A Case Based Methodology for Problem Solving aiming at Knee Osteoarthritis Detection

Knee osteoarthritis is the most common type of arthritis and a major cause of impaired mobility and disability for the ageing populations. Therefore, due to the increasing prevalence of the malady, it is expected that clinical and scientific practices had to be set in order to detect the problem in its early stages. Thus, this work will be focused on the improvement of methodologies for problem solving aiming at the development of Artificial Intelligence based decision support system to detect knee osteoarthritis. The framework is built on top of a Logic Programming approach to Knowledge Representation and Reasoning, complemented with a Case Based approach to computing that caters for the handling of incomplete, unknown, or even self-contradictory information.

Age Prediction through Pelvis X-Ray Images - A Case Based approach to Problem Solving

It is well known that the dimensions of the pelvic bones depend on the gender and vary with the age of the individual. Indeed, and as a matter of fact, this work will focus on the development of an intelligent decision support system to predict individual’s age based on pelvis’ dimensions criteria. On the one hand, some basic image processing technics were applied in order to extract the relevant features from pelvic X-rays. On the other hand, the computational framework presented here was built on top of a Logic Programming approach to knowledge representation and reasoning, that caters for the handling of incomplete, unknown, or even self-contradictory information, complemented with a Case Base approach to computing.

Desenvolvimento e implementação de uma abordagem CTSA do conceito de acidez no ensino da física e química

A emergência de questões tecnológicas, sociais e ambientais transformam o ensino das ciências num enorme desafio. A escassez e a contaminação da água, resultante de actividades antropogénicas, perspectiva-se hoje como um problema de futuro. Este tema, parte integrante do programa de Química do 11o Ano, inspirou uma intervenção didáctica baseada numa metodologia de resolução problemas que se pode enquadrar numa abordagem do tipo CTSA. A intervenção proposta, a partir de uma saída de campo que se concretizou na Mina de S. Domingos, teve por objectivos melhorar as aprendizagens realizadas pelos alunos e promover a mudança de atitudes face ao Ambiente e ao consumo de água em particular. Os dados recolhidos, analisados segundo métodos qualitativos e quantitativos, revelaram melhores conhecimentos e atitudes mais favoráveis relativamente à Ciência e à disciplina de Física e Química, e face ao Ambiente e ao consumo de água, reforçando a importância deste tipo de abordagens. ABSTRACT; The emergent technology, social and environmental issues are making the science teaching a huge challenge. The shortage and the contamination of water, as result of anthropogenic activities, are faced today like a future problem. This theme is part of the Chemistry subject curriculum of the eleventh grade level and it inspired a didactic intervention based upon a problem solving methodology that can be framed in a STSE approach. The goals of the proposed intervention, taking Mina de S. Domingos for a field trip, meant to improve the students' learnings and to promote a change of attitudes in relation to the environment and to the water consumption, in particular. The collected data, analyzed according to qualitative and quantitative methods, showed better knowledge and more favorable attitudes towards Science and Physics and Chemistry, as well as regarding the environment and water consumption, enhancing the importance of this kind of approach.

Assessing the Role of General Chemistry Learning in Higher Education

The inclusion of General Chemistry (GC) in the curricula of higher education courses in science and technology aims, on the one hand, to develop students' skills necessary for further studies and, on the other hand, to respond to the need of endowing future professionals of knowledge to analyze and solve multidisciplinary problems in a sustainable way. The participation of students in the evaluation of the role played by the GC in their training is crucial, and the analysis of the results can be an essential tool to increase success in the education of students and improving practices in various professions. Undeniably, this work will be focused on the development of an intelligent system to assess the role of GC. The computational framework is built on top of a Logic Programming approach to Knowledge Representation and Reasoning, complemented with a problem solving methodology moored on Artificial Neural Networks. The results so far obtained show that the proposed model stands for a good start, being its overall accuracy higher than 95%.

Prediction of Length of Hospital Stay in Preterm Infants - A Case-Based Reasoning View

The length of stay of preterm infants in a neonatology service has become an issue of a growing concern, namely considering, on the one hand, the mothers and infants health conditions and, on the other hand, the scarce healthcare facilities own resources. Thus, a pro-active strategy for problem solving has to be put in place, either to improve the quality-of-service provided or to reduce the inherent financial costs. Therefore, this work will focus on the development of a diagnosis decision support system in terms of a formal agenda built on a Logic Programming approach to knowledge representation and reasoning, complemented with a case-based problem solving methodology to computing, that caters for the handling of incomplete, unknown, or even contradictory in-formation. The proposed model has been quite accurate in predicting the length of stay (overall accuracy of 84.9%) and by reducing the computational time with values around 21.3%.

An Evaluative Model to Assess the Organizational Efficiency in Training Corporations

In an organisation any optimization process of its issues faces increasing challenges and requires new approaches to the organizational phenomenon. Indeed, in this work it is addressed the problematic of efficiency dynamics through intangible variables that may support a different view of the corporations. It focuses on the challenges that information management and the incorporation of context brings to competitiveness. Thus, in this work it is presented the analysis and development of an intelligent decision support system in terms of a formal agenda built on a Logic Programming based methodology to problem solving, complemented with an attitude to computing grounded on Artificial Neural Networks. The proposed model is in itself fairly precise, with an overall accuracy, sensitivity and specificity with values higher than 90 %. The proposed solution is indeed unique, catering for the explicit treatment of incomplete, unknown, or even self-contradictory information, either in a quantitative or qualitative arrangement.