Tootfinder

The tool that transforms a very precise description of a problem and how it shall be solved into executable machine code is called a compiler¹ and not AI.
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¹or interpreter or anything between, these things get fuzzy, especially with JIT and virtual runtime environments

Virtual Laboratories: Domain-agnostic workflows for research
Carlos Sevilla-Salcedo, Armi Tiihonen, Mahsa Asadi, Kevin Sebastian Luck, Aras Umut Erarslan, Arto Klami, Samuel Kaski
https://arxiv.org/abs/2507.06271

Virtual Laboratories: Domain-agnostic workflows for research
Many scientific disciplines have traditionally advanced by iterating over hypotheses using labor-intensive trial-and-error, which is a slow and expensive process. Recent advances in computing, digitalization, and machine learning have introduced tools that promise to make scientific research faster by assisting in this iterative process. However, these advances are scattered across disciplines and only loosely connected, with specific computational methods being primarily developed for narrow d…

Multi-Loop Design of Virtual Synchronous Machine Control for DFIG-Based Wind Farms
Javier Garcia-Aguilar, Aurelio Garcia-Cerrada, Juan L. Zamora, Emilio Bueno, Elena Saiz, Almudena Mu\~noz-Babiano, Mohammad E. Zarei
https://arxiv.org/abs/2510.05043

Multi-Loop Design of Virtual Synchronous Machine Control for DFIG-Based Wind Farms
The displacement of synchronous generators by converter-interfaced renewable energy sources obliges wind farms to provide inertia, damping, and voltage support, above all in increasingly weak grid conditions. This paper presents a co-ordinated frequency-domain methodology for tuning all control layers of doubly-fed induction generators (DFIGs) within a wind farm operated as a Virtual Synchronous Machine (VSM). Starting from a full small-signal linearisation that preserves loop-to-loop and machi…

Constraint-Level Design of zkEVMs: Architectures, Trade-offs, and Evolution
Yahya Hassanzadeh-Nazarabadi, Sanaz Taheri-Boshrooyeh
https://arxiv.org/abs/2510.05376 https://

Constraint-Level Design of zkEVMs: Architectures, Trade-offs, and Evolution
Zero-knowledge Ethereum Virtual Machines (zkEVMs) must reconcile a fundamental contradiction: the Ethereum Virtual Machine was designed for transparent sequential execution, while zero-knowledge proofs require algebraic circuit representations. This survey provides the first systematic analysis of how existing major production zkEVM implementations resolve this tension through distinct constraint engineering strategies. We develop a comparative framework that maps the design space across three …

Crosslisted article(s) found for cs.HC. https://arxiv.org/list/cs.HC/new
[1/1]:
- Combine Virtual Reality and Machine-Learning to Identify the Presence of Dyslexia: A Cross-Lingui...
Materazzini, Morciano, Alcalde-Llergo, Yeguas-Bolivar, Calabro, Zingoni, Taborri

Ah yes, I am making a virtual machine entirely out of monads in C . C has always been Haskell and C hiding under a very big trenchcoat made from < and >

A virtual sensor fusion approach for state of charge estimation of lithium-ion cells
Davide Previtali, Daniele Masti, Mirko Mazzoleni, Fabio Previdi
https://arxiv.org/abs/2508.04268

A virtual sensor fusion approach for state of charge estimation of lithium-ion cells
This paper addresses the estimation of the State Of Charge (SOC) of lithium-ion cells via the combination of two widely used paradigms: Kalman Filters (KFs) equipped with Equivalent Circuit Models (ECMs) and machine-learning approaches. In particular, a recent Virtual Sensor (VS) synthesis technique is considered, which operates as follows: (i) learn an Affine Parameter-Varying (APV) model of the cell directly from data, (ii) derive a bank of linear observers from the APV model, (iii) train a m…

Quantum Machine Learning for Predicting Binding Free Energies in Structure-Based Virtual Screening
Pei-Kun Yang
https://arxiv.org/abs/2507.18425 https://ar…

Quantum Machine Learning for Predicting Binding Free Energies in Structure-Based Virtual Screening
In structure-based virtual screening, it is often necessary to evaluate the binding free energy of protein-ligand complexes by considering not only molecular conformations but also how these structures shift and rotate in space. The number of possible combinations grows rapidly and can become overwhelming. While classical computing has limitations in this context, quantum computing offers a promising alternative due to its inherent parallelism. In this study, we introduce a quantum machine lear…

Crosslisted article(s) found for cs.LG. https://arxiv.org/list/cs.LG/new
[3/5]:
- Improving Virtual Contrast Enhancement using Longitudinal Data
Fayolle, B\^one, Debs, Robert, Bourdon, Guillevin, Helbert

