CORTEXA
← Browse
openalexZenodo (CERN European Organization for Nuclear Research)2026-07-26Cited by 0

Isurwars/Correlation: Correlation 3.7.2

Isaías Rodríguez Aguirre, Mineralwater Xu

[3.7.2] - 2026-07-26 Fixed Native File Dialog Linkage: Enforced static library compilation (BUILD_SHARED_LIBS=OFF) for nativefiledialog-extended (nfd) on Linux to resolve runtime libnfd.so.1 shared library loading errors. [3.7.0] - 2026-07-24 Added Multi-Vendor GPU Acceleration Framework: Implemented SYCL-based GPU acceleration for distance, $S(Q)$, and Steinhardt parameter calculators (GPUDistanceCalculator, GPUSQCalculator, GPUSteinhardtCalculator) with runtime fallback and device detection. GPU Portability Abstraction Layer: Added GPUPortability layer featuring unified HIP and CUDA compatibility wrappers for high-throughput pairwise distance calculations. Machine Learning Interatomic Potentials (MLIP): Integrated MLIPCalculator and MLIPInterface for machine learning interatomic potential calculations. Modular SIMD Acceleration Framework: Introduced modular SIMD acceleration with AVX2, AVX512, and scalar fallbacks, including vectorized dot_block kernels and templatized SIMD data structures (Vector3SIMD). Configurable Floating-Point Precision: Replaced hardcoded double precision with real_t type aliases across all core calculators, readers, plotters, and test suites, enabling runtime/compile-time single or double precision builds via USE_SINGLE_PRECISION. Cross-Platform PyPI Wheel Automation: Added repair_wheel.py helper script to automate oneTBB dependency vendoring and rpath patching for Python wheel builds. Changed & Refactored Parameter Struct Standardization: Refactored DADCalculator, VDOSCalculator, ScaleBins, and RDFCalculator call interfaces to use dedicated parameter structures (ScaleBinsParams, VDOSParams, RDFNormalizationParams) for type-safe dispatch. Graph Edge Representation: Introduced unified Edge structure and overloaded addDirectedEdge in DistanceCalculator for cleaner AST and graph edge insertion. Codebase Modernization & Linter Compliance: Replaced reinterpret_cast with C++20 std::bit_cast, standardized PRNG seeding in tests, and eliminated all NOLINT/NOLINTNEXTLINE inline suppressions across source files and documentation. Project-Wide Formatting: Applied uniform clang-format styling across the entire project codebase. Packaging & Build System: Enforced static builds for voro++, standardized installation prefixes, and updated .desktop entry paths. Performance & Optimization Voronoi Topology Optimization: Accelerated VoronoiCalculator by caching thread-local buffers, filtering parasitic edges in Voronoi signatures, and optimizing particle ordering in periodic boundary containers. Bounds-Checked Operator Efficiency: Replaced unchecked raw array indexing with bounds-safe .at() calls in mathematical structures, while keeping direct array indexing in performance-critical Matrix3 operator kernels. Bit-Canonical Sampling: Implemented portable bit-canonical random sampling and modularized linear slope fitting in analysis modules. Fixed Voronoi Coordinate Normalization: Corrected floating-point normalization and hyperuniformity fitting bounds for Voronoi coordinate calculations. Cross-Platform Stat Header: Corrected header paths for filesystem stat structure to ensure cross-platform header compatibility. Precision Test Assertions: Migrated floating-point test assertions to custom IsRealEq matchers for reliable multi-precision test validation.

View free PDFSource page

Related papers

openalexZenodo (CERN European Organization for Nuclear Research)2026-08-14

Auditable AI Decision Intelligence for Aviation MRO A KPI Governance Architecture

SeyyedAbdolHojjat MoghadasNian

Aviation Maintenance, Repair and Overhaul (MRO) organizations increasingly possess enterprise resource planning data, inventory records, work-order histories, procurement evidence, quality documentation, finance approvals, and customer commitments, yet many operational decisions…

Also available via: European Organization for Nuclear Research

View free PDFSource page
openalexZenodo (CERN European Organization for Nuclear Research)2026-08-14

Data of the paper: "A probabilistic digital twin framework for corrosion-fatigue prognosis of floating offshore wind turbines"

Yasmin Ali, Ahmed Elgammal, Chengjun Li, Junlin Heng, Kaoshan Dai

These are the data and results reported in the paper "A probabilistic digital twin framework for corrosion-fatigue prognosis of floating offshore wind turbines".

Also available via: European Organization for Nuclear Research

View free PDFSource page
openalexZenodo (CERN European Organization for Nuclear Research)2026-08-12

Research data and code supporting "Label-free biochemical imaging and time point analysis of neural organoids via deep learning–enhanced Raman microspectroscopy"

Dimitar Georgiev, Ruoxiao Xie, Daniel Reumann, X Zhao, A. Fernandez-Galiana, Mauricio Barahona, et al.

This repository contains the datasets and source code associated with Georgiev et al., Science Advances (2026). https://doi.org/10.1126/sciadv.aec5080 To get started with the software, visit our GitHub repository. The software provides both a graphical user interface (GUI) and a…

Also available via: European Organization for Nuclear Research

View free PDFSource page
openalexZenodo (CERN European Organization for Nuclear Research)2026-08-11

Low Dose and High Contrast Biomedical Imaging Using SelfSupervised Deep Learning

Xiao Fan Ding, Xiaoman Duan, Ning Zhu

Self-supervised deep learning has emerged as a powerful method for image enhancement when a priori ground-truth references are not available. Stemming from Noise2Noise , it was shown that a convolutional neural network (CNN) can be trained from a noisy input and target pair of th…

Also available via: European Organization for Nuclear Research

View free PDFSource page
openalexZenodo (CERN European Organization for Nuclear Research)2026-08-09

Artificial Intelligence in Financial Systems

Dattatreya G. Tapas

Artificial intelligence is being used in financial systems to make tasks more efficient, detect fraud, and offer personalized services. It is changing industries like banking, trading, and insurance by making processes faster, cutting costs, and helping manage risks better. Some…

Also available via: European Organization for Nuclear Research

View free PDFSource page
openalexZenodo (CERN European Organization for Nuclear Research)2026-08-15

Deep Learning for Human Activity Recognition: A Comprehensive Review of Architectures, Performance, and Challenges Across Five Sensory Datasets

Abeer FathAllah Brery, Ascensión Gallardo-Antolín, Mahmoud Fakhry, Israel Gonzalez-Carrasco

Human activity recognition (HAR) using sensor data allows the automatic detection of human behavior and actions in everyday environments. The development of scalable and privacy-preserving HAR systems is supported by the nonintrusive collection of time-series data using wearable…

Also available via: European Organization for Nuclear Research

View free PDFSource page