Zobrazeno 1 - 10
of 10
pro vyhledávání: '"Manuel P. Cuéllar"'
Autor:
Elfi Fertl, Do Dinh Tan Nguyen, Martin Krueger, Georg Stettinger, Rubén Padial-Allué, Encarnación Castillo, Manuel P. Cuéllar
Publikováno v:
Sensors, Vol 24, Iss 9, p 2740 (2024)
As the number of electronic gadgets in our daily lives is increasing and most of them require some kind of human interaction, this demands innovative, convenient input methods. There are limitations to state-of-the-art (SotA) ultrasound-based hand ge
Externí odkaz:
https://doaj.org/article/39a24964ba344b8c8c9f70174895557f
Autor:
Luis Fermin Capitán-Vallvey, Ignacio de Orbe-Payá, Alberto José Palma, Nuria López-Ruiz, Maria del Carmen Pegalajar, Manuel P. Cuéllar, Antonio Martinez-Olmos, Sonia Capel-Cuevas
Publikováno v:
Sensors, Vol 12, Iss 5, Pp 6746-6763 (2012)
The aim of this work was the determination of pH with a sensor array-based optical portable instrument. This sensor array consists of eleven membranes with selective colour changes at different pH intervals. The method for the pH calculation is based
Externí odkaz:
https://doaj.org/article/e269f21b0fb94915a180450972261b17
Autor:
Carlos Augusto do Nascimento Oliveira, Cezar Henrique Gonzalez, Oscar Olimpio Filho, Niédson José da Silva, Pablo Batista Guimarães, Esau Nuñez-Mendoza, Enrique Manuel López Cuéllar
Publikováno v:
Materials Research, Vol 18, Iss suppl 2, Pp 17-24 (2015)
Shape memory alloys (SMAs) present some characteristics, which make it unique material to be use in applications that require strength and shape recovery. This alloys was been used to manufacture smart actuators for mechanical industry devices and se
Externí odkaz:
https://doaj.org/article/5a263d97eda143eda55a6cb3f71fb5b0
Publikováno v:
Expert Systems with Applications. 224:119955
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::755736aec89bc3110a46b04507413679
https://doi.org/10.1016/j.eswa.2023.119955
https://doi.org/10.1016/j.eswa.2023.119955
Autor:
Gianfranco Mauro, Maria De Carlos Diez, Julius Ott, Lorenzo Servadei, Manuel P. Cuellar, Diego P. Morales-Santos
Publikováno v:
Sensors, Vol 23, Iss 2, p 804 (2023)
Vital signs estimation provides valuable information about an individual’s overall health status. Gathering such information usually requires wearable devices or privacy-invasive settings. In this work, we propose a radar-based user-adaptable solut
Externí odkaz:
https://doaj.org/article/0ee1a29256024c4c99f1603e8f9ba106
Publikováno v:
Sensors, Vol 21, Iss 12, p 3992 (2021)
There have been significant advances regarding target detection in the autonomous vehicle context. To develop more robust systems that can overcome weather hazards as well as sensor problems, the sensor fusion approach is taking the lead in this cont
Externí odkaz:
https://doaj.org/article/86e9f56a33f840a78093eaa9585288aa
Publikováno v:
Mathematics, Vol 12, Iss 8, p 1230 (2024)
In recent years, advancements in brain science and neuroscience have significantly influenced the field of computer science, particularly in the domain of reinforcement learning (RL). Drawing insights from neurobiology and neuropsychology, researcher
Externí odkaz:
https://doaj.org/article/474a3b5a2019491e8102552d64cb05bd
Publikováno v:
Energies, Vol 15, Iss 16, p 6034 (2022)
In the last few years, deep reinforcement learning has been proposed as a method to perform online learning in energy-efficiency scenarios such as HVAC control, electric car energy management, or building energy management, just to mention a few. On
Externí odkaz:
https://doaj.org/article/401f24a3c24c4959b1426f1743b8a0a7
Autor:
Natalia Díaz-Rodríguez, Olmo León Cadahía, Manuel Pegalajar Cuéllar, Johan Lilius, Miguel Delgado Calvo-Flores
Publikováno v:
Sensors, Vol 14, Iss 10, Pp 18131-18171 (2014)
Human activity recognition is a key task in ambient intelligence applications to achieve proper ambient assisted living. There has been remarkable progress in this domain, but some challenges still remain to obtain robust methods. Our goal in this wo
Externí odkaz:
https://doaj.org/article/1d150e5ede9f4240a85e2408d295df70
Autor:
Luis Gonzaga Baca Ruiz, Manuel Pegalajar Cuéllar, Miguel Delgado Calvo-Flores, María Del Carmen Pegalajar Jiménez
Publikováno v:
Energies, Vol 9, Iss 9, p 684 (2016)
This paper addresses the problem of energy consumption prediction using neural networks over a set of public buildings. Since energy consumption in the public sector comprises a substantial share of overall consumption, the prediction of such consump
Externí odkaz:
https://doaj.org/article/0cc0dc0af0034bdba1a63a15804c4647