Security in DevOps (DevSecOps)
Security in DevOps (DevSecOps) DevSecOps – a portmanteau of Development, Security, and Operations – is an approach to software development that integrates security practices into every phase of the DevOps Read More …
Hypersonic Technologies: Engineering Foundations, Enduring Challenges, and Evolving Global Impact
I. Executive Summary Hypersonic flight, defined as atmospheric travel at speeds greater than Mach 5, represents a frontier in aerospace engineering characterized by extreme physical phenomena and multidisciplinary complexities.1 This Read More …
Hypergraph Learning and Higher-Order Network Modeling
Executive Summary The landscape of data science is undergoing a profound transformation, driven by the increasing recognition that real-world systems are rarely confined to simple pairwise interactions. Traditional graph theory, Read More …
Biosensor and IoT Security in Healthcare Systems
1. Introduction: Defining the Connected Healthcare Landscape The integration of biosensors and the Internet of Things (IoT) is fundamentally reshaping the healthcare sector, moving it towards an era of unprecedented Read More …
Graph Neural Networks (GNN): Foundations, Architectures, Applications, and Future Directions
Executive Summary Graph Neural Networks (GNNs) represent a transformative class of neural networks uniquely designed to process and learn from non-Euclidean, graph-structured data. Their fundamental purpose lies in capturing complex Read More …
Gradient Descent – How Optimization Works
Introduction Gradient Descent is one of the most fundamental optimization algorithms in machine learning and deep learning. It is used to minimize a cost (or loss) function by iteratively moving Read More …
GPU-Accelerated Simulation in Automotive and Aerospace Industries
Executive Summary GPU-accelerated simulation has emerged as a transformative force in the automotive and aerospace industries, fundamentally reshaping design, testing, and validation workflows. By leveraging the massively parallel architecture of Read More …
Feature Engineering Techniques: Encoding, Scaling, and PCA
Feature Engineering Techniques: Encoding, Scaling, and PCA Feature engineering is a critical preprocessing step in machine learning that transforms raw data into a more effective set of inputs for algorithms[1]. Read More …
Extreme Low-bit Quantization: Advancing Efficient Deep Learning for Resource-Constrained Environments
1. Introduction to Extreme Low-bit Quantization The rapid evolution of deep learning models, particularly Large Language Models (LLMs), has led to unprecedented capabilities across various domains. However, this advancement comes Read More …
Ambient Power: A Comprehensive Technical Report on Energy Harvesting for Self-Sustaining Electronics
Executive Summary The proliferation of the Internet of Things (IoT), wearable technology, and distributed sensing has created an unprecedented demand for power in locations where traditional batteries and grid connections Read More …