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Adding Flexibly in Distributed Simulation of Space Missions by Enhancing the SpaceFOM Standard

SpaceFOM is the reference standard adopted by space agencies for simulating space missions. Although specifically designed for handling space systems, it currently faces a significant limitation when simulating interplanetary missions: a fixed Federation Time Step. This constraint hinders accurate and flexible modeling of space missions, which limits the dynamic changes of simulation pace, especially during critical phases that require particular temporal granularities. This work proposes ext...

Software system testing assisted by large language models: an exploratory study

Large language models (LLMs) based on transformer architecture have revolutionized natural language processing (NLP), demonstrating excellent capabilities in understanding and generating human-like text. In Software Engineering, LLMs have been applied in code generation, documentation, and report writing tasks, to support the developer and reduce the amount of manual work. In Software Testing, one of the cornerstones of Software Engineering, LLMs have been explored for generating test code, t...

Atti I convegno «Beni culturali in Puglia. Dialoghi multidisciplinari per la ricerca, la tutela e la valorizzazione» (Bari, 16-17 settembre 2020)

Lo studio dell’architettura romana residenziale in Puglia può essere affrontato con un nuovo approccio multidisciplinare che integra l’analisi archeologica con quella scientifica della luce naturale ed artificiale in modo da identificarne l’impatto sullo svolgimento in antico delle attività quotidiane in termini di performance e percezione visiva. Così il concorso di dati storici e di apporti tecnologici diventa dirimente nella definizione delle ipotesi di ricostruzione 3D per inedite interpr...

EEG signal pre-processing for segmentation into significants regions, major artefacts removal, and uncertainty reduction in epilectic seizure characterization

EEG analysis is a key tool in clinical research for diagnosing neurological disorders, but it presents challenges due to the low amplitude of the signals, the multichannel nature of recordings, and the frequent presence of artifacts and various events. These factors can compromise the accuracy of clinical interpretations. To address this, preprocessing methods are essential. They aim to remove major artifacts without losing valuable information, segment the EEG into meaningful epochs, and acc...

Towards identity-aware cross-modal retrieval: a dataset and a baseline

Recent advancements in deep learning have significantly enhanced content-based retrieval methods, notably through models like CLIP that map images and texts into a shared embedding space. However, these methods often struggle with domain-specific entities and long-tail concepts absent from their training data, particularly in identifying specific individuals. In this paper, we explore the task of identity-aware cross-modal retrieval, which aims to retrieve images of persons in specific contex...

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