Suchergebnisse - (dynamic OR dynamik) graph conventional autoencoder

A Comprehensive Method for Anomaly Detection in Complex Dynamic IoT Systems

Autoren: Andrii Liashenko Larysa Globa

Quelle: Proceedings of the International Conference on Applied Innovations in IT, Vol 13, Iss 1, Pp 101-107 (2025)

Schlagwörter: anomaly detection, temporal graphs, temporal graph neural networks, autoencoder, graph neural networks, reconstruction error, dynamic systems, transportation network, Electronic computers. Computer science, QA75.5-76.95, Technology

Dateibeschreibung: electronic resource

Relation: https://icaiit.org/paper.php?paper=13th_ICAIIT_1/2_4; https://doaj.org/toc/2199-8876

Zugangs-URL: https://doaj.org/article/fd3af3924db04d33b178b0d3e4f8eedf

ADG-KAE: novel adaptive dynamic graph embedded kernel autoencoder algorithm for industrial process monitoring and fault detection

Autoren: Ruining Tong Zhiyu Xu Haini Qu et al.

Quelle: Measurement Science and Technology. 36:066212

Dual-Branch Reconstruction Pre-Training with Multi-Layer Supervision and Regional Dynamic Graph Convolution for 2D Tooth Segmentation.

Autoren: Wang, Haibin Liu, Li

Quelle: Sensing & Imaging; 10/18/2025, Vol. 26 Issue 1, p1-14, 14p

Spatio-temporal graph convolutional autoencoder for transonic wing pressure distribution forecasting.

Autoren: Immordino, Gabriele Vaiuso, Andrea Da Ronch, Andrea et al.

Quelle: Aerospace Science & Technology. Oct2025, Vol. 165, pN.PAG-N.PAG. 1p.

Schlagwörter: *AUTOENCODERS, *TRANSONIC aerodynamics, *NONLINEAR mechanics, *GRAPH neural networks, *SPATIOTEMPORAL processes, *AERODYNAMIC load, *FORECASTING

Detecting Anomalies in Dynamic Graphs via Memory enhanced Normality

Autoren: Liu, Jie Shang, Xuequn Han, Xiaolin et al.

Index Begriffe: Computer Science - Machine Learning, Computer Science - Artificial Intelligence, text

URL: http://arxiv.org/abs/2403.09039

Variational Graph Convolutional Networks for Dynamic Graph Representation Learning

Autoren: Aabid A. Mir Megat F. Zuhairi Shahrulniza Musa et al.

Quelle: IEEE Access, Vol 12, Pp 161697-161717 (2024)

Schlagwörter: network security, deep learning, graph neural networks, Anomaly detection, complex networks, Electrical engineering. Electronics. Nuclear engineering, heterogeneous networks, TK1-9971

Zugangs-URL: https://doaj.org/article/205888aa585544ec8d0e7f0c49e14058

Signed versus isomorphic graph autoencoders for microRNA-single-nucleotide polymorphisms network reconstruction in periodontal osteo-genomic landscapes.

Alternate Title: Autocodificadores de grafos isomorfos versus firmados para la reconstrucción de redes de polimorfismos de un solo nucleótido de microARN en paisajes osteogenómicos periodontales. (Spanish)

Autoren: Sharma, Sarvagya Yadalam, Pradeep Kumar Ardila, Carlos M.

Quelle: Gaceta Médica de Caracas; jul-sep2025, Vol. 133 Issue 3, p675-685, 11p

Graph-Variational Convolutional Autoencoder-Based Fault Detection and Diagnosis for Photovoltaic Arrays.

Autoren: Arifeen, Murshedul Petrovski, Andrei Hasan, Md Junayed et al.

Quelle: Machines; Dec2024, Vol. 12 Issue 12, p894, 15p

Schlagwörter: SOLAR cells, RENEWABLE energy sources, PHOTOVOLTAIC power systems, SOLAR energy, AUTOENCODERS

Multi-Task Graph Attention Net for Electricity Consumption Prediction and Anomaly Detection

Autoren: Na Bai Jian Zhang Zhaoli Wu

Quelle: Computers, Vol 14, Iss 9, p 350 (2025)

Schlagwörter: electricity consumption anomaly detection, electricity consumption prediction, multi-task learning, graph autoencoder, sequence entropy, Electronic computers. Computer science, QA75.5-76.95

Dateibeschreibung: electronic resource

Relation: https://www.mdpi.com/2073-431X/14/9/350; https://doaj.org/toc/2073-431X

Zugangs-URL: https://doaj.org/article/184b86f77e564534bf7653d6a1220839

GNPNM: A graph neural pore network model for predicting quasi-static drainage displacement patterns.

