User expectations for media sharing practices in open display networks

Open Display Networks have the potential to allow many content creators to publish their media to an open-ended set of screen displays. However, this raises the issue of how to match that content to the right displays. In this study, we aim to understand how the perceived utility of particular media sharing scenarios is affected by three independent variables, more specifically: (a) the locativeness of the content being shared; (b) how personal that content is and (c) the scope in which it is being shared. To assess these effects, we composed a set of 24 media sharing scenarios embedded with different treatments of our three independent variables. We then asked 100 participants to express their perception of the relevance of those scenarios. The results suggest a clear preference for scenarios where content is both local and directly related to the person that is publishing it. This is in stark contrast to the types of content that are commonly found in public displays, and confirms the opportunity that open displays networks may represent a new media for self-expression. This novel understanding may inform the design of new publication paradigms that will enable people to share media across the display networks.

A geographic opportunistic forwarding strategy for vehicular named data networking

Studies in Computational Intelligence, 616

Abstract computation in schizophrenia detection through artificial neural network based systems

Schizophrenia stands for a long-lasting state of mental uncertainty that may bring to an end the relation among behavior, thought, and emotion; that is, it may lead to unreliable perception, not suitable actions and feelings, and a sense of mental fragmentation. Indeed, its diagnosis is done over a large period of time; continuos signs of the disturbance persist for at least 6 (six) months. Once detected, the psychiatrist diagnosis is made through the clinical interview and a series of psychic tests, addressed mainly to avoid the diagnosis of other mental states or diseases. Undeniably, the main problem with identifying schizophrenia is the difficulty to distinguish its symptoms from those associated to different untidiness or roles. Therefore, this work will focus on the development of a diagnostic support system, in terms of its knowledge representation and reasoning procedures, based on a blended of Logic Programming and Artificial Neural Networks approaches to computing, taking advantage of a novel approach to knowledge representation and reasoning, which aims to solve the problems associated in the handling (i.e., to stand for and reason) of defective information.

Artificial neural networks in diagnosis of liver diseases

Liver diseases have severe patients’ consequences, being one of the main causes of premature death. These facts reveal the centrality of one`s daily habits, and how important it is the early diagnosis of these kind of illnesses, not only to the patients themselves, but also to the society in general. Therefore, this work will focus on the development of a diagnosis support system to these kind of maladies, built under a formal framework based on Logic Programming, in terms of its knowledge representation and reasoning procedures, complemented with an approach to computing grounded on Artificial Neural Networks.

Logic programming and artificial neural networks in breast cancer detection

About 90% of breast cancers do not cause or are capable of producing death if detected at an early stage and treated properly. Indeed, it is still not known a specific cause for the illness. It may be not only a beginning, but also a set of associations that will determine the onset of the disease. Undeniably, there are some factors that seem to be associated with the boosted risk of the malady. Pondering the present study, different breast cancer risk assessment models where considered. It is our intention to develop a hybrid decision support system under a formal framework based on Logic Programming for knowledge representation and reasoning, complemented with an approach to computing centered on Artificial Neural Networks, to evaluate the risk of developing breast cancer and the respective Degree-of-Confidence that one has on such a happening.

A hybrid MAC Scheme to improve the transmission performance in body sensor networks

Wireless body sensor networks (WBSNs) constitute a key technology for closing the loop between patients and healthcare providers, as WBSNs provide sensing ability, as well as mobility and portability, essential characteristics for wide acceptance of wireless healthcare technology. However, one important and difficult aspect of WBSNs is to provide data transmissions with quality of service, among other factors due to the antennas being small size and placed close to the body. Such transmissions cannot be fully provided without the assumption of a MAC protocol that solves the problems of the medium sharing. A vast number of MAC protocols conceived for wireless networks are based on random or scheduled schemes. This paper studies firstly the suitability of two MAC protocols, one using CSMA and the other TDMA, to transmit directly to the base station the signals collected continuously from multiple sensor nodes placed on the human body. Tests in a real scenario show that the beaconed TDMA MAC protocol presents an average packet loss ratio lower than CSMA. However, the average packet loss ratio is above 1.0 %. To improve this performance, which is of vital importance in areas such as e-health and ambient assisted living, a hybrid TDMA/CSMA scheme is proposed and tested in a real scenario with two WBSNs and four sensor nodes per WBSN. An average packet loss ratio lower than 0.2 % was obtained with the hybrid scheme. To achieve this significant improvement, the hybrid scheme uses a lightweight algorithm to control dynamically the start of the superframes. Scalability and traffic rate variation tests show that this strategy allows approximately ten WBSNs operating simultaneously without significant performance degradation.