✨ Smartcard passthrough support, comprehensive resource monitoring dashboard, and many more features being added regularly to enhance functionality
🔧 Technical approach: #Electron application running Windows as virtual machine inside #Docker container, uses

The Cost Advantage of Virtual Machine Migrations: Empirical Insights into Amazon's EC2 Marketspace
Benedikt Pittl, Werner Mach, Erich Schikuta
https://arxiv.org/abs/2508.14883

The Cost Advantage of Virtual Machine Migrations: Empirical Insights into Amazon's EC2 Marketspace
In recent years, cloud providers have introduced novel approaches for trading virtual machines. For example, Virtustream introduced so-called muVMs to charge cloud computing resources while other providers such as Google, Microsoft, or Amazon re-invented their marketspaces. Today, the market leader Amazon runs six marketspaces for trading virtual machines. Consumers can purchase bundles of virtual machines, which are called cloud-portfolios, from multiple marketspaces and providers. An industry…

Accelerated Discovery of High-\k{appa} Oxides with Physics-Based Factorized Machine Learning
Atsushi Takigawa, Shin Kiyohara, Yu Kumagai
https://arxiv.org/abs/2509.26022 https:/…

Accelerated Discovery of High-\k{appa} Oxides with Physics-Based Factorized Machine Learning
Considerable effort continues to be devoted to the exploration of next-generation high-\k{appa} materials that combine a high dielectric constant with a wide band gap. However, machine learning (ML)-based virtual screening has remained challenging, primarily due to the low accuracy in predicting the ionic contribution to the dielectric tensor, which dominates the dielectric performance of high-\k{appa} materials. We here propose a joint ML model that predicts Born effective charges using an equ…

After more than 5 years I've finally written a post on my old blog because this post is longer. It's about my recent success of repurposing old hardware at the office to build a PC with two graphics cards. It hosts two virtual machines and each one has access to a dedicated Nvidia GPU.
With two monitors, mice and keyboards two people could even work on site at the same machine 😎 But this is primarily meant to provide remote desktops for I/O and editorial.

Real-Time Applicability of Emulated Virtual Circuits for Tokamak Plasma Shape Control
Pedro Cavestany (STFC Hartree Centre), Alasdair Ross (STFC Hartree Centre), Adriano Agnello (STFC Hartree Centre), Aran Garrod (STFC Hartree Centre), Nicola C. Amorisco (UK Atomic Energy Authority), George K. Holt (STFC Hartree Centre), Kamran Pentland (UK Atomic Energy Authority), James Buchanan (UK Atomic Energy Authority)

Real-Time Applicability of Emulated Virtual Circuits for Tokamak Plasma Shape Control
Machine learning has recently been adopted to emulate sensitivity matrices for real-time magnetic control of tokamak plasmas. However, these approaches would benefit from a quantification of possible inaccuracies. We report on two aspects of real-time applicability of emulators. First, we quantify the agreement of target displacement from VCs computed via Jacobians of the shape emulators with those from finite differences Jacobians on exact Grad-Shafranov solutions. Good agreement ($\approx$5-1…

Accelerating Transpilation in Quantum Machine Learning with Haiqu's Rivet-transpiler
Aleksander Kaczmarek, Dikshant Dulal
https://arxiv.org/abs/2508.21342 https://

Accelerating Transpilation in Quantum Machine Learning with Haiqu's Rivet-transpiler
Transpilation is a crucial process in preparing quantum circuits for execution on hardware, transforming virtual gates to match device-specific topology by introducing swap gates and basis gates, and applying optimizations that reduce circuit depth and gate count, particularly for two-qubit gates. As the number of qubits increases, the cost of transpilation escalates significantly, especially when trying to find the optimal layout with minimal noise under the qubit connectivity constraints impo…

EVMx: An FPGA-Based Smart Contract Processing Unit
Joel Poncha Lemayian, Hachem Bensalem, Ghyslain Gagnon, Kaiwen Zhang, Pascal Giard
https://arxiv.org/abs/2507.23518 https://…

EVMx: An FPGA-Based Smart Contract Processing Unit
Ethereum blockchain uses smart contracts (SCs) to implement decentralized applications (dApps). SCs are executed by the Ethereum virtual machine (EVM) running within an Ethereum client. Moreover, the EVM has been widely adopted by other blockchain platforms, including Solana, Cardano, Avalanche, Polkadot, and more. However, the EVM performance is limited by the constraints of the general-purpose computer it operates on. This work proposes offloading SC execution onto a dedicated hardware-based …

Data-Driven Energy Estimation for Virtual Servers Using Combined System Metrics and Machine Learning
Amandip Sangha
https://arxiv.org/abs/2509.09991 https://

