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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.
- arXiv · Published · First archived
Observer-Based Model Predictive Control for Isoflux Regulation in the EXL-50U Spherical Tokamak ↗
Isoflux control in spherical tokamaks requires coordinated plasma-current and boundary regulation under coil-voltage and computational constraints. This study develops observer-based constrained model predictive control (MPC) for EXL-50U. Vacuum-vessel spatial coarsening reduces a 538-state linearized model to 40 states while retaining control-relevant responses. A Kalman observer provides full-state estimates, and MPC jointly optimizes current and boundary-flux tracking with explicit voltage bounds. Matrix precomputation, specialized solver code generation, and structured linear-system soluti…
- OpenAlex · Published · First archived
A casting defect detection algorithm based on multi-dimensional efficient feature fusion convolution ↗
In the sand casting process, identifying and sorting defects such as surface porosity, inclusions, and cracks are crucial for ensuring casting quality. Existing casting defect detection algorithms are deficient in recognition accuracy and detection efficiency. To solve these problems, this study proposes an improved convolutional layer architecture based on the YOLOv8 model: efficient feature fusion convolution (EFFC) and multi-dimensional efficient feature fusion convolution (MEFFC). These architectures can simultaneously capture multi-scale features of casting defects while maintaining high…
- OpenAlex · Published · First archived
Symmetry and Asymmetry in Adaptive Selection and Fuzzy Fusion for Industrial Anomaly Detection: The MSPNet Framework ↗
Unsupervised industrial anomaly detection learns from normal images and identifies defects unseen during training. In reconstruction-based detectors, the features used to represent normality and the residuals used to localize defects vary across images, yet these signals are commonly selected with fixed category-level rules. We propose MSPNet, a Mirrored Selection Policy Network that learns these choices from validation performance. Its feature selection policy chooses channels that characterize normal appearance, and its residual selection policy chooses residuals for localization. The polici…
- OpenAlex · Published · First archived
Auditing Multimodal Fusion Benchmarks: Leakage, Attribution, and Calibration in Elderly Fall Detection ↗
Reported gains from multimodal fusion, feature-attribution explanations, and model-confidence scores are only as trustworthy as the evaluation protocol and preprocessing pipeline behind them, yet these are rarely audited together. We develop a benchmarking-and-auditing methodology addressing four failure points jointly, subject-overlapping evaluation, class-imbalance correction under a subject-wise split, feature attribution, and calibration, instantiated on seven models under leave-one-subject-out (LOSO) cross-validation spanning three encoder-backbone pairings and early, late, and hybrid fus…
- OpenAlex · Published · First archived
ASIF: A Resource-Aware Selective Network Traffic Inspection Framework Integrating Certificate Screening, Targeted Decryption, and Feature Fusion ↗
The widespread use of TLS in IoT and networked systems increases inspection cost while restricting direct access to payload content. This paper presents the Adaptive Secure Inspection Framework (ASIF), a resource-aware selective network traffic inspection framework that coordinates certificate-based routing, authorized targeted decryption, known-signature matching, and learned flow classification. ASIF contains three components: (1) a Certificate Screening Module (CSM), which applies configured checks of root trust, chain integrity, and leaf-certificate validity as an early routing signal; (2)…
- OpenAlex · Published · First archived
A rotor dynamic balancing method without trial weights based on multi-sensor feature fusion with an attention mechanism ↗
Accurate identification of unbalance parameters lies at the core of rotor dynamic balancing technology. In this paper, a deep learning approach is integrated with rotor dynamic balancing theory, and a multi-sensor feature fusion dynamic balancing method without trial weights based on the attention mechanism is proposed. First, considering the unique nature of the dynamic balancing process, a rotor model with varying unbalance parameters was established, and the dataset for model training was augmented by adding bandpass noise. Subsequently, a neural network model for unbalance identification b…
- OpenAlex · Published · First archived
MA-YOLO for robust multimodal feature fusion under weak cross-modal alignment in remote sensing object detection ↗
Abstract Multimodal remote sensing object detection benefits from the complementary characteristics of visible and infrared modalities. However, owing to the heterogeneous imaging mechanisms of RGB and infrared sensors, feature representations from the two modalities progressively become semantically inconsistent during hierarchical feature extraction, even when the input image pairs are geometrically registered. Such feature-level semantic inconsistency weakens the robustness of multimodal feature fusion and ultimately degrades object localization accuracy. To address this issue, we propose M…
- arXiv · Published · First archived
Implicit-Explicit time integration scheme with Physics-based preconditioning for two-fluid tokamak boundary simulations ↗
In this work, a globally stiffly accurate Implicit-Explicit (IMEX) Runge-Kutta scheme is developed and implemented in the GBS code [Ricci et al., Plasma Phys. Control. Fusion, 2012], for two-fluid plasma turbulence simulations. The stiffest phenomena, governed by shear Alfvén waves and parallel diffusion, are treated implicitly, while the remaining non-stiff terms are advanced explicitly. This splitting enables time steps well beyond the Courant-Friedrichs-Lewy limit, without incurring the full computational cost of a globally implicit formulation. To efficiently solve the implicit subsystem a…
- arXiv · Published · First archived
A Rapid Integrated Tokamak Modelling Approach for Coupled Profile and Equilibrium Evolution ↗
During plasma heating and current ramps the thermal and magnetic states of a tokamak evolve on different timescales. We present a rapid integrated tokamak modelling approach, which couples a variational fixed-boundary Grad--Shafranov equilibrium to sparse particle and energy flux matching and to weak-form current diffusion. An ITER-like pure-deuterium scenario is examined: a current ramp from 10 to 15~MA over 20~s, a 20~s flat-top and a 20~s ramp-down to 14~MA, under 80~MW of electron-cyclotron heating applied at the start. The toroidal current density at the pedestal top more than doubles dur…
- OpenAlex · Published · First archived
Real-time recognition model of 3D workpiece for transmission tower based on uniseg3d and vision-inertia fusion ↗
To tackle the challenges existing in point cloud segmentation for transmission tower components-specifically, weak small-target perception, blurred boundaries, poor cross-scene adaptability, and insufficient real-time performance-this study develops a real-time recognition model by integrating LiDAR-IMU with UniSeg3D. The core contribution lies in formulating a systematic solution architecture. First, to address the issues of small targets and boundary ambiguity, a multi-scale boundary-aware module is designed. By jointly optimizing classification and boundary losses, it substantially strength…
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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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