Abstract
In open-ended domains, robots must continuously learn new object categories. When the training sets are created offline, it is not possible to ensure their representativeness with respect to the object categories and features the system will find when operating online. In the Bag of Words model, visual codebooks are usually constructed from training sets created offline. This might lead to non-discriminative visual words and, as a consequence, to poor recognition performance. This paper proposes a visual object recognition system which concurrently learns in an incremental and online fashion both the visual object category representations as well as the codebook words used to encode them. The codebook is defined using Gaussian Mixture Models which are updated using new object views. The approach contains similarities with the human visual object recognition system: evidence suggests that the development of recognition capabilities occurs on multiple levels and is sustained over large periods of time. Results show that the proposed system with concurrent learning of object categories and codebooks is capable of learning more categories, requiring less examples, and with similar accuracies, when compared to the classical Bag of Words approach using codebooks constructed offline.

Abstract

Abstract
Many definitions for operations strategy appear in literature. Yet, after analysing some of these important definitions, there were some common denominators: planning and decision-making. It is through correct operations strategy planning and decisions that organizations achieve competitive edge, and for this reason, the subject is of major importance. In this paper we present a review on operations strategy (OS) in manufacturing, services and product-service organizations. Through the literature analysis we found several differences and fewer similarities between OS in manufacturing and services and also the positioning of product-service systems (PSS) OS, comparing to OS in manufacturing and in services. Our foremost contribution is providing a literature review and an analysis on the content of the OS frameworks.

Abstract
In the moment that social networks arise as a new source of information, we also started to concern about the information shared in this environment. It is difficult to users of social networks to distinguish the accuracy of the information spreaded. The combination of auditability features and research directions in human-computer interaction area will guide the development of tools for evaluating information. We present prototypes of tools that once available, will allow users to decide about the credibility of information that they access and share. © Springer International Publishing Switzerland 2015.

Abstract
This thesis aims at contributing with new research at the intersection of the research fields of information management and supply chain risk management. Information is a fundamental element for an effective risk management in supply networks. In spite of this, research on how to use internal and external information for risk management decisions in supply networks is scarce. Therefore, this thesis main goal is to characterize information models used in supply networks and the supply chain risk management process in order to propose an aggregated model of internal and external information for risk management decision support in supply networks. This work is based on the Design Science paradigm, which will be applied through several research methods: systematic literature review to analyse the current state of the art on information management in supply networks; field research to analyse the influence of different information organisation models in the process of supply chain risk management and to develop an information model based (artifact); and action research to implement the artifact for the definition of risk mitigation strategies in aeronautic supply networks.

Abstract
We present a methodology to assess cell level alterations on the human retina responsible for functional changes observable in the Optical Coherence Tomography data in healthy ageing and in disease conditions, in the absence of structural alterations. The methodology is based in a 3D multilayer Monte Carlo computational model of the human retina. The optical properties of each layer are obtained by solving the Maxwell's equations for 3D domains representative of small regions of those layers, using a Discontinuous Galerkin Finite Element Method (DG-FEM). Here we present the DG-FEM Maxwell 3D model and its validation against Mie's theory for spherical scatterers. We also present an application of our methodology to the assessment of cell level alterations responsible for the OCT data in Diabetic Macular Edema. It was possible to identify which alterations are responsible for the changes observed in the OCT scans of the diseased groups.