Data-Driven Energy Estimation for Virtual Servers Using Combined System Metrics and Machine Learning
This paper presents a machine learning-based approach to estimate the energy consumption of virtual servers without access to physical power measurement interfaces. Using resource utilization metrics collected from guest virtual machines, we train a Gradient Boosting Regressor to predict energy consumption measured via RAPL on the host. We demonstrate, for the first time, guest-only resource-based energy estimation without privileged host access with experiments across diverse workloads, achiev…

Virtual Observatory and machine learning for the study of low-mass objects in photometric and spectroscopic surveys
Pedro Mas-Buitrago
https://arxiv.org/abs/2508.07998 https://

Virtual Observatory and machine learning for the study of low-mass objects in photometric and spectroscopic surveys
Low-mass objects are ubiquitous in our Galaxy. Their low temperature provides them with complex atmospheres characterised by the presence of strong molecular absorption bands which, together with their faintness, have made their accurate characterisation a great challenge for astronomers over the last decades. M dwarfs account for 75% of the census of stars within 10 pc of the Sun, and their suitability as targets in the search for Earth-like planets has led many research groups to focus on the…

An Online A/B Testing Decision Support System for Web Usability Assessment Based on a Linguistic Decision-making Methodology: Case of Study a Virtual Learning Environment
Noe Zerme\~no, Cristina Zuheros, Lucas Daniel Del Rosso Calache, Francisco Herrera, Rosana Montes
https://arxiv.org/abs/2507.12118

An Online A/B Testing Decision Support System for Web Usability Assessment Based on a Linguistic Decision-making Methodology: Case of Study a Virtual Learning Environment
In recent years, attention has increasingly focused on enhancing user satisfaction with user interfaces, spanning both mobile applications and websites. One fundamental aspect of human-machine interaction is the concept of web usability. In order to assess web usability, the A/B testing technique enables the comparison of data between two designs. Expanding the scope of tests to include the designs being evaluated, in conjunction with the involvement of both real and fictional users, presents a…

A High-performance Real-time Container File Monitoring Approach Based on Virtual Machine Introspection
Kai Tan, Dongyang Zhan, Lin Ye, Hongli Zhang, Binxing Fang, Zhihong Tian
https://arxiv.org/abs/2509.16030

A High-performance Real-time Container File Monitoring Approach Based on Virtual Machine Introspection
As cloud computing continues to advance and become an integral part of modern IT infrastructure, container security has emerged as a critical factor in ensuring the smooth operation of cloud-native applications. An attacker can attack the service in the container or even perform the container escape attack by tampering with the files. Monitoring container files is important for APT detection and cyberspace security. Existing file monitoring methods are usually based on host operating system or …

Towards Efficient VM Placement: A Two-Stage ACO-PSO Approach for Green Cloud Infrastructure
Ali M. Baydoun, Ahmed S. Zekri
https://arxiv.org/abs/2510.00541 https://

Towards Efficient VM Placement: A Two-Stage ACO-PSO Approach for Green Cloud Infrastructure
Datacenters consume a growing share of energy, prompting the need for sustainable resource management. This paper presents a Hybrid ACO-PSO (HAPSO) algorithm for energy-aware virtual machine (VM) placement and migration in green cloud datacenters. In the first stage, Ant Colony Optimization (ACO) performs energy-efficient initial placement across physical hosts, ensuring global feasibility. In the second stage, a discrete Particle Swarm Optimization (PSO) refines allocations by migrating VMs fr…

Challenging Disability and Interaction Norms in XR: Cooling Down the Empathy Machine in Waiting for Hands
Yesica Duarte, Puneet Jain
https://arxiv.org/abs/2507.15481

Challenging Disability and Interaction Norms in XR: Cooling Down the Empathy Machine in Waiting for Hands
Virtual Reality (VR) is often described as the "ultimate empathy machine," framing disability as an experience to be simulated through such technologies, which can reduce disability to a spectacle of pity or inspiration. In response, we present Waiting for Hands (WfH), an interactive eXtended Reality (XR) installation that critiques this logic by: (1) repurposing interaction norms in XR through the creation of Alternative Controllers, and (2) staging an absurd XR performance using the built con…

Replaced article(s) found for stat.ML. https://arxiv.org/list/stat.ML/new
[1/1]:
- Multi-task and few-shot learning in virtual flow metering
Kristian L{\o}vland, Bjarne Grimstad, Lars S. Imsland

You know, I still never got to the bottom of how I will cope with new storage devices being 4K native.
The problem I experience is that if I bitwise copy a virtual machine's block device from a 512B storage device to a 4KB storage device, it can no longer be booted. The (DOS MBR) partition table is wrong.
I haven't been able to come up with a way to do this without rsync of data filesystem to filesystem, which is not feasible for customer data.

