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Generative modelling of multi-user datasets has become prominent in science and engineering. Generating a data point for a given user requires employing user information, and conventional generative models, including variational…
In this paper two intensive problems faced during software application's analysis and development process arose by the software industry are briefly conversed i.e. identification of fault proneness and increase in rate of variability in the…
The development of an aircraft industrial system is a complex process which faces the challenge of digital discontinuity in multidisciplinary engineering due to various interfaces between different digital tools, leading to extra…
Providing architectural support is crucial for newly arising applications to achieve high performance and high system efficiency. Currently there is a trend in designing accelerators for special applications, while arguably a debate is…
Machine learning and deep learning methods have been widely explored in understanding the chaotic behavior of the atmosphere and furthering weather forecasting. There has been increasing interest from technology companies, government…
The incorporation of Artificial Intelligence (AI) into Enterprise Resource Planning (ERP) is a dramatic transition from static, on-premises systems to systems that can adapt and operate in cloud-native architectures. Cloud ERP solutions…
This work examines how AI, especially agentic systems, is being adopted in engineering and manufacturing workflows, what value it provides today, and what is needed for broader deployment. This is an exploratory and qualitative…
1. Many ecological decisions are slowed by the gap between collecting and analysing biodiversity data. Edge computing moves processing closer to the sensor, with edge artificial intelligence (AI) enabling on-device inference, reducing…
Edge Artificial Intelligence (Edge AI) embeds intelligence directly into devices at the network edge, enabling real-time processing with improved privacy and reduced latency by processing data close to its source. This review systematically…
The engineering design process often demands expertise from multiple domains, leading to complex collaborations and iterative refinements. Traditional methods can be resource-intensive and prone to inefficiencies. To address this, we…
Edge computing has been developed to utilize multiple tiers of resources for privacy, cost and Quality of Service (QoS) reasons. Edge workloads have the characteristics of data-driven and latency-sensitive. Because of this, edge systems…
The escalating challenges of managing vast sensor-generated data, particularly in audio applications, necessitate innovative solutions. Current systems face significant computational and storage demands, especially in real-time applications…
Selecting appropriate sensors and actuators is a pivotal aspect of design and engineering, particularly in projects involving interactive systems. This article introduces the Design Thinking Based Iterative Sensor and Actuator Selection…
Researchers have been highly active to investigate the classical machine learning workflow and integrate best practices from the software engineering lifecycle. However, deep learning exhibits deviations that are not yet covered in this…
In the industrial Internet of Things domain, applications are moving from the Cloud into the edge, closer to the devices producing and consuming data. This means applications move from the scalable and homogeneous cloud environment into a…
As organizations face increasing pressure to understand their corporate and products' carbon footprints, artificial intelligence (AI)-assisted calculation systems for footprinting are proliferating, but with widely varying levels of rigor…
In the rapidly evolving landscape of software engineering, the integration of Artificial Intelligence (AI) into the Software Development Life-Cycle (SDLC) heralds a transformative era for developers. Recently, we have assisted to a pivotal…
Distributed digital infrastructures for computation and analytics are now evolving towards an interconnected ecosystem allowing complex applications to be executed from IoT Edge devices to the HPC Cloud (aka the Computing Continuum, the…
The advent of sixth-generation (6G) mobile networks introduces two groundbreaking capabilities: sensing and artificial intelligence (AI). Sensing leverages multi-modal sensors to capture real-time environmental data, while AI brings…
We describe a framework and tool specification that represents a step towards cybersecurity testing and monitoring of IoT ecosystems. We begin with challenges from a previous paper and discuss an integrated approach and tools to enable…