NEW METHODOLOGY FOR FEEDER RECONFIGURATION IN DISTRIBUTION NETWORKS WITH DISTRIBUTED ENERGY RESOURCES

This doctoral Thesis defines and develops a new methodology for feeder reconfiguration in distribution networks with Distributed Energy Resources (DER). The proposed methodology is based on metaheuristic Ant Colony Optimization (ACO) algorithms. The methodology is called Item Oriented Ant System (IOAS) and the doctoral Thesis also defines three variations of the original methodology, Item Oriented Ant Colony System (IOACS), Item Oriented Max-min Ant System (IOMMAS) y Item Oriented Max-min Ant Colony System (IOACS). All methodologies pursue a twofold objective, to minimize the power losses and maximize DER penetration in distribution networks. The aim of the variations is to find the algorithm that adapts better to the present optimization problem, solving it most efficiently. The main feature of the methodology lies in the fact that the heuristic information and the exploitation information (pheromone) are attached to the item not to the path. Besides, the doctoral Thesis proposes to use feeder reconfiguration in order to increase the distribution network capacity of accepting a major degree of DER. The proposed methodology and its three variations have been tested and verified in two distribution networks well documented in the existing bibliography. These networks have been modeled and used to test all proposed methodologies for different scenarios with various DER penetration degrees.

PIM-SM extension for Source-Specific Multicast through non multicast networks

Barneko ikerkuntza-txostena

How central are clients in sexual networks created by commercial sex?

Sex workers are traditionally considered important vectors of transmission of sexually transmitted infections (STI). The role of clients is commonly overlooked, partially due to the lack of evidence on clients' position in the sexual network created by commercial sex. Contrasting the diffusion importance of sex workers and their clients in the map of their sexual encounters in two Web-mediated communities, we find that from diffusion perspective, clients are as important as sex workers. Their diffusion importance is closely linked to the geography of the sexual encounters: as a result of different movement patterns, travelling clients shorten network distances between distant network neighborhoods and thus facilitate contagion among them more than sex workers, and find themselves more often in the core of the network by which they could contribute to the persistence of STIs in the community. These findings position clients into the set of the key actors and highlight the role of human mobility in the transmission of STIs in commercial sexual networks.

Prediction of Multi-Target Networks of Neuroprotective Compounds with Entropy Indices and Synthesis, Assay, and Theoretical Study of New Asymmetric 1,2-Rasagiline Carbamates

In a multi-target complex network, the links (L-ij) represent the interactions between the drug (d(i)) and the target (t(j)), characterized by different experimental measures (K-i, K-m, IC50, etc.) obtained in pharmacological assays under diverse boundary conditions (c(j)). In this work, we handle Shannon entropy measures for developing a model encompassing a multi-target network of neuroprotective/neurotoxic compounds reported in the CHEMBL database. The model predicts correctly >8300 experimental outcomes with Accuracy, Specificity, and Sensitivity above 80%-90% on training and external validation series. Indeed, the model can calculate different outcomes for >30 experimental measures in >400 different experimental protocolsin relation with >150 molecular and cellular targets on 11 different organisms (including human). Hereafter, we reported by the first time the synthesis, characterization, and experimental assays of a new series of chiral 1,2-rasagiline carbamate derivatives not reported in previous works. The experimental tests included: (1) assay in absence of neurotoxic agents; (2) in the presence of glutamate; and (3) in the presence of H2O2. Lastly, we used the new Assessing Links with Moving Averages (ALMA)-entropy model to predict possible outcomes for the new compounds in a high number of pharmacological tests not carried out experimentally.

Estimating relative abundance from catch and effort data, using neural networks

We develop and test a method to estimate relative abundance from catch and effort data using neural networks. Most stock assessment models use time series of relative abundance as their major source of information on abundance levels. These time series of relative abundance are frequently derived from catch-per-unit-of-effort (CPUE) data, using general linearized models (GLMs). GLMs are used to attempt to remove variation in CPUE that is not related to the abundance of the population. However, GLMs are restricted in the types of relationships between the CPUE and the explanatory variables. An alternative approach is to use structural models based on scientific understanding to develop complex non-linear relationships between CPUE and the explanatory variables. Unfortunately, the scientific understanding required to develop these models may not be available. In contrast to structural models, neural networks uses the data to estimate the structure of the non-linear relationship between CPUE and the explanatory variables. Therefore neural networks may provide a better alternative when the structure of the relationship is uncertain. We use simulated data based on a habitat based-method to test the neural network approach and to compare it to the GLM approach. Cross validation and simulation tests show that the neural network performed better than nominal effort and the GLM approach. However, the improvement over GLMs is not substantial. We applied the neural network model to CPUE data for bigeye tuna (Thunnus obesus) in the Pacific Ocean.

Diseño e implementación de complemento OpenFlow para ejecución de mensajes en un tiempo predefinido en Software Defined Networks.

[ES]El objetivo de este trabajo es el diseño e implementación de un complemento adicional a OpenFlow que permita la ejecución de los mensajes en el switch dentro de un espacio de tiempo concreto que previamente ha sido definido. El primer paso será la definición de objetivos y especificaciones del trabajo, para posteriormente realizar el diseño de un escenario mediante el análisis de posibles alternativas, y que permitirá la consecución de dichos objetivos. A continuación se añadirá el código necesario para que los equipos sean capaces de realizar el envío y ejecución de los mensajes en el tiempo programado y se finalizará realizando simulaciones y pruebas tanto del funcionamiento como del formato que utilizan los mensajes intercambiados entre el controlador y los switches que maneja, con el objetivo de verificar la viabilidad del módulo desarrollado.