Testing Cayley graph densities

We present a computer-assisted analysis of combinatorial properties of the Cayley graphs of certain finitely generated groups: Given a group with a finite set of generators, we study the density of the corresponding Cayley graph, that is, the least upper bound for the average vertex degree (= number of adjacent edges) of any finite subgraph. It is known that an m-generated group is amenable if and only if the density of the corresponding Cayley graph equals to 2m. We test amenable and non-amenable groups, and also groups for which amenability is unknown. In the latter class we focus on Richard Thompson’s group F.

A Retail benchmarking approach to eficient two-way access pricing

We study a retail benchmarking approach to determine access prices for interconnected networks. Instead of considering fixed access charges as in the existing literature, we study access pricing rules that determine the access price that network i pays to network j as a linear function of the marginal costs and the retail prices set by both networks. In the case of competition in linear prices, we show that there is a unique linear rule that implements the Ramsey outcome as the unique equilibrium, independently of the underlying demand conditions. In the case of competition in two-part tariffs, we consider a class of access pricing rules, similar to the optimal one under linear prices but based on average retail prices. We show that firms choose the variable price equal to the marginal cost under this class of rules. Therefore, the regulator (or the competition authority) can choose one among the rules to pursue additional objectives such as consumer surplus, network covera.

Theoretical aspects of graph models for MANETs

We survey the main theoretical aspects of models for Mobile Ad Hoc Networks (MANETs). We present theoretical characterizations of mobile network structural properties, different dynamic graph models of MANETs, and finally we give detailed summaries of a few selected articles. In particular, we focus on articles dealing with connectivity of mobile networks, and on articles which show that mobility can be used to propagate information between nodes of the network while at the same time maintaining small transmission distances, and thus saving energy.

A linear optimization technique for graph pebbling

Graph pebbling is a network model for studying whether or not a given supply of discrete pebbles can satisfy a given demand via pebbling moves. A pebbling move across an edge of a graph takes two pebbles from one endpoint and places one pebble at the other endpoint; the other pebble is lost in transit as a toll. It has been shown that deciding whether a supply can meet a demand on a graph is NP-complete. The pebbling number of a graph is the smallest t such that every supply of t pebbles can satisfy every demand of one pebble. Deciding if the pebbling number is at most k is NP 2 -complete. In this paper we develop a tool, called theWeight Function Lemma, for computing upper bounds and sometimes exact values for pebbling numbers with the assistance of linear optimization. With this tool we are able to calculate the pebbling numbers of much larger graphs than in previous algorithms, and much more quickly as well. We also obtain results for many families of graphs, in many cases by hand, with much simpler and remarkably shorter proofs than given in previously existing arguments (certificates typically of size at most the number of vertices times the maximum degree), especially for highly symmetric graphs. Here we apply theWeight Function Lemma to several specific graphs, including the Petersen, Lemke, 4th weak Bruhat, Lemke squared, and two random graphs, as well as to a number of infinite families of graphs, such as trees, cycles, graph powers of cycles, cubes, and some generalized Petersen and Coxeter graphs. This partly answers a question of Pachter, et al., by computing the pebbling exponent of cycles to within an asymptotically small range. It is conceivable that this method yields an approximation algorithm for graph pebbling.

CubeExplorer : Sistema Gestor de Cubs OLAP .NET

Els sistemes OLAP són solucions molt utilitzades actualment en el camp de la intel·ligència empresarial (Business Intelligence). Sovint els sistemes que construeixen aquest tipus de solucions son massa complexos, difícils d'instal·lar i configurar o massa costosos. El present Treball de Fi de Carrera ofereix una solució informàtica que facilita la implementació d'aquest tipus de sistemes, presentant una aplicació molt configurable que pot generar cubs de diferents sistemes gestors de bases de dades i que per tant es pot adaptar a diferents entorns empresarials. L'aplicació s'ha desenvolupat en plataforma .NET.

Análisis de la proyección profesional del Grado de Ingeniería Informática y Telecomunicación : Viabilidad profesional en tiempos de crisis y benchmarking

El objetivo específico del TFG es el de realizar un análisis riguroso en base a fuentes externas y referencias de probada veracidad en relación a la oferta universitaria actual de estudios de Grado de Informática y Telecomunicación en España en la modalidad de e-learning o educación a distancia.

Clustering algorithms for anti-money laundering using graph theory and social network analysis

HEMOLIA (a project under European community’s 7th framework programme) is a new generation Anti-Money Laundering (AML) intelligent multi-agent alert and investigation system which in addition to the traditional financial data makes extensive use of modern society’s huge telecom data source, thereby opening up a new dimension of capabilities to all Money Laundering fighters (FIUs, LEAs) and Financial Institutes (Banks, Insurance Companies, etc.). This Master-Thesis project is done at AIA, one of the partners for the HEMOLIA project in Barcelona. The objective of this thesis is to find the clusters in a network drawn by using the financial data. An extensive literature survey has been carried out and several standard algorithms related to networks have been studied and implemented. The clustering problem is a NP-hard problem and several algorithms like K-Means and Hierarchical clustering are being implemented for studying several problems relating to sociology, evolution, anthropology etc. However, these algorithms have certain drawbacks which make them very difficult to implement. The thesis suggests (a) a possible improvement to the K-Means algorithm, (b) a novel approach to the clustering problem using the Genetic Algorithms and (c) a new algorithm for finding the cluster of a node using the Genetic Algorithm.