Autoren: Kim, Yejin Suh, Hyoung Suk

Quelle: Computers & Geotechnics. Nov2025, Vol. 187, pN.PAG-N.PAG. 1p.

Schlagwörter: *GRAPH neural networks, *FLUID dynamics, *CAPILLARY flow, *MACHINE learning, *ELECTRIC network topology, *PREDICTION models

Reconstructing brain causal dynamics for subject and task fingerprints using fMRI time-series data.

Autoren: Song, Dachuan Shen, Li Duong-Tran, Duy et al.

Quelle: Health Information Science & Systems; 10/28/2025, Vol. 13 Issue 1, p1-17, 17p

Adaptive Sparsified Graph Learning Framework for Vessel Behavior Anomalies

Autoren: Kim, Jeehong Kim, Minchan Ju, Jaeseong et al.

Index Begriffe: Computer Science - Machine Learning, Computer Science - Artificial Intelligence, text

URL: http://arxiv.org/abs/2502.14197

Autoencoder with Constraints for Subsurface Defect Detection in Quadratic Frequency Modulated Thermal Wave Imaging.

Autoren: Bandari, Enosh Oleti, Siva Subrahmanyam Prasanthi, Y. Naga et al.

Quelle: Sensing & Imaging; 8/18/2025, Vol. 26 Issue 1, p1-17, 17p

Assessment of energy-efficient wireless network using autoencoders with unsupervised deep learning.

Autoren: Abdullah, Mahmood Zaki Hummadi, Fadia Noori

Quelle: Service Oriented Computing & Applications; Dec2024, Vol. 18 Issue 4, p349-360, 12p

Effective Treatment of Drug-Resistant Cancers (Pancreatic, Glioblastoma, Metastatic) — Vaccine and Drug Development through the Hamzah Model

