MobiMed: Framework for Rapid Application Development of Medical Mobile Apps

In the medical field images obtained from high definition cameras and other medical imaging systems are an integral part of medical diagnosis. The analysis of these images are usually performed by the physicians who sometimes need to spend long hours reviewing the images before they are able to come up with a diagnosis and then decide on the course of action. In this dissertation we present a framework for a computer-aided analysis of medical imagery via the use of an expert system. While this problem has been discussed before, we will consider a system based on mobile devices. Since the release of the iPhone on April 2003, the popularity of mobile devices has increased rapidly and our lives have become more reliant on them. This popularity and the ease of development of mobile applications has now made it possible to perform on these devices many of the image analyses that previously required a personal computer. All of this has opened the door to a whole new set of possibilities and freed the physicians from their reliance on their desktop machines. The approach proposed in this dissertation aims to capitalize on these new found opportunities by providing a framework for analysis of medical images that physicians can utilize from their mobile devices thus remove their reliance on desktop computers. We also provide an expert system to aid in the analysis and advice on the selection of medical procedure. Finally, we also allow for other mobile applications to be developed by providing a generic mobile application development framework that allows for access of other applications into the mobile domain. In this dissertation we outline our work leading towards development of the proposed methodology and the remaining work needed to find a solution to the problem. In order to make this difficult problem tractable, we divide the problem into three parts: the development user interface modeling language and tooling, the creation of a game development modeling language and tooling, and the development of a generic mobile application framework. In order to make this problem more manageable, we will narrow down the initial scope to the hair transplant, and glaucoma domains.

Towards near-threshold server processors

The popularity of cloud computing has led to a dramatic increase in the number of data centers in the world. The ever-increasing computational demands along with the slowdown in technology scaling has ushered an era of power-limited servers. Techniques such as near-threshold computing (NTC) can be used to improve energy efficiency in the post-Dennard scaling era. This paper describes an architecture based on the FD-SOI process technology for near-threshold operation in servers. Our work explores the trade-offs in energy and performance when running a wide range of applications found in private and public clouds, ranging from traditional scale-out applications, such as web search or media streaming, to virtualized banking applications. Our study demonstrates the benefits of near-threshold operation and proposes several directions to synergistically increase the energy proportionality of a near-threshold server.

William Layton en España

This year 2015 marks the 55th anniversary of the establishment in Spain of the first theatre academy whose methodological principles for actors were based on the Stanislavski system —although transformed by the perspective of the Method, developed in America by the Group Theatre during the 1930s and then implanted in some famous schools such as the Actor’s Studio—. It was in October 1960 when the American actor, teacher and director William Layton (1913-1995) opened the Teatro Estudio de Madrid (TEM). By then, he had already been living in Spain for two years. In that adventure Layton was accompanied by the Spanish Miguel Narros (a stage director) and the American Elizabeth H. Buckley. This private academy began its activity by offering the Method, a discipline that Layton had learned in his country with Sandford Meisner; one member of the Group Theatre along with Lee Strasberg, Stella Adler, Harold Clurmann or Elia Kazan. Thanks to the TEM, concepts till then completely unknown in Spanish academic venues for actors such as organicity, truth, mood, sensory memory, etc., started being implemented in the theatrical interpretation. Firstly, in exercises of improvisation; secondly, in scenes and characters; and finally, after a time of performing, those concepts were tested in the scenarios, by display to the public, which is the biggest challenge for any actor, author or director. That way, a singular model of interpretation, a naturalistic type, which have prevailed in the West over other ways of interpreting, came to Spain. A system (which could be defined as organic interpretation) that had been systematized by the Russian Konstantin Stanislavski in the early twentieth century and rapidly was exported abroad by some of his first students: Richard Boleslavsky, Maria Ouspenskaya, Michael Chekhov, Pietro Scharoff, P. Pauloff... Its popularity in the USA increased mainly due to the Actor’s Studio and also thanks to professor Lee Strasberg, through the famous Method working. While in 1960 Layton founded in Madrid the TEM, together with Narros and Buckley, the Brechtian technique was arriving to Barcelona. In that city, Ricard Salvat —who had trained in Germany— and Maria Aurélia Capmany opened the School of Dramatic Art Adrià Gual (EADAG). From Catalonia and over the years, this center will project the first formulas about “distancing”. That way, after decades of delay, that same year 1960 landed in Spain two key trends that shaped and influenced the development of Western theatrical art in the first half of the twentieth century. SYNTHESIS: The knowledge and deep analysis of William Layton’s work as acting teacher in Spain will allow us to get closer to a major figure in the history of theater education in our country. Our main goal is to demonstrate that he was responsible for breaking the isolation that, from secular times, suffered the training of actors in Spain. Layton not only did achieve that, but did it consistently, without interruption. Also, by analyzing his work as stage manager, we will discover how this methodology was implemented in two aspects regarding the theatrical play: in the actor himself and in the dramatic text...

