Salutogenesis: a new paradigm for pervasive computing in healthcare environments?

Salutogenesis is now accepted as a part of the contemporary model of disease: an individual is not only affected by pathogenic factors in the environment, but those that promote well-being or salutogenesis. Given that "environment" extends to include the built environment, promotion of salutogenesis has become part of the architectural brief for contemporary healthcare facilities, drawing on an increasing evidence-base. Salutogenesis is inextricably linked with the notion of person-environment "fit". MyRoom is a proposal for an integrated architectural and pervasive computing model, which enhances psychosocial congruence by using real-time data indicative of the individual's physical status to enable the environment of his/her room (colour, light, temperature) to adapt on an on-going basis in response to bio-signals. This work is part of the PRTLI-IV funded programme NEMBES, investigating the use of embedded technologies in the built environment. Different care contexts require variations in the model, and iterative prototyping investigating use in different contexts will progressively lead to the development of a fully-integrated adaptive salutogenic single-room prototype.

Programas de tertulia política en Twitter: un modelo neurocomunicativo de análisis del discurso

En este trabajo aplicamos a la red social Twitter un modelo de análisis del discurso político y mediático desarrollado en publicaciones previas, que permite hacer compatible el estudio de los datos discursivos con propuestas explicativas surgidas a propósito de la comunicación política (neurocomunicación) y de la comunicación digital (la red como quinto estado, convergencia, inteligencia colectiva). Asumimos que hay categorías del encuadre discursivo (frame) que pueden ser tratadas como indicadores de habilidades cognitivas y comunicativas. Analizamos estas categorías agrupándolas en tres dimensiones fundamentales: la intencional (ilocutividad del tuit, encuadre interpretativo de las etiquetas), referencial (temas, protagonistas), e interactiva (alineamiento estructural, predictibilidad; marcas de intertextualidad y dialogismo; afiliación partidista). El corpus consta de 4116 tuits: 3000 tuits pertenecientes a los programas Al Rojo Vivo (La Sexta: A3 Media), Las Mañanas Cuatro (Cuatro: Mediaset) y Los Desayunos de TVE (RTVE), 1116 tuits de seguidores de los programas, que corresponden a 45 tuits de cada programa. Los resultados confirman que el modelo permite establecer diferentes perfiles de subjetividad política en las cuentas de Twitter.

The Importance of Learning History and Philosophy of Computing

Computers have invaded our offices, our homes, cars and coffee-pots; they have become ubiquitous. However, the advance of computing technologies is associated with an increasing lack of “visibility” of the underlying software and hardware technologies. While we use and accept the computer, we neither know its history nor functionality. In this paper, we argue that this is not a healthy situation. Also, recruitment onto UK Computing degree courses is steadily falling; these courses are appearing less attractive to school-leavers. This may be associated with the increasing ubiquity. In this paper we reflect on an MSc. module of instruction, Concepts and Philosophy of Computing, and a BSc. module Computer Games Development developed at the University of Worcester which address these issues. We propose that the elements of these modules form a necessary part of the education of all citizens, and we suggest how this may be realized. We also suggest how to re-enthuse our youth about computing as a discipline and halt the drop in recruitment.

The Importance of Learning History and Philosophy of Computing

Computers have invaded our offices, our homes, cars and coffee-pots; they have become ubiquitous. However, the advance of computing technologies is associated with an increasing lack of “visibility” of the underlying software and hardware technologies. While we use and accept the computer, we neither know its history nor functionality. In this paper, we argue that this is not a healthy situation. Also, recruitment onto UK Computing degree courses is steadily falling; these courses are appearing less attractive to school-leavers. This may be associated with the increasing ubiquity. In this paper we reflect on an MSc. module of instruction, Concepts and Philosophy of Computing, and a BSc. module Computer Games Development developed at the University of Worcester which address these issues. We propose that the elements of these modules form a necessary part of the education of all citizens, and we suggest how this may be realized. We also suggest how to re-enthuse our youth about computing as a discipline and halt the drop in recruitment.

Arte, museu, educação: uma integração necessária na superação das tecnologias de controle social

This research aims to reflect on the strategies and mediation used by Oscar Niemeyer and Museum of contemporary art, in Curitiba, and Pinacoteca and Museum of modern art of São Paulo, to approximate audience of art. Recognizes that the gap between the two and that is reflected in the low visitation to art museums is the result of social control technologies historically elaborate and maintained to keep track of who has economic power over others , are people , as in the case of artistic appreciation, or countries, such as what happens with technology.It also presents some possibilities of subversion of this control , which occur especially because the human being creative and interpretive. Finally, it notes that the work carried out by the educational sectors of museums to attract different audiences is very relevant institutions and committed. With regard to teaching materials prepared and distributed to visitors, however, the need for some adjustments so that they communicate better with visitors and contribute, in fact, to deconstruct the idea of the Museum as an elite space and available only to a few privileged.

