Tootfinder

from my link log —
Wasm SpecTec has been adopted.
https://webassembly.org/news/2025-03-27-spectec/
saved 2025-03-28 https://

SpecTec has been adopted - WebAssembly
WebAssembly (abbreviated Wasm) is a binary instruction format for a stack-based virtual machine. Wasm is designed as a portable compilation target for programming languages, enabling deployment on the web for client and server applications.

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…

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…

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…

Plug. Play. Persist. Inside a Ready-to-Go Havoc C2 Infrastructure
Alessio Di Santo
https://arxiv.org/abs/2507.00189 https://arxiv.org…

Plug. Play. Persist. Inside a Ready-to-Go Havoc C2 Infrastructure
This analysis focuses on a single Azure-hosted Virtual Machine at 52.230.23.114 that the adversary converted into an all-in-one delivery, staging and Command-and-Control node. The host advertises an out-of-date Apache 2.4.52 instance whose open directory exposes phishing lures, PowerShell loaders, Reflective Shell-Code, compiled Havoc Demon implants and a toolbox of lateral-movement binaries; the same server also answers on 8443/80 for encrypted beacon traffic. The web tier is riddled with publ…

Low Overhead Allocation Sampling in a Garbage Collected Virtual Machine
Christoph Jung, C. F. Bolz-Tereick
https://arxiv.org/abs/2506.16883 https://…

Low Overhead Allocation Sampling in a Garbage Collected Virtual Machine
Compared to the more commonly used time-based profiling, allocation profiling provides an alternate view of the execution of allocation heavy dynamically typed languages. However, profiling every single allocation in a program is very inefficient. We present a sampling allocation profiler that is deeply integrated into the garbage collector of PyPy, a Python virtual machine. This integration ensures tunable low overhead for the allocation profiler, which we measure and quantify. Enabling alloca…

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…

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 …

Instead of using butter with your garlic bread, you should switch to Linux. You can set up a virtual machine to try out various distros to see which one works best for your needs.

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…

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…

New Power Decoupling Method for Grid Forming Inverter Based on Adaptive Virtual-Synchronous Machine in Weak Grids
Waleed Breesam, Stefan M. Goetz
https://arxiv.org/abs/2506.18619 …

New Power Decoupling Method for Grid Forming Inverter Based on Adaptive Virtual-Synchronous Machine in Weak Grids
Many countries' policies have shifted rapidly towards using renewable energy for climate reasons. As a result, inverter-based resources are beginning to dominate power systems. Key elements for managing the loss of conventional generators are virtual-synchronous-generator-based grid-forming inverters. Despite the unique advantages of this technology, there are still various challenges, most notably the problem of active-reactive power coupling due to a nonzero power angle and high grid impedanc…

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…

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…

Efficient Memory Tiering in a Virtual Machine
Chandra Prakash, Aravinda Prasad, Sandeep Kumar, Sreenivas Subramoney
https://arxiv.org/abs/2506.06067 https:…

Efficient Memory Tiering in a Virtual Machine
Memory tiering is the norm to effectively tackle the increasing server memory total cost of ownership (TCO) and the growing data demands of modern data center workloads. However, the host-based state-of-the-art memory tiering solutions can be inefficient for a virtualized environment when (i) the frequently accessed data are scattered across the guest physical address space or (ii) the accesses to a huge page inside the guest are skewed due to a small number of subpages being hot. Scattered or …

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

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.

LANTERN: A Machine Learning Framework for Lipid Nanoparticle Transfection Efficiency Prediction
Asal Mehradfar, Mohammad Shahab Sepehri, Jose Miguel Hernandez-Lobato, Glen S. Kwon, Mahdi Soltanolkotabi, Salman Avestimehr, Morteza Rasoulianboroujeni
https://arxiv.org/abs/2507.03209

LANTERN: A Machine Learning Framework for Lipid Nanoparticle Transfection Efficiency Prediction
The discovery of new ionizable lipids for efficient lipid nanoparticle (LNP)-mediated RNA delivery remains a critical bottleneck for RNA-based therapeutics development. Recent advances have highlighted the potential of machine learning (ML) to predict transfection efficiency from molecular structure, enabling high-throughput virtual screening and accelerating lead identification. However, existing approaches are hindered by inadequate data quality, ineffective feature representations, low predi…