El Libro del Governador o Suma de collaciones o de ayuntamientos: versión castellana del "Communiloquium" de Juan de Gales

The intellectual production of Johannes Gallensis (also known as John of Wales, c. 1210/30 – 1285), regent-master of the Friars Minor at Oxford and later a lecturer and Doctor of Theology at Paris, was oriented towards furnishing Catholic preachers with a variety of compilations of moral philosophy aimed to serve them in their pastoral ministry. One of these compilations is the Communiloquium, a manual of a kind, which displays its author's attempt to provide adequate and specific argumentation for admonishing all sorts and types of devotees. Its most prominent characteristic is a highly accurate use of classical auctoritates and exempla, which turned this work into a kind of anthology of quotations and references, for it offered its readers the possibility of citing sources and texts that they themselves had never actually consulted. The impressive number of manuscript copies of the Communiloquium that reached our times bears witness to its great popularity (some one hundred and sixty dispersed in different European libraries, according to Jenny Swanson’s John of Wales. A Study of the Work and Ideas of a Thirteenth-Century Friar). The Communiloquium must have reached the Iberian soil by means of Franciscan friars and soon spread through courtly circles, as much as in the religious milieu, due to the political taint of its first part, rooted in the organological metaphor and containing extensive reflections on the virtues and the due behaviour of a monarch. In the Crown of Aragon, the Communiloquium used to be read out loud even among the artisans. In Castile, on the other hand, particularly between the XIIIth and the XVth centuries, its main audience happened to be the lettered nobility and those intellectuals who, dedicated to composing glosas and specula principum, required its resources...

The presence of three Portuguese TV news channels (RTP3, SIC NOTÍCIAS, and TVI24) on facebook

The growing popularity of social networks, and their impact on the daily lives of consumers, contributed to news organizations marking their presence on different online platforms. In the case of Facebook, a social network that began as a personal space, it has gradually transformed into a content-sharing space (Oeldorf-Hirsch & Sundar, 2015). Nowadays, Facebook is the second most viewed website in Portugal (Alexa, 2016), and therefore, it has become crucial for Portuguese news agencies to be present on this social network. Although television continues to be the main information source in Portugal, social networks, and specifically Facebook, are increasingly important in news consumption by users (ERC, 2015). This new way of news dissemination, as well as the proliferation that these contents reach in social networks, led to news agencies exploiting these new channels, both to attract new audiences, and to redirect users to their own websites (Castillo, El-Haddad, Pfeffer, & Stempeck, 2014). Thus, it is important to understand how, and what kind of content these agencies put on their Facebook channels, as well as the strategies they use to share these same contents. This study aims to understand how the main news channels of Portuguese TV (RTP3, SIC Notícias, and TVI24) manage and use the social network Facebook to share news contents. To this end, the authors collected quantitative data of all posts placed on Facebook between February 8 and February 14 2016. Approximately 1063 posts were collected and analysed from the three Facebook pages. The results indicate that two of the three channels extensively used their Facebook pages to share and target content to their official websites. Regarding the news sources and type of media used, the three Portuguese TV news channels use similar strategies. However, in what concerns the main themes and quantity of messages per day, as well as the level of redundancy of information, the three channels manage their pages differently.

