Results 161 to 170 of about 869,216 (289)

Short-term forecasting of COVID-19 using support vector regression: An application using Zimbabwean data. [PDF]

Am J Infect Control, 2023
Shoko C, Sigauke C.
europepmc   +1 more source

Generative Models for Crystalline Materials

Advanced Materials, EarlyView.
Generative machine learning models are increasingly used in crystalline materials design. This review outlines major generative approaches and assesses their strengths and limitations. It also examines how generative models can be adapted to practical applications, discusses key experimental considerations for evaluating generated structures, and ...
Houssam Metni, Laura Ruple, Lauren N. Walters, Luca Torresi, Jonas Teufel, Henrik Schopmans, Jona Östreicher, Yumeng Zhang, Marlen Neubert, Yuri Koide, Kevin Steiner, Paul Link, Lukas Bär, Mariana Petrova, Gerbrand Ceder, Pascal Friederich   +15 more
wiley   +1 more source

Efficient Support Vector Regression for Wideband DOA Estimation Using a Genetic Algorithm. [PDF]

Sensors (Basel)
Zhao Y, Zheng G, Wang J, Liu J, Dong S, Xin J.   +5 more
europepmc   +1 more source

Bat echolocation modelling using spike kernels with Support Vector Regression [PDF]

, 2007
FONTAINE, B, PEREMANS, H, Schrauwen, Benjamin   +2 more
core  

Study of a Novel Bi‐Layered Thermoplastic Polyurethane Patch for Congenital Diaphragmatic Hernia

Advanced Materials Interfaces, EarlyView.
Large congenital diaphragmatic hernia remains a challenge due to the poor compatibility of current prostheses. To tackle this problem, a bilayer thermoplastic polyurethane patch with tunable mechanical properties is engineered, whose fibrous side supports rapid fibroblast and myoblast colonization, while the smooth film limits adhesions.
Guillaume Leks, Julie Favre, Manon Zislin, Rodolphe Migneret, Jordana Hirtzel, Vincent Ball, Cendrine Seguin, Anne Hebraud, Emeline Lobry, Guy Schlatter, Nadia Bahlouli, Hamdi Jmal, Benoît Frisch, Sylvie Fournel, Isabelle Talon   +14 more
wiley   +1 more source

Prediction of body weight in indigenous sheep using random forest regression, support vector regression, and classification and regression trees algorithms. [PDF]

Vet Anim Sci
Megersa AG, Negash F, Hailu A, Melak A, Assefa A, Aseged T, Sinkie S.   +6 more
europepmc   +1 more source

Forecasting and change point test for nonlinear heteroscedastic time series based on support vector regression. [PDF]

PLoS One, 2022
Wang H, Guo M, Lee S, Chua CH.
europepmc   +1 more source

Flow‐Adaptive Gas Sensing Enabled Using a Uniform Au Nanosheet Sensor Array and a Neural Network Inference

Advanced Materials Technologies, EarlyView.
Integrated Au nanosheet sensor array enables simultaneous inference of gas concentration and flow rate via deep neural network analysis, without external flow control. ABSTRACT Gas sensor responses are considerably affected by gas flow rates, thereby inhibiting the accurate detection of target gas concentrations in variable‐flow applications such as ...
Taro Kato, Takahisa Tanaka, Yusuke Hamanaka, Ryo Toyoshima, Ken Uchida   +4 more
wiley   +1 more source

Correction: Senceroglu et al. Constructing an Intelligent Model Based on Support Vector Regression to Simulate the Solubility of Drugs in Polymeric Media. <i>Pharmaceuticals</i> 2022, <i>15</i>, 1405. [PDF]

Pharmaceuticals (Basel)
Senceroglu S, Ayari MA, Rezaei T, Faress F, Khandakar A, Chowdhury MEH, Jawhar ZH.   +6 more
europepmc   +1 more source

End‐to‐End Sensing Systems for Breast Cancer: From Wearables for Early Detection to Lab‐Based Diagnosis Chips

Advanced Materials Technologies, EarlyView.
This review explores advances in wearable and lab‐on‐chip technologies for breast cancer detection. Covering tactile, thermal, ultrasound, microwave, electrical impedance tomography, electrochemical, microelectromechanical, and optical systems, it highlights innovations in flexible electronics, nanomaterials, and machine learning.
Neshika Wijewardhane, Lyn I. Jones, Richard M. Martin, Helen Winter, Faezeh Arab Hassani   +4 more
wiley   +1 more source