Mental vision: a computer graphics teaching platform

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Let K be an algebraically closed field of characteristic zero, and let G be a connected reductive algebraic group over K. We address the problem of classifying triples (G, H, V ), where H is a proper connected subgroup of G, and V is a finitedimensional ir ...

Motion forecasting is crucial in enabling autonomous vehicles to anticipate the future trajectories of surrounding agents. To do so, it requires solving mapping, detection, tracking, and then forecasting problems, in a multi-step pipeline. In this complex ...

Because building-integrated photovoltaic (BIPV) modules are fully integrated into a building envelope, the back of the module can be exposed to little or no ventilation, resulting in increased operating temperatures. As the temperature increases, the perfo ...

This study explores the differences in performance and results by various versions of the ISORROPIA thermodynamic module implemented within the ECHAM/MESSy Atmospheric Chemistry (EMAC) model. Three different versions of the module were used, ISORROPIA II v ...

Modular robotics link the reliability of a centralised system with the adaptivity of a decentralised system. It is difficult for a robot with a fixed shape to be able to perform many different types of tasks. As the task space grows, the number of functi ...

This paper aims to propose an implementation framework for the adoption and management of Open Educational Resources (OER), focusing on their lifecycle, as well as the integration of AI for supporting educators in their classification of the created conten ...

A correspondence functor is a functor from the category of finite sets and correspondences to the category of k-modules, where k is a commutative ring. By means of a suitably defined duality, new correspondence functors are constructed, having remarkable p ...

Computing light reflection from rough surfaces is an important topic in computer graphics. Reflection models developed based on geometric optics fail to capture wave effects such as diffraction and interference, while existing models based on physical opti ...

In high energy physics, semiconductor-based sensors are widely used in particle tracking applications. These sensors are typically glued on low-mass cooling substrates, which guarantee the correct thermal management and, at the same time, minimise their in ...

In recent years, there has been a significant revolution in the field of deep learning, which has demonstrated its effectiveness in automatically capturing intricate patterns from large datasets. However, the majority of these successes in Computer Vision ...

Regulation of gene expression is a complex but highly guided process. While genomic technologies and computational approaches have allowed high-throughput mapping of cis-regulatory elements (CREs) and their interactions in 3D, their precise role in regulat ...

Current Dynamic Texture Synthesis (DyTS) models can synthesize realistic videos. However, they require a slow iterative optimization process to synthesize a single fixed-size short video, and they do not offer any post-training control over the synthesis p ...

The high-efficiency silicon heterojunction (SHJ) technology is now perceived mature enough to enter the Giga-Watt manufacturing scale with several players around the globe. The growth of the SHJ technology requires confidence from manufacturers, investors, ...

As historical stone masonry structures are vulnerable and prone to damage in earthquakes, investigating their structural integrity is important to reduce injuries and casualties while preserving their historical value. Stone masonry is a composite material ...

Let G be either a simple linear algebraic group over an algebraically closed field of characteristic l>0 or a quantum group at an l-th root of unity. The category Rep(G) of finite-dimensional G-modules is non-semisimple. In this thesis, we develop new tech ...

Neurons are characterized by thin and long interleaving arborizations in which creating accurate mesh models of their cellular membranes is challenging. While union operators are central for CAD/CAM modeling and computer graphics applications, their applic ...

We present DARKFLUX, a software tool designed to analyze indirect-detection signatures for next-generation models of dark matter (DM) with multiple annihilation channels. Version 1.0 of this tool accepts user-generated models with 2 -> 2 tree-level dark ma ...

In many situations, the data one has access to at test time follows a different distribution from the training data. Over the years, this problem has been tackled by closed-set domain adaptation techniques. Recently, open-set domain adaptation has emerged ...

Corrosion is one of the main end-of-life degradation and failure modes in photovoltaic (PV) modules. However, it is a gradual process and can take many years to become a major risk factor because of the slow accumulation of water and acetic acid (from enca ...

In this thesis, we advocate that Computer-Aided Engineering could benefit from a Geometric Deep Learning revolution, similarly to the way that Deep Learning revolutionized Computer Vision. To do so, we consider a variety of Computer-Aided Engineering pr ...

Mental vision: a computer graphics teaching platform

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Multiplicity-free Representations of Algebraic Groups

Towards Motion Forecasting with Real-World Perception Inputs: Are End-to-End Approaches Competitive?

Correlating long-term performance and aging behaviour of building integrated PV modules

Implementation of the ISORROPIA-lite aerosol thermodynamics model into the EMAC chemistry climate model (based on MESSy v2.55): implications for aerosol composition and acidity

Memento Mori: Reliable robustness in self-reconfigurable modular robots

Implementation Framework and Strategies for AI-augmented Open Educational Resources (OER): A Comprehensive Approach Applied to Secondary and Higher Education

Correspondence functors and duality

A Full-Wave Reference Simulator for Computing Surface Reflectance

Interlocking modular microfluidic cooling substrates for future high energy physics experiments

Deep Learning for 3D Surface Modelling and Reconstruction

Chromatin modules and their implication in genomic organization and gene regulation

DyNCA: Real-time Dynamic Texture Synthesis Using Neural Cellular Automata

Long-term performance and reliability of silicon heterojunction solar modules

Geometrical Treatise on the Modelling of 3D Particulate Inclusion-Matrix Microstructures with an Application to Historical Stone Masonry Walls

Generic direct summands of tensor products for simple algebraic groups and quantum groups at roots of unity

Meshing of Spiny Neuronal Morphologies using Union Operators

DARKFLUX: A new tool to analyze indirect-detection spectra of next-generation dark matter models

Learning to Generate the Unknowns as a Remedy to the Open-Set Domain Shift

Corrosion testing of solar cells: Wear-out degradation behavior

Synthesis and Analysis of 3D shapes with Geometric Deep Learning in Computer-Aided Engineering