Ambient assisted living technology: comparative perspectives of users and caregivers

Developed societies are currently facing severe demographic changes: the world population is ageing at an unprecedented rate. This demographic trend will be also followed by an increase of people with physical limitations. New challenges are being raised to the traditional health care systems, not only in Portugal, but also in all other European states. There is an urgent need to find solutions that allow extending the time people can live in their preferred environment by increasing their autonomy, self-confidence and mobility. AAL4ALL is a project currently being developed in cooperation with 34 Portuguese interdisciplinary partners, from industry to academia, R&D and social disciplines, which employs a novel conceptual approach through the development of an ecosystem of products and services for Ambient Assisted Living (AAL) associated to a business model and validated through large scale trial. This paper presents a comparative perspective of the needs and attitudes towards technology of the AAL users and caregivers identified in the analysis of a set of three different surveys: a users survey targeted at the Portuguese seniors and pre-seniors; an informal caregivers survey targeted at the family, friends and neighbours who provide care without any financial compensation; and a formal caregivers survey targeted at physicians, nurses,psychologists, social workers, and direct-care workers providing care to elders. The first results indicate that AAL solutions must be affordable,user friendly and have a true perceived benefit to their users.

Piezoresistive sensors for force mapping of hip-prostheses

The success of artificial prosthetic replacements depends on the fixation of the artificial prosthetic component after being implanted in the thighbone. The materials for fixation are subject to mechanical stresses, which originate permanent deformations, incipient cracks and even fatigue fractures. This work shows the possibility of monitoring the mechanical stress over time in prosthesis. In this way, highly sensitive silicon thin-film piezoresistive sensors were developed attached to prosthesis and their results compared with commercial strain gauge sensors. Mechanical stress-strain experiments were performed in compressive mode, during 10,000 cycles. Experimental data was acquired at mechanical vibration frequencies of 0.5 Hz, 1 Hz and 5 Hz, and sent to a computer by means of a wireless link. The results show that there is a decrease in sensitivity of the thin-film silicon piezoresistive sensors when they are attached to the prosthesis, but this decrease does not compromise its monitoring performance. The sensitivity, compared to that of commercial strain gauges, is much larger due to their higher gauge factors (-23.5), when compared to the GFs of commercial sensors (2).

Mapping Culture and Compromised Art in the Era of Globalization

This work presents an analysis of the cultural and artistic field, positively compromised with social and political questions. The authors start with the categorization of the idea of culture and move to vindication art movements. These movements, which followed the first vanguards and worked from the compromise with “otherness”, are at the origin of the contemporary denomination of political art. In this context, the authors approach the origins of activist art, referring to issues of gender, multiculturalism, globalization, and poverty. The different forms of presenting content are also an object of analysis: from art tradition to the contamination of daily life, from local to global, from street contact to digital.

Comparative analysis between statistical and artificial intelligence models in business failure prediction

A growing number of predicting corporate failure models has emerged since 60s. Economic and social consequences of business failure can be dramatic, thus it is not surprise that the issue has been of growing interest in academic research as well as in business context. The main purpose of this study is to compare the predictive ability of five developed models based on three statistical techniques (Discriminant Analysis, Logit and Probit) and two models based on Artificial Intelligence (Neural Networks and Rough Sets). The five models were employed to a dataset of 420 non-bankrupt firms and 125 bankrupt firms belonging to the textile and clothing industry, over the period 2003–09. Results show that all the models performed well, with an overall correct classification level higher than 90%, and a type II error always less than 2%. The type I error increases as we move away from the year prior to failure. Our models contribute to the discussion of corporate financial distress causes. Moreover it can be used to assist decisions of creditors, investors and auditors. Additionally, this research can be of great contribution to devisers of national economic policies that aim to reduce industrial unemployment.

Comparative Analysis between Statistical and Artificial Intelligence Models in Business Failure Prediction

A growing number of predicting corporate failure models has emerged since 60s. Economic and social consequences of business failure can be dramatic, thus it is not surprise that the issue has been of growing interest in academic research as well as in business context. The main purpose of this study is to compare the predictive ability of five developed models based on three statistical techniques (Discriminant Analysis, Logit and Probit) and two models based on Artificial Intelligence (Neural Networks and Rough Sets). The five models were employed to a dataset of 420 non-bankrupt firms and 125 bankrupt firms belonging to the textile and clothing industry, over the period 2003–09. Results show that all the models performed well, with an overall correct classification level higher than 90%, and a type II error always less than 2%. The type I error increases as we move away from the year prior to failure. Our models contribute to the discussion of corporate financial distress causes. Moreover it can be used to assist decisions of creditors, investors and auditors. Additionally, this research can be of great contribution to devisers of national economic policies that aim to reduce industrial unemployment.