The presence of three portuguese TV news channels (RTP3, SIC Notícias, and TVI24) on Facebook

The growing popularity of social networks, and their impact on the daily lives of consumers, contributed to news organizations marking their presence on different online platforms. In the case of Facebook, a social network that began as a personal space, it has gradually transformed into a content-sharing space (Oeldorf-Hirsch & Sundar, 2015). Nowadays, Facebook is the second most viewed website in Portugal (Alexa, 2016), and therefore, it has become crucial for Portuguese news agencies to be present on this social network. Although television continues to be the main information source in Portugal, social networks, and specifically Facebook, are increasingly important in news consumption by users (ERC, 2015). This new way of news dissemination, as well as the proliferation that these contents reach in social networks, led to news agencies exploiting these new channels, both to attract new audiences, and to redirect users to their own websites (Castillo, El-Haddad, Pfeffer, & Stempeck, 2014). Thus, it is important to understand how, and what kind of content these agencies put on their Facebook channels, as well as the strategies they use to share these same contents. This study aims to understand how the main news channels of Portuguese TV (RTP3, SIC Notícias, and TVI24) manage and use the social network Facebook to share news contents. To this end, the authors collected quantitative data of all posts placed on Facebook between February 8 and February 14 2016. Approximately 1063 posts were collected and analysed from the three Facebook pages. The results indicate that two of the three channels extensively used their Facebook pages to share and target content to their official websites. Regarding the news sources and type of media used, the three Portuguese TV news channels use similar strategies. However, in what concerns the main thematic and quantity of messages per day, as well as the level of redundancy of information, the three channels operate their pages differently.

Efeitos da prática do Jiu-Jitsu brasileiro no controle cognitivo de estudantes do Ensino Secundário da Rede Pública de Abu Dhabi, Emirados Árabes Unidos

Uma das formas de atividade física que tem revelado expressivos resultados na mediação comportamental e cognitiva são as Artes Marciais (AM). Dentre elas, o Jiu-Jitsu Brasileiro ou BJJ (Brazilian Jiu-Jitsu) tem se mostrado cada vez mais popular entre jovens de idade escolar, no entatanto nenhum estudo sobre os seus efeitos nas Funções Executivas (FE) foi encontrado. O objetivo desse estudo foi primeiramente, encontrar diferenças nas FE com a pratica do BJJ; secundariamente, pretendeu-se observar o tipo de correlação entre as FE e os niveis de participação; e por fim posicionar os resultados deste estudo a outros trabalhos similares da literatura científica. O estudo avaliou 125 alunos de uma escola pública de Abu Dhabi, antes e após 6 meses de prática, através de um modelo não randomizado. Após todas as exclusões, 59 alunos foram separados em 3 niveis de participação e correlacionados com os resultados do teste de Stroop (VST - Victoria Stroop Test). Os resultados deste estudo mostraram que 30 sessões de BJJ, foram suficientes para oferecer significativas diferenças no Controle Inibitório (CI). Sua boa participação (2 a 3 vezes por semana), não somente mostrou grande tamanho de efeito (SE) comparado a baixa e media participação, como maiores SE comparado a outras formas de Atividade Fisica e Artes Marciais Tradicionais como o Tae Kwon Do e Wu Shu (Kung Fu). Com uma moderada correlação, sua participação apontou uma capacidade de influenciar em 20,8% o (CI) sobre atividades automáticas, bem como 27,3% a distração sobre atividades irrelevantes. Esses achados sugerem que a pratica do BJJ possa levar a melhoras nas Funções Executivas de pré-adolescentes nativos dos Emirados Arabes Unidos.

Hilbert Space Valued Signal Plus Noise Models: Analysis of Structural Breaks under High Dimensionality and Temporal Dependence

