Mujeres empresarias en el uso de la web 2.0: discursos de un preludio

Este trabajo presenta los principales resultados de una investigación cuya finalidad es conocer la adopción de las redes sociales on-line en las pymes dirigidas por mujeres. Se parte de la base de que el uso de redes, como elemento estratégico de comunicación, se encuentra todavía en una fase incipiente de desarrollo, lejos aún de ser una práctica consolidada. Nuestro interés en este trabajo es conocer la predisposición y motivaciones de las empresarias hacia el uso estas redes, así como las utilidades y dificultades a las que han de enfrentarse. Nos interesa visibilizar el cambio actitudinal y competencial que las empresarias están imprimiendo en sus empresas dentro del marco competitivo en el que se encuentran. En definitiva, nos interesa estudiar la percepción que tienen las empresarias sobre el uso de las redes sociales online en la medida en que están insertas, como una herramienta más de gestión empresarial. Nos situamos ante un nuevo ámbito de conocimiento sobre el que apenas existen referencias bibliográficas ni se ha realizado apenas investigación; de ahí que la investigación tenga una finalidad fundamentalmente exploratoria y de carácter cualitativo. Para la obtención de la información se realizaron catorce entrevistas semi-estructuradas entre empresarias andaluzas de distintos sectores de actividad. Entre los principales resultados encontramos que algo menos de la mitad de ellas las utilizan, o están implantadas en sus empresas, como herramientas de comunicación. El resto, y relacionado con el tamaño de sus negocios, las utilizan como una prolongación del uso personal en el que se iniciaron.

Open educational resources: the role of OCW, blogs and videos in computer network classrooms

This paper analyzes the learning experiences and opinions obtained from a group of undergraduate students in their interaction with several on-line multimedia resources included in a free on-line course about Computer Networks. These new educational resources employed are based on the Web 2.0 approach such as blogs, videos and virtual labs which have been added in a web-site for distance self-learning.

A formal framework for modelling complex network management systems

Society today is completely dependent on computer networks, the Internet and distributed systems, which place at our disposal the necessary services to perform our daily tasks. Subconsciously, we rely increasingly on network management systems. These systems allow us to, in general, maintain, manage, configure, scale, adapt, modify, edit, protect, and enhance the main distributed systems. Their role is secondary and is unknown and transparent to the users. They provide the necessary support to maintain the distributed systems whose services we use every day. If we do not consider network management systems during the development stage of distributed systems, then there could be serious consequences or even total failures in the development of the distributed system. It is necessary, therefore, to consider the management of the systems within the design of the distributed systems and to systematise their design to minimise the impact of network management in distributed systems projects. In this paper, we present a framework that allows the design of network management systems systematically. To accomplish this goal, formal modelling tools are used for modelling different views sequentially proposed of the same problem. These views cover all the aspects that are involved in the system; based on process definitions for identifying responsible and defining the involved agents to propose the deployment in a distributed architecture that is both feasible and appropriate.

On Modeling an Innovative Monitoring Network for Protecting and Managing Cultural Heritage from Risk Events

In this paper the model of an Innovative Monitoring Network involving properly connected nodes to develop an Information and Communication Technology (ICT) solution for preventive maintenance of historical centres from early warnings is proposed. It is well known that the protection of historical centres generally goes from a large-scale monitoring to a local one and it could be supported by a unique ICT solution. More in detail, the models of a virtually organized monitoring system could enable the implementation of automated analyses by presenting various alert levels. An adequate ICT solution tool would allow to define a monitoring network for a shared processing of data and results. Thus, a possible retrofit solution could be planned for pilot cases shared among the nodes of the network on the basis of a suitable procedure utilizing a retrofit catalogue. The final objective would consist in providing a model of an innovative tool to identify hazards, damages and possible retrofit solutions for historical centres, assuring an easy early warning support for stakeholders. The action could proactively target the needs and requirements of users, such as decision makers responsible for damage mitigation and safeguarding of cultural heritage assets.

A new betweenness centrality measure based on an algorithm for ranking the nodes of a network

We propose and discuss a new centrality index for urban street patterns represented as networks in geographical space. This centrality measure, that we call ranking-betweenness centrality, combines the idea behind the random-walk betweenness centrality measure and the idea of ranking the nodes of a network produced by an adapted PageRank algorithm. We initially use a PageRank algorithm in which we are able to transform some information of the network that we want to analyze into numerical values. Numerical values summarizing the information are associated to each of the nodes by means of a data matrix. After running the adapted PageRank algorithm, a ranking of the nodes is obtained, according to their importance in the network. This classification is the starting point for applying an algorithm based on the random-walk betweenness centrality. A detailed example of a real urban street network is discussed in order to understand the process to evaluate the ranking-betweenness centrality proposed, performing some comparisons with other classical centrality measures.

Analyzing the commercial activities of a street network by ranking their nodes: a case study in Murcia, Spain

Urban researchers and planners are often interested in understanding how economic activities are distributed in urban regions, what forces influence their special pattern and how urban structure and functions are mutually dependent. In this paper, we want to show how an algorithm for ranking the nodes in a network can be used to understand and visualize certain commercial activities of a city. The first part of the method consists of collecting real information about different types of commercial activities at each location in the urban network of the city of Murcia, Spain. Four clearly differentiated commercial activities are studied, such as restaurants and bars, shops, banks and supermarkets or department stores, but obviously we can study other. The information collected is then quantified by means of a data matrix, which is used as the basis for the implementation of a PageRank algorithm which produces a ranking of all the nodes in the network, according to their significance within it. Finally, we visualize the resulting classification using a colour scale that helps us to represent the business network.

Feature selection by multi-objective optimisation: Application to network anomaly detection by hierarchical self-organising maps

Feature selection is an important and active issue in clustering and classification problems. By choosing an adequate feature subset, a dataset dimensionality reduction is allowed, thus contributing to decreasing the classification computational complexity, and to improving the classifier performance by avoiding redundant or irrelevant features. Although feature selection can be formally defined as an optimisation problem with only one objective, that is, the classification accuracy obtained by using the selected feature subset, in recent years, some multi-objective approaches to this problem have been proposed. These either select features that not only improve the classification accuracy, but also the generalisation capability in case of supervised classifiers, or counterbalance the bias toward lower or higher numbers of features that present some methods used to validate the clustering/classification in case of unsupervised classifiers. The main contribution of this paper is a multi-objective approach for feature selection and its application to an unsupervised clustering procedure based on Growing Hierarchical Self-Organising Maps (GHSOMs) that includes a new method for unit labelling and efficient determination of the winning unit. In the network anomaly detection problem here considered, this multi-objective approach makes it possible not only to differentiate between normal and anomalous traffic but also among different anomalies. The efficiency of our proposals has been evaluated by using the well-known DARPA/NSL-KDD datasets that contain extracted features and labelled attacks from around 2 million connections. The selected feature sets computed in our experiments provide detection rates up to 99.8% with normal traffic and up to 99.6% with anomalous traffic, as well as accuracy values up to 99.12%.