Autoren: JALALI, SEYED RASOUL

Schlagwörter: cancer, oncology, drug resistance, multidrug resistance, tumour heterogeneity, pancreatic cancer, glioblastoma, metastatic cancer, resistant tumours, adaptive resistance, tumour relapse, chemotherapy, radiotherapy, immunotherapy, targeted therapy, nanomedicine, nanotechnology, nanoparticle drug delivery, liposomal delivery, lipid nanoparticles, PLGA nanoparticles, PEGylated nanoparticles, controlled release, targeted release, tumour microenvironment, hypoxia, angiogenesis, vascularisation, tumour stem cells, immune evasion, T–cell activation, CTL response, Th1 induction, immune checkpoint inhibition, PD–1, PD–L1, CTLA–4, CAR–T therapy, NK cells, macrophages, dendritic cells, adaptive immunity, innate immunity, cytokines, interleukins, interferons, chemokines, tumour–associated macrophages, tumour infiltrating lymphocytes, tumour–associated fibroblasts, stromal interactions, tumour signalling, EGFR resistance, PI3K/AKT pathway, MAPK pathway, mTOR signalling, tyrosine kinase inhibition, DNA repair mechanisms, homologous recombination, non–homologous end joining, mismatch repair, DNA repair overdrive, genomic instability, chromosomal instability, mutational landscape, oncogenic mutations, tumour suppressor loss, TP53, BRCA1, BRCA2, KRAS, NRAS, BRAF, EGFR mutations, HER2 amplification, MYC activation, cell cycle dysregulation, apoptosis evasion, senescence bypass, autophagy regulation, metabolic rewiring, Warburg effect, glycolysis, oxidative phosphorylation, mitochondrial dysfunction, lactate export, pH regulation, proton transporters, ion channels, tumour acidity, ROS signalling, redox balance, antioxidant defences, glutathione, thioredoxin, peroxiredoxin, ferroptosis, necroptosis, pyroptosis, cell death pathways, fractional calculus, fractal derivatives, fractional order models, complex integration, multiscale integration, matter–energy transformation, quantum biology, quantum noise, stochastic modelling, chaos theory, bifurcation analysis, attractors, strange attractors, phase transitions, metastability, dynamic equilibrium, complex adaptive systems, systems biology, integrative modelling, computational oncology, mathematical oncology, bioinformatics, omics integration, genomics, transcriptomics, proteomics, metabolomics, epigenomics, pharmacogenomics, pharmacokinetics, pharmacodynamics, PK–PD modelling, absorption, distribution, metabolism, excretion, clearance, plasma volume, bioavailability, half–life, dose–response, EC50, IC50, Emax, Hill coefficient, drug synergy, drug antagonism, combination therapy, polytherapy, cocktail therapy, adaptive dosing, dose escalation, therapeutic window, therapeutic index, off–target effects, side effect minimisation, toxicity reduction, safety margin, quality of life, survival rate, progression–free survival, overall survival, relapse–free survival, clinical trials, preclinical trials, in vivo models, in vitro models, xenografts, organoids, patient–derived xenografts, spheroids, co–culture systems, 3D models, microfluidics, lab–on–chip, organ–on–chip, bioreactors, lyophilisation, freeze drying, nanofabrication, nanocarriers, smart nanoparticles, responsive nanoparticles, stimuli–responsive release, pH–sensitive release, temperature–sensitive release, redox–sensitive release, enzyme–sensitive release, targeted ligands, antibodies, aptamers, peptides, folate targeting, transferrin targeting, EGFR targeting, HER2 targeting, integrins, RGD peptides, nuclear localisation, mitochondrial targeting, lysosomal escape, endosomal release, exosomes, extracellular vesicles, vesicular trafficking, clathrin mediated endocytosis, caveolin mediated endocytosis, macropinocytosis, receptor mediated endocytosis, intracellular trafficking, pharmacological modelling, biophysics, thermodynamics, statistical mechanics, entropy, enthalpy, free energy, Gibbs free energy, Helmholtz free energy, partition functions, state transitions, molecular dynamics, Monte Carlo simulations, lattice models, Ising model, spin systems, neural networks, deep learning, convolutional neural networks, recurrent neural networks, reinforcement learning, generative adversarial networks, variational autoencoders, XGBoost, random forest, decision trees, ensemble learning, predictive modelling, classification, regression, clustering, dimensionality reduction, PCA, t–SNE, UMAP, feature engineering, feature selection, biomarkers, predictive biomarkers, prognostic biomarkers, diagnostic biomarkers, liquid biopsy, circulating tumour DNA, circulating tumour cells, exosomal RNA, tumour