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Sensor-based structural health monitoring systems are commonly used to provide real-time information and detect damage in complex structures. In particular, wireless structural health monitoring systems are of low cost but, since wireless sensors are powered with batteries, a low power consumption is critical. A common approach for wireless structural health monitoring is to use a distributed computation strategy, which is usually based on consensus algorithms. Power consumption in such wireless consensus networks depends on the number of connections of the network. If sensors are randomly connected, there is no control on the power consumption. In this article, we present a novel strategy to connect a large number of wireless sensors for distributed consensus with low power consumption by combining small networks with basic topologies using the Kronecker product.

In this paper, we give upper bounds for the rate-distortion function (RDF) of any Gaussian vector, and we propose coding strategies to achieve such bounds. We use these strategies to reduce the computational complexity of coding Gaussian asymptotically wide sense stationary (AWSS) autoregressive (AR) sources. Furthermore, we also give sufficient conditions for AR processes to be AWSS.

In this paper, we present upper bounds for the rate distortion function (RDF) of finite-length data blocks of Gaussian wide sense stationary (WSS) sources and we propose coding strategies to achieve such bounds. In order to obtain those bounds, we previously derive new results on the discrete Fourier transform (DFT) of WSS processes.

Using some recent results on asymptotically equivalent sequences of matrices, we present in this paper, a new derivation of the capacity formula given by Brandenburg and Wyner for a discrete-time Gaussian multiple-input-multiple-output channel with memory. In this paper, we tackle not only the case considered by them, where the number of channel inputs and the number of channel outputs are the same, but also when both numbers are different.

El trabajo en equipo es una de las competencias clave para el desarrollo de muchos profesionales, más si cabe, para el de los futuros ingenieros. Es por ello que dicha competencia se debe definir primeramente en los planes de estudios de estas titulaciones como posteriormente debe controlarse y asegurarse la adquisición de la misma por parte de los alumnos. El artículo que aquí se presenta propone un modelo que sirve de referencia para entender los factores y procesos que surgen del desarrollo del trabajo en equipo y lo completa con la definición de unas herramientas que sirve para evaluar el grado de consecución de la competencia por parte de los alumnos a lo largo de un grado en ingeniería industrial. El modelo se ha probado en base a datos experimentales realizados en una escuela de ingenieros española, aunque está diseñado para que pueda adaptarse a cualquier nivel educativo en el que el trabajo en equipo sea definido como una competencia a desarrollar en el alumno.

Introduction. The aim of this study is to obtain deeper knowledge about the information practices and competences that evidence information capability in a company. The first objective of this study is to define a set of practices that can be implemented in order to develop information capability in a company and to explore the common underlying dimensions of these practices, that is, the information competences. The second is to explore which information competences can be expected to have a greater influence on the quality of the information managed. Method. Our target population for the study was companies committed to total quality management models because those models are information-intensive management systems. Data was collected with a questionnaire designed to elicit information regarding information practices. Forty-six companies that have applied the European framework for quality management excellence model were respondents to the survey. Analysis. Quantitative analyses with the support of the Minitab software package were carried out on the data. More specifically we performed an exploratory factor analysis and a multiple regression analysis to achieve the objectives of the study. Results. Main findings reveal eighteen information-related practices that can be pooled in 6 information competences that make up information capability. Key information competences which would most affect information quality are also found. Conclusion. The competences identified by this study are presented in other literature as being equally important to business performance; however just three of these competences have a significant influence on the quality of information managed.

Information is a strategic company resource, but there is no consensus in the literature regarding the set of dimensions to be considered when measuring the quality of the information. Most measures of information quality depend on user perception. Using multiple correlation analysis, we obtain a model that allows us to explain how information quality dimensions influence information consumers¿ overall feeling of being well informed. A set of dimensions that any measure of information quality should at least include is proposed. This exploratory study reports the results of a research survey among managers of companies committed to quality management within the framework of a Total Quality Management (TQM) model, which is an information-intensive management model.

This study considers the effect of the usage of a social network site (www.grouply.com) for a class related group project on the development of individual abilities and performance in group work. Data were collected from three sections of an intermediate macroeconomic class at a Spanish university and groups were randomly assigned to work (or not) using the social network. Findings suggest that, although students are in general attracted by the idea of using SNS in class-related team work, the introduction of a tool they are not familiar with may hamper their self-perceived level of competence in a number of skills.