Artificial intelligence for advanced manufacturing quality

100 p.This Thesis addresses the challenge of AI-based image quality control systems applied to manufacturing industry, aiming to improve this field through the use of advanced techniques for data acquisition and processing, in order to obtain robust, reliable and optimal systems. This Thesis presents contributions onthe use of complex data acquisition techniques, the application and design of specialised neural networks for the defect detection, and the integration and validation of these systems in production processes. It has been developed in the context of several applied research projects that provided a practical feedback of the usefulness of the proposed computational advances as well as real life data for experimental validation

Simulación molecular de agua supercrítica

[ES] El agua en condiciones supercríticas (T > 374ºC y P > 218 atm) es de un grán interés como disolvente en procesos de síntesis de cristales. En este trabajo se pretende comprobar si los potenciales empíricos denominados ReaxFF son adecuados para el estudio de agua en condiciones supercríticas. Para ello se realizarán varias simulaciones de dinámica molecular y se compararán los resultados con los datos experimentales y con otros potenciales empíricos ya estudiados

Simulación molecular de agua supercrítica

[ES] El agua en condiciones supercríticas (T > 374ºC y P > 218 atm) es de un grán interés como disolvente en procesos de síntesis de cristales. En este trabajo se pretende comprobar si los potenciales empíricos denominados ReaxFF son adecuados para el estudio de agua en condiciones supercríticas. Para ello se realizarán varias simulaciones de dinámica molecular y se compararán los resultados con los datos experimentales y con otros potenciales empíricos ya estudiados

Digital quantum simulation of an extended Agassi model: Using machine learning to disentangle its phase-diagram

A digital quantum simulation for the extended Agassi model is proposed using a quantum platform with eight trapped ions. The extended Agassi model is an analytically solvable model including both short range pairing and long range monopole-monopole interactions with applications in nuclear physics and in other many-body systems. In addition, it owns a rich phase diagram with different phases and the corresponding phase transition surfaces. The aim of this work is twofold: on one hand, to propose a quantum simulation of the model at the present limits of the trapped ions facilities and, on the other hand, to show how to use a machine learning algorithm on top of the quantum simulation to accurately determine the phase of the system. Concerning the quantum simulation, this proposal is scalable with polynomial resources to larger Agassi systems. Digital quantum simulations of nuclear physics models assisted by machine learning may enable one to outperform the fastest classical computers in determining fundamental aspects of nuclear matter.Comment: 15 pages, 11 figures. New title and minor changes. Published in PR

Digital-analog quantum computation with arbitrary two-body Hamiltonians

Digital-analog quantum computing is a computational paradigm which employs an analog Hamiltonian resource together with single-qubit gates to reach universality. Here, we design a new scheme which employs an arbitrary two-body source Hamiltonian, extending the experimental applicability of this computational paradigm to most quantum platforms. We show that the simulation of an arbitrary two-body target Hamiltonian of n qubits requires O(n2) analog blocks with guaranteed positive times, providing a polynomial advantage compared to the previous scheme. Additionally, we propose a classical strategy which combines a Bayesian optimization with a gradient descent method, improving the performance by ∼55% for small systems measured in the Frobenius norm.The Spanish Grants No. PID2019-104002GB-C21, No. PID2019-104002GB-C22, No. PID2022-136228NB-C21, and No. PID2022-136228NB-C22 funded by Ministerio de Ciencia e Innovación/Agencia Estatal de Investigación MCIN/AEI/10.13039/501100011033, FEDER “A Way of Making Europe,” Consejería de Conocimiento, Investigación y Universidad, Junta de Andalucía, European Regional Development Fund (ERDF) under Project No. US-1380840, Grant Groups FQM-160 and FQM-177, and the project PAIDI 2020 with Reference No. P20_01247 and No. P20_00617 funded by the Consejería de Economía, Conocimiento, Empresas y Universidad, Junta de Andalucía (Spain).ERDF/MINECO Project No. UNHU-15CE-2848EU FET Open project EPIQUS (899368)HORIZON-CL4-2022-QUANTUM01-SGA Project No. 101113946 OpenSuperQPlus100 of the EU Flagship on Quantum TechnologiesSpanish Ramón y Cajal Grant No. RYC-2020-030503-I, Grant No. PID2021-125823NA-I00 funded by MCIN/AEI/10.13039/501100011033 and by “ERDF A way of making Europe”“ERDF Invest in your Future,” Basque Government, through Grant No. IT1470-22IKUR Strategy under the collaboration agreement between Ikerbasque Foundation and BCAM on behalf of the Department of Education of the Basque GovernmentUPV/EHU and TECNALIA 2021 PIF contract callMinistry for Digital Transformation and of Civil Service of the Spanish Government through the QUANTUM ENIA project call–Quantum Spain projectThe European Union through the Recovery, Transformation and Resilience Plan–NextGenerationEU within the framework of the “Digital Spain 2026 Agenda

