Abstract

Abstract
In this paper we propose and analyse methods for expanding state-of-the-art performance on text classification. We put forward an ensemble-based structure that includes Support Vector Machines (SVM) and Artificial Immune Systems (AIS). The underpinning idea is that SVM-like approaches can be enhanced with A IS approaches which can capture dynamics in models. While having radically different genesis, and probably because of that, SVM and AIS can cooperate in a committee setting, using a heterogeneous ensemble to improve overall performance, including a confidence on each system classification as the differentiating factor. Results on the well-known Reuters-21578 benchmark are presented, showing promising classification performance gains, resulting in a classification that improves upon all baseline contributors of the ensemble committee.

Abstract
The growth of available broadband access technologies has brought an enormous challenge for operators wanting to ensure seamless mobility to its customers in heterogeneous environments. In this paper we present an enhanced Mobility Management entity focused on a real heterogeneous environments and based on IEEE802.21 standard. This entity is capable to perform terminal and handover management regardless the access technology used. This entity was deployed in a real heterogeneous environment with Wi-Fi, WiMAX and HSPA using an Android smartphone. In order to provide Layer 3 mobility support it was integrated with a modified version of MIPv6. The results show not only the impact of a centralized entity to manage vertical handovers, but also the performance of IEEE802.21 protocol in a real scenario with a real implementation. ©2011 IEEE © 2011 IEEE.© 2011 IEEE.

Abstract
The purpose of this paper is to present a methodology that allows higher education institutions (HEIs) to promote, to evaluate and to report on sustainability. The ultimate goal of the afore-mentioned methodology is to help HEIs achieve sustainability. First, a model entitled Sustainability in Higher Education Institutions (SusHEI) that generally describes and characterizes the functioning of an HEI was defined. SusHEI takes into account the core activities of any HEI (education and research), its impacts at economic, environmental and social levels, and the role of its community. SusHEI allowed for the establishment of internal dimensions interrelated to the functioning of an HEI. Then, a matricial representation of the model was developed. The matrix crosses internal dimensions (and eventually sub-dimensions) with sustainability dimensions (and eventually sub-dimensions) and it is quantified through indicators. There is a wide range of possible sustainability indicators that can be chosen, depending on the purpose and the public to whom the indicators/reports are addressed. The methodology is illustrated by a case-study - the Faculty of Engineering of the University of Porto (FEUP). This paper provides a methodology that enables the selection of sustainability indicators for sustainability reporting, assessment or even for benchmarking, and also eliminates some of the main weaknesses found in the models currently available. Higher Education Policy (2011) 24, 459-479. doi:10.1057/hep.2011.18

Abstract

Abstract
Long term electricity markets models tend to use simplified representations of both the demand and the generation units, to reduce the amount of input data and decision variables used, and also to decrease their execution times. On the one hand, hourly demand curves are usually simplified into a reduced set of non-chronological demand levels, each one representing hours with similar demand values. On the other hand, individual generation units are condensed into technologies grouping their costs curves by similarity in different appropriated technological cost mappings. This paper proposes several novel Mixed Integer Programming models to solve these two curve-fitting problems when the approximating function is a Piece-Wise Linear Function. By means of two real cases study it shows that the approximation approach has real applicability since it does not significantly compromise the traditional system representation. © 2011 IEEE.