Results 141 to 150 of about 9,360,077 (298)

Perbandingan K-Nearest Neighbor Dan Fuzzy K-Nearest Neighbor Pada Diagnosis Penyakit Diabetes Melitus [PDF]

, 2013
Pada Perkembangan Di Dunia Kedokteran Saat Ini, Peneliti Dan Praktisi Memusatkan Perhatiannya Untuk Mendeteksi Diabetes Melitus (DM) Dan Mencegah Atau Menghambat Berkembangnya Komplikasi.
Meristika, YanitaSelly
core  

Bidirectional k-nearest neighbor spatial crowdsourcing allocation protocol based on edge computing. [PDF]

PeerJ Comput Sci, 2023
Zhang J, Ding Q, Li B, Ye X.
europepmc   +1 more source

Revisiting Stability Criteria in Ball‐Milled High‐Entropy Alloys: Do Hume–Rothery and Thermodynamic Rules Equally Apply?

Advanced Engineering Materials, Volume 27, Issue 6, March 2025.
The stability criteria affecting the formation of high‐entropy alloys, particularly focusing in supersaturated solid solutions produced by mechanical alloying, are analyzed. Criteria based on Hume–Rothery rules are distinguished from those derived from thermodynamic relations. The formers are generally applicable to mechanically alloyed samples.
Javier S. Blázquez, Alejandro F. Manchón‐Gordón, Antonio Vidal‐Crespo, Rafael Caballero‐Flores, Jhon J. Ipus, Clara F. Conde   +5 more
wiley   +1 more source

Analisis Sentimen Pengguna Twitter Mengenai “Sedotan Plastik” Dengan Metode K-Nearest Neighbor (KNN) Dan Neighbor-Weighted K-Nearest Neighbor (NWKNN) [PDF]

, 2019
Tahun 2017 Divers Clean Action, kelompok pemerhati lingkungan khususnya laut menyebutkan bahwa pemakaian sedotan di Indonesia mencapai 93.244.847 batang setiap harinya.
Utami, Shindy Sari
core  

A Workflow to Accelerate Microstructure‐Sensitive Fatigue Life Predictions

Advanced Engineering Materials, EarlyView.
This study introduces a workflow to accelerate predictions of microstructure‐sensitive fatigue life. Results from frameworks with varying levels of simplification are benchmarked against published reference results. The analysis reveals a trade‐off between accuracy and model complexity, offering researchers a practical guide for selecting the optimal ...
Luca Loiodice, Krzysztof S. Stopka, Michael D. Sangid   +2 more
wiley   +1 more source

Cervical cancer detection using K nearest neighbor imputer and stacked ensemble learningmodel. [PDF]

Digit Health, 2023
Chen X, Aljrees T, Umer M, Saidani O, Almuqren L, Mzoughi O, Ishaq A, Ashraf I.   +7 more
europepmc   +1 more source

Field Report from Collaborative Research Center 1625: Heterogeneous Research Data Management Using Ontology Representations

Advanced Engineering Materials, EarlyView.
A unified research data management framework for heterogeneous materials data is presented. The system integrates multimodal datasets using ontologies and knowledge graphs, enabling interoperability and FAIR (findable, accessible, interoperable, reusable) data principles. By linking data across scales and workflows, it supports reproducible, Artifitial
Doaa Mohamed, Samuel García Vázquez, Behnam Mardani, Victor Dudarev, Alfred Ludwig, Maribel Acosta, Markus Stricker   +6 more
wiley   +1 more source

Fostering Innovation: Streamlining Magnetocaloric Materials Research by Digitalization

Advanced Engineering Materials, EarlyView.
Magnetocaloric cooling (MCE) is an environmentally friendly refrigeration method with great potential. Optimizing MCE materials involves the preparation and screening of large quantities of samples, which in turn generates a large amount of data. A digitalization approach is presented that uses ontologies, knowledge graphs, and digital workflows to ...
Simon Bekemeier, Moritz Blum, Luana Caron, Alisa Chirkova, Philipp Cimiano, Basil Ell, Inga Ennen, Michael Feige, Maik Gaerner, Thomas Hilbig, Andreas Hütten, Günter Reiss, Tapas Samanta, Sonja Schöning, Christian Schröder, Lennart Schwan, Chris Taake, Martin Wortmann   +17 more
wiley   +1 more source

Short-Term Demand Forecasting of Urban Online Car-Hailing Based on the K-Nearest Neighbor Model. [PDF]

Sensors (Basel), 2022
Xiao Y, Kong W, Liang Z.
europepmc   +1 more source

Workflow for Design of Experiments‐Based Modeling of Species Transport and Growth Kinetics in GaN Hydride Vapor Phase Epitaxy

Advanced Engineering Materials, EarlyView.
A novel workflow for investigating hydride vapor phase epitaxy for GaN bulk crystal growth is proposed. It combines Design of experiments (DoE) with physical simulations of mass transport and crystal growth kinetics, serving as an intermediate step between DoE and experiments.
J. Tomkovič, G. Lukin, H. Torkashvand, A. Kerschbaum, M. Müller, S. Besendörfer, J. Heitmann, J. Friedrich   +7 more
wiley   +1 more source