Validation of a Scale of Student Satisfaction with Final Year Degree Projects

Introducción. Este artículo analiza un aspecto referencial en las enseñanzas en el marco de la Educación Superior como es el de la satisfacción de los estudiantes con la realización de los trabajos de fin de titulación (TFT). Método. Se realizó un estudio longitudinal durante tres cursos académicos sobre la satisfac-ción de los estudiantes con los TFT. Se trabajó con una muestra de 1331 estudiantes, 1014 de grado y 317 de máster distribuidos en 30 grados y 23 másteres. Los objetivos de este estudio fueron 1) Hallar los indicadores de fiabilidad y de validez de la Escala de satisfacción, 2) Comprobar si existían diferencias significativas atendiendo a las variables el tipo de estudios y tipo de rama de conocimiento, 3) Estudiar las propuestas de mejora sugeridas por los estu-diantes. Resultados. Respecto del primer objetivo se encontraron indicadores de fiabilidad altos (α = .88; α = .90) y de validez que se comprobaron con un Análisis Factorial Confirmatorio (AFC). Respecto del segundo objetivo, se hallaron diferencias significativas en la satisfacción de los estudiantes en las dos variables en todos los ítems de la Escala, salvo en la satisfacción gene-ral. Relativo al tercer objetivo, las indicaciones de mejora se concretaron en optimizar la pla-nificación y la tutorización. Discusión y conclusiones. Futuras acciones formativas se concretan en un plan de formación del profesorado que contemple las acciones de mejora detectadas, así como su seguimiento en una propuesta de mejora continua.Introduction. This paper analyzes a referential aspect into the Higher Education framework as well as the students´ satisfaction with the final degree projects (FDP). Method. Therefore, a longitudinal study has been carried out during three academic years on the satisfaction of students with FDP. We have worked with 1331 students, 1014 of degree and 317 of masters distributed in 30 degrees and 23 masters. The aims of this study were: 1) Find the reliability and validity indicators of the satisfaction Scale, 2) Check if there were significant differences depending on the variables the type of studies (degree or master's de-gree) and the type of branch of knowledge, 3) Study the student improvement proposals. Results. Regarding the first objective, high reliability indicators and high validity were found (α = .87; α = .90) that were checked with a Confirmatory Factor Analysis (CFA). In relation to the second objective, significant differences were found in the satisfaction of the students depending on the degree (degree vs. masters) and the branch of knowledge in all the items of the scale, except for general satisfaction. With respect to the third objective, the indications for improvement were summarized in optimizing the planning and the tutorship. Discussion or Conclusion. So future training actions will be specified in teacher training plan that to improvement actions, as well as its follow-up in a proposal for continuous improve-ment.Ayudas a la traducción y difusión del Vicerrecto-rado de Personal Docente e investigador de la Universidad de Burgos 2018

Quantum Simulation of the Agassi Model in Trapped Ions: determining the shape of the system

Transparencias de la conferencia impartida en "Quantum Computing for Many-Body problems (QCMB): atomic nuclei, neutrinos, and other strongly correlated Fermi systems" (Orsay, Francia)

Assessing Knowledge Management in the Power Sector through a Connectionist Model

It has been proven that Artificial Intelligence, in general, and Artificial Neural Networks, in particular, can be successfully applied to problems in the field of Knowledge Management (KM). One such problem is the identification and assessment of a company’s KM status. Nowadays the importance of KM to organisational survival and for the maintenance of competitive strength is widely acknowledged. Several connectionist models for the assessment and analysis of KM status are proposed and applied in this work. These models account for the specific features of a company in the Energy sector/Power sector: a dynamic, essential service and one of the basic pillars that supports the so-called “welfare state”, constituting an established strategic sector in any globalized economy