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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.
SYMTRI organizes observations from public sources into a living map. Connections reflect shared subject matter; they do not establish causation or endorse a source.
Open in the map ↗125 classified signals in the fourteen-day window. These counts include signals awaiting readable evidence.
Recent 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.
- Europe PMC · Published · First archived
Comparison of Lateral Decubitus versus Prone Lateral Lumbar Interbody Fusion Using Impact Scores: A Method to Quantify Intraoperative Supply Cost and Variability in Surgery. ↗
Surgical value metrics report intraoperative supply costs as aggregate institutional dollars, which do not identify which supply categories drive cost. To introduce the Impact Score, each supply category's percentage share of total intraoperative supply cost, as a descriptive framework and, using lateral decubitus (LD-LIF) versus prone lateral (PL-LIF) lateral lumbar interbody fusion as a proof of concept, to determine whether impact scores differ by supply category and align with median-cost rankings, whether exploratory outcome-based value metrics differ between approaches, and whether meani
- OpenAlex · Published · First archived
Density-Frequency Dual-Feature Fusion for Intelligent Reel Spoke Recognition ↗
The number and orientation of spokes are critical parameters for spray-path planning of cable reels. Aiming at the low efficiency of manual counting, contour fragmentation of slender structures caused by traditional edge detection, and the inability to automatically determine the spoke quantity, this paper proposes an automatic spoke-detection method based on radial density fusion and frequency-domain analysis. First, Hough-gradient-based circle transform is adopted to locate the outer-circle boundary, and a multi-feature fusion algorithm is utilized to accurately extract inner-circle paramete…
- OpenAlex · Published · First archived
IIGF-Net: An interpretability-driven intensity-geometry fusion framework for shield tunnel leakage segmentation in 3D point clouds ↗
Automated leakage detection from MLS-acquired 3D point clouds is essential for the preventive maintenance of shield tunnels. However, existing deep learning methods must reconcile the use of physically grounded handcrafted descriptors with the opaque representations learned by high-capacity networks. Without a principled means to verify whether handcrafted descriptors are effectively utilized by the trained network, descriptor design remains heuristic and the integration of domain knowledge with deep learning remains unverified. This study proposes an interpretability-driven intensity-geometry…
- Hacker News · Posted on Hacker News · First archived
Show HN: Geometry Check, a Fusion 360 add-in that finds slightly-wrong geometry ↗
Hacker News discussion.
- OpenAlex · Published · First archived
Physics-data fusion multi-modal deep learning for spindle current prediction in digital twin-driven machining state perception ↗
Accurate perception of machining states is essential for intelligent Computer Numerical Control (CNC) systems, yet modeling key process variables remains challenging due to the nonlinear and multi-modal nature of cutting processes. Empirical models lack adaptability, while purely data-driven methods often neglect physical constraints. Direct measurement of cutting force is challenging in practice, as complex workpiece geometries, limited ranges of detection instruments, and high deployment costs make large-scale force data acquisition difficult. Therefore, spindle current is adopted as a more…
- OpenAlex · Published · First archived
A Cue-Level Fusion Framework for Robust Soccer Player Tracking: Integrating Appearance, Motion, and Geometric Cues for Adaptive Tracklet Linking ↗
Cue-level fusion of complementary information channels—appearance for identity, motion for trajectory, and geometry for spatial consistency—is central to multi-object tracking in soccer broadcast videos, yet existing tracking-by-detection frameworks are validated mainly on pedestrian data. This paper proposes a cue-level fusion framework for soccer player tracking on the SoccerNet SN-Tracking dataset (57 train, 49 test sequences). Fusion is performed at two levels: (i) motion-appearance gating during online association, fusing Mahalanobis distance and cosine distance through gated cascade matc…
- OpenAlex · Published · First archived
Design of an intralayer data-based controller for laser powder bed fusion processing ↗
Abstract This paper proposes a data-based approach to reduce defect-prone process conditions during the additive manufacturing of Ti-6Al-4V alloy parts using the laser powder bed fusion technique. The focus is on controlling melt pool emissions intensity used as a temperature-related proxy generated as the laser interacts with the alloy powder to avoid processing conditions which generate defects such as lack-of-fusion (LOF) or keyhole porosity. A data-based controller is developed using photodiode signals from the melt pool emissions to predict future melt pool data and then update the contro…
- OpenAlex · Published · First archived
IonFusion: Multimodal Fusion for Hierarchical Classification and Functional Annotation of Ion Channels and Transporters ↗
Ion channels and transporters are diverse membrane proteins that regulate ion flux across biological membranes and play essential roles in cellular signaling, homeostasis, and physiological processes. Accurate classification and functional annotation of these proteins are important for characterizing membrane protein function, interpreting pathogenic mutations, and identifying therapeutic targets. However, classification of ion channels and transporters is complicated by similar fine-grained classes, hierarchical labels, and functional determinants spanning sequence motifs, domains, and struct…
- OpenAlex · Published · First archived
Dielectric and Measurement-Domain Feature Fusion for Machine Learning-Based Broadband Microwave Sensing: Application to Ethanol Concentration Estimation ↗
This study investigates the predictive capability of different microwave-derived feature types for machine learning-based ethanol concentration estimation in water–ethanol mixtures. Eleven mixtures were prepared at 10 wt.% concentration intervals, and cyclic measurements were performed over the 2–6 GHz frequency range to construct an experimental dataset. The input variables included conventional dielectric parameters together with reflection-based measurement features. Three ensemble regression models, namely Random Forest, Extra Trees, and XGBoost, were evaluated using group-wise 5-fold cros…
- OpenAlex · Published · First archived
A lightweight dynamic network framework based on feature complexity awareness and frequency-domain feature fusion for rail surface defect detection ↗
In real rail surface defect images, defect targets are small and the background is complex. Traditional deep learning methods struggle to capture small defect features, leading to low recognition accuracy. However, improving small-target recognition performance requires higher model complexity, which reduces running speed on edge computing devices and fails to meet real-time detection requirements. To address these problems, we propose a lightweight dynamic network framework based on feature complexity awareness and frequency-domain feature fusion for rail surface defect detection. This framew…
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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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