgent challenge of Android security, the study introduces a robust framework that integrates static analysis with genetic algorithms, demonstrating how adaptive machine learning strategies can strengthen defenses against evolving malware threats. This work not only advances cybersecurity research but also emphasizes the critical role of scalable, automated solutions.
Moving from security to embedded systems, Siddhesh Ghatole, Ajinkya Ghogare, and Gaurav Bachulkar present “Interfacing and Configuration of Dynamic Sensors.” Their study underscores the importance of real-time data acquisition and user-configurable sensor systems, offering a practical approach to bridging hardware limitations of Raspberry Pi. The research resonates with the expanding relevance of IoT applications in education and industry.
The theme of technological disruption continues in “Blockchain Beyond Cryptocurrencies: A Study on Its Impact on Corporate Governance Practices” by Shilpi Sahi and Roopa Johri. The paper explores blockchain’s potential to enhance transparency, accountability, and shareholder engagement, illustrating how this technology is poised to transform governance frameworks in corporate environments.
In the domain of industrial reliability, “Gear Fault Detection with InceptionResNetV2 Transfer Learning” by DurgaPrasad Charakanam showcases the application of deep learning models for predictive maintenance. The impressive accuracy achieved using vibration spectrograms affirms the value of AI-driven diagnostics for minimizing downtime in critical machinery.
Education, too, benefits from intelligent systems. Devendra Ghule’s contribution, “AI Powered Predictive Analytics for Personalized Learning and Improved Holistic Development: An Ethical Framework,” evaluates machine learning algorithms in predicting student performance and supporting adaptive learning. The emphasis on ethics and bias mitigation is especially pertinent as educational institutions adopt data-driven decision-making.
Finally, Vikas Kumar, Chetna, Ankita Kumari, and Anchal Kumari offer “The Role of Computerised Data Mining Techniques in Shaping Modern Marketing Strategies.” This paper provides a qualitative exploration of how advanced analytics is redefining customer segmentation, campaign optimization, and strategic planning.
Together, these articles represent a rich tapestry of contemporary research where artificial intelligence, data mining, blockchain, and IoT technologies are not only solving present challenges but also shaping the future of diverse fields. We trust that readers will find inspiration and valuable perspectives within these pages.