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2,492 papers
LiteDANN, a lightweight semi-supervised domain-adaptation framework for cross-condition bearing fault diagnosis, provides a practical basis for real-time bearing diagnosis on resource-constrained edge platforms.
Our research topic has inspired studies on new results on lightweight computer vision (CV) models and edge deployment strategies for crop production. With the proliferation of unmanned aerial vehicles (UAVs), autonomous harvesters, and Internet-of-Things (IoT) devices in agriculture, the demand for efficient, accurate,...
Addressing the extremely complex challenges of high-dynamic and highly reflective spatial perception in industrial environments, this paper innovatively proposes a large-model-driven vision-language cross-modal semantic SLAM and heuristic topology planning architecture. The system achieves zero-sample 3D geometric matc...
Cloud computing and the Internet of Things (IoT) have emerged as transformative technologies driving digital innovation across industries. Cloud computing offers scalable, on-demand computing resources, while IoT interconnects billions of physical devices to generate real-time data for intelligent decision-making. T...
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Neutron computed tomography (nCT) was acquired from a corner of each sample to guarantee that a distinct edge remained visible during the full rotation.
This paper addresses the shortcomings of single-sensor modal representation capabilities and fragmented features in virtual model space during the operation and maintenance of complex mechanical equipment. A predictive maintenance algorithm framework coupling target detection and digital twins is proposed. By construct...
A preregistration, deposited before any confirmatory production run under the protocol it specifies, for an information-theoretic analysis of per-history fluctuations in Monte Carlo water radiolysis (OpenTOPAS / TOPAS-nBio, Geant4-DNA IRT chemistry). The data matrix has one row per particle history and one column per c...
A transição do monitoramento de ativos e da manutenção preditiva para dispositivos de borda (Edge Computing) enfrenta um severo gargalo tecnológico: o processamento matemático intensivo em microcontroladores de baixo custo. Este artigo técnico apresenta uma proposta inédita de arquitetura de software não-bloqueante par...
MetaFlux v2.4.0 Two things in this release. An optional phylogeny stage for 16S data, which is off by default, and a set of changes that make an amplicon run reproducible from the raw reads to the final tree — that second part applies to every amplicon run whether or not the phylogeny stage is ever switched on. Reprodu...
This paper develops the next foundational layer of the AASC formalism: the exact structure of admissibility once non-degenerate determinate construction has already incurred the kernel roles of Admissibility, Standing, Reference, and Irreversibility. Its central contribution is to distinguish three questions that are o...
The transition of asset monitoring and predictive maintenance to Edge Computing devices faces a severe technological bottleneck: intensive mathematical processing on low-cost microcontrollers. This technical report presents a novel non-blocking software architecture to solve this challenge, enabling prescriptive autono...
Lossless prime-space encoding of natural language, the measured Betti-number topology of the knowledge manifold, and a ten-law constitution proved in Lean 4, Python, and C. DISCLAIMER — READ THIS FIRST: HOW THIS WAS MADE This deposit is honest about its own authorship, because honesty is the entire thesis. The machine...
By rethinking how large cloud computing systems operate, Associate Professor Christina Delimitrou seeks to make data centers more energy efficient.
An ongoing survey tracks the latest AI accelerator systems to keep hardware relevant for Lincoln Laboratory staff and sponsors.
Jennifer Neville did not want to go into computer science—but that’s exactly where she landed. Neville discusses the starts and stops that led to her professional sweet spot and her work identifying “surprising failures” making it hard for AI to handle complexity. The post What AI gets wrong and what failure teaches us appeared first on Microsoft Research.
Associate Professor Cathy Wu uses reinforcement learning to help map out improvements to transportation and other multifaceted systems.
Announcing Gemini 4 Argon, our frontier model for real-world coding, enterprise knowledge work and cyber defense, rolling out soon.
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