Solid-State Storage and Work Sharing for Efficient Scaleup Data Analytics

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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 ...

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 ...

Enterprises collect data in large volumes and leverage them to drive numerous concurrent decisions and business processes. Their teams deploy multiple applications that often operate concurrently on the same data and infrastructure but have widely differen ...

Graph signal processing represents an important advancement in the field of data analysis, extending conventional signal processing methodologies to complex networks and thereby facilitating the exploration of informative patterns and structures across var ...

The 70 kDa heat shock protein (Hsp70) chaperones control protein homeostasis in all ATP-containing cellular compartments. J-domain proteins (JDPs) coevolved with Hsp70s to trigger ATP hydrolysis and catalytically upload various substrate polypeptides in ne ...

In light of the challenges posed by climate change and the goals of the Paris Agreement, electricity generation is shifting to a more renewable and decentralized pattern, while the operation of systems like buildings is increasingly electrified. This calls ...

Driven by the demand for real-time processing and the need to minimize latency in AI algorithms, edge computing has experienced remarkable progress. Decision-making AI applications stand out for their heavy reliance on data-centric operations, predominantl ...

This paper proposes a data-driven control design method for nonlinear systems that builds upon the Koopman operator framework. In particular, the Koopman operator is used to lift the nonlinear dynamics to a higher-dimensional space where the so-called obse ...

Masonry aggregates, which emerged as layouts of cities and villages became denser, make up historical centres all over the world. In these aggregates, neighbouring structures may share structural walls that are joined at the interfaces by mortar or interlo ...

Image information about the state of a building after an earthquake, which can be collected without endangering the post-earthquake reconnaissance activities, can be used to reduce uncertainties in response predictions for future seismic events. This paper ...

Here we provide the neural data, activation and predictions for the best models and result dataframes of our article "Task-driven neural network models predict neural dynamics of proprioception". It contains the behavioral and neural experimental data (cu ...

Dynamic downscaling of atmospheric forcing data to the hectometer resolution has shown increases in accuracy for landsurface models, but at great computational cost. Here we present a validation of a novel intermediate complexity atmospheric model, HICAR, ...

Implanted medical devices (IMDs) have been widely developed to support the monitoring and recording of biological data inside the body or brain. Wirelessly powered IMDs, a subset of implantable electronics, have been proposed to eliminate the limitations r ...

Solid-State Storage and Work Sharing for Efficient Scaleup Data Analytics

Chattez avec Graph Search

Extensions of Peer Prediction Incentive Mechanisms

Spectral Estimators for High-Dimensional Matrix Inference

Oligolithic Cross-task Optimizations across Isolated Workloads

Informed Graph Learning By Domain Knowledge Injection and Smooth Graph Signal Representation

Autorepression of yeast Hsp70 cochaperones by intramolecular interactions involving their J-domains

Quantifying the Unknown: Data-Driven Approaches and Applications in Energy Systems

EdgeAI-Aware Design of In-Memory Computing Architectures

Data-Driven Control Synthesis using Koopman Operator: A Robust Approach

Seismic Testing of Adjacent Interacting Masonry Structures – Analysis of a Blind Prediction

Reducing uncertainties in response predictions of earthquake-damaged masonry buildings using data from image-based inspection

Task-driven neural network models predict neural dynamics of proprioception: Experimental data, activations and predictions of neural network models

Intermediate complexity atmospheric modeling in complex terrain: is it right?

Integrated Wireless Power, Data Communication, and Thermal Sensing System for Autonomous Multisite Brain Implants