Zobrazeno 1 - 10
of 141
pro vyhledávání: '"José C. Riquelme"'
Publikováno v:
Heliyon, Vol 10, Iss 4, Pp e25821- (2024)
The global surge in energy demand, driven by technological advances and population growth, underscores the critical need for effective management of electricity supply and demand. In certain developing nations, a significant challenge arises because
Externí odkaz:
https://doaj.org/article/944ecb6ef11b4dc78e4068afdd72ded2
Publikováno v:
Heliyon, Vol 10, Iss 3, Pp e25838- (2024)
CO2 emissions play a crucial role in international politics. Countries enter into agreements to reduce the amount of pollution emitted into the atmosphere. Energy generation is one of the main contributors to pollution and is generally considered the
Externí odkaz:
https://doaj.org/article/8130ee3e71a84c6793067f1a5eb926ec
Autor:
Beatriz Pontes Balanza, Juan M. Castillo Tuñón, Daniel Mateos García, Javier Padillo Ruiz, José C. Riquelme Santos, José M. Álamo Martinez, Carmen Bernal Bellido, Gonzalo Suarez Artacho, Carmen Cepeda Franco, Miguel A. Gómez Bravo, Luis M. Marín Gómez
Publikováno v:
Frontiers in Surgery, Vol 10 (2023)
BackgroundThe complex process of liver graft assessment is one point for improvement in liver transplantation. The main objective of this study is to develop a tool that supports the surgeon who is responsible for liver donation in the decision-makin
Externí odkaz:
https://doaj.org/article/f84dbda27f254bc298ef747754ce07d0
Autor:
Francisco J. Núñez-Benjumea, Sara González-García, Alberto Moreno-Conde, José C. Riquelme-Santos, José L. López-Guerra
Publikováno v:
Clinical and Translational Radiation Oncology, Vol 41, Iss , Pp 100640- (2023)
Background and purpose: Radiation-induced toxicities are common adverse events in lung cancer (LC) patients undergoing radiotherapy (RT). An accurate prediction of these adverse events might facilitate an informed and shared decision-making process b
Externí odkaz:
https://doaj.org/article/c69129fcd6044fdd9890712ab9ea3c42
Autor:
Laura Madrid-Márquez, Cristina Rubio-Escudero, Beatriz Pontes, Antonio González-Pérez, José C. Riquelme, Maria E. Sáez
Publikováno v:
Applied Sciences, Vol 12, Iss 8, p 3987 (2022)
Background and Objectives: The burst of high-throughput omics technologies has given rise to a new era in systems biology, offering an unprecedented scenario for deriving meaningful biological knowledge through the integration of different layers of
Externí odkaz:
https://doaj.org/article/cb0216c11586475a979161697d4d5baa
Publikováno v:
Nanomaterials, Vol 11, Iss 10, p 2706 (2021)
The morphology of nanoparticles governs their properties for a range of important applications. Thus, the ability to statistically correlate this key particle performance parameter is paramount in achieving accurate control of nanoparticle properties
Externí odkaz:
https://doaj.org/article/fe8f342d0dc0408fae61ee0c46cda2c1
Publikováno v:
Applied Sciences, Vol 10, Iss 7, p 2322 (2020)
Modern energy systems collect high volumes of data that can provide valuable information about energy consumption. Electric companies can now use historical data to make informed decisions on energy production by forecasting the expected demand. Many
Externí odkaz:
https://doaj.org/article/dc45b7c9246e47188b80098603a7e63f
Publikováno v:
Energies, Vol 8, Iss 11, Pp 13162-13193 (2015)
Data mining has become an essential tool during the last decade to analyze large sets of data. The variety of techniques it includes and the successful results obtained in many application fields, make this family of approaches powerful and widely us
Externí odkaz:
https://doaj.org/article/1efe373b025f4f5fa3fe03fda73b3031
Publikováno v:
Remote Sensing, Vol 11, Iss 3, p 274 (2019)
Analyzing land use and land cover (LULC) using remote sensing (RS) imagery is essential for many environmental and social applications. The increase in availability of RS data has led to the development of new techniques for digital pattern classific
Externí odkaz:
https://doaj.org/article/7c25ca23b59349638f2a97410677c42e
Publikováno v:
Energies, Vol 11, Iss 11, p 3224 (2018)
This editorial summarizes the performance of the special issue entitled Data Science and Big Data in Energy Forecasting, which was published at MDPI’s Energies journal. The special issue took place in 2017 and accepted a total of 13 papers from 7 d
Externí odkaz:
https://doaj.org/article/36968b733afb49d8ada39ebd65d1eda2