Measurement Scheduling for Soil Moisture Sensing: From Physical Models to Optimal Control

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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 ...

Many challenges of modern graph processing stem from the fact that graphs have become massive and change frequently. Numerous techniques have been developed to address those issues, with graph cut sparsification offering to replace original graphs with th ...

This work aims to develop a scalable surrogate modelling framework for robust multidisciplinary design optimisation (RMDO) in complex engineering systems. Focusing on gas-bearing supported rotors, it addresses the need to maintain system performance under ...

In this work, we study online submodular maximization and how the requirement of maintaining a stable solution impacts the approximation. In particular, we seek bounds on the best-possible approximation ratio that is attainable when the algorithm is allowe ...

For robots to operate in unstructured environments, they are required to interact with objects through contact. Those contacts may be used to push objects to the side, deform objects, or manipulate objects in-hand. This thesis addresses the problem of cont ...

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 ...

Reduction in snow cover, depth, onset, and duration of seasonal snow in mid-latitude regions due to climate warming has multiple global and local scale ecosystem impacts. These effects include modulations of the hydrological cycles and increases in land su ...

Buildings play a pivotal role in the ongoing worldwide energy transition, accounting for 30% of the global energy consumption. With traditional engineering solutions reaching their limits to tackle such large-scale problems, data-driven methods and Machine ...

The aluminium sector relies on natural gas for the conversion of recycled scrap into new feedstock, which results in substantial atmospheric emissions. Hydric resources are also impacted, as they serve as heat sinks for the waste heat generated during the ...

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 ...

Healthcare sector buildings, particularly hospitals, significantly contribute to global energy consumption and greenhouse gas emissions. Hospitals require a substantial amount of steam, including the essential hygienic or " clean steam, " that is currently ...

The Tensor Isomorphism Problem (TIP) has been shown equivalent to the matrix code equivalence problem, making it an interesting candidate on which to build post-quantum cryptographic primitives. These hard problems have already been used in protocol develo ...

Frontal polymerisation has the potential to bring unprecedented reductions in energy demand and process time to produce fibre reinforced polymer composites. Production of epoxy-based fibre reinforced polymer parts with high fibre volume content, commonly e ...

Heating, Ventilation, and Air Conditioning (HVAC) Systems utilize much energy, accounting for 40% of total building energy use. The temperatures in buildings are commonly held within narrow limits, leading to higher energy use. Measurements from office bui ...

The scientific progress is significantly transforming contemporary society with the introduction and widespread application of technologies like artificial intelligence and quantum computing. Despite their profound impact, these technologies necessitate en ...

Operators from various industries have been pushing the adoption of wireless sensing nodes for industrial monitoring, and such efforts have produced sizeable condition monitoring datasets that can be used to build diagnosis algorithms capable of warning ma ...

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 ...

SKIPTRAIN is a novel Decentralized Learning (DL) algorithm, which minimizes energy consumption in decentralized learning by strategically skipping some training rounds and substituting them with synchronization rounds. These trainingsilent periods, besides ...

A frequency scaling governor is critical for the performance management of cloud servers, as it enhances energy efficiency and helps to control operational temperatures, thereby ensuring system reliability. However, our in-depth analysis of the application ...

The transition to sustainable energy demands a fundamental redesign of the electrical grid, especially at the distribution level. With the increasing deployment of distributed energy resources, the development of reliable models, accurate state estimation ...

Measurement Scheduling for Soil Moisture Sensing: From Physical Models to Optimal Control

Chattez avec Graph Search

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

Graph sparsification, sketching and adaptivity

Dimensionless Group-Driven Ensemble Neural Networks for Robust Design Optimisation in Engineering

The Cost of Consistency: Submodular Maximization with Constant Recourse

A Stochastic Approach to Contact-rich Manipulation

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

Effects of reduced snowpack due to climate warming on abiotic and biotic soil properties in alpine and boreal forest systems

Fusing Pre-existing Knowledge and Machine Learning for Enhanced Building Thermal Modeling and Control

Renewable energy integration and waste heat valorization in aluminum remelting for co-producing kerosene and methanol

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

Solar-assisted clean steam generator, a cleaner production approach for sustainable healthcare facilities

Solving the Tensor Isomorphism Problem for Special Orbits with Low Rank Points: Cryptanalysis and Repair of an Asiacrypt 2023 Commitment Scheme

Self-catalysed frontal polymerisation enables fast and low-energy processing of fibre reinforced polymer composites

DIET Controller: Dynamic Indoor Environment using Deep Reinforcement Learning

Electrical and Optical Manifestations of Flat Band Physics in Van der Waals Materials

Federated learning with uncertainty-based client clustering for fleet-wide fault diagnosis

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

Energy-Aware Decentralized Learning with Intermittent Model Training

Is the powersave governor really saving power?

Estimation and control under uncertainty with application to power systems