Uncertainty modeling of household appliance loads for smart energy management

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Context. Imaging in radio interferometry requires solving an ill-posed noisy inverse problem, for which the most adopted algorithm is the original CLEAN algorithm and its variants. Alternative explicit optimization methods have gained increasing attention, ...

This study integrates deep learning and geospatial analysis to enhance soil loss estimation in the Moulouya Watershed, a region prone to erosion due to diverse topography and climatic conditions. Traditional models like the Universal Soil Loss Equation (US ...

Measurements are presented of inclusive and differential cross sections for Z boson associated production of top quark pairs (t (t) over barZ) and single top quarks (tZq or tWZ). The data were recorded in proton-proton collisions at a center-of-mass energy ...

The first observation of the

{{{{\varXi } ^0_{b}} \!\rightarrow {{J \hspace{-1.66656pt}/\hspace{-1.111pt}\psi }} {{\varXi } ^-} {{\pi } ^+} }}

decay and the most precise measurement of the branching fraction of the ${{{\varLambda } ^0_{b}} !\rightarrow ...

Developing agents that can reliably act on our behalf is central to artificial intelligence (AI). These agents must seamlessly interact with tools, like search engines and databases, and collaborate. In this thesis, we study the abstractions, methods, and ...

Accurate and reliable electricity load forecasts are becoming increasingly important as the share of intermittent resources in the system increases. Distribution System Operators (DSOs) are called to accurately forecast their production and consumption to ...

Global water models allow us to explore the terrestrial water cycle in earth-sized digital laboratories to support science and guide policy. However, these models are still subject to considerable but also reducible uncertainties that can be attributed to ...

To support the decarbonisation of the power sector and offset the volatility of a system with high levels of renewables, there is growing interest in residential Demand-Side Management (DSM) solutions. Traditional DSM strategies require consumers to active ...

Most codes of practice adopt a semi probabilistic design approach for the dimensioning and assessment of structures. Accordingly, structural safety is ensured by performing limit state verifications using design values determined with adequately calibrated ...

In this work, we examine a network of agents operating asynchronously, aiming to discover an ideal global model that suits individual local datasets. Our assumption is that each agent independently chooses when to participate throughout the algorithm and t ...

The thesis explores the issue of fairness in the real-time (RT) control of battery energy storage systems (BESSs) hosted in active distribution networks (ADNs) in the presence of uncertainties by proposing and experimentally validating appropriate control ...

In robotic throwing, the release phase involves complex dynamic interactions due to object deformation and limited gripper opening speed, often resulting in inaccurate and nonrepeatable throws. While data-driven methods can be employed to compensate for th ...

Quantification of multiple drugs is of great importance and urgently needed in therapeutic drug monitoring (TDM) and personalized therapy. Especially, based on cyclic voltammograms (CVs) obtained by electrochemical sensors, the use of artificial neural net ...

The global energy system transforming from fossil fuels to renewable green energy through the adaption of innovative and dynamic green technologies. Energy-saving buildings (ESBs) are attracting extensive attention as intelligent architectures capable of s ...

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 ...

Aluminium is one of the most widely used metals in the world, but its production is highly energy intensive and largely dependent on the use of fossil fuels. A typical secondary aluminium production facility consumes 700-1,000 kWh of natural gas and 200-40 ...

High Damping Rubber Bearings (HDRBs) are widely used in seismic isolation of structures, and their force-deformation constitutive behavior controls the lateral structural response during an earthquake. However, given the many components and steps involved ...

Liquid composite moulding methods are widely applied for manufacturing of fibre reinforced polymer (FRP) composites and consist of two main stages: impregnation of fibrous reinforcements by a liquid monomer resin and curing of this resin. This thesis work ...

Nowadays, the integration of home automation systems with smart thermostats is a common trend, designed to enhance resident comfort and conserve energy. The introduction of smart thermostats that can run machine learning algorithms has opened the door for ...

Uncertainty modeling of household appliance loads for smart energy management

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PolyCLEAN: Atomic optimization for super-resolution imaging and uncertainty estimation in radio interferometry

Application of Deep Learning and Geospatial Analysis in Soil Loss Risk in the Moulouya Watershed, Morocco

Measurements of Inclusive and Differential Cross Sections for Top Quark Production in Association with a Z Boson in Proton-proton Collisions at √s=13 Tev

Observation of the ${{{\varLambda } ^0_{b}} \!\rightarrow {{J \hspace{-1.66656pt}/\hspace{-1.111pt}\psi }} {{\varXi } ^-} {{K} ^+} }$ and ${{{{\varXi } ^0_{b}} \!\rightarrow {{J \hspace{-1.66656pt}/\hspace{-1.111pt}\psi }} {{\varXi } ^-} {{\pi } ^+} }}$ decays

Collaborative AI Agents in the Era of Large Language Models

Probabilistic Load Forecasting of distribution power systems based on empirical copulas

Uncertainties as a Guide for Global Water Model Advancement

Beyond the average consumer: Mapping the potential of demand-side management among patterns of appliance usage

Influence of model uncertainty and long term deformations in action effects calculation in reinforced concrete structures

Asynchronous Diffusion Learning with Agent Subsampling and Local Updates

Fair real-time control of energy storage systems in active distribution networks in the presence of uncertainties

Tube Acceleration: Robust Dexterous Throwing Against Release Uncertainty

Optimized Quantification of Multiple Drug Concentrations by WeightedMSE With Machine Learning on Electrochemical Sensor

Smart Photovoltaic Windows for Next-Generation Energy-Saving Buildings

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

Modelling The Effect of Future Uncertainty in Energy Prices on Decarbonization Pathways for Secondary Aluminium Production

UNCERTAINTY QUANTIFICATION IN THE CONSTITUTIVE BEHAVIOR OF HDRBs

Strategies for energy-efficient frontal polymerisation processing and microstructural evaluation of fibre reinforced composites

PePTM: An Efficient and Accurate Personalized P2P Learning Algorithm for Home Thermal Modeling