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Seamless integration of artificial intelligence (AI) and machine learning (ML) techniques with wireless systems is a crucial step for 6G AInization. However, such integration faces challenges in terms of model functionality and lifecycle…
Workflow technology is rapidly evolving and, rather than being limited to modeling the control flow in business processes, is becoming a key mechanism to perform advanced data management, such as big data analytics. This survey focuses on…
The proliferation of big data and analytic workloads has driven the need for cloud compute and cluster-based job processing. With Apache Spark, users can process terabytes of data at ease with hundreds of parallel executors. At Microsoft,…
The Internet of Things (IoT) and edge computing applications aim to support a variety of societal needs, including the global pandemic situation that the entire world is currently experiencing and responses to natural disasters. The need…
The deployment of machine learning in high-stakes services relies on ``human-in-the-loop'' architectures to mitigate algorithmic uncertainty. However, existing static policies fail to address a fundamental tension: algorithms suffer from…
This study investigates the adoption and effectiveness of AI-based anomaly detection in cross-provider electronic health record (EHR) environments. It aims to (1) identify the organisational and digital capabilities required for successful…
We present DIO, a generic tool for observing inefficient and erroneous I/O interactions between applications and in-kernel storage systems that lead to performance, dependability, and correctness issues. DIO facilitates the analysis and…
With the deepening of digital transformation, business process optimisation has become the key to improve the competitiveness of enterprises. This study constructs a business process optimisation model integrating artificial intelligence…
Today we live in the age of artificial intelligence and machine learning; from small startups to HW or SW giants, everyone wants to build machine intelligence chips, applications. The task, however, is hard: not only because of the size of…
System administration is a difficult, often tedious, job requiring many skilled laborers. The data that is protected by system administrators is often valued at or above the value of the institution maintaining that data. A number of…
Agentic AI represents a significant shift in how intelligence is applied within organizations, moving beyond AI-assisted tools toward autonomous systems capable of reasoning, decision-making, and coordinated action across workflows. As…
Computer systems are facing biggest threat in the form of malicious data which causing denial of service, information theft, financial and credibility loss etc. No defense technique has been proved successful in handling these threats.…
The proliferation of cloud-native architectures, characterized by microservices and dynamic orchestration, has rendered modern IT infrastructures exceedingly complex and volatile. This complexity generates overwhelming volumes of…
The proliferation of SQL for data processing has often occurred without the rigor of traditional software development, leading to siloed efforts, logic replication, and increased risk. This ad-hoc approach hampers data governance and makes…
Companies report on their financial performance for decades. More recently they have also started to report on their environmental impact and their social responsibility. The latest trend is now to deliver one single integrated report where…
AI application developers typically begin with a dataset of interest and a vision of the end analytic or insight they wish to gain from the data at hand. Although these are two very important components of an AI workflow, one often spends…
"AI slop", that is, low-quality AI-generated content, is increasingly affecting software development, from generated code and pull requests to documentation and bug reports. However, there is limited empirical research on how developers…
Although Machine Learning model building has become increasingly accessible due to a plethora of tools, libraries and algorithms being available freely, easy operationalization of these models is still a problem. It requires considerable…
The evolution of High-Performance Computing (HPC) platforms enables the design and execution of progressively larger and more complex workflow applications in these systems. The complexity comes not only from the number of elements that…
Artificial intelligence (AI) governance is the body of standards and practices used to ensure that AI systems are deployed responsibly. Current AI governance approaches consist mainly of manual review and documentation processes. While such…