Zerrendatu Kongresuak-Ingeniaritza honen arabera: izenburua
303-tik 180-199 emaitza erakusten
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Kernel hautapen dinamikoa Optimizazio Bayesiarrean
(UEU, 2015)In Bayesian Optimization, when using a Gaussian Process prior, some kernels adapt better than others to the objective function. This research evaluates the possibility of dynamically changing the kernel function based on ... -
Labor Induction failure prediction based on B-Mode Ultrasound Image Processing using Multiscale Local Binary Patterns
(IEEE, 2016)Labor induction is defined as the artificial onset of labor for the purpose of vaginal birth. Cesarean section is one of the potential risks of labor induction as it occurs in about 20% of the inductions. A ripe cervix ... -
Labor Induction failure prediction using Gabor filterbanks and Center Symmetric Local Binary Patterns
(IEEE, 2018)Labor induction is defined as the artificial stimulation of uterine contractions aimed to induce vaginal birth. Occurring in about 20% of pregnancies labor induction has become one the most commonly practiced procedures ... -
Latentziarik gabeko sareko identifikatzaileen aleatorizazioa kontrol industrialerako sistemetan proaktiboki errekonozimendu erasoak mitigatzeko
(UEU, 2023)Kontrol industrialerako sistemak askotariko instalazio industrialetan erabiltzen dira, azpiegitura kritikoetan barne, segurtasun-eraso anitzen helburu nagusi bihurtuz. Sare industrialen konfigurazio eta topologia estatikoek, ... -
Li-ion Battery State-of-Charge estimation algorithm with CNN-LSTM and Transfer Learning using synthetic training data
(2022)The development of State-of-Charge (SoC) algorithms for Li-ion batteries involves carrying out different laboratory tests with the money and time that this entails. Furthermore, such laboratory labours must typically be ... -
Lithium-ion Battery Aging Prediction with Electrochemical Models: P2D vs SPMe
(IEEE, 2023)Battery aging models are essential tools when predicting how much a battery will age under certain working conditions, which is key when sizing a battery pack and controlling its operation. Nowadays, mostly empirical battery ... -
Machining behaviour of Ti-6Al-4V and Ti-5553 alloys in interrupted cutting with PVD coated cemented carbide
(Elsevier, 2012)Machining behaviour of Ti-5553, Ti-6Al-4 V mill-annealed (MA) and Ti-6Al-4 V solution treated and aged (STA) alloys was studied in different interrupted cutting operations using PVD coated cemented carbide tools. Single ... -
Magnet eddy current loss calculation method for segmentation analysis on permanent magnet machines
(IEEE, 2011)Eddy current losses generated in the rotor of permanent magnet machines may lead to an excessive magnet heating. This can cause the magnets to get fully demagnetized so it is very important to analyze the losses on them. ... -
Makina Elektrikoen Portaera Bibroakustikoaren Neurketa eta Simulazioa
(UEU, 2015)Noise and vibration of electrical machines is a major concern. Changes in the machine design to improve its ef f iciency can lead to unacceptable vibrations. Tools to predict its vibratory and acoustic performance at the ... -
Mapping human factors in virtual reality: VRUX
(AEIPRO, 2023)Industry 5.0 addresses the technocentric limitations of Industry 4.0 and opts for a more humancentred industry. This affects the different technologies that are already being implemented in manufacturing such as exoskeletons, ... -
El marco de la formación dual universitaria en MU: la transición del modelo de alternancia a la formación dual
(Universidade de Santiago de Compostela, 2018) -
MDE based IoT Service to enhance the safety of controllers at runtime
(Aachen University, 2019)One of the challenges for complex IoT software systems is toincrease their safety. A Model Driven Development approach helps in the design and development phase of these systems while runtime checkin gtechniques help to ... -
Mechanical and electrical properties of additively manufactured copper
(IOP Publishing, 2021)Additive Manufacturing (AM) has become the new paradigm of design and production strategies. While structural and functional materials are the most implemented ones, it is also possible to manufacture parts using precious ... -
A meta-learning strategy based on deep ensemble learning for tool condition monitoring of machining processes
(Elsevier, 2023)For Industry 4.0, tool condition monitoring (TCM) of machining processes aims to increase process efficiency and quality and lower tool maintenance costs. To this end, TCM systems monitor variables of interest, such as ... -
Metamorphic Testing of Autonomous Vehicles: a Case Study on Simulink
(2021)Autonomous Vehicles (AVs) will revolutionize the way people travel by car. However, in order to deploy autonomous vehicles, effective testing techniques are required. The driving quality of an AV should definitely be ... -
Methodology for thermal modelling of lithium-ion batteries
(IEEE, 2013)Temperature is a determinant parameter in terms of performance, lifespan and safety working with li-ion batteries. Working above 45°C, in hot climates, has direct influence in the cycle life of the battery and can cause a ... -
Methodology to Study Demagnetization Risk in Permanent Magnet Machines by Finite Element Method
(IEEE, 2017)Nowadays the majority of applications are demanding more and more compact, cost effective and robust solutions for their electric drives. In this context permanent magnet synchronous machines are considered as a good ... -
Metodología UCAD: Principios para garantizar el desarrollo de soluciones digitales que tienen en cuenta a los usuarios
(AEIPRO, 2017)The so-called Industry 4.0 has caused the introduction of new digital technologies that increase and improve the production and potential of the new intelligent industry. For that, it’s necessary a good communication between ... -
Microservices for Continuous Deployment, Monitoring and Validation in Cyber-Physical Systems: an Industrial Case Study for Elevators Systems
(IEEE, 2021)Cyber-Physical Systems (CPSs) are systems that integrate digital cyber computations with physical processes. The software embedded in CPSs has a long life-cycle, requiring constant evolution to support new requirements, ... -
Model driven Hardware-in-the-Loop Fault analysis of railway traction systems
(IEEE, 2017)Classical Dependability Analysis techniques, such as Failure Mode and Effects Analysis (FMEA) and Fault Tree Analysis, have been used during the last decades to demonstrate the reliability, availability, maintainability ...