markers, CA19–9, CEA, AFP, PSA, CA125, imaging biomarkers, radiomics, PET imaging, MRI, CT imaging, functional imaging, diffusion weighted imaging, perfusion imaging, metabolic imaging, nuclear imaging, image–guided therapy, image processing, signal processing, time series analysis, Fourier analysis, Laplace transforms, fractional Laplacian, differential equations, partial differential equations, integro–differential equations, fractional differential equations, boundary conditions, initial conditions, stability criteria, numerical analysis, discretisation, finite element analysis, spectral methods, operator theory, eigenvalues, eigenvectors, Hilbert space, Banach space, functional analysis, operator semigroups, semigroup theory, stochastic differential equations, Ito calculus, Stratonovich calculus, Langevin dynamics, Fokker–Planck equation, Kolmogorov equations, path integrals, quantum field theory, string theory, cosmological models, general relativity, special relativity, spacetime curvature, energy density, dark matter, dark energy, entropy flow, holographic principle, quantum entanglement, decoherence, superposition, wavefunction collapse, Schrödinger equation, Dirac equation, Heisenberg uncertainty, Planck constant, Boltzmann constant, Avogadro constant, dimensional analysis, scaling laws, renormalisation group, universality, critical phenomena, nonlinearity, nonlocality, long–range interactions, fractional Brownian motion, Lévy flights, anomalous diffusion, subdiffusion, superdiffusion, percolation theory, fractal geometry, Hausdorff dimension, Minkowski dimension, Cantor sets, Sierpinski structures, Koch curve, fractal networks, scale–free networks, small–world networks, network theory, graph theory, adjacency matrices, Laplacian matrices, spectral graph theory, network robustness, percolation threshold, epidemics on networks, cancer networks, signalling networks, metabolic networks, gene regulatory networks, protein–protein interaction networks, immune networks, dynamical networks, multiscale networks, hierarchical clustering, modularity, community detection, information theory, Shannon entropy, mutual information, Kullback–Leibler divergence, Jensen–Shannon divergence, complexity theory, algorithmic complexity, Kolmogorov complexity, Turing machines, computational complexity, NP–hard problems, optimisation, convex optimisation, non–convex optimisation, gradient descent, stochastic gradient descent, Adam optimiser, evolutionary algorithms, genetic algorithms, particle swarm optimisation, ant colony optimisation, simulated annealing, Bayesian optimisation, Markov chain Monte Carlo, Gibbs sampling, variational inference, probabilistic programming, causal inference, counterfactual analysis, sensitivity analysis, robustness analysis, uncertainty quantification, error propagation, variance reduction, surrogate modelling, reduced order models, high performance computing, parallel computing, distributed computing, GPU acceleration, CUDA programming, MPI, OpenMP, quantum computing, quantum algorithms, Grover's algorithm, Shor's algorithm, quantum annealing, quantum machine learning, hybrid quantum–classical models, future contingencies, scenario planning, stress testing, resilience modelling, adaptive systems, evolutionary dynamics, co–evolution, arms race, predator–prey models, ecological modelling, fitness landscapes, landscape ruggedness, adaptive peaks, valley crossing, tumour evolution, clonal evolution, immune surveillance, immune escape, therapeutic resistance, evolutionary game theory, replicator dynamics, Nash equilibria, evolutionary stable strategies, cancer ecosystems, tumour ecology, competition, cooperation, parasitism, resource allocation, niche construction, tumour dormancy, relapse mechanisms, latency, minimal residual disease, eradication thresholds, cure probability, survival probability, remission, remission durability, patient stratification, personalised medicine, precision medicine, systems oncology, integrative oncology, translational oncology, computational biomedicine, mathematical medicine, fractal oncology, ψ–Hamzah Equation, Hamzah model, Seyed Rasoul Jalali, ψ–Hamzah multiscale framework, ψ–Hamzah fractional–fractal derivative, ψ–Hamzah complex integration, ψ–Hamzah cancer resistance model, ψ–Hamzah pharmacokinetics, ψ–Hamzah pharmacodynamics, ψ–Hamzah adaptive dosing, ψ–Hamzah entropy analysis, ψ–Hamzah intelligence index, ψ–Hamzah validation, ψ–Hamzah field simulation, ψ–Hamzah therapeutic design, ψ–Hamzah vaccine, ψ–Hamzah drug, ψ–Hamzah intellectual property, ψ–Hamzah universal cure