Impact on transient stability of self-synchronisation control strategies in grid-forming VSC-based generators
Regulo E. Avila-Martinez, Xavier Guillaud, Javier Renedo, Luis Rouco, Aurelio Garcia-Cerrada, Lukas Sigrist
https://arxiv.org/abs/2509.04388

Impact on transient stability of self-synchronisation control strategies in grid-forming VSC-based generators
Grid-forming voltage source converters (GFM-VSCs) are emerging as a solution for integrating renewable energy resources (RERs) into power systems. GFM-VSCs need a self-synchronisation strategy to ensure that all converters and generators in the power system are in synchronism and they reach the same frequency in steady state. The self-synchronisation strategy in GFM-VSCs that has received most attention in previous research is virtual synchronous machine (VSM) control. However, no systematic st…

Explainable AI-Enhanced Supervisory Control for High-Precision Spacecraft Formation
Reza Pirayeshshirazinezhad
https://arxiv.org/abs/2509.13331 https://arx…

Explainable AI-Enhanced Supervisory Control for High-Precision Spacecraft Formation
We use artificial intelligence (AI) and supervisory adaptive control systems to plan and optimize the mission of precise spacecraft formation. Machine learning and robust control enhance the efficiency of spacecraft precision formation of the Virtual Telescope for X-ray Observation (VTXO) space mission. VTXO is a precise formation of two separate spacecraft making a virtual telescope with a one-kilometer focal length. One spacecraft carries the lens and the other spacecraft holds the camera to …

My #Linux machine is ready, my caffeine is brewing, and my virtual lightsaber is... probably still on cooldown. Time to stream some #SWTOR! What could go wrong? #StarWarsTheOldRepublic

Virtual Sensing for Solder Layer Degradation and Temperature Monitoring in IGBT Modules
Andrea Urgolo, Monika Stipsitz, Helios Sanchis-Alepuz
https://arxiv.org/abs/2508.10515 ht…

Virtual Sensing for Solder Layer Degradation and Temperature Monitoring in IGBT Modules
Monitoring the degradation state of Insulated Gate Bipolar Transistor (IGBT) modules is essential for ensuring the reliability and longevity of power electronic systems, especially in safety-critical and high-performance applications. However, direct measurement of key degradation indicators - such as junction temperature, solder fatigue or delamination - remains challenging due to the physical inaccessibility of internal components and the harsh environment. In this context, machine learning-b…

WireBend-kit: A Computational Design and Fabrication Toolkit for Wirebending Custom 3D Wireframe Structures
Faraz Faruqi, Josha Paonaskar, Riley Schuler, Aiden Prevey, Carson Taylor, Anika Tak, Anthony Guinto, Eeshani Shilamkar, Natarith Cheenaruenthong, Martin Nisser
https://arxiv.org/abs/2509.24083…

WireBend-kit: A Computational Design and Fabrication Toolkit for Wirebending Custom 3D Wireframe Structures
This paper introduces WireBend-kit, a desktop wirebending machine and computational design tool for creating 3D wireframe structures. Combined, they allow users to rapidly and inexpensively create custom 3D wireframe structures from aluminum wire. Our design tool is implemented in freely available software and allows users to generate virtual wireframe designs and assess their fabricability. A path-planning procedure automatically converts the wireframe design into fabrication instructions for …

Crosslisted article(s) found for cs.LG. https://arxiv.org/list/cs.LG/new
[5/7]:
- Virtual Consistency for Audio Editing
Matthieu Cervera, Francesco Paissan, Mirco Ravanelli, Cem Subakan
…

Past, Present and Future: Exploring Adaptive AI in Software Development Bots
Omar Elsisi, Glaucia Melo
https://arxiv.org/abs/2507.10822 https://

Past, Present and Future: Exploring Adaptive AI in Software Development Bots
Conversational agents, such as chatbots and virtual assistants, have become essential in software development, boosting productivity, collaboration, and automating various tasks. This paper examines the role of adaptive AI-powered conversational agents in software development, highlighting their ability to offer dynamic, context-aware assistance to developers. Unlike traditional rule-based systems, adaptive AI agents use machine learning and natural language processing to learn from interaction…

Human Digital Twin: Data, Models, Applications, and Challenges
Rong Pan, Hongyue Sun, Xiaoyu Chen, Giulia Pedrielli, Jiapeng Huang
https://arxiv.org/abs/2508.13138 https://

Human Digital Twin: Data, Models, Applications, and Challenges
Human digital twins (HDTs) are dynamic, data-driven virtual representations of individuals, continuously updated with multimodal data to simulate, monitor, and predict health trajectories. By integrating clinical, physiological, behavioral, and environmental inputs, HDTs enable personalized diagnostics, treatment planning, and anomaly detection. This paper reviews current approaches to HDT modeling, with a focus on statistical and machine learning techniques, including recent advances in anomal…