System and method for monitoring quality of service

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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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

Molecular quantum dynamics simulations are essential for understanding many fundamental phenomena in physics and chemistry. They often require solving the time-dependent Schrödinger equation for molecular nuclei, which is challenging even for medium-sized ...

Diffusion-based generative methods have proven effective in modeling trajectories with offline datasets. However, they often face computational challenges and can falter in generalization, especially in capturing temporal abstractions for long- horizon tas ...

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 ...

Conventional techniques for purifying macromolecular conjugates often require complex and costly installments that are inaccessible to most laboratories. In this work, we develop a one-step micropreparative method based on a trilayered polyacrylamide gel e ...

Given a sequence of functions

f_1,\ldots,f_n

with

f_i:\mathcal{D}\mapsto \mathbb{R}

, finite-sum minimization seeks a point

{x}^\star \in \mathcal{D}

minimizing

\sum_{j=1}^nf_j(x)/n

. In this work, we propose a key twist into the finite-sum minimizat ...

In this paper, we propose a reduced-order modeling strategy for two-way Dirichlet-Neumann parametric coupled problems solved with domain-decomposition (DD) sub-structuring methods. We split the original coupled differential problem into two sub-problems wi ...

Modern integrated circuits are tiny yet incredibly complex technological artifacts, composed of millions and billions of individual structures working in unison. Managing their complexity and facilitating their design drove part of the co-evolution of mode ...

Superconducting qubits are among the most advanced candidates for achieving fault-tolerant quantum computing. Despite recent significant advancements in the qubit lifetimes, the origin of the loss mechanism for state-of-the-art qubits is still subject to i ...

Driven by the need for more efficient and seamless integration of physical models and data, physics -informed neural networks (PINNs) have seen a surge of interest in recent years. However, ensuring the reliability of their convergence and accuracy remains ...

The invention relates to methods for the preparation of method of preparation of Tau aggregates, including fibrils, fibrillar species, soluble and insoluble oligomeric species, new Tau aggregates and uses thereof. The invention further relates to the uses ...

Industrial information integration engineering (IIIE) is an interdisciplinary field to facilitate the industrial information integration process. In the age of complex and large-scale systems, model-based systems engineering (MBSE) is widely adopted in ind ...

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 ...

Previous studies have shown that access to a satisfactory view to the outside with sufficient daylight is essential for building occupants' health and well-being. It has also been suggested that certain features of visual content improve view-out quality, ...

System and method for monitoring quality of service

Chattez avec Graph Search

Extensions of Peer Prediction Incentive Mechanisms

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

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

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

Stability: a search for structure

Reduced Training Data for Laser Ultrasound Signal Interpretation by Neural Networks

High-order geometric integrators for the variational Gaussian wavepacket dynamics and application to vibronic spectra at finite temperature

SIMPLE HIERARCHICAL PLANNING WITH DIFFUSION

Data-driven statistical optimization of a groundwater monitoring network

Micropreparative Gel Electrophoresis for Purification of Nanoscale Bioconjugates

Efficient Continual Finite-Sum Minimization

A Reduced Order Model for Domain Decompositions with Non-conforming Interfaces

Graph generative deep learning models with an application to circuit topologies

Mechanically induced correlated errors on superconducting qubits with relaxation times exceeding 0.4 ms

Residual-based attention in physics-informed neural networks

Method of preparation of amyloidogenic protein aggregates and uses thereof

Design ontology for cognitive thread supporting traceability management in model-based systems engineering

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

Dynamism in the context of views out: A literature review