The integration of machine learning with self-healing capabilities represents a significant advancement in the development of adaptive AI systems. These systems are designed to independently identify, analyze, and rectify operational anomalies, ensuring...
The advancement of full-stack development frameworks has transformed the software development domain, facilitating the seamless integration of front-end and back-end operations. As dependence on web and mobile apps grows, security and compliance have...
Hybrid cloud had evolved as the most popular choice for cloud solution, it enhances the flexibility of enterprises to process and manage data at a quicker pace by integrating both public and private clouds. However, achieving data reliability – consistency,...
The rapid growth of data across scientific, industrial, and social domains has created an increasing demand for professionals skilled in data mining and knowledge discovery. This proposal presents a structured and comprehensive data mining curriculum...
Small and Medium Enterprises (SMEs) increasingly rely on cloud computing to drive innovation, scalability, and operational efficiency. However, managing cloud costs effectively remains a significant challenge, often leading to resource wastage and budget...
In the digital era, cloud computing has become integral to modern data storage and processing, offering scalability and cost-effectiveness. However, ensuring data integrity defined as the accuracy, consistency, and reliability of data—remains a critical...
In the contemporary digital economy, organizations increasingly depend on data as a strategic asset for decision-making, innovation, and regulatory compliance. As a result, data governance has emerged as a critical organizational function that ensures data...
Cloud ecosystems are of particular importance in terms of providing supporting framework for a wide range of current and future digital services and applications, but they also have potentially fatal flaws in terms of resource management and data integrity....
Cloud computing has developed at a very fast pace and has transformed data engineering for organizations to handle big data. But limitations including reliability of data, the ability to expand the cloud-based systems, and security become major issues. This...
To optimize marketing and sales efforts, ML enables more precise audience segmentation and campaign optimization, which in turn triggers a paradigm change in these fields. In order to determine the best channels and marketing strategies for each cohort, ML...
The exponential growth of data generated by digital platforms, enterprise systems, and emerging technologies has significantly increased the complexity of data governance within modern organizations. Data Governance Analysts are tasked with ensuring that...
Growing Internet of Things (IoT) networks incorporating artificial intelligence (AI) requires effective and highly reliable communication schemes to achieve high coverage low latency, and guaranteed performance. The problems presented by real-world...
Data quality assurance is a critical but resource-intensive component of citizen science projects. As project scale and data volume have grown, traditional expert-based quality assurance approaches have become increasingly inadequate, creating a need for...
In today’s fast-evolving digital landscape, cloud-native environments have emerged as the cornerstone of scalable and flexible computing. However, ensuring data reliability within these environments remains a critical challenge due to the dynamic nature of...
An international, open-access academic press.
YUKTAB Publisher
Awan Tower, Peshawar, Pakistan
Monday – Friday, 9:00 AM – 6:00 PM (PKT)
For manuscript status queries, please contact the relevant journal's editorial team directly rather than the general office.
