An ecosystem of products and systems for ambient intelligence – the AAL4ALL users perspective

Developed societies are currently facing severe demographic changes: the world is getting older at an unprecedented rate. In 2000, about 420 million people, or approximately 7 percent of the world population, were aged 65 or older. By 2050, that number will be nearly 1.5 billion people, about 16 percent of the world population. This demographic trend will be also followed by an increase of people with physical limitations. New challenges will be 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 presents an idea for an answer 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 the results of the first survey developed within the AAL4ALL project: the users’ survey targeted at the Portuguese seniors and pre-seniors. This paper is, thus, about the lives of the Portuguese population aged 50 and over.

Application to quantify fetal lung branching on rat explants

Recently, regulating mechanisms of branching morphogenesis of fetal lung rat explants have been an essential tool for molecular research. The development of accurate and reliable segmentation techniques may be essential to improve research outcomes. This work presents an image processing method to measure the perimeter and area of lung branches on fetal rat explants. The algorithm starts by reducing the noise corrupting the image with a pre-processing stage. The outcome is input to a watershed operation that automatically segments the image into primitive regions. Then, an image pixel is selected within the lung explant epithelial, allowing a region growing between neighbouring watershed regions. This growing process is controlled by a statistical distribution of each region. When compared with manual segmentation, the results show the same tendency for lung development. High similarities were harder to obtain in the last two days of culture, due to the increased number of peripheral airway buds and complexity of lung architecture. However, using semiautomatic measurements, the standard deviation was lower and the results between independent researchers were more coherent

DEVELOPMENT OF A MECHATRONIC SYSTEM FOR BEDRIDDEN PEOPLE SUPPORT

This work is developed in the context of Ambient Assisted Living (AAL) and has, as main purpose, the development of a mechatronic system that allows caring of bedridden patients with ongoing medical care terminal (MCT), by a single person. This system allows higher autonomy in domiciliary care, safety, comfort and hygiene of bedridden patients. It contributes to a large increase in their quality of life as well as the ease of monitoring by providers of continuous care, which, in many cases, may be the family itself. The product includes an embedded processing interface for acquiring physiological data to support online monitoring. The development of this project was focused on improving the quality of life, autonomy, participation in social life and reducing healthcare costs in the area AAL. The developed societies currently face severe demographic changes: the world is aging at an unprecedented rate. In 2000, about 420 million people, or about 7 percent of the world population were over 65 years old. In 2050, that number will be near 1500 million people, about 16 percent of the world population. This demographic trend will be accompanied by the increase of people with physical limitations. This will impose new challenges for traditional health systems, not only for Portugal but also for all European countries. There is an urgent need to find solutions to improve the lives of people in their preferred environment by increasing their autonomy, self-confidence and mobility. Therefore, in the case of household scenarios, the provision of effective health services is of fundamental importance to the welfare and economic development of each country. This ongoing project aims to develop a mechatronic system to meet the diverse needs, namely: improving life, health care, safety, comfort, and remote monitoring of bedridden person.

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.

Organisational and professional commitments: the influence in nurses´organizational citizenship behaviours

The way an employee behaves in his work can be influenced by the organisational and professional commitment. Nurses are professionals who are guided by organisational and professional goals and values. Among nurses, professional commitment may be an important antecedent of organisational citizenship behaviours. The study shows how organisational and professional commitment is related with nurses’ organisational citizenship behaviours. Data from a sample of 420 nurses working in two hospitals --- the Hospital of St. Marcos, Braga and the Hospital Centre of Alto Ave, Guimarães and Fafe units were collected. The main findings are as follows: (a) organisational commitment and professional commitment contribute to the explanation of nurses’ organisational citizenship behaviours, (b) affective organisational commitment, continuance organisational commitment --- personal sacrifice, affective professional commitment and continuance professional commitment explain 28.6% of variance of organisational citizenship behaviours. © 2013 Instituto Politécnico do Cávado e do Ave (IPCA). Published by Elsevier España, S.L.U. All rights reserved.