Tangible Interfaces for Learning : Training Spatial Skills in Vocational Classrooms

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High-entropy alloys (HEAs), containing several metallic elements in near-equimolar proportions, have long been of interest for their unique mechanical properties. More recently, they have emerged as a promising platform for the development of novel heterog ...

The official Spherical Tokamak for Energy Production mission aims to demonstrate the ability to generate net electricity from fusion with the STEP Prototype Power plant. One of the key technological and engineering challenges in fusion power plants is mana ...

Dynamic aperture is an important concept for the study of non-linear beam dynamics in circular accelerators. It describes the extent of the phase-space region where a particle's motion remains bounded over a given number of turns. Understanding the feature ...

Superconducting electronics provide us with cryogenic digital circuits that can rival established technologies in performance and energy consumption. Today, the lack of tools for the design of large-scale integrated superconducting circuits is a major obst ...

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In the past few years, Machine Learning (ML) techniques have ushered in a paradigm shift, allowing the harnessing of ever more abundant sources of data to automate complex tasks. The technical workhorse behind these important breakthroughs arguably lies in ...

Type inference in the presence of first-class or "impredicative" second-order polymorphism a la System F has been an active research area for several decades, with original works dating back to the end of the 80s. Yet, until now many basic problems remain ...

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The design and control of winged aircraft and drones is an iterative process aimed at identifying a compromise of mission-specific costs and constraints. When agility is required, shape-shifting (morphing) drones represent an efficient solution. However, m ...

Distributed learning is the key for enabling training of modern large-scale machine learning models, through parallelising the learning process. Collaborative learning is essential for learning from privacy-sensitive data that is distributed across various ...

Reinforcement learning (RL) is crucial for learning to adapt to new environments. In RL, the prediction error is an important component that compares the expected and actual rewards. Dopamine plays a critical role in encoding these prediction errors. In my ...

We present a new algorithm for imitation learning in infinite horizon linear MDPs dubbed ILARL which greatly improves the bound on the number of trajectories that the learner needs to sample from the environment. In particular, we re- move exploration assu ...

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In the development of implantable bioelectronics, the establishment of efficient wireless RF links between implants and external nodes is crucial, providing substantial contributions to the advancement of medical diagnosis, therapies, and basic science. Im ...

Light and sound waves can move objects through the transfer of linear or angular momentum, which has led to the development of optical and acoustic tweezers, with applications ranging from biomedical engineering to quantum optics. Although impressive manip ...

Tangible Interfaces for Learning : Training Spatial Skills in Vocational Classrooms

Chat with Graph Search

Surface segregation in high-entropy alloys from alchemical machine learning

Models implemented in the methodological approach to design the initial STEP first wall contour

Optimizing Dynamic Aperture Studies with Active Learning

Technology-Aware Logic Synthesis for Superconducting Electronics

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

Topics in statistical physics of high-dimensional machine learning

When Subtyping Constraints Liberate A Novel Type Inference Approach for First-Class Polymorphism

Transversal skills priorities and curricular support as experienced by engineering students on their path to becoming responsible engineers

Co-Design Optimisation of Morphing Topology and Control of Winged Drones

Optimization Algorithms for Decentralized, Distributed and Collaborative Machine Learning

Unveiling the complexity of learning and decision-making

Imitation Learning in Discounted Linear MDPs without exploration assumptions

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

Electromagnetic Radiation of Implantable Antennas

Wave-momentum shaping for moving objects in heterogeneous and dynamic media