Category: Research Paper

As modern applications increasingly rely on distributed architectures to handle large-scale data processing, real-time communication, and fault tolerance, efficient network planning becomes essential.

Modern computer networks have undergone significant advancements, driven by rapid technological growth and increasing demands for high-speed, reliable communication.

Advanced methods such as ensemble learning, transfer learning, and cross-validation further enhance model performance and generalizability.

Artificial Intelligence (AI) and Machine Learning (ML) have rapidly evolved from conceptual theories into transformative technologies shaping nearly every aspect of modern life.

The study of Advanced Topics in Algorithm Analysis and Design delves into the deeper aspects of algorithmic thinking, extending beyond foundational techniques to explore complex strategies for solving computational problems efficiently.

Optimization techniques in algorithm design are essential for developing efficient, scalable, and high-performing solutions to complex problems.

As robots become more autonomous and integrated into daily life, concerns about privacy, job displacement, accountability, and decision-making arise.

Recent advancements in robotics have significantly transformed both industrial and everyday life, driven by breakthroughs in artificial intelligence, machine learning, sensor technology, and automation.

As data lakehouse technologies gain traction, tools like Delta Lake, Apache Iceberg, and Apache Hudi have emerged as leading solutions for enabling transactional data operations over data lakes.

The automotive industry is undergoing rapid digital transformation, generating vast amounts of data from sensors, manufacturing systems, connected vehicles, and customer interactions.