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Bringing together the ICT and the business layer of a service-oriented system (SoS) remains a great challenge. Few papers tackle the management of SoS from the business and organizational point of view. One solution is to use the well-known…
Validating process model against corresponding requirements is one of the most important problems in domain of collaborative processes. In this paper collaborative processes are modeled using the interaction view of BPMN 2.0 standard. Then,…
Programming by example (PBE) is an emerging programming paradigm that automatically synthesizes programs specified by user-provided input-output examples. Despite the convenience for end-users, implementing PBE tools often requires strong…
A number of companies are trying to migrate large monolithic software systems to Service Oriented Architectures. A common approach to do this is to first identify and describe desired services (i.e., create a model), and then to locate…
Workplaces of the future require advanced competence profiles from employees, not least due to new options for teleworking and new complex digital tools. The acquisition of advanced competence profiles is to be addressed by formal…
Sparse Mixture-of-Experts (MoE) architectures are increasingly popular for frontier large language models (LLM) but they introduce training challenges due to routing complexity. Fully leveraging parameters of an MoE model requires all…
Network virtualization allows one to build dynamic distributed systems in which resources can be dynamically allocated at locations where they are most useful. In order to fully exploit the benefits of this new technology, protocols need to…
This paper details the methodology behind CoPE, a policy-steerable small language model capable of fast and accurate content labeling. We present a novel training curricula called Contradictory Example Training that enables the model to…
Scalability of evolutionary algorithms refers to assessing how their performance changes as problem size increases. In the area of multi-objective optimisation, research on the scalability of multi-objective evolutionary algorithms (MOEAs)…
Existing toxic detection models face significant limitations, such as lack of transparency, customization, and reproducibility. These challenges stem from the closed-source nature of their training data and the paucity of explanations for…
Distributed Software Development today is in its childhood and not too widespread as a method of developing software in the global IT Industry. In this context, Petrinets are a mathematical model for describing distributed systems…
Large uncertainties in many phenomena have challenged decision making. Collecting additional information to better characterize reducible uncertainties is among decision alternatives. Value of information (VoI) analysis is a mathematical…
One of the strength of Virtual Organisations is their ability to dynamically and rapidly adapt in response to changing environmental conditions. Dynamic adaptability has been studied in other system areas as well and system management…
Network virtualization enables Internet service providers to run multiple heterogeneous and dedicated network architectures for different customers on a shared substrate. In existing works on virtual network embedding (VNE), each customer…
Mentorship in open source software (OSS) is a vital, multifaceted process that includes onboarding newcomers, fostering skill development, and enhancing community building. This study examines task-focused mentoring strategies that help…
Training an agent to adapt to specific tasks through co-optimization of morphology and control has widely attracted attention. However, whether there exists an optimal configuration and tactics for agents in a multiagent competition…
A generic architecture for a class of distributed robotic systems is presented. The architecture supports openness and heterogeneity, i.e. heterogeneous components may be joined and removed from the systems without affecting its basic…
The Collaborative Analysis Versioning Environment System (CAVES) project concentrates on the interactions between users performing data and/or computing intensive analyses on large data sets, as encountered in many contemporary scientific…
Expensive optimization problems (EOPs) have attracted increasing research attention over the decades due to their ubiquity in a variety of practical applications. Despite many sophisticated surrogate-assisted evolutionary algorithms (SAEAs)…
Many organizations seek to ensure that machine learning (ML) and artificial intelligence (AI) systems work as intended in production but currently do not have a cohesive methodology in place to do so. To fill this gap, we propose MLTE…