Cloud Computing to Automate Information Units

This article will address the main technical aspects that facilitate the use and growth of computer technology in the cloud, which go hand in hand with the emergence of more and better services on the Internet and technological development of the broadband. Finally, we know what is the impact that the cloud computing technologies in the automation of information units.

Análise de risco para computação em nuvem

Têm-se notado nos últimos anos um crescimento na adoção de tecnologias de computação em nuvem, com uma adesão inicial por parte de particulares e pequenas empresas, e mais recentemente por grandes organizações. Esta tecnologia tem servido de base ao aparecimento de um conjunto de novas tendências, como a Internet das Coisas ligando os nossos equipamentos pessoais e wearables às redes sociais, processos de big data que permitem tipificar comportamentos de clientes ou ainda facilitar a vida ao cidadão com serviços de atendimento integrados. No entanto, tal como em todas as novas tendências disruptivas, que trazem consigo um conjunto de oportunidades, trazem também um conjunto de novos riscos que são necessários de serem equacionados. Embora este caminho praticamente se torne inevitável para uma grande parte de empresas e entidades governamentais, a sua adoção como funcionamento deve ser alvo de uma permanente avaliação e monitorização entre as vantagens e riscos associados. Para tal, é fundamental que as organizações se dotem de uma eficiente gestão do risco, de modo que possam tipificar os riscos (identificar, analisar e quantificar) e orientar-se de uma forma segura e metódica para este novo paradigma. Caso não o façam, os riscos ficam evidenciados, desde uma possível perda de competitividade face às suas congéneres, falta de confiança dos clientes, dos parceiros de negócio e podendo culminar numa total inatividade do negócio. Com esta tese de mestrado desenvolve-se uma análise genérica de risco tendo como base a Norma ISO 31000:2009 e a elaboração de uma proposta de registo de risco, que possa servir de auxiliar em processos de tomada de decisão na contratação e manutenção de serviços de Computação em Nuvem por responsáveis de organizações privadas ou estatais.

Exploiting the environment for structural health monitoring: Strategies, algorithms, and technologies

A densely built environment is a complex system of infrastructure, nature, and people closely interconnected and interacting. Vehicles, public transport, weather action, and sports activities constitute a manifold set of excitation and degradation sources for civil structures. In this context, operators should consider different factors in a holistic approach for assessing the structural health state. Vibration-based structural health monitoring (SHM) has demonstrated great potential as a decision-supporting tool to schedule maintenance interventions. However, most excitation sources are considered an issue for practical SHM applications since traditional methods are typically based on strict assumptions on input stationarity. Last-generation low-cost sensors present limitations related to a modest sensitivity and high noise floor compared to traditional instrumentation. If these devices are used for SHM in urban scenarios, short vibration recordings collected during high-intensity events and vehicle passage may be the only available datasets with a sufficient signal-to-noise ratio. While researchers have spent efforts to mitigate the effects of short-term phenomena in vibration-based SHM, the ultimate goal of this thesis is to exploit them and obtain valuable information on the structural health state. First, this thesis proposes strategies and algorithms for smart sensors operating individually or in a distributed computing framework to identify damage-sensitive features based on instantaneous modal parameters and influence lines. Ordinary traffic and people activities become essential sources of excitation, while human-powered vehicles, instrumented with smartphones, take the role of roving sensors in crowdsourced monitoring strategies. The technical and computational apparatus is optimized using in-memory computing technologies. Moreover, identifying additional local features can be particularly useful to support the damage assessment of complex structures. Thereby, smart coatings are studied to enable the self-sensing properties of ordinary structural elements. In this context, a machine-learning-aided tomography method is proposed to interpret the data provided by a nanocomposite paint interrogated electrically.