This thesis is concerned with change point analysis for time series, i.e. with detection of structural breaks in time-ordered, random data. This long-standing research field regained popularity over the last few years and is still undergoing, as statistical analysis in general, a transformation to high-dimensional problems. We focus on the fundamental »change in the mean« problem and provide extensions of the classical non-parametric Darling-Erdős-type cumulative sum (CUSUM) testing and estimation theory within highdimensional Hilbert space settings. In the first part we contribute to (long run) principal component based testing methods for Hilbert space valued time series under a rather broad (abrupt, epidemic, gradual, multiple) change setting and under dependence. For the dependence structure we consider either traditional m-dependence assumptions or more recently developed m-approximability conditions which cover, e.g., MA, AR and ARCH models. We derive Gumbel and Brownian bridge type approximations of the distribution of the test statistic under the null hypothesis of no change and consistency conditions under the alternative. A new formulation of the test statistic using projections on subspaces allows us to simplify the standard proof techniques and to weaken common assumptions on the covariance structure. Furthermore, we propose to adjust the principal components by an implicit estimation of a (possible) change direction. This approach adds flexibility to projection based methods, weakens typical technical conditions and provides better consistency properties under the alternative. In the second part we contribute to estimation methods for common changes in the means of panels of Hilbert space valued time series. We analyze weighted CUSUM estimates within a recently proposed »high-dimensional low sample size (HDLSS)« framework, where the sample size is fixed but the number of panels increases. We derive sharp conditions on »pointwise asymptotic accuracy« or »uniform asymptotic accuracy« of those estimates in terms of the weighting function. Particularly, we prove that a covariance-based correction of Darling-Erdős-type CUSUM estimates is required to guarantee uniform asymptotic accuracy under moderate dependence conditions within panels and that these conditions are fulfilled, e.g., by any MA(1) time series. As a counterexample we show that for AR(1) time series, close to the non-stationary case, the dependence is too strong and uniform asymptotic accuracy cannot be ensured. Finally, we conduct simulations to demonstrate that our results are practically applicable and that our methodological suggestions are advantageous.

Linked Data in the Digital Humanities: Examples, Projects, and Tools

Harnessing the potential of semantic web technologies to support and diversify scholarship is gaining popularity in the digital humanities. This talk describes a number of projects utilising Linked Data ranging from musicology and library metadata, to the representation of the narrative structure, philological, bibliographical, and museological data of ancient Mesopotamian literary compositions.

Las limitaciones de la implementación del soft power en la política exterior China hacia Chile (2002-2012)

Este estudio de caso tiene como objetivo principal analizar la manera en la que las limitaciones de la implementación del soft power de la política exterior China hacia Chile han condicionado las relaciones sino-chilenas al aspecto económico en detrimento del aspecto político y cultural bajo el gobierno de Hu Jintao (2002-2012). Este análisis se elabora a partir de la conceptualización hecha por Joseph Nye en torno al soft power; al cual, se le han otorgado características adicionales dadas por teóricos chinos, como la introducción y, fortalecimiento de China a través de la diplomacia pública para la proyección de su imagen internacional, basada en la cooperación y beneficio mutuo, con el fin de lograr el desarrollo pacífico en el siglo XXI.

TELFest: an approach to encouraging the adoption of educational technologies

Barriers to technology adoption in teaching and learning are well documented, with a corresponding body of research focused on how these can be addressed. As a way to combine a variety of these adoption strategies, the University of Sheffield developed a Technology Enhanced Learning Festival, TELFest. This annual, week-long event, emphasises the role technology can play through an engaging learning experience which combines expert-led practical workshops, sharing of practice, discussions and presentations by practitioners. As the popularity of the event has grown and the range of topics expanded, a community of practice has organically coalesced among attendees, supporting the mainstream adoption of several technologies and helping to broaden educational innovation beyond isolated pockets. This paper situates TELFest within the technology adoption literature by providing details about TELFest, outlining the results of an investigation into the impact that it has had on attendees' teaching practice and summarising some of the limitations of the method along with reflections on how to address these limitations in the future.

Propagation modelling and resource allocation in mobile radio communications

Over the past years, ray tracing (RT) models popularity has been increasing. From the nineties, RT has been used for field prediction in environment such as indoor and urban environments. Nevertheless, with the advent of new technologies, the channel model has become decidedly more dynamic and to perform RT simulations at each discrete time instant become computationally expensive. In this thesis, a new dynamic ray tracing (DRT) approach is presented in which from a single ray tracing simulation at an initial time t0, through analytical formulas we are able to track the motion of the interaction points. The benefits that this approach bring are that Doppler frequencies and channel prediction can be derived at every time instant, without recurring to multiple RT runs and therefore shortening the computation time. DRT performance was studied on two case studies and the results shows the accuracy and the computational gain that derives from this approach. Another issue that has been addressed in this thesis is the licensed band exhaustion of some frequency bands. To deal with this problem, a novel unselfish spectrum leasing scheme in cognitive radio networks (CRNs) is proposed that offers an energy-efficient solution minimizing the environmental impact of the network. In addition, a network management architecture is introduced and resource allocation is proposed as a constrained sum energy efficiency maximization problem. System simulations demonstrate an increment in the energy efficiency of the primary users’ network compared with previously proposed algorithms.

