Results 151 to 160 of about 80,641 (302)
Advanced Intelligent Discovery, EarlyView.A novel convolutional neural network architecture enables rapid, unsupervised analysis of IR spectroscopic data from DRIFTS and IRRAS. By combining synthetic data generation with parallel convolutional layers and advanced regularization, the model accurately resolves spectral features of adsorbed CO, offering real‐time insights into ceria surface ...
Mehrdad Jalali +5 more
wiley +1 more source
Time series data mining methods
, 2015 Today, real world time series data sets can take a size up to a trillion observations and even more. Data miners’ task is it to detect new information that is hidden in this massive amount of data. While well known techniques for data mining in cross sections have been developed, time series data mining methods are not as sophisticated and established ...
openaire +1 more source
Advanced Intelligent Discovery, EarlyView.This study presents an automated system integrating a capillary force gripper and machine learning‐based object detection for sorting and placing submillimeter objects. The system achieved stable and simultaneous manipulation of four object types, with an average task time of 86.0 seconds and a positioning error of 157 ± 84 µm, highlighting its ...
Satoshi Ando +4 more
wiley +1 more source
A framework for trend mining with application to medical data
This thesis presents research work conducted in the field of knowledge discovery. It presents an integrated trend-mining framework and SOMA, which is the application of the trend-mining framework in diabetic retinopathy data.
Somaraki, Vassiliki
core
Mining Emerging Patterns from Time Series Data with Time Gap Constraint
, 2012 Discovery of powerful contrasts between datasets is an important issue in data mining. To address this, the concept of emerging patterns (EPs) has thus been introduced by Dong and Li. EPs are a set of itemsets whose support changes significantly from one
Tseng, Vincent S. +1 more
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Deep Learning‐Assisted Coherent Raman Scattering Microscopy
Advanced Intelligent Discovery, EarlyView.The analytical capabilities of coherent Raman scattering microscopy are augmented through deep learning integration. This synergistic paradigm improves fundamental performance via denoising, deconvolution, and hyperspectral unmixing. Concurrently, it enhances downstream image analysis including subcellular localization, virtual staining, and clinical ...
Jianlin Liu +4 more
wiley +1 more source
A Bayesian network approach to explaining time series with changing structure
, 2004 Many examples exist of multivariate time series where dependencies between variables change over time. If these changing dependencies are not taken into account, any model that is learnt from the data will average over the different dependency structures.
Liu, X, Tucker, A
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A Comprehensive Assessment and Benchmark Study of Large Atomistic Foundation Models for Phonons
Advanced Intelligent Discovery, EarlyView.We benchmark six large atomistic foundation models on 2429 crystalline materials for phonon transport properties. The rapid development of universal machine learning potentials (uMLPs) has enabled efficient, accurate predictions of diverse material properties across broad chemical spaces.
Md Zaibul Anam +5 more
wiley +1 more source
Flood forecasting using time series data mining
, 2005 Earthquakes, floods, rainfall represent a class of nonlinear systems termed chaotic, in which the relationships between variables in a system are dynamic and disproportionate, however completely deterministic.
Damle, Chaitanya
core +1 more source
Advanced Intelligent Discovery, EarlyView.Memristors based on trimethylsulfonium (phenanthroline)tetraiodobismuthate have been utilised as a nonlinear node in a delayed feedback reservoir. This system allowed an efficient classification of acoustic signals, namely differentiation of vocalisation of the brushtail possum (Trichosurus vulpecula).
Ewelina Cechosz +4 more
wiley +1 more source