Taxonomy of broker's functions in virtual enterprises

Not just with the emergence but also with the growing of the electronic market, that is, the growth of online suppliers of services and products and Internet users (potential consumers), the necessary conditions to the affirmation of the agile/virtual enterprises (A/VE) as a present and future enterprise organizational model are created. In this context, it is our understanding that the broker may have an important role in its development, namely, if the broker performs functions for the A/VE with better efficacy and efficiency. In this article, we will present first a revision of the broker’s models in a structured form. We present a taxonomy of possible broker’s functions for the broker’s actuation near the A/VE and then the classification of the literature broker’s models. This classification will permit an analysis of a broker’s model and establish a mainframe for our broker’s model according to the BM_Virtual Enterprise Architecture Reference Model (BM_VEARM).

Distributed processing of large remote sensing images using MapReduce - A case of Edge Detection

Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.

IaaS, infraestructura com a servei

El propósito de este documento es adentrarnos en los nuevos modelos de negocio basados en las tecnologías Cloud Computing con el objetivo de consolidar nuevos conocimientos complementarios a los estudios de ingeniería informática. Se quiere realizar un estudio de productos open-source basados en un modelo de servicio como infraestructura (IaaS), y, implementarlos desde la vertiente más práctica.

Hire me: Computational inference of hirability in employment interviews based on nonverbal behavior

Understanding the basis on which recruiters form hirability impressions for a job applicant is a key issue in organizational psychology and can be addressed as a social computing problem. We approach the problem from a face-to-face, nonverbal perspective where behavioral feature extraction and inference are automated. This paper presents a computational framework for the automatic prediction of hirability. To this end, we collected an audio-visual dataset of real job interviews where candidates were applying for a marketing job. We automatically extracted audio and visual behavioral cues related to both the applicant and the interviewer. We then evaluated several regression methods for the prediction of hirability scores and showed the feasibility of conducting such a task, with ridge regression explaining 36.2% of the variance. Feature groups were analyzed, and two main groups of behavioral cues were predictive of hirability: applicant audio features and interviewer visual cues, showing the predictive validity of cues related not only to the applicant, but also to the interviewer. As a last step, we analyzed the predictive validity of psychometric questionnaires often used in the personnel selection process, and found that these questionnaires were unable to predict hirability, suggesting that hirability impressions were formed based on the interaction during the interview rather than on questionnaire data.

A Novel Slotless PMBLDC Motor for Precise Positioning Applications

This paper presents the design and analysis of a novel machine family of Siotiess Permanent Magnet Brushless DC motors (PMBLDC) for precise positioning applications of spacecrafts. Initial design, selection of major parameters and air gap magnetic flux density are estimated using the analytical model of the machine. The proportion of the halbach array in the machine was optimized using FE to obtain near trapezoidal flux pattern. The novel machine topology is found to deliver high torque density, high efficiency, zero cogging torque, better positional stability, high torque to inertia ratio and zero magnetic stiction suiting space requirements. The machine provides uniform air gap flux density along the radius thus avoiding circulating currents in stator conductors and hence reducing torque ripple

ECG Noise Removal using GA tuned Sign-Data Least Mean Square Algorithm

Adaptive filter is a primary method to filter Electrocardiogram (ECG), because it does not need the signal statistical characteristics. In this paper, an adaptive filtering technique for denoising the ECG based on Genetic Algorithm (GA) tuned Sign-Data Least Mean Square (SD-LMS) algorithm is proposed. This technique minimizes the mean-squared error between the primary input, which is a noisy ECG, and a reference input which can be either noise that is correlated in some way with the noise in the primary input or a signal that is correlated only with ECG in the primary input. Noise is used as the reference signal in this work. The algorithm was applied to the records from the MIT -BIH Arrhythmia database for removing the baseline wander and 60Hz power line interference. The proposed algorithm gave an average signal to noise ratio improvement of 10.75 dB for baseline wander and 24.26 dB for power line interference which is better than the previous reported works

An Improved Technique for Evolving Wavelet Coefficients for Fingerprint Image Compression

In this paper, an improved technique for evolving wavelet coefficients refined for compression and reconstruction of fingerprint images is presented. The FBI fingerprint compression standard [1, 2] uses the cdf 9/7 wavelet filter coefficients. Lifting scheme is an efficient way to represent classical wavelets with fewer filter coefficients [3, 4]. Here Genetic algorithm (GA) is used to evolve better lifting filter coefficients for cdf 9/7 wavelet to compress and reconstruct fingerprint images with better quality. Since the lifting filter coefficients are few in numbers compared to the corresponding classical wavelet filter coefficients, they are evolved at a faster rate using GA. A better reconstructed image quality in terms of Peak-Signal-to-Noise-Ratio (PSNR) is achieved with the best lifting filter coefficients evolved for a compression ratio 16:1. These evolved coefficients perform well for other compression ratios also.