Augmenting the human interactome for disease prediction through gene networks inferred from human cell atlas.

Autoren: Sung, Euijeong Cha, Junha Baek, Seungbyn et al.

Quelle: Animal Cells & Systems. Dec2025, Vol. 29 Issue 1, p173-182. 10p.

Quantum deep learning-enhanced ethereum blockchain for cloud security: intrusion detection, fraud prevention, and secure data migration.

Autoren: Nagarjun, A. Venkata Rajkumar, Sujatha

Quelle: Scientific Reports. 11/5/2025, Vol. 15 Issue 1, p1-21. 21p.

Quantoscope: Quantum Reconstruction Revolution for Time-Symmetric Imaging of Quantum Memory, Gluons, and Vacuum Fields

Autoren: JALALI, SEYED RASOUL

Schlagwörter: Quantoscope, Quantum Imaging, Quantum Reconstruction, Time-Symmetric Imaging, Quantum Memory, Gluons, Vacuum Fields, ψ–Hamzah Equation, Informational Geometry, Sub-Planck Imaging, Retrocausality, Fractal Lenses, Memory Wavefunction, ψ–Vision Algorithm, Quantum Neural Networks, Nano-Quantum Accelerator, HNAQ, Nonlinear Optics, Quantum Resonance, Informational Vacuum, Quantum Silence, Consciousness Imaging, Quantum Awareness, Informational Reconstruction, ψ–Memory, Sub-Planckian Phenomena, Quantum Chromodynamics, QCD Imaging, Quark Observation, SU(3) Color Structures, Virtual Particles, Quantum Noise Cancellation, Decoherence Mitigation, Informational Spectrum, ψ–Color Vector, Temporal Feedback, Informational Interferometry, ψ–Optical Matrix, ψ–Resonance Spectrum, Quantum Information Theory, Zero-Noise Communication, Quantum Coherence, Quantum Entanglement, Informational Phase, ψ–Encoding, Temporal Memory Index, Fractal Derivatives, Informational Lenses, Memory-Based Imaging, Cognitive Quantum Science, Quantum Biology, Quantum Computing, Quantum Sensors, ψ–Fractal Lens, Informational Feedback, Retrocausal Models, Non-Abelian Gauge Theory, Vacuum Oscillations, ψ–Vacuum Field, ψ–Resonance, Informational Field Theory, Quantum Awareness Models, Quantum Silence Spectrum, Informational Signal, Quantum Mind, Cognitive Resonance, Brain–Quantum Interface, ψ–Brain Interface, Quantum Neuroimaging, Quantum Prosthetics, Informational Nanomedicine, Quantum Diagnosis, Quantum Nano-Machines, ψ–Medical Imaging, Quantum Therapy, DNA Resonance, Protein Quantum Memory, Photosynthesis Efficiency, Cellular Quantum Coherence, Informational Biology, Quantum Mind Models, Cognitive Encoding, Informational Awareness, Conscious Silence, Awareness Fields, Quantum Philosophy, Epistemological Imaging, Informational Epistemology, Consciousness Studies, Retrocausal Cognition, Informational Awareness Fields, Temporal Nonlocality, Quantum Cognition, Informational Psychology, ψ–Mind Model, Informational Consciousness, Quantum Decision-Making, Informational Cognition, Future Feedback, Quantum Human Sciences, Informational Sociology, Quantum Anthropology, Informational Archaeology, Informational Epistemics, Dark Energy Imaging, Cosmic Silence, Informational Cosmology, Quantum Vacuum Analysis, Casimir Hotspots, Vacuum Condensation, Informational Dark Matter, Astrophysical ψ–Imaging, Cosmic Resonance, Interstellar Vacuum Fluctuations, Extraterrestrial Signal Analysis, ETI Scan, ψ–Cosmic Spectrum, Quantum Universe Imaging, ψ–Cosmology, Informational Astronomy, Particle Memory, Informational Quark–Gluon Plasma, Informational Nucleon Structure, ψ–Strong Force Imaging, Informational Gluon Fields, QCD Resonance, Informational Color Vectors, ψ–Color Mapping, Informational Quantum Chromodynamics, ψ–Topological Phases, Quantum Topological Imaging, Informational SU(3), ψ–QCD Feedback, Informational Energy Gaps, Informational Phase Nodes, ψ–Phase Analysis, ψ–Energy Density, Informational Spectrum Analysis, Informational Coherence, Informational Decoherence, Informational Noise Filtering, ψ–Decoherence Mitigation, Informational Qubit Stability, Informational Entanglement, ψ–Qubit Imaging, Informational Quantum Computing, ψ–Qubit Memory, ψ–Quantum Machine Learning, Quantum Perception, ψ–Perceptual Awareness, Quantum Cognitive AI, ψ–Quantum Neural