Related papers: Majorana Demonstrator Data Release for AI/ML Appli…

This paper represents a systematic way for generation of Aaria, a simulated model for serial manipulators for the purpose of kinematic or dynamic analysis with a vast variety of structures based on Simulink SimMechanics. The proposed model…

We present megas, a new software tool that improves the simulation of the Micromegas gas detectors. Our tool offers the possibility to configure multiple arrangements with one or more layers of MM detectors. A series of simple commands can…

Data set generated from the scintillation detector is used to build a mathematical model based on three different algorithms: (a) Multiple Polynomial Regression (b) Support Vector Regression (c) Neural Network algorithm. Using…

Context: Machine Learning (ML) is integrated into a growing number of systems for various applications. Because the performance of an ML model is highly dependent on the quality of the data it has been trained on, there is a growing…

The rapid advancement of AI, particularly large language models (LLMs), has raised significant concerns about the energy use and carbon emissions associated with model training and inference. However, existing tools for measuring and…

We introduce Replica, a dataset of 18 highly photo-realistic 3D indoor scene reconstructions at room and building scale. Each scene consists of a dense mesh, high-resolution high-dynamic-range (HDR) textures, per-primitive semantic class…

In recent years, the amount of information collected about human beings has increased dramatically. This development has been partially driven by individuals posting and storing data about themselves and friends using online social networks…

Complex phenomena are generally modeled with sophisticated simulators that, depending on their accuracy, can be very demanding in terms of computational resources and simulation time. Their time-consuming nature, together with a typically…

A metadata schema, named Plasma-MDS, is introduced to support research data management in plasma science. Plasma-MDS is suitable to facilitate the publication of research data following the FAIR principles in domain-specific repositories…

Data analyses in particle physics rely on an accurate simulation of particle collisions and a detailed simulation of detector effects to extract physics knowledge from the recorded data. Event generators together with a GEANT-based…

This is a colloquium-style introduction to the midgap excitations in superconductors known as Majorana fermions. These elusive particles, equal to their own antiparticle, may or may not exist in Nature as elementary building blocks, but in…

Predictive simulations and experimental design involving extreme aero-chemo-thermo-mechanical regimes require high-fidelity material representation across diverse physical states. However, data for metals, polymers, and propellants,…

There is a growing demand for the use of Artificial Intelligence (AI) and Machine Learning (ML) in healthcare, particularly as clinical decision support systems to assist medical professionals. However, the complexity of many of these…

Industrial applications of machine learning face unique challenges due to the nature of raw industry data. Preprocessing and preparing raw industrial data for machine learning applications is a demanding task that often takes more time and…

We introduce a robust, interpretable machine learning (ML) framework that combines numerical regression for high-accuracy predictions with symbolic regression to uncover the underlying physics. This hybrid approach effciently derives…

Unfolding of reconstructed event properties to identify the true features of collider events is a complementary method to the established practice of detector calibration, and is particularly relevant to large, composite particle detectors…

Motivated by an imaging proteomics study for Alzheimer's disease (AD), in this article, we propose a mediation analysis approach with high-dimensional exposures and high-dimensional mediators to integrate data collected from multiple…

The existence of Majorana neutrinos must lead to lepton-number violating processes, and the Majorana nature of neutrinos can only be experimentally verified via lepton-number violating processes. We propose a new approach to search for…

In this paper, we propose to adopt the MDE paradigm for the development of Machine Learning (ML)-enabled software systems with a focus on the Internet of Things (IoT) domain. We illustrate how two state-of-the-art open-source modeling…

The proliferation of wearable technology enables the generation of vast amounts of sensor data, offering significant opportunities for advancements in health monitoring, activity recognition, and personalized medicine. However, the…