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

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Blind use patterns significantly impact visual comfort and energy efficiency in office buildings. To quantify this impact on building performance, blind control occupant behaviour models (BC-OBMs) are typically integrated into building performance simulati ...

This work proposes a transfer learning-based encoder-decoder framework to predict the relationship between loading conditions and residual stiffness in carbon fiber reinforced composites and adhesives. The encoder, built from a Convolutional Neural Network ...

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Energy piles represent an innovative technology that can help provide sustainable geothermal heating or cooling energy for thermal conditioning purposes. In hot-dominated climates, the interest is to inject heat in the ground and extract energy for space-c ...

The combination of several interesting characteristics makes metal-organic frameworks (MOFs) a highly sought-after class of nanomaterials for a broad range of applications like gas storage and separation, catalysis, drug delivery, and so on. However, the e ...

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 ...

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 ...

Deep neural networks provide magnificent results for vision tasks. However, their complex structures and numerous parameters make them computationally and memory-wise intensive. Execution of these models on resource-constrained, camera-equipped devices suc ...

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 ...

The European Union's Green Deal aims for a 55% reduction in greenhouse gas emissions by 2030. To reach this goal, a massive integration of Renewable Energy Sources (RES) into the power grid is necessary. As RES become a large part of the electricity genera ...

Solar photovoltaics (PV) is one of the most competitive renewable energy technologies in order to meet the increasing global energy demand and decrease CO2 emissions by competing effectively with fossil fuels. One of the important applications of PV energy ...

Human babies have a natural desire to interact with new toys and objects, through which they learn how the world around them works, e.g., that glass shatters when dropped, but a rubber ball does not. When their predictions are proven incorrect, such as whe ...

In recent years, many efforts have been made to find alternative renewable energy sources that can ideally replace the use of fossil fuels in all aspects. One of the new emerging energy technologies is the bioelectrochemical system, of which two types are ...

The ability to reason, plan and solve highly abstract problems is a hallmark of human intelligence. Recent advancements in artificial intelligence, propelled by deep neural networks, have revolutionized disciplines like computer vision and natural language ...

Modern computing has enhanced our understanding of how social interactions shape collective behaviour in animal societies. Although analytical models dominate in studying collective behaviour, this study introduces a deep learning model to assess social in ...

The transition towards clean renewable energy sources, where wind and solar are prone to variation, requires adequate energy storage. Power-to-methane (PtM) systems can be part of the solution. Specifically, solid-oxide-electrolyser (SOE) based PtM systems ...

The field of biometrics, and especially face recognition, has seen a wide-spread adoption the last few years, from access control on personal devices such as phones and laptops, to automated border controls such as in airports. The stakes are increasingly ...

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

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Development of a blind control occupant behaviour model (BC-OBM) based on contextual and time-related factors through supervised machine learning approaches

Transfer learning-based approach for evaluating residual stiffness in carbon fiber reinforced composites and adhesives

Correlation of the L-mode density limit with edge collisionality

Sparse representations, inference and learning

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

Performance of energy piles foundation in hot-dominated climate: A case study in Dubai

Inverse design of metal-organic frameworks for direct air capture of CO2via deep reinforcement learning

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

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

Smart Edge for Hierarchical Vision Systems

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

Advanced control strategies to exploit the hydropower potential enhancing ancillary services provision to the power system

Reliability and Long-term Performance of Building Integrated Photovoltaic (BIPV) Modules

Seeking the new, learning from the unexpected: Computational models of surprise and novelty in the brain

Green hydrogen production using Shewanella oneidensis MR-1 bioanode and cuprous oxide-based photocathode

Infusing structured knowledge priors in neural models for sample-efficient symbolic reasoning

Predicting the long-term collective behaviour of fish pairs with deep learning

Design and assessment of an evaporating water-cooled methanation reactor for a SOE-based power-to-methane system

Performing and Detecting Backdoor Attacks on Face Recognition Algorithms