SOCIAL REPRESENTATIONS OF BASICS LIFE SUPPORT

Victims of cardiac arrest need immediate Basic Life Support, in order to preserve as much as possible, the flow of blood to the brain and heart and other vital organs, it is essential to gain time pending differentiated help, performing simple acts and practical (BLS) to save lives. Learn how to perform RPC is an interactive process that requires knowledge and skills, but at the same time an act of solidarity, social responsibility, civic consciousness, and a duty of citizenship. Because no one revives alone, it requires a coordinated work of a team, all citizens must join forces in a single goal: Save Lives, the massification of the BLS (RPC, 2014). We conducted an exploratory study that aimed to identify the social representations of basic life support in the general population. We used the technique of free association of words through a short questionnaire, we obtained a sample of 45 participants. The results show that participants were mostly female and 27 that fashion of age was in the age group 40 to 59 years. With regard to social representations, we find an organized structure follows the core: help, help to revive, and save is giving life, are in fact structural and consensual elements in basic life support. In more peripheral elements we find extremely important elements, which can be worked in a way so that the core is more efficient such as to act coordinately as a team in face of an accident, it can thus be successful in practice. The social representation of basic life support does not differ from that referred in the literature on the subject, but it is common knowledge that these skills can only be acquired if they are systematically trained, because they obey an algorithm that if it is not settled theoretical and instrumentally it is not effective in practice.

A Case-base Approach to Workforces’ Satisfaction Assessment

It is well known that human resources play a valuable role in a sustainable organizational development. Indeed, this work will focus on the development of a decision support system to assess workers’ satisfaction based on factors related to human resources management practices. The framework is built on top of a Logic Programming approach to Knowledge Representation and Reasoning, complemented with a Case Based approach to computing. The proposed solution is unique in itself, once it caters for the explicit treatment of incomplete, unknown, or even self-contradictory information, either in terms of a qualitative or quantitative setting. Furthermore, clustering methods based on similarity analysis among cases were used to distinguish and aggregate collections of historical data or knowledge in order to reduce the search space, therefore enhancing the cases retrieval and the overall computational process.

An Artificial Intelligence Approach to Individuals' Age Assessment

A link between patterns of pelvic growth and human life history is supported by the finding that, cross-culturally, variation in maturation rates of female pelvis are correlated with variation in ages of menarche and first reproduction, i.e., it is well known that the human dimensions of the pelvic bones depend on the gender and vary with the age. Indeed, one feature in which humans appear to be unique is the prolonged growth of the pelvis after the age of sexual maturity. Both the total superoinferior length and mediolateral breadth of the pelvis continues to grow markedly after puberty, and do not reach adult proportions until the late teens years. This continuation of growth is accomplished by relatively late fusion of the separate centers of ossification that form the bones of the pelvis. Hence, in this work we will focus on the development of an intelligent decision support system to predict individual’s age based on a pelvis' dimensions criteria. Some basic image processing techniques were applied in order to extract the relevant features from pelvic X-rays, being the computational framework 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.

Analysis of Dyscalculia Evidences through Artificial Intelligence Systems

Dyscalculia is usually perceived of as a specific learning difficulty for mathematics or, more appropriately, arithmetic. Because definitions and diagnoses of dyscalculia are in their infancy and sometimes are contradictory. However, mathematical learning difficulties are certainly not in their infancy and are very prevalent and often devastating in their impact. Co-occurrence of learning disorders appears to be the rule rather than the exception. Co-occurrence is generally assumed to be a consequence of risk factors that are shared between disorders, for example, working memory. However, it should not be assumed that all dyslexics have problems with mathematics, although the percentage may be very high, or that all dyscalculics have problems with reading and writing. Because mathematics is very developmental, any insecurity or uncertainty in early topics will impact on later topics, hence to need to take intervention back to basics. However, it may be worked out in order to decrease its degree of severity. For example, disMAT, an app developed for android may help children to apply mathematical concepts, without much effort, that is turning in itself, a promising tool to dyscalculia treatment. Thus, this work will focus on the development of a Decision Support System to estimate children evidences of dyscalculia, based on data obtained on-the-fly with disMAT. The computational framework is built on top of a Logic Programming approach to Knowledge Representation and Reasoning, grounded on a Case-based approach to computing, that allows for the handling of incomplete, unknown, or even self-contradictory information.

Na expressão de um sonho: Barreiras da carreira em universitários com incapacidade

Este estudo teve como objetivo analisar a perceção de barreiras ao desenvolvimento da carreira num grupo de estudantes Universitários portadores de incapacidade. Participaram 19 estudantes de 3 estabelecimentos de Ensino Superior, com idades compreendidas entre os 19 e os 45 anos. Responderam a uma entrevista semiestruturada que avaliava a perceção de barreiras e de sistemas de apoio ao seu desenvolvimento da carreira no passado, no presente e no futuro. Os resultados obtidos evidenciam dimensões de estabilidade e de mudança na perceção de barreiras: as persistentes nos três momentos avaliativos e as específicas a esses momentos. Também revelam que as pessoas significativas e as ajudas pedagógicas são os tipos de apoio ao desenvolvimento da carreira mais referidos. Os resultados são discutidos quanto às suas implicações para a prática e às perspetivas que abrem à investigação do desenvolvimento da carreira desta população. ABSTRACT: The aim of this study is to examine barriers perception to career development in a group of disabled university students. Nineteen students of three institutions of colleges participated, aged between nineteen and forty-five years. they responded to a semi-structured interview that appraised support systems and barriers perception to their career development in past, present and future. The results show barriers perception’s change and stability dimensions: the persistent in the three analise moments and those specific to these moments. lt also reveals that the most said career development's types of support are significant persons and pedagogical aids. The results are discussed regarding their implications for practice and prospects that open for research career development of this population.

Quality of Judgment Assessment

The intersection of Artificial Intelligence and The Law stands for a multifaceted matter, and its effects set the advances on culture, organization, as well as the social matters, when the emergent information technologies are taken into consideration. From this point of view, the weight of formal and informal Conflict Resolution settings should be highlighted, and the use of defective data, information or knowledge must be emphasized. Indeed, it is hard to do it with traditional problem solving methodologies. Therefore, in this work the focus is on the development of decision support systems, in terms of its knowledge representation and reasoning procedures, under a formal framework based on Logic Programming, complemented with an approach to computing centered on Artificial Neural Networks. It is intended to evaluate the Quality-of-Judgments and the respective Degree-of-Confidence that one has on such happenings.

Healthcare Computer Reasoning Addressing Chronically Ill Societies Using IoT: Deep Learning AI to the Rescue of Home-Based Healthcare

The authors present a proposal to develop intelligent assisted living environments for home based healthcare. These environments unite the chronical patient clinical history sematic representation with the ability of monitoring the living conditions and events recurring to a fully managed Semantic Web of Things (SWoT). Several levels of acquired knowledge and the case based reasoning that is possible by knowledge representation of the health-disease history and acquisition of the scientific evidence will deliver, through various voice based natural interfaces, the adequate support systems for disease auto management but prominently by activating the less differentiated caregiver for any specific need. With these capabilities at hand, home based healthcare providing becomes a viable possibility reducing the institutionalization needs. The resulting integrated healthcare framework will provide significant savings while improving the generality of health and satisfaction indicators.