A Probabilistic Framework for Decentralized Management of Trust and Quality

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Accurately measuring behavior is critical to understanding brain function. While traditional behavioral analysis has relied on human observation and manual processing, advances in machine learning and computer vision have begun to automate the field. This ...

Commercial high-voltage circuit breaker (CB) condition monitoring systems rely on directly observable physical parameters such as gas filling pressure with pre-defined thresholds. While these parameters are crucial, they only cover a small subset of malfun ...

Retrieval-Augmented Generation (RAG) is a widely used strategy in Large-Language Models (LLMs) to extrapolate beyond the inherent pre-trained knowledge. Hence, RAG is crucial when working in data-sparse fields such as Chemistry. The evaluation of RAG syste ...

Automatically tracking and segmenting every video entity remains a significant challenge. Despite rapid advancements in video segmentation, even state-of-the-art models like SAM 2 struggle to consistently track all entities across a video—a task we refer t ...

As large, data-driven artificial intelligence models become ubiquitous, guaranteeing high data quality is imperative for constructing models. Crowdsourcing, community sensing, and data filtering have long been the standard approaches to guaranteeing or imp ...

We propose a comparative study of three different methods aimed at optimizing existing groundwater monitoring networks. Monitoring piezometric heads in subsurface porous formations is crucial at regional scales to properly characterize the relevant subsurf ...

Statistical (machine-learning, ML) models are more and more often used in computational chemistry as a substitute to more expensive ab initio and parametrizable methods. While the ML algorithms are capable of learning physical laws implicitly from data, ad ...

Mechanical resonators are widely used in sensors, transducers and optomechanical systems, where mechanical dissipation sets the ultimate limit to performance. Over the past 15 years, the quality factors in strained mechanical resonators have increased by f ...

The COVID-19 pandemic has led to a significant increase in working from home worldwide, making the workfrom-home (WFH) setting a crucial context for studying the influence of indoor environmental quality (IEQ) on workers' well-being and productivity. A nar ...

At room temperature, mechanical motion driven by the quantum backaction of light has been observed only in pioneering experiments in which an optical restoring force controls the oscillator stiffness1,2. For solid-state mechanical resonators in which oscil ...

Anomaly detection (AD) is essential in identifying rare and often critical events in complex systems, finding applications in fields such as network intrusion detection, financial fraud detection, and fault detection in infrastructure and industrial system ...

A key challenge across many disciplines is to extract meaningful information from data which is often obscured by noise. These datasets are typically represented as large matrices. Given the current trend of ever-increasing data volumes, with datasets grow ...

Dataset corresponding to the following manuscript: Slagter, A., Setyadji, J.A., Vogt, E.L. et al. Nanoindentation Hardness and Modulus of Al2O3–SiO2–CaO and MnO–SiO2–FeO Inclusions in Iron. Metall Mater Trans A (2024). https://doi.org/10.1007/s11661-024-0 ...

This paper presents a novel hybrid framework for generating and updating a synthetic population. We call it hybrid because it combines model-based and data-driven approaches. Existing generators produce a snapshot of synthetic data that becomes outdated ov ...

This repository contains microphysics routines, scripts, and processed data from the Weather Research and Forecasting (WRF) model simulations presented in the paper "RaFSIP: Parameterizing ice multiplication in models using a machine learning approach", by ...

This data set contains the data collected during the FNS project Green Piezo (Grant no. 179064) in association with the recent publication entitled “3D printing of customizable transient bioelectronics and sensors”. This work aims to study and demonstrate ...

Decentralized storage networks offer services with intriguing possibilities to reduce inequalities in an extremely centralized market. Fair distribution of rewards, however, is still a persistent problem in the current generation of decentralized applicati ...

This document contains all the data and the details of the analysis used in the manuscript titled " Control of Ge island coalescence for the formation of nanowires on silicon." https://doi.org/10.1039/D3NH00573A ...

Human babies have a natural desire to interact with new toys and objects, through which they learn how the world around them works, e.g., that glass shatters when dropped, but a rubber ball does not. When their predictions are proven incorrect, such as whe ...

In this thesis we study stability from several viewpoints. After covering the practical importance, the rich history and the ever-growing list of manifestations of stability, we study the following. (i) (Statistical identification of stable dynamical syste ...

A Probabilistic Framework for Decentralized Management of Trust and Quality

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From Pose to Behavior: Advancing Multi-Individual Pose Estimation and Hierarchical Action Segmentation with Transformers

Explainable AI guided unsupervised fault diagnostics for high-voltage circuit breakers

ChemLit-QA: a human evaluated dataset for chemistry RAG tasks

EntitySAM: Segment Everything in Video

Extensions of Peer Prediction Incentive Mechanisms

Data-driven statistical optimization of a groundwater monitoring network

Encoding quantum-chemical knowledge into machine-learning models of complex molecular properties

Ultrahigh-quality-factor micro- and nanomechanical resonators using dissipation dilution

A state-of-the-art, systematic review of indoor environmental quality studies in work-from-home settings

Room-temperature quantum optomechanics using an ultralow noise cavity

NNG-Mix: Improving Semi-Supervised Anomaly Detection with Pseudo-Anomaly Generation

Spectral Estimators for High-Dimensional Matrix Inference

Nanoindentation hardness and modulus of Al2O3-SiO2-CaO and MnO-SiO2-FeO inclusions in iron

Hybrid Simulator for Capturing Dynamics of Synthetic Populations

Data and scripts for the RaFSIP scheme

Dataset for '3D printing of customizable transient bioelectronics and sensors'

Altruism, reciprocity, and tokens to reward forwarding data: Is that fair?

Data set for control of Ge island coalescence for the formation of nanowires on silicon

Seeking the new, learning from the unexpected: Computational models of surprise and novelty in the brain

Stability: a search for structure