Modelo de datos para la monitorización de cambios geométricos del parcelario catastral

La presente investigación propone un modelo de datos que puede ser utilizado en diversos tipos de aplicaciones relacionados con la estructura de la propiedad (Catastro, Registro de la propiedad, Notarías, etc). Este modelo definido en lenguaje universal de modelado (UML), e implementado sobre gestor de base de datos orientada a grafos (Neo4j), permite almacenar y consultar ese histórico, pudiendo ser explotado posteriormente tanto por aplicaciones de escritorio como por servicios web.

Place marketing performance: benchmarking european cities as business destinations

The aim of this study is to develop a model measuring the performance of cities' marketing efforts. The model and the benchmarking methodology presented can be used by local authorities to position their marketing efforts and achievements against other (competing) cities and to identify best practices that can assist place marketers in learning how to be more efficient obtaining desired place marketing results, e.g., improved city brand image, with the available resources/budgets. The major implication for practitioners is that place marketing should be managed as a process, taking into account both the resource flows and the outputs, as well as the efficiency of this process.

Comparativa de rendiment OLAP per a diferents motors de bases de dades orientades a columnes

En aquest projecte es realitza una comparativa de rendiment i utilització entre els diferents models de bases de dades orientades a columnes mitjançant la construcció i explotació d'un cub OLAP utilitzant la suite de BI Pentaho.

Asset pricing implications of benchmarking: A two-factor CAPM

In this paper we consider the equilibrium effects of an institutionalinvestor whose performance is benchmarked to an index. In a partialequilibrium setting, the objective of the institutional investor is modeledas the maximization of expected utility (an increasing and concave function,in order to accommodate risk aversion) of final wealth minus a benchmark.In equilibrium this optimal strategy gives rise to the two-beta CAPM inBrennan (1993): together with the market beta a new risk-factor (that wecall active management risk) is brought into the analysis. This new betais deffined as the normalized (to the benchmark's variance) covariancebetween the asset excess return and the excess return of the market overthe benchmark index. Different to Brennan, the empirical test supports themodel's predictions. The cross-section return on the active management riskis positive and signifficant especially after 1990, when institutionalinvestors have become the representative agent of the market.

A retail benchmarking approach to efficient two-way access pricing

We study a retail benchmarking approach to determine access prices for interconnected networks. Instead of considering fixed access charges as in the existing literature, we study access pricing rules that determine the access price that network i pays to network j as a linear function of the marginal costs and the retail prices set by both networks. In the case of competition in linear prices, we show that there is a unique linear rule that implements the Ramsey outcome as the unique equilibrium, independently of the underlying demand conditions. In the case of competition in two-part tariffs, we consider a class of access pricing rules, similar to the optimal one under linear prices but based on average retail prices. We show that firms choose the variable price equal to the marginal cost under this class of rules. Therefore, the regulator (or the competition authority) can choose one among the rules to pursue additional objectives such as consumer surplus, network coverage or investment: for instance, we show that both static and dynamic e±ciency can be achieved at the same time.

Comparing Random-based and k-Anonymity-Based Algorithms for Graph Anonymization

Recently, several anonymization algorithms have appeared for privacy preservation on graphs. Some of them are based on random-ization techniques and on k-anonymity concepts. We can use both of them to obtain an anonymized graph with a given k-anonymity value. In this paper we compare algorithms based on both techniques in orderto obtain an anonymized graph with a desired k-anonymity value. We want to analyze the complexity of these methods to generate anonymized graphs and the quality of the resulting graphs.

Benchmarking for routines and organizational knowledge

We use best practice benchmarking rationales to propose a dynamic research design that accounts for the endogenous components of across-firms heterogeneous routines to study changes in performance and their link to organizational knowledge investments. We thus contribute to the operationalization of management theoretical frameworks based on resources and routines. The research design employs frontier measures that provide industry-level benchmarking in organizational settings, and proposes some new indicators for firm-level strategic benchmarking. A profit-oriented analysis of the U.S. technology industry during 2000-2011 illustrates the usefulness of our design. Findings reveal that industry revival following economic distress comes along with wider gaps between best and worst performers. Second stage analyses show that increasing intangibles stocks is positively associated with fixed target benchmarking, while enhancing R&D spending is linked to local frontier progress. The discussion develops managerial interpretations of the benchmarking measures that are suitable for control mechanisms and reward systems.