Results 41 to 50 of about 5,787,304 (258)

Intelligent Orthopedics: Machine Learning in Diagnosis of Bone Disease, Implants, and Bone Health Monitoring

Advanced Healthcare Materials, EarlyView.
Efficient recovery from traumatic or degenerative diseases is a great challenge, even after all the advancements in bone and cartilage regeneration. Machine learning (ML) algorithms have presented opportunities to enhance these aspects by accurately analyzing imaging data.
Maryam Kamaei, Hesam Mohammadi, Shamim Golafshan, Mojtaba Alehosseini, Mahsa Mohammadzadeh, Atefeh Golshirazi, Nasim Golafshan, Tatiane Eufrásio‐da‐Silva, Alireza Dolatshahi‐Pirouz, Gorka Orive   +9 more
wiley   +1 more source

Performance Quantile Regression and Bayesian Quantile Regression in Dealing with Non-normal Errors (Case Study on Simulated Data)

Numerical: Jurnal Matematika dan Pendidikan Matematika
This research discusses the performance of quantile regression and Bayesian quantile regression methods. Quantile regression uses parameter estimation by maximizing the value of the likelihood function, while Bayesian quantile regression uses parameter ...
Lilis Harianti Hasibuan, Ferra Yanuar, Vika Pradinda Harahap, Latifatul Qalbi   +3 more
doaj   +1 more source

Elliptical Orbits Mode Application for Approximation of Fuel Volume Change

Cauchy: Jurnal Matematika Murni dan Aplikasi, 2022
This article discusses the Elliptical Orbits Mode (EOM) as a method of approximating the function of changing the volume of fuel in the Underground Yank (UT). This research was conducted at the 45.507.21 Candirejo Tuntang Pertamina Gas Station.
Jovian Dian Pratama, Ratna Herdiana, Susilo Hariyanto   +2 more
doaj   +1 more source

Minimum mean square distance estimation of a subspace [PDF]

, 2011
We consider the problem of subspace estimation in a Bayesian setting. Since we are operating in the Grassmann manifold, the usual approach which consists of minimizing the mean square error (MSE) between the true subspace U and its estimate U may not be ...
Jean-Yves Tourneret, Besson, Olivier, Olivier Besson, Nicolas Dobigeon, Dobigeon, Nicolas, Tourneret, Jean-Yves   +5 more
core   +1 more source

Normalized Root-Mean-Square Error (RMSE) of TorchDIVA motor signal.

, 2023
Normalized Root-Mean-Square Error (RMSE) of TorchDIVA motor signal.
Visar Berisha (2218258), Julie M. Liss (5924550), Sean P. Kinahan (14642407)   +2 more
core   +1 more source

Hydrophobic MFI‐Type Zeolites via Alkali‐Cation‐Induced Defect Healing: Implications for Adsorbent and Catalyst Design

Advanced Materials, EarlyView.
Sub‐stoichiometric amounts of Na+ or K+ enhance defect healing during Silicalite‐1 (MFI) and TS‐1 calcination by promoting Si–O–Si annealing and healing framework vacancies. The resulting defect‐free zeolites are more hydrophobic and show improved butanol/water separation and improved activity and selectivity in the epoxidation of 1‐hexene, offering a ...
Christos Kanteler, Pau Ferri, Francisco Javier Escobar‐Bedia, Álvaro Mayoral, Alejandro Vidal‐Moya, Richard Kendra, Chen Lei, Miguel Palomino, Fernando Rey, Lukáš Grajciar, Christopher James Heard, Pedro Serna, Mercedes Boronat, Cristina Martínez, Manuel Moliner   +14 more
wiley   +1 more source

New adjusted missing value imputation in multiple regression with simple random sampling and rank set sampling methods.

PLoS ONE
This research compared the efficiency of several adjusted missing value imputation methods in multiple regression analysis. The four imputation methods were the following: regression-ratio quartile1,3 (R-RQ1,3) imputation of Al-Omari, Jemain and Ibrahim;
Juthaphorn Sinsomboonthong, Saichon Sinsomboonthong   +1 more
doaj   +1 more source

A steady-state analysis of the ε-normalized sign-error least mean square (NSLMS) adaptive algorithm

, 2011
In this work, expressions are derived for the steady-state excess-mean-square error (EMSE) of the ε-normalized sign-error least mean square (NSLMS) adaptive algorithm for both cases of real- and complex-valued data.
Zerguine, A., Ulla Faiz, M.
core   +1 more source

Directional Latent Hybridization: Beyond Random Noise in Physics‐Informed Generative Inverse Design of Nonlinear Metamaterials

Advanced Materials Technologies, EarlyView.
A physics‐informed generative framework introduces Directional Latent Hybridization (DLH) for the deterministic inverse design of nonlinear metamaterials. By hybridizing dominant traits from parent geometries in the latent space, DLH overcomes the instabilities of stochastic models to ensure high structural precision at high densities.
Semin Ahn, Jun Young Choi, Sung‐Hoon Ahn   +2 more
wiley   +1 more source

Migrative armadillo optimization enabled a one-dimensional quantum convolutional neural network for supply chain demand forecasting.

PLoS ONE
Demand forecasting is a quite challenging task, which is sensitive to several factors such as endogenous and exogenous parameters. In the context of supply chain management, demand forecasting aids to optimize the resources effectively.
Mohamed Irhuma, Ahmad Alzubi, Tolga Öz, Kolawole Iyiola   +3 more
doaj   +1 more source