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Earlier sources: Fusion
This energy thread follows fusion through original research, public projects, and source reports. Read the evidence below to see which developments are represented in SYMTRI’s archive.
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Open in the map ↗129 classified signals in the fourteen-day window. These counts include signals awaiting readable evidence.
Earlier sources
Up to ten sources with readable evidence, ordered by their feed timestamp. These archive sources can be older than the live fourteen-day window. This list is a sample, not a measure of total activity. Dates distinguish paper publication, repository creation, model/dataset activity, Hacker News posts, and KEV catalog additions. “First archived” records when SYMTRI first stored the signal.
- OpenAlex · Published · First archived
Improving DDoS detection in cloud computing through deep learning and feature fusion with TWBO optimization ↗
Abstract A Distributed Denial of Service (DDoS) attack is considered a subclass of Denial of Service (DoS) that causes the severity of the attack in the cloud environment, and the actual service of the network is disturbed by several malicious attempts. One of the general forms of attack is a DDoS attack, which leads to substantial harm and negatively impacts the efficiency of cloud services. Hence, the hybrid Sequential Convolutional Neural Network with Taylor’s Wolf Bird Optimization (SCNN-TWBO) is introduced. The cloud is simulated initially, where the attacker stops the valid users from ac…
- OpenAlex · Published · First archived
An attention guided local global feature fusion network for robust point cloud registration ↗
Abstract Point cloud registration in complex environments remains challenging because measurement noise, partial overlap, and structural variations can reduce correspondence reliability and registration robustness, while computational efficiency is also critical for practical deployment. These difficulties are closely related to insufficient adaptive modeling of local geometric structures, inadequate suppression of weak global graph connections, and limited exploitation of inter-cloud similarity and discrepancy information. To address these issues, we propose AGLGNet, an attention guided local…
- OpenAlex · Published · First archived
Massively Multiplexed Photonic Chip With Cross‐Channel Fusion For Harmonized Biosensing ↗
ABSTRACT Accurate, label‐free analysis of complex biological mixtures is limited by poor multiplexing scalability and inconsistent responses across sensor samples. We introduce a transformative sensing platform that integrates large‐scale photonic multiplexing with data‐driven analytics to overcome these constraints. Our modular, affordable glass‐chip whispering–gallery–mode (WGM) photonic architecture is designed to support simultaneous readout of up to 100 sensing channels comprising over 10 000 high‐Q microresonators, exceeding existing multiplexing capabilities by more than two orders of m…
- OpenAlex · Published · First archived
Intelligent Ore Sorting Method Based on Multi-Feature Fusion of Dual-Energy X-Ray Responses ↗
The conventional attenuation-ratio feature R remains affected by particle thickness, material heterogeneity, and beam hardening in practical dual-energy X-ray transmission (DE-XRT) measurements. This study proposes an ore-sorting method based on multi-feature fusion of dual-energy X-ray transmission responses. An aluminium step wedge was used to establish a reference relationship between R and high-energy attenuation αH. The deviation from this relationship was defined as the residual feature Rc. Particle-level statistics of R, αH, and Rc were combined in a linear support vector machine (SVM)…
- OpenAlex · Published · First archived
USF-Net: a Unified Spatiotemporal Fusion Network for ground-based remote sensing cloud image sequence extrapolation ↗
Accurate extrapolation of ground-based cloud imagery is foundational to the stability of photovoltaic (PV) power generation systems. However, current methods rely on static kernels that neglect multi-scale cloud dynamics and lack robust temporal guidance for long-range dependency modelling. Moreover, the quadratic computational cost of standard attention mechanisms increases the computational burden of high-resolution inference. To bridge these gaps, we propose the Unified Spatiotemporal Fusion Network (USF-Net), whose principal methodological contribution lies in a directional temporal-to-spa…
- arXiv · Published · First archived
Real-time Tokamak Equilibrium Reconstruction Under Limited Experimental Data via Physics-Grounded Synthetic Pre-training ↗
Real-time equilibrium reconstruction is essential for tokamak plasma control. Data-driven surrogates are usually trained on high-quality labeled experimental data, but producing a large amount of labeled data sufficient for surrogate learning requires many expensive discharge shots, and few exist at the start of a new campaign or the operation of a new device. To reduce this cost, we propose to pre-train on simulated equilibria, generated at low cost by physics-based simulation, then fine-tune on limited real data. We evaluate under three settings with increasing difficulties, i.e., in-distrib…
- OpenAlex · Published · First archived
ASAF-MedRec: Auxiliary-supervised semantic alignment and fusion for medication recommendation ↗
Medication recommendation aims to predict appropriate medication combinations according to a patient’s clinical status. Existing methods have made important progress by modeling longitudinal EHR trajectories, medication relations, external knowledge graphs, molecular structures, and large language model (LLM) knowledge, but the direct semantic matching between textual patient conditions and candidate medication descriptions remains insufficiently explored. This paper investigates current-visit textual semantic matching and proposes ASAF-MedRec, an auxiliary-supervised semantic alignment and fu…
- OpenAlex · Published · First archived
Hierarchical Feature Fusion Reconstruction of Missing Acceleration Responses for Offshore Platforms ↗
Missing acceleration responses caused by sensor faults and transmission interruptions can compromise the reliability of structural health monitoring for offshore platforms. To address continuous data loss, this study proposes a hierarchical feature fusion reconstruction (HFFR) method. HFFR organizes response information at three complementary levels. Multi-scale local response morphology encoding captures local dynamic characteristics over different temporal neighborhoods, bidirectional temporal modeling exploits response evolution before and after the missing segment, and correlation-based ad…
- OpenAlex · Published · First archived
Systematic modelling of a large-scale, historicised, well-detailed building land use, with the fusion of massive and heterogeneous datasets ↗
Buildings are the primary venues for human activity. Generating precise numeric building models is of great interest for many applications. At regional and national scales, many different formalisms are employed to represent the various components of buildings, yet the building land use is frequently oversimplified - even when mixed-use buildings are considered. Inferring a realistic building land use, defined as an inventory of the distinct functional spaces hosted by a building, brings valuable knowledge for building models. Manual measurement can produce highly realistic interior models, bu…
- OpenAlex · Published · First archived
Cracked Blade Detection Method Through Data- and Decision-Level Vibration Fusion Framework ↗
As the core rotating components of the air supply system, the compressor and its blades are prone to crack initiation under long-term cyclic loading and high-temperature erosion. Failure to detect cracks in a timely manner may lead to blade fracture, subsequently causing catastrophic unit failure. Affected by environmental noise and the weak vibration signatures of blade cracks, the existing methods for detecting blade cracks lack sufficient accuracy and reliability. To address this problem, a cracked blade detection method is proposed based on a vibration deep fusion framework for compressors…
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How to assess evidence about Fusion
Check each original source for its methods, release status, limitations, and supporting data. A repository announcement, a preprint, and a published study provide different kinds of evidence. SYMTRI’s subject classification helps discovery; it does not independently validate the source’s claims.
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