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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
Multi-modal feature fusion and classification of histopathological images using ensemble learning ↗
Early and correct detection of cancer regions in histopathology images is important for timely diagnosis and treatment. In this work, we proposed a Explainable Artificial Intelligence based convolutional Neural network (CNN) framework for the classification of lung and colon cancer. The framework combines deep features from a CNN with hand-crafted features in a single hybrid feature pipeline. From each image, we first extract a 512-dimensional feature vector using a CNN. We then join this vector with 6084 HOG features and 10 LBP features to obtain a 6606-dimensional feature vector. To remove r…
- OpenAlex · Published · First archived
Multi-view stereo-based 3D modeling of waste pits in waste-to-energy plants with spatial-context feature fusion ↗
Three-dimensional (3D) modeling of waste pits can support waste pile monitoring and crane-assisted feeding in waste-to-energy (WtE) plants. RGB image-based multi-view stereo (MVS) offers a flexible perception route, but its performance remains limited by non-uniform illumination, weakly textured waste surfaces, local specular highlights, occlusion, and changes in pile morphology. This study aims to improve the reconstruction continuity and relative accuracy of RGB-MVS under these waste-pit-oriented visual conditions. To this end, SCFM-MVSNet is proposed by introducing a Spatial-Context Fusion…
- OpenAlex · Published · First archived
Damaged Building Identification in Earthquake-Stricken Areas Based on Multi-Feature Fusion of Optical and SAR Imagery ↗
Rapid and reliable damaged building identification after earthquakes is of great significance for emergency rescue and post-disaster assessment. Remote sensing imagery provides important technical support for post-earthquake building damage assessment. To address the strong interference from background land-cover types in earthquake-stricken areas and the insufficient stability of damage identification based on single data source, this study proposes an optical–SAR multi-feature collaborative framework for damaged building identification. Firstly, by using pre-earthquake GF-2 optical imagery a…
- OpenAlex · Published · First archived
A Fusion Framework Integrating UAV LiDAR and SBAS-InSAR for Enhanced Mining-Induced Surface Subsidence Modeling ↗
To address the differences in spatial resolution, monitoring accuracy, and applicability across different subsidence-gradient conditions between Digital Subsidence Models (DSuMs) derived from UAV LiDAR and SBAS-InSAR, this study proposes a multi-source fusion framework that integrates systematic discrepancy correction, spatial residual modeling, and differentiated fusion for constructing a high-precision surface subsidence model. First, systematic biases between LiDAR-DSuM and InSAR-DSuM are identified through consistency analysis of subsidence differences within their overlapping areas. After…
- OpenAlex · Published · First archived
Combustion behavior of various biomass wastes pellet fuel: Thermogravimetric analysis and ash fusion characteristics ↗
This study compared rapeseed straw (RS), flower waste (FW), and tobacco straw (TS) in terms of fuel properties, combustion behavior, kinetics, and ash fusion characteristics. Proximate and ultimate analyses, scanning electron microscopy (SEM), thermogravimetric analysis (TGA), X-ray diffraction (XRD), ash fusion tests, and kinetic modeling were conducted to evaluate their energy utilization potential. FW exhibited the highest carbon content and heating value, indicating superior energy density. SEM observations revealed distinct microstructures that influenced oxygen diffusion and combustion b…
- OpenAlex · Published · First archived
PS-CAHE: Protocol-Semantic and Confusion-Pair-Aware Fusion for UAV Intrusion Detection ↗
Flow-based intrusion detection in unmanned aerial vehicle (UAV) networks can underuse protocol relationships and model complementarity. The Protocol-Semantic and Confusion-Pair-Aware Heterogeneous Ensemble (PS-CAHE) combines semantic features, training-only confusion-pair selection and two fusion weights. On 113,952 deduplicated UAVIDS-2025 flows, PS-CAHE achieved 95.58% Macro-F1 and 93.88% Matthews correlation coefficient on the fixed holdout. The full pipeline improved Macro-F1 by 0.83 percentage points over Original XGBoost; the pair-aware increment over global out-of-fold (OOF) weighting w…
- OpenAlex · Published · First archived
Underwater image enhancement via boundary-aware gradient domain reconstruction and intuitionistic fuzzy set similarity measure-guided wavelet fusion for lowlight conditions ↗
Due to the light absorption and scattering effects of water in dark underwater environments, along with the sensitivity limitations of imaging devices, captured images generally suffer from color distortion, low contrast, blurred details, and uneven illumination. These issues severely constrain the performance of underwater vision systems. Existing underwater image enhancement (UIE) algorithms are mostly designed for well-lit scenes and perform poorly in lowlight underwater environments, struggling to achieve a balance between image clarity and scene fidelity. Therefore, this paper proposes an…
- OpenAlex · Published · First archived
A physics-informed dynamic graph and evidence fusion method for fault alarm detection in building HVAC systems ↗
To address the superposition of normal thermal disturbances and fault characteristics in building heating, ventilation, and air conditioning (HVAC) systems, as well as conflicts among different diagnostic evidence sources, a physics-constrained dynamic graph and multi-source evidence fusion method for fault alarm detection is developed. The method employs the Dynamic Coupling-Informed Graph Attention Network to characterize the time-varying directional coupling relationships among air-side temperature variables, equipment control variables, and operational states. The graph structure is subjec…
- OpenAlex · Published · First archived
An enhanced sparse representation framework incorporating CoSaMP-BLOTLESS for improved multi-focus image fusion ↗
Abstract The efficiency of the dictionary learning and sparse recovery mechanisms plays a crucial role in sparse-representation-based image fusion. The recently proposed Block Total Least Squares (BLOTLESS) update algorithm is able to better perform dictionary learning, but it has higher computational complexity and longer dictionary learning time, which hinders its application in practice. To address this disadvantage, in this paper, we suggest a modified over the dictionary learning framework, which is modified the sparse coding stage in the BLOTLESS optimization process to overcome this dis…
- arXiv · Published · First archived
Numerical error analysis of EMC3-EIRENE simulations in the HSX stellarator ↗
Plasma edge simulations with codes like EMC3-EIRENE are widely used to study fusion magnetic confinement devices. However, numerical errors can significantly impact the simulation solution and are often insufficiently characterized. These errors consist of the statistical error, bias, and time integration error, resulting from the finite sampling and tracking of Monte Carlo particles, and the discretization error, resulting from a finite grid resolution. This work presents the first comprehensive numerical error analysis of EMC3-EIRENE simulations in stellarator geometries, focusing on edge pl…
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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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