Network, ψ–Autoencoder, ψ–Memory Graphs, Informational Memory Maps, ψ–Graph Processing, ψ–Quantum GPU, ψ–Quantum Hardware, ψ–Nanoelectronics, ψ–Metamaterial Lenses, Informational Nanotechnology, ψ–Quantum Optoelectronics, Informational Feedback Systems, Informational Quantum Photonics, ψ–HyperQuantum Processor, ψ–QNN Imaging, ψ–Quantum Processor, Quantum Photonic Imaging, Informational Holography, ψ–HoloProjector, ψ–7D Projections, Informational Spin Imaging, ψ–Temporal Imaging, Informational Time-Symmetric Operators, ψ–Bidirectional Wave Equations, ψ–Feedback Kernels, Retarded Kernels, Advanced Kernels, Informational Retrodynamics, ψ–Temporal Symmetry, ψ–Vacuum Information, Informational Ground State, ψ₀(x,t), Informational Oscillations, ψ–Fourier Transform, ψ–Wavelet Transform, ψ–Hermitian Transform, ψ–Fractional Transform, Informational Phase Mapping, Informational Frequency Filtering, ψ–Delay Embedding, ψ–Deconvolution Engine, ψ–Reconstruction Algorithm, ψ–AutoCorrelated Filters, Informational Gradient Mapping, ψ–Informational Interference, Informational Feedback Mapping, ψ–Vacuum Resonance, Informational Color Filters, ψ–Color Amplification, ψ–Quantum Wavelet Transform, Informational Phase Coherence, ψ–Decoherence Delay, Informational SU(3) Mapping, ψ–Memory Fidelity, Informational Fidelity Metrics, Informational SSIM, Informational PSNR, ψ–Error Management, ψ–Noise Spectrum, Informational Stability Analysis, ψ–Stability Dynamics, Informational Nonlocality, ψ–Feedback Resonance, ψ–Fractal Feedback, Informational Recursion, ψ–Recursive Functions, Informational Phase Diffusion, ψ–NonGaussian Memory, ψ–Fractional Diffusion, ψ–Nonlinear Memory, Informational Nonlinearity, ψ–Tensorial Functions, ψ–Optical Matrix, ψ–Resonance Domain, ψ–Resonant Peaks, Informational Imaging Spectrum, Informational Tensor Analysis, ψ–Graphical Reconstruction, ψ–Heatmaps, ψ–Quantum Spectrum Analysis, ψ–Spectral Tensor, ψ–Resonant Mapping, Informational Phase–Time Mapping, ψ–Fractal Information Spectrum, ψ–Informational Holography, Informational Retro-Imaging, ψ–Feedback Loops, Informational Chronodynamics, ψ–Temporal Coherence, ψ–Vacuum Noise Resonance, ψ–Informational Silence, Quantum Silence Imaging, Informational Zero-Noise, ψ–Signal-to-Silence Mapping, Informational Signal Extraction, ψ–Silence Coherence, ψ–Silent Awareness, ψ–Silent Intelligence, Informational Vacuum Intelligence, ψ–Quantum Silence Spectrum, ψ–Vacuum Intelligence, ψ–Epistemic Interface, ψ–Ontological Imaging, Informational Ontology, ψ–Epistemology, ψ–Technological Framework, Informational Cognitive Interface, ψ–Cognitive Lens, ψ–Cognitive Feedback, ψ–Cognitive Awareness, ψ–Artificial Consciousness, ψ–Neuromorphic AI, ψ–Quantum AI, ψ–Cognitive Quantum Networks, ψ–Awareness Encoding, ψ–Conscious Encoding, ψ–Resonant Cognition, ψ–Philosophy of Mind, ψ–Informational Awareness Studies, ψ–Mind–Machine Interface, ψ–Informational Epistemics, ψ–Hamzah Microscope, ψ–Hamzah Imaging, ψ–Hamzah Lens, ψ–Hamzah Neural Imaging, ψ–Hamzah Neural Networks, ψ–Hamzah QNN, ψ–Hamzah Imaging Systems, ψ–Hamzah Cognitive Field, ψ–Hamzah Resonance, ψ–Hamzah Retrocausal Models, ψ–Hamzah Informational Awareness, ψ–Hamzah Quantum Feedback, ψ–Hamzah Physics, ψ–Hamzah Medicine, ψ–Hamzah Biology, ψ–Hamzah AI, ψ–Hamzah Cognitive Science, ψ–Hamzah Quantum Information, ψ–Hamzah Quantum Cosmology, ψ–Hamzah Quantum Mind, ψ–Hamzah Quantum Cognition, ψ–Hamzah Quantum Medicine, ψ–Hamzah Quantum Biology, ψ–Hamzah Quantum Computing, ψ–Hamzah Quantum Neuroscience, ψ–Hamzah Quantum Philosophy, ψ–Hamzah Universal Applications

Designing metamaterials with programmable nonlinear responses and geometric constraints in graph space.

Autoren: Maurizi, Marco Xu, Derek Wang, Yu-Tong et al.

Quelle: Nature Machine Intelligence; Jul2025, Vol. 7 Issue 7, p1023-1036, 14p

Kolmogorov–Arnold graph neural networks for molecular property prediction.

Autoren: Li, Longlong Zhang, Yipeng Wang, Guanghui et al.

Quelle: Nature Machine Intelligence; Aug2025, Vol. 7 Issue 8, p1346-1354, 9p