Results 81 to 90 of about 35,332 (261)
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
Advanced Intelligent Discovery, EarlyView.Automated procedural analysis is recognized as one of the major game changers for robotic surgery. Meaning digital analysis needs to replace the manual assessments that set todays standard. Mechanical robotic‐instrument tracking enables the derivation of quantitative kinematic metrics that support behavior‐based workflow segmentation into distinct ...
Kateryna Pirkovets +4 more
wiley +1 more source
Advanced Intelligent Discovery, EarlyView.This work establishes a correlation between solvent properties and the charge transport performance of solution‐processed organic thin films through interpretable machine learning. Strong dispersion interactions (δD), moderate hydrogen bonding (δH), closely matching and compatible with the solute (quadruple thiophene), and a small molar volume (MolVol)
Tianhao Tan, Lian Duan, Dong Wang
wiley +1 more source
Topology‐Aware Machine Learning for High‐Throughput Screening of MOFs in C8 Aromatic Separation
Advanced Intelligent Discovery, EarlyView.We screened 15,335 Computation‐Ready, Experimental Metal–Organic Frameworks (CoRE‐MOFs) using a topology‐aware machine learning (ML) model that integrates structural, chemical, pore‐size, and topological descriptors. Top‐performing MOFs exhibit aromatic‐enriched cavities and open metal sites that enable π–π and C–H···π interactions, serving as ...
Yu Li, Honglin Li, Jialu Li, Wan‐Lu Li
wiley +1 more source
DATA WAREHOUSE AND DATA MINING - DATABASES NEXT STEP [PDF]
Annals of the University of Oradea: Economic Science, 2010 Data Warehouses and Data Mining are indispensable and inseparable parts for modern organization. Organizations will create data warehouses in order for them to be used by business executives to take important decisions.
BURTESCU Claudia, BURTESCU Emil
doaj
Drilling Material Data Warehouse ETL System Research Based on Crowd-Sourcing
MATEC Web of Conferences, 2018 Drilling material data warehouse is an important platform for assisting drilling engineering decision support and data analysis. The construction of high-efficiency and high-quality enterprise-level data warehouse puts high requirements on data quality ...
Zhou Jie, Fang Ming, Cao Xin-ran
doaj +1 more source
Deep Learning‐Assisted Design of Mechanical Metamaterials
Advanced Intelligent Discovery, EarlyView.This review examines the role of data‐driven deep learning methodologies in advancing mechanical metamaterial design, focusing on the specific methodologies, applications, challenges, and outlooks of this field. Mechanical metamaterials (MMs), characterized by their extraordinary mechanical behaviors derived from architected microstructures, have ...
Zisheng Zong +5 more
wiley +1 more source
PEMAHAMAN TEORI DATA WAREHOUSE BAGI MAHASISWA TAHUN AWAL JENJANG STRATA SATU BIDANG ILMU KOMPUTER
Jurnal Informatika, 2015 As a Computer scientist, a computer science students should have understanding about database theory as a concept of data maintenance. Database will be needed in every single human real life computer implementation such as information systems ...
Harco Leslie Hendric Spits Warnars +2 more
doaj
Discussion on Integration of Data Warehouse and Big Data
Dianxin kexue, 2015 In view of the traditional enterprise couldn't use such unstructured data efficiently,a big data solutions based on integration of data warehouse and big data was discussed.Based on the theory of data warehouse construction and architecture of the next ...
Juan Yu
doaj +2 more sources
Large Language Model in Materials Science: Roles, Challenges, and Strategic Outlook
Advanced Intelligent Discovery, EarlyView.Large language models (LLMs) are reshaping materials science. Acting as Oracle, Surrogate, Quant, and Arbiter, they now extract knowledge, predict properties, gauge risk, and steer decisions within a traceable loop. Overcoming data heterogeneity, hallucinations, and poor interpretability demands domain‐adapted models, cross‐modal data standards, and ...
Jinglan Zhang +4 more
wiley +1 more source