PhishingHook: Catching Phishing Ethereum Smart Contracts leveraging EVM Opcodes
Pasquale De Rosa, Simon Queyrut, Y\'erom-David Bromberg, Pascal Felber, Valerio Schiavoni
https://arxiv.org/abs/2506.19480

PhishingHook: Catching Phishing Ethereum Smart Contracts leveraging EVM Opcodes
The Ethereum Virtual Machine (EVM) is a decentralized computing engine. It enables the Ethereum blockchain to execute smart contracts and decentralized applications (dApps). The increasing adoption of Ethereum sparked the rise of phishing activities. Phishing attacks often target users through deceptive means, e.g., fake websites, wallet scams, or malicious smart contracts, aiming to steal sensitive information or funds. A timely detection of phishing activities in the EVM is therefore crucial …

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…

A System Level Compiler for Massively-Parallel, Spatial, Dataflow Architectures
Dirk Van Essendelft, Patrick Wingo, Terry Jordan, Ryan Smith, Wissam Saidi
https://arxiv.org/abs/2506.15875

A System Level Compiler for Massively-Parallel, Spatial, Dataflow Architectures
We have developed a novel compiler called the Multiple-Architecture Compiler for Advanced Computing Hardware (MACH) designed specifically for massively-parallel, spatial, dataflow architectures like the Wafer Scale Engine. Additionally, MACH can execute code on traditional unified-memory devices. MACH addresses the complexities in compiling for spatial architectures through a conceptual Virtual Machine, a flexible domain-specific language, and a compiler that can lower high-level languages to m…

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…

This https://arxiv.org/abs/2504.16552 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csDC_…

DTVM: Revolutionizing Smart Contract Execution with Determinism and Compatibility
We introduce the DeTerministic Virtual Machine (DTVM) Stack, a next-generation smart contract execution framework designed to address critical performance, determinism, and ecosystem compatibility challenges in blockchain networks. Building upon WebAssembly (Wasm) while maintaining full Ethereum Virtual Machine (EVM) ABI compatibility, DTVM introduces a Deterministic Middle Intermediate Representation (dMIR) and a hybrid lazy-JIT compilation engine to balance compilation speed and execution eff…

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…

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…

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…

MalVol-25: A Diverse, Labelled and Detailed Volatile Memory Dataset for Malware Detection and Response Testing and Validation
Dipo Dunsin, Mohamed Chahine Ghanem, Eduardo Almeida Palmieri
https://arxiv.org/abs/2507.03993

MalVol-25: A Diverse, Labelled and Detailed Volatile Memory Dataset for Malware Detection and Response Testing and Validation
This paper addresses the critical need for high-quality malware datasets that support advanced analysis techniques, particularly machine learning and agentic AI frameworks. Existing datasets often lack diversity, comprehensive labelling, and the complexity necessary for effective machine learning and agent-based AI training. To fill this gap, we developed a systematic approach for generating a dataset that combines automated malware execution in controlled virtual environments with dynamic moni…

On the Performance of Cloud-based ARM SVE for Zero-Knowledge Proving Systems
Dumitrel Loghin, Shuang Liang, Shengwei Liu, Xiong Liu, Pingcheng Ruan, Zhigang Ye
https://arxiv.org/abs/2506.09505

On the Performance of Cloud-based ARM SVE for Zero-Knowledge Proving Systems
Zero-knowledge proofs (ZKP) are becoming a gold standard in scaling blockchains and bringing Web3 to life. At the same time, ZKP for transactions running on the Ethereum Virtual Machine require powerful servers with hundreds of CPU cores. The current zkProver implementation from Polygon is optimized for x86-64 CPUs by vectorizing key operations, such as Merkle tree building with Poseidon hashes over the Goldilocks field, with Advanced Vector Extensions (AVX and AVX512). With these optimizations…

Static Analysis for Detecting Transaction Conflicts in Ethereum Smart Contracts
Zareh Chahoki Atefeh, Roveri Marco
https://arxiv.org/abs/2507.04357 https:/…

Static Analysis for Detecting Transaction Conflicts in Ethereum Smart Contracts
Ethereum smart contracts operate in a concurrent environment where multiple transactions can be submitted simultaneously. However, the Ethereum Virtual Machine (EVM) enforces sequential execution of transactions within each block to prevent conflicts arising from concurrent access to the same state variables. Although this approach guarantees correct behavior, it limits the ability of validators to leverage multi-core architectures for faster transaction processing, thus restricting throughput.…