Design of VR app applied to cognitive training

Currently, the world of virtual reality (VR) is taking more and more strength and is expanding in multiple areas of our day to day. The augmented reality began to have a lot of repercussion in the world of videogames since it brought the user a greater immersion in the environment and, therefore, increase the sensory experience in the game to a much higher level. However, the virtual reality did not remain in the recreational area, but it has been expanding in other professional areas focused on technologies such as engineering, architecture, medicine, etc... In this project, we will see the virtual reality focused on the world of medicine and the advantages that this technological advance in this field can bring. For this, the project will be carried out in collaboration with the Clinical Hospital, with which real tests with patients can be done to see the effectiveness of the project and virtual reality in the world of medicine. There will also be the support of the Visyon 3D company that will provide us with the necessary equipment and technology to carry out the project. The project consists of the continuation of the application to improve and refine it to make the adaptability, control and playability of said application using virtual reality easier and simpler to facilitate the patient experience and work of the doctor in charge of the user of the application. Several applications of different projects will also be implemented in one to have a global set. The part of the project memory includes the list of all the elements, organization and structure of the application design and how it has been programmed. In this way, the improvements that have been introduced and the result with the tests of the patients with the determined analyzes are presented. Finally, the project has been valued with some conclusions in the final part with which, we also wanted to emphasize the future lines in which the current application can be worked on

Strategic Deployment of Swarm of UAVs for Secure IoT Networks

Security provisioning for low-complex and constrained devices in the Internet of Things (IoT) is exacerbating the concerns for the design of future wireless networks. To unveil the full potential of the sixth generation (6G), it is becoming even more evident that security measurements should be considered at all layers of the network. This work aims to contribute in this direction by investigating the employment of unmanned aerial vehicles (UAVs) for providing secure transmissions in ground IoT networks. Toward this purpose, it is considered that a set of UAVs acting as aerial base stations provide secure connectivity between the network and multiple ground nodes. Then, the association of IoT nodes, the 3D positioning of the UAVs and the power allocation of the UAVs are obtained by leveraging game theoretic and convex optimization-based tools with the goal of improving the secrecy of the system. It is shown that the proposed framework obtains better and more efficient secrecy performance over an IoT network than state-of-the-art greedy algorithms for positioning and association

Heuristic methods for solving two discrete optimization problems

In this thesis we study two discrete optimization problems: Traffic Light Synchronization and Location with Customers Orderings. A widely used approach to solve the synchronization of traffic lights on transport networks is the maximization of the time during which cars start at one end of a street and can go to the other without stopping for a red light (bandwidth maximization). The mixed integer linear model found in the literature, named MAXBAND, can be solved by optimization solvers only for small instances. In this manuscript we review in detail all the constraints of the original linear model, including those that describe all the cyclic routes in the graph, and we generalize some bounds for integer variables which so far had been presented only for problems that do not consider cycles. Furthermore, we summarized the first systematic algorithm to solve a simpler version of the problem on a single street. We also propose a solution algorithm that uses Tabu Search and Variable Neighbourhood Search and we carry out a computational study. In addition we propose a linear formulation for the shortest path problem with traffic lights constraints (SPTL). On the other hand, the simple plant location problem with order (SPLPO) is a variant of the simple plant location problem (SPLP) where the customers have preferences on the facilities which will serve them. In particular, customers define their preferences by ranking each of the potential facilities. Even though the SPLP has been widely studied in the literature, the SPLPO has been studied much less and the size of the instances that can be solved is very limited. In this manuscript, we propose a heuristic that uses a Lagrangean relaxation output as a starting point of a semi-Lagrangean relaxation algorithm to find good feasible solutions (often the optimal solution). We also carry out a computational study to illustrate the good performance of our method. Last, we introduce the partial and stochastic versions of SPLPO and apply the Lagrangean algorithm proposed for the deterministic case to then show examples and results

Estudio de flujos de carga, arranque de motores, fallas y coordinación de protecciones del campo petrolero VHR, usando el programa ETAP

El objetivo principal de este trabajo es realizar el estudio de flujos de carga, cortocircuitos, coordinación de protecciones y arranque dinámico de motores, para la ampliación del campo petrolero VHR, con lo cual se definirá los lineamientos y características de operación del sistema eléctrico de potencia y sus partes. Con lo que se pretende, optimizar el sistema para una adecuada generación y distribución, salvaguardando la integridad de los equipos y el personal que laborará en estas instalaciones

Multi UAV-enabled Distributed Sensing: Cooperation Orchestration and Detection Protocol

This paper proposes an unmanned aerial vehicle (UAV)-based distributed sensing framework that uses orthogonal frequency-division multiplexing (OFDM) waveforms to detect the position of a ground target, and UAVs operate in half-duplex mode. A spatial grid approach is proposed, where an specific area in the ground is divided into cells of equal size, then the radar cross-section (RCS) of each cell is jointly estimated by a network of dual-function UAVs. For this purpose, three estimation algorithms are proposed employing the maximum likelihood criterion, and digital beamforming is used for the local signal acquisition at the receive UAVs. It is also considered that the coordination, fusion of sensing data, and central estimation is performed at a certain UAV acting as a fusion center (FC). Monte Carlo simulations are performed to obtain the absolute estimation error of the proposed framework. The results show an improved accuracy and resolution by the proposed framework, if compared to a single monostatic UAV benchmark, due to the distributed approach among the UAVs. It is also evidenced that a reduced overhead is obtained when compared to a general compressive sensing (CS) approach