Graphene-based nanostructures: Plasmonics in the THz range

The properties of surface plasmon-polaritons (SPPs) in graphene are discussed and several possible ways of coupling electromagnetic radiation in the terahertz (THz) spectral range to this type of surface waves are described: (i) the attenuated total reflection (ATR) method employing a prism, (ii) graphene-based gratings or graphene monolayers with modulated conductivity, (iii) a metal stripe on top of the graphene layer, and (iv) a nanoparticle located above it. Potentially interesting for applications SPP effects, such as switching, modulation and polarization of THz radiation, as well as its enhanced absorption in graphene, are considered. The discussion also concerns the impact of the nonlinear properties of graphene, such as optical bistability.

Column-based databases: estudo exploratório no âmbito das bases de dados NoSQL

Dissertação de mestrado integrado em Engenharia e Gestão de Sistemas de Informação

Quantifying, generating and mitigating radio interference in Low-Power Wireless Networks

Doctoral Programme in Telecommunication - MAP-tele

Optimization of magnetoelectric composites based on electroactive polymers for energy harvesting and sensor application

Tese de Doutoramento em Engenharia de Materiais.

Flow updating: fault-tolerant aggregation for dynamic networks

Documento submetido para revisão pelos pares. A publicar em Journal of Parallel and Distributed Computing. ISSN 0743-7315

Highly robust chitosan hydrogels via a fast, simple and biocompatible dual crosslinking-based process

Load-bearing soft tissues such as cartilage, blood vessels and muscles are able to withstand a remarkable compressive stress of several MPa without fracturing. Interestingly, most of these structural tissues are mainly composed of water and in this regard, hydrogels, as highly hydrated 3D-crosslinked polymeric networks, constitute a promising class of materials to repair lesions on these tissues. Although several approaches can be employed to shape the mechanical properties of artificial hydrogels to mimic the ones found on biotissues, critical issues regarding, for instance, their biocompatibility and recoverability after loading are often neglected. Therefore, an innovative hydrogel device made only of chitosan (CHI) was developed for the repair of robust biological tissues. These systems were fabricated through a dual-crosslinking process, comprising a photo- and an ionic-crosslinking step. The obtained CHIbased hydrogels exhibited an outstanding compressive strength of ca. 20 MPa at 95% of strain, which is several orders of magnitude higher than those of the individual components and close to the ones found in native soft tissues. Additionally, both crosslinking processes occur rapidly and under physiological conditions, enabling cellsâ encapsulation as confirmed by high cell survival rates (ca. 80%). Furthermore, in contrast with conventional hydrogels, these networks quickly recover upon unloading and are able to keep their mechanical properties under physiological conditions as result of their non-swell nature.

Production of whey protein-based aggregates under ohmic heating

Formation of whey protein isolate protein aggregates under the influence of moderate electric fields upon ohmic heating (OH) has been monitored through evaluation of molecular protein unfolding, loss of its solubility, and aggregation. To shed more light on the microstructure of the protein aggregates produced by OH, samples were assayed by transmission electron microscopy (TEM). Results show that during early steps of an OH thermal treatment, aggregation of whey proteins can be reduced with a concomitant reduction of the heating chargeby reducing the come-up time (CUT) needed to reach a target temperatureand increase of the electric field applied (from 6 to 12 V cm1). Exposure of reactive free thiol groups involved in molecular unfolding of -lactoglobulin (-lg) can be reduced from 10 to 20 %, when a CUT of 10 s is combined with an electric field of 12 V cm1. Kinetic and multivariate analysis evidenced that the presence of an electric field during heating contributes to a change in the amplitude of aggregation, as well as in the shape of the produced aggregates. TEM discloses the appearance of small fibrillar aggregates upon the influence of OH, which have recognized potential in the functionalization of food protein networks. This study demonstrated that OH technology can be used to tailor denaturation and aggregation behavior of whey proteins due to the presence of a constant electric field together with the ability to provide a very fast heating, thus overcoming heat transfer limitations that naturally occur during conventional thermal treatments.

From perfect strangers to research partners: a study of relationships, resource sharing and perceived benefits within R&D cooperation networks

Doctoral thesis in Marketing and Strategy.