Learning representations for graph-structured socio-technical systems

The recent widespread use of social media platforms and web services has led to a vast amount of behavioral data that can be used to model socio-technical systems. A significant part of this data can be represented as graphs or networks, which have become the prevalent mathematical framework for studying the structure and the dynamics of complex interacting systems. However, analyzing and understanding these data presents new challenges due to their increasing complexity and diversity. For instance, the characterization of real-world networks includes the need of accounting for their temporal dimension, together with incorporating higher-order interactions beyond the traditional pairwise formalism. The ongoing growth of AI has led to the integration of traditional graph mining techniques with representation learning and low-dimensional embeddings of networks to address current challenges. These methods capture the underlying similarities and geometry of graph-shaped data, generating latent representations that enable the resolution of various tasks, such as link prediction, node classification, and graph clustering. As these techniques gain popularity, there is even a growing concern about their responsible use. In particular, there has been an increased emphasis on addressing the limitations of interpretability in graph representation learning. This thesis contributes to the advancement of knowledge in the field of graph representation learning and has potential applications in a wide range of complex systems domains. We initially focus on forecasting problems related to face-to-face contact networks with time-varying graph embeddings. Then, we study hyperedge prediction and reconstruction with simplicial complex embeddings. Finally, we analyze the problem of interpreting latent dimensions in node embeddings for graphs. The proposed models are extensively evaluated in multiple experimental settings and the results demonstrate their effectiveness and reliability, achieving state-of-the-art performances and providing valuable insights into the properties of the learned representations.

Artisanal food productions of animal origin: exploring food safety in the age of Whole Genome Sequencing

The artisanal food chain is enriched by a wide diversity of local food productions with delightful organoleptic characteristics and valuable nutritional properties. Despite their increasing worldwide popularity and appeal, several food safety challenges are addressed in artisanal facilities context suffering from less standardized processing conditions. In such scenario, recent advances in molecular typing and genomic surveillance (e.g., Whole Genome Sequencing [WGS]) represent an unprecedent solution capable of inferring sources of contamination as well as contributing to food safety along the artisanal food continuum. The overall objective of this PhD thesis was to explore potential microbial hazards among different artisanal food productions of animal origins (dairy and meat-derived) typical of the food culture and heritage landscape belonging to Mediterranean countries. Three different studies were then carried out, specifically focussing on: 1) compare the seasonal variability of microbiological quality and potential occurrence of microbial hazards in two batches of Italian artisanal fermented dairy and meat productions; 2) Investigate genetic relationships as well as virulome and resistome of foodborne pathogens isolated within dairy and meat-derived productions located in Italy, Spain, Portugal and Morocco; 3) investigate the population structure, virulome, resistome and mobilome of Klebsiella spp. isolates collected from study 1, including an extended range of public sequences.

Advanced statistical models for the segregation, identification and measurement of coexisting sound sources

Long-term monitoring of acoustical environments is gaining popularity thanks to the relevant amount of scientific and engineering insights that it provides. The increasing interest is due to the constant growth of storage capacity and computational power to process large amounts of data. In this perspective, machine learning (ML) provides a broad family of data-driven statistical techniques to deal with large databases. Nowadays, the conventional praxis of sound level meter measurements limits the global description of a sound scene to an energetic point of view. The equivalent continuous level Leq represents the main metric to define an acoustic environment, indeed. Finer analyses involve the use of statistical levels. However, acoustic percentiles are based on temporal assumptions, which are not always reliable. A statistical approach, based on the study of the occurrences of sound pressure levels, would bring a different perspective to the analysis of long-term monitoring. Depicting a sound scene through the most probable sound pressure level, rather than portions of energy, brought more specific information about the activity carried out during the measurements. The statistical mode of the occurrences can capture typical behaviors of specific kinds of sound sources. The present work aims to propose an ML-based method to identify, separate and measure coexisting sound sources in real-world scenarios. It is based on long-term monitoring and is addressed to acousticians focused on the analysis of environmental noise in manifold contexts. The presented method is based on clustering analysis. Two algorithms, Gaussian Mixture Model and K-means clustering, represent the main core of a process to investigate different active spaces monitored through sound level meters. The procedure has been applied in two different contexts: university lecture halls and offices. The proposed method shows robust and reliable results in describing the acoustic scenario and it could represent an important analytical tool for acousticians.