Related papers: A Practical Guide for Establishing a Technical Deb…
Multi-task learning (MTL) aims to leverage shared information among tasks to improve learning efficiency and accuracy. However, MTL often struggles to effectively manage positive and negative transfer between tasks, which can hinder…
Research software (also called scientific software) is essential for advancing scientific endeavours. Research software encapsulates complex algorithms and domain-specific knowledge and is a fundamental component of all science. A pervasive…
Dynamic Mode Decomposition (DMD) is an unsupervised machine learning method that has attracted considerable attention in recent years owing to its equation-free structure, ability to easily identify coherent spatio-temporal structures in…
We present the Classroom Technology Deployment Matrix (CTDM), a tool for high-level Planning, Monitoring, Evaluating and Reporting of classroom deployments of educational technologies, enabling researchers, teachers and schools to work…
Large Language Models (LLMs) are increasingly embedded in software via APIs like OpenAI, offering powerful AI features without heavy infrastructure. Yet these integrations bring their own form of self-admitted technical debt (SATD). In this…
Fault tolerance is a critical aspect of modern computing systems, ensuring correct functionality in the presence of faults. This paper presents a comprehensive survey of fault tolerance methods and software-based mitigation techniques in…
Increasing automation in the healthcare sector calls for a Hybrid Intelligence (HI) approach to closely study and design the collaboration of humans and autonomous machines. Ensuring that medical HI systems' decision-making is ethical is…
This paper reports on our definition of guidelines for managing global software development (GSD) that implements the specific practice - manage requirements changes - of the Capability Maturity Model Integration (CMMI) Level 2. The…
Microservices have been recognized for over a decade. They reshaped system design enabling decentralization and independence of development teams working on particular microservices. While loosely coupled microservices are desired, it is…
Quantum computing is a rapidly growing field attracting the interest of both researchers and software developers. Supported by its numerous open-source tools, developers can now build, test, or run their quantum algorithms. Although the…
A precise vulnerability discovery model (VDM) will provide a useful insight to assess software security, and could be a good prediction instrument for both software vendors and users to understand security trends and plan ahead patching…
Pre-trained models (PTMs) have gained widespread popularity and achieved remarkable success across various fields, driven by their groundbreaking performance and easy accessibility through hosting providers. However, the challenges faced by…
Inspired by the success of the Transformer architecture in natural language processing and computer vision, we investigate the use of Transformers in Reinforcement Learning (RL), specifically in modeling the environment's dynamics using…
Predictive monitoring of business processes is concerned with the prediction of ongoing cases on a business process. Lately, the popularity of deep learning techniques has propitiated an ever-growing set of approaches focused on predictive…
Preventing machine failure is inherently superior to reactive remediation, particularly for critical assets like gas turbines, where early fault detection (FD) is a cornerstone of industrial sustainability. However, modern deep…
Scalable AI tutoring for procedural skill learning requires structured knowledge representations, yet constructing these representations remains a labor-intensive bottleneck. This paper introduces a new LLM-assisted text-to-model (TTM)…
Designing effective debt collection systems is crucial for improving operational efficiency and reducing costs in the financial industry. However, the challenges of maintaining script diversity, contextual relevance, and coherence make this…
We introduce a novel data-driven method to mitigate the risk of cascading failures in delayed discrete-time Linear Time-Invariant (LTI) systems. Our approach involves formulating a distributionally robust finite-horizon optimal control…
There is a lack of quantitative measures to evaluate the progression of topics through time in dynamic topic models (DTMs). Filling this gap, we propose a novel evaluation measure for DTMs that analyzes the changes in the quality of each…
IT operates in dynamic environments with the need always to change and adapt. There is a need to improve performance. Many gaps were found when we conduct the IT audit and we tried to seek to close gaps in capabilities. One way to the close…