Answer validation for generic crowdsourcing tasks with minimal efforts

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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 ...

The performance of machine learning algorithms is conditioned by the availability of training datasets, which is especially true for the field of nondestructive evaluation. Here we propose one reconfigurable specimen instead of numerous reference specimens ...

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 ...

Federated Learning by nature is susceptible to low-quality, corrupted, or even malicious data that can severely degrade the quality of the learned model. Traditional techniques for data valuation cannot be applied as the data is never revealed. We present ...

Modern data-driven science often consists of iterative cycles of data discovery, acquisition, preparation, analysis, model building and validation leading to knowledge discovery as well as dissemination at scale. The unique challenges of building and simul ...

A crucial building block of responsible artificial intelligence is responsible data governance, including data collection. Its importance is also underlined in the latest EU regulations. The data should be of high quality, foremost correct and representati ...

As an emerging technology in the era of Industry 4.0, digital twin is gaining unprecedented attention because of its promise to further optimize process design, quality control, health monitoring, decision- and policy-making, and more, by comprehensively m ...

We present the first detection of the baryon acoustic oscillations (BAOs) signal obtained using unblinded data collected during the initial 2 months of operations of the Stage-IV ground-based Dark Energy Spectroscopic Instrument (DESI). From a selected sam ...

We present a dataset of 264 annotated piano pieces of nine composers, composed in the long 19th century (https://doi.org/10.5281/zenodo.7483349). Annotations adhere to the DCML harmony annotation standard and include Roman numerals, phrase boundaries, and ...

In an attempt to go beyond the conventional laboratory experiments widely reported in literature around the emerging technique of soil bio-cementation, this work addresses key challenges related to its large-scale application. Precisely, a state-of-the-art ...

In capacity-designed steel moment resisting frames (MRFs), inelastic deformations are mostly concentrated in the steel beams and the column fixed ends of the first story, while the participation of the panel zones in energy dissipation is limited. In such ...

There are many sources providing atmospheric weather station data for the Antarctic continent. However, variable naming, timestamps and data types are highly variable between the different sources. The published python code intends to make processing of di ...

Production quality and process efficiency are the two main drivers that lead any industrial strategy. To ensure product quality, a duality historically existed between two approaches, namely batch sampling and systematic sampling. In batch sampling, the ba ...

An attempt is made to translate five generic key performance indicators (KPIs) into a continuous real-time cost function in a batch order-based manufacturing environment. The challenge of controlling and optimizing resource utilization, production efficien ...

Reconstruction algorithms are at the forefront of accessible and compact data collection. In this paper, we present a novel reconstruction algorithm, SpecRA, that adapts based on the relative rarity of a signal compared to previous observations. We leverag ...

As an emerging technology in the era of Industry 4.0, digital twin is gaining unprecedented attention because of its promise to further optimize process design, quality control, health monitoring, decision and policy making, and more, by comprehensively mo ...

Virtual metrology (VM) involves estimating a product's quality directly from production process data without physically measuring it. This enables the product quality of each unit of production to be monitored in real time, while preserving the process eff ...

Classic image-restoration algorithms use a variety of priors, either implicitly or explicitly. Their priors are hand-designed and their corresponding weights are heuristically assigned. Hence, deep learning methods often produce superior image restoration ...

Intelligence involves processing sensory experiences into representations useful for prediction. Understanding sensory experiences and building these contextual representations without prior knowledge of sensor models and environment is a challenging unsup ...

Visual inspection with acetic acid (VIA) is recommended by theWorld Health Organization for primary cervical cancer screening or triage of human papillomavirus-positive women living in low-resource settings. Nonetheless, traditional VIA with the naked-eye ...

Answer validation for generic crowdsourcing tasks with minimal efforts

Chattez avec Graph Search

Extensions of Peer Prediction Incentive Mechanisms

Reduced Training Data for Laser Ultrasound Signal Interpretation by Neural Networks

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

A Practical Influence Approximation for Privacy-Preserving Data Filtering in Federated Learning

Blue Brain Nexus: An open, secure, scalable system for knowledge graph management and data-driven science

incentive Mechanism Design for Responsible Data Governance: A Large-Scale Field Experiment

A comprehensive review of digital twin-part 2: roles of uncertainty quantification and optimization, a battery digital twin, and perspectives

First detection of the BAO signal from early DESI data

An Annotated Corpus of Tonal Piano Music from the Long 19th Century

Addressing the challenges of homogeneity, quality control and waste handling in soil bio-cementation: A large-scale experiment

Towards instability-free welded moment connections

Preprocessing Antarctic Weather Station (AWS) data in python

Virtual metrology applied to milling process

Cost-Based Decision Support System: A Dynamic Cost Estimation of Key Performance Indicators in Manufacturing

Towards ‘Fourth Paradigm’ Spectral Sensing

A comprehensive review of digital twin - part 1: modeling and twinning enabling technologies

Virtual metrology as an approach for product quality estimation in Industry 4.0: a systematic review and integrative conceptual framework

BIGPrior: Towards Decoupling Learned Prior Hallucination and Data Fidelity in Image Restoration

Mechanical intelligence for learning embodied sensor-object relationships

Smartphone-Based Visual Inspection with Acetic Acid: An Innovative Tool to Improve Cervical Cancer Screening in Low-Resource Setting