Armando B. Mendes

An Algorithm to Discover the k-Clique Cover in Networks

In social network analysis, a k-clique is a relaxed clique, i.e., a k-clique is a quasi-complete sub-graph. A k-clique in a graph is a sub-graph where the distance between any two vertices is no greater than k. The visualization of a small number of vertices can be easily performed in a graph. However, when the number of vertices and edges increases the visualization becomes incomprehensible. In this paper, we propose a new graph mining approach based on k-cliques. The concept of relaxed clique is extended to the whole graph, to achieve a general view, by covering the network with k-cliques. The sequence of k-clique covers is presented, combining small world concepts with community structure components. Computational results and examples are presented.

Efficiency Measures in the Agricultural Sector: With Applications

Part I Efficiency Measures and Methods 1 Efficiency Measures in the Agricultural Sector: The Beginning Emiliana Silva, Armando Mendes and Jorge Santos 2 Review of Frontier Models and Efficiency Analysis: A Parametric Approach Ana Sampaio 3 Introduction to Data Envelopment Analysis Jorge Santos, Elsa Rosario Negas and Luis Cavique Santos 4 Superefficiency and Multiplier Adjustment in Data Envelopment Analysis Jorge Santos, Luis Cavique Santos, Armando Mendes Part II Farm Efficiency Applications 5 An Application of Data Envelopment Analysis (DEA) in Azores Dairy Farms Emiliana Silva, Amilcar Arzubi and Julio Berbel 6 Animal Grazing System Efficiency Emiliana Silva, Carlos Santos and Armando Mendes 7 Technical Efficiency of the Spanish Dairy Processing Industry: Do Size and Exporting Matter? Magdalena Kapelko and Alfons Oude Lansink 8 Inefficiency in Animal Production - A Parametric Approach Emiliana Silva and Fatima Venancio 9 Azorean Agriculture Efficiency by PAR Armando B Mendes, Veska Noncheva and Emiliana Silva 10 Sustainable Tourism and Agriculture Multifunctionality by PAR: A Variable Selection Approach Armando Mendes, Veska Noncheva and Emiliana Silva 11 The Importance of Subsidies in Azorean Dairy Farms Efficiency Emiliana Silva and Eusebio Marote 12 Multi-Ouput Technical Efficiency in the Olive Oil Industry and its Relation to the Form of Business Organisation Rafaela Dios-Palomares, Jose M. Martinez-Paz and Angel Prieto 13 Efficiency Assessment: Final Remarks Jorge Santos, Emiliana Silva and Armando Mendes Index

Facebook vs moodle: Surveying university students on the use of learning management systems to support learning activities outside the classroom

Learning management systems and social networks on Web have been tools most used by students in higher education institutions as learning support tools outside of the classroom. In this paper, we present the results from a survey conducted at a Portuguese university to 159 students in Computer Science and Psychology about the purposes and reasons for the use of Moodle and Facebook. We conclude, among other conclusions, that they complement each other: while the first is mostly used for formal communication with teachers, the second is mostly used for informal communication with peers.

Animal Grazing System Efficiency

This chapter proposes to estimate the technical efficiency in agricultural grazing systems (dairy, beef and mixed) in Azores, in the year 2002. This research used 184 agricultural farms of FADN – Farm Accountancy Data Network. DEA, a non-parametric methodology, was used to estimate efficiency by means of DEAP software.

Efficiency Measures in the Agricultural Sector: The Beginning

The agricultural productivity is often based on non-parametric models (DEA), or stochastic models (SFA). In this initial article, the editors start by pointing that the models (DEA and SFA) allow estimating the efficiency of the production frontier and their structural forms. Then, it is presented, in general terms, the differences between DEA and SFA models: DEA model involves the use of technical linear programming to construct a non-parametric piecewise surface, and SFA models comprise econometric models with a random variable, or an error term, including two components: one to account for random effects and another to take care of the technical inefficiency effects. Finally, it shows a comparison between the two approaches (SFA and DEA) and the advantages and disadvantages of their utilizations.

Azorean Agriculture Efficiency by PAR

The producers always aspire at increasing the efficiency of their production process. However, they do not always succeed in optimising their production. In the last years, the interest on Data Envelopment Analysis (DEA) as a powerful tool for measuring efficiency has increased. This is due to the large amount of data sets collected to better understand the phenomena under study and, at the same time, to the need of timely and inexpensive information.

A Feature Selection Algorithm Based on Heuristic Decomposition

Feature selection is one of the most important concepts in data mining when dimensionality reduction is needed. The performance measures of feature selection encompass predictive accuracy and result comprehensibility. Consistency based feature selection is a significant category of feature selection research that substantially improves the comprehensibility of the result using the parsimony principle. In this work, the feature selection algorithm LAID, Logical Analysis of Inconsistent Data, is applied to large volumes of data. In order to deal with hundreds of thousands of attributes, a problem de-composition strategy associated with a set covering problem formulation is used. The algorithm is applied to artificial datasets with genome-like characteristics of patients with rare diseases.

A Decision Support System for Municipal Budget Plan Decisions

This paper describes a Decision Support System to provide indicators to support budget plan decisions, in a local government organization, the municipality of Lagoa - S. Miguel, Azores. The work includes system modeling, using the UML notation, the development of a MySQL relational database, algorithms for data collection using PHP, and forecasting models using R functions, such as exponential smoothing, classical decomposition with linear trend, and ARIMA models. Users have access to predictions made by different models for several indicators, being suggested to use the models with closest to zero errors. From the analysis performed considering 12 years data, it is concluded that for most of indicators, the classical decomposition model is the most successful. However, for some indicators, it was found that the two error measures used are not consistent. In these cases, the final decision is left to the decision-maker, taking advantage of his domain knowledge.

Superefficiency and Multiplier Adjustment in Data Envelopment Analysis

Superefficiency is an important extension of DEA that overcomes some limitations of the traditional models, specifically allowing ranking of efficient units and a unique set of weights for those units. Weights restriction is a well-known technique in the DEA field. When those techniques are applied, weights cluster around its new limits, making its evaluation dependent of its levels. This chapter introduces a new approach to weights adjustment by goal programming techniques, avoiding the imposition of hard restrictions that can even lead to unfeasibility. This method results in models that are more flexible.

Efficiency Assessment: Final Remarks

In this concluding chapter the editors make some important remarks on the importance and conclusions of the book as a whole, focusing on its importance, relevance and adequacy to an extended audience of researchers in the efficiency analysis in the agricultural and environment fields.