Related papers: A tool to convert CAD models for importation into …
Geometric Deep Learning techniques have become a transformative force in the field of Computer-Aided Design (CAD), and have the potential to revolutionize how designers and engineers approach and enhance the design process. By harnessing…
For several years, attempts have been made to interface Geant4 and other software packages with the aim of simulating the complete response of a gaseous particle detector. In such a simulation, Geant4 is always responsible for the primary…
On a very fundamental level, particle detectors share similar requirements for their read-out chain. This is reflected in the way that typical read-out solutions are developed, where a previous design is taken and modified to fit some…
We introduce G2T-LLM, a novel approach for molecule generation that uses graph-to-tree text encoding to transform graph-based molecular structures into a hierarchical text format optimized for large language models (LLMs). This encoding…
In this paper, we introduce AutoRDF2GML, a framework designed to convert RDF data into data representations tailored for graph machine learning tasks. AutoRDF2GML enables, for the first time, the creation of both content-based features --…
We introduce TD-Interpreter, a specialized ML tool that assists engineers in understanding complex timing diagrams (TDs), originating from a third party, during their design and verification process. TD-Interpreter is a visual…
A sampling calorimeter equipped with gaseous sensor layers with digital readout is near perfect for "Particle Flow Algorithm" approach, since it is homogeneous over large surfaces, robust, cost efficient, easily segmentable to any readout…
Learning dense correspondences across deformable 3D shapes remains a long-standing challenge due to structural variability, non-isometric deformation, and inconsistent topology. Existing methods typically trade off generalization, geometric…
Accurate simulation of physical processes is crucial for the success of modern particle physics. However, simulating the development and interaction of particle showers with calorimeter detectors is a time consuming process and drives the…
Recent advances in large language models for test case generation have improved branch coverage via prompt-engineered mutations. However, they still lack principled mechanisms for steering models toward specific high-risk execution…
An innovative particle detector that offers a compelling combination of cost-effectiveness and high accuracy is introduced. The detector features plastic scintillators paired with a sparse arrangement of SiPMs, strategically positioned…
The increasing size and complexity of machine learning (ML) models have driven the growing need for custom hardware accelerators capable of efficiently supporting ML workloads. However, the design of such accelerators remains a…
Hadronic calorimeters with dual readout measure both scintillation and Cherenkov lights produced in their active media. They offer improvements in energy resolution and, therefore, have become increasingly interesting due to the need for…
This paper introduces SGNMT, our experimental platform for machine translation research. SGNMT provides a generic interface to neural and symbolic scoring modules (predictors) with left-to-right semantic such as translation models like NMT,…
This paper addresses the methodology for achieving the user interface design reusability of a qualitative software system and effort minimization by applying the inference on the stored design documents. The pictorial design documents are…
The ever higher complexity of manufacturing systems, continually shortening life cycles of products and their increasing variety, as well as the unstable market situation of the recent years require introducing grater flexibility and…
This study introduces a new Scintillator Simulation Library called SSLG4 for the Geant4 Monte Carlo simulation package. With SSLG4, we aim to enhance efficiency and accelerate progress in optical simulations within the Geant4 framework by…
Large language models (LLMs) have shown remarkable abilities to generate code, however their ability to develop software for embedded systems, which requires cross-domain knowledge of hardware and software has not been studied. In this…
Designing complex computer-aided design (CAD) models is often time-consuming due to challenges such as computational inefficiency and the difficulty of generating precise models. We propose a novel language-guided framework for industrial…
Cross-organizational collaboration in Model-Based Systems Engineering (MBSE) faces many challenges in achieving semantic alignment across independently developed system models. SysML v2 introduces enhanced structural modularity and formal…