Smart platform towards batteries analysis based on internet-of-things

This paper presents a new approach of pre-defined profiles, based in different voltage and current values, to control the charging and discharging processes of batteries in order to assess their performance. This new approach was implemented in a prototype that was specially developed for such purpose. This prototype is a smart power electronics platform that allows to perform batteries analysis and to control the charging and discharging processes through a web application using pre-defined profiles. This platform was developed aiming to test different batteries technologies. Considering the relevance of the energy storage area based in batteries, especially for the batteries applied to electric mobility systems, this platform allows to perform controlled tests to the batteries, in order to analyze the batteries performance under different scenarios of operation. Besides the results obtained with the batteries, this work also intends to produce results that can contribute to an involvement in the strengthening of the Internet-of-Things.

Detection of dangerous situations using a smart internet of things system

The Internet of Things (IoT) is a concept that can foster the emergence of innovative applications. In order to minimize parents’s concerns about their children’s safety, this paper presents the design of a smart Internet of Things system for identifying dangerous situations. The system will be based on real time collection and analysis of physiological signals monitored by non-invasive and non-intrusive sensors, Frequency IDentification (RFID) tags and a Global Positioning System (GPS) to determine when a child is in danger. The assumption of a state of danger is made taking into account the validation of a certain number of biometric reactions to some specific situations and according to a self-learning algorithm developed for this architecture. The results of the analysis of data collected and the location of the child will be able in real time to child’s care holders in a web application.

Automatic generation of ETL physical systems from BPMN conceptual models

ETL conceptual modeling is a very important activity in any data warehousing system project implementation. Owning a high-level system representation allowing for a clear identification of the main parts of a data warehousing system is clearly a great advantage, especially in early stages of design and development. However, the effort to model conceptually an ETL system rarely is properly rewarded. Translating ETL conceptual models directly into something that saves work and time on the concrete implementation of the system process it would be, in fact, a great help. In this paper we present and discuss a hybrid approach to this problem, combining the simplicity of interpretation and power of expression of BPMN on ETL systems conceptualization with the use of ETL patterns to produce automatically an ETL skeleton, a first prototype system, which has the ability to be executed in a commercial ETL tool like Kettle.

A cumulative risk model of child physical maltreatment potential: findings from a community-based study

"Published online before print November 20, 2015"

From a NoSQL data source to a business intelligence solution: An experiment

We are living in the era of Big Data. A time which is characterized by the continuous creation of vast amounts of data, originated from different sources, and with different formats. First, with the rise of the social networks and, more recently, with the advent of the Internet of Things (IoT), in which everyone and (eventually) everything is linked to the Internet, data with enormous potential for organizations is being continuously generated. In order to be more competitive, organizations want to access and explore all the richness that is present in those data. Indeed, Big Data is only as valuable as the insights organizations gather from it to make better decisions, which is the main goal of Business Intelligence. In this paper we describe an experiment in which data obtained from a NoSQL data source (database technology explicitly developed to deal with the specificities of Big Data) is used to feed a Business Intelligence solution.

Child abuse monitor system model: a health care critical knowledge monitor system

The Childhood protection is a subject with high value for the society, but, the Child Abuse cases are difficult to identify. The process from suspicious to accusation is very difficult to achieve. It must configure very strong evidences. Typically, Health Care services deal with these cases from the beginning where there are evidences based on the diagnosis, but they aren’t enough to promote the accusation. Besides that, this subject it’s highly sensitive because there are legal aspects to deal with such as: the patient privacy, paternity issues, medical confidentiality, among others. We propose a Child Abuses critical knowledge monitor system model that addresses this problem. This decision support system is implemented with a multiple scientific domains: to capture of tokens from clinical documents from multiple sources; a topic model approach to identify the topics of the documents; knowledge management through the use of ontologies to support the critical knowledge sensibility concepts and relations such as: symptoms, behaviors, among other evidences in order to match with the topics inferred from the clinical documents and then alert and log when clinical evidences are present. Based on these alerts clinical personnel could analyze the situation and take the appropriate procedures.

Communications with QoS in IoT&Cloud environment

Dissertação de mestrado integrado em Engenharia de Telecomunicações e Informática

Reverse engineering of web applications

The MAP-i Doctoral Program of the Universities of Minho, Aveiro and Porto

Parents' physical victimization in childhood and current risk of child maltreatment: the mediator role of psychosomatic symptoms

Objective: To test the potential mediation effect of psychosomatic symptoms on the relationship between parents' history of childhood physical victimization and current risk for child physical maltreatment. Methods: Data from the Portuguese National Representative Study of Psychosocial Context of Child Abuse and Neglect were used. Nine-hundred and twenty-four parents completed the Childhood History Questionnaire, the Psychosomatic Scale of the Brief Symptom Inventory, and the Child Abuse Potential Inventory. Results: Mediation analysis revealed that the total effect of the childhood physical victimization on child maltreatment risk was significant. The results showed that the direct effect from the parents' history of childhood physical victimization to their current maltreatment risk was still significant once parents' psychosomatic symptoms were added to the model, indicating that the increase in psychosomatic symptomatology mediated in part the increase of parents' current child maltreatment risk. Discussion: The mediation analysis showed parents' psychosomatic symptomatology as a causal pathway through which parents' childhood history of physical victimization exerts its effect on increased of child maltreatment risk. Somatization-related alterations in stress and emotional regulation are discussed as potential theoretical explanation of our findings. A cumulative risk perspective is also discussed in order to elucidate about the mechanisms that contribute for the intergenerational continuity of child physical maltreatment.

Physical activity, health-related quality of life and depression during pregnancy

This study examines physical activity patterns among women, from pre-pregnancy to the second trimester of pregnancy, and the relationship between physical activity status based on physical activity guidelines and health-related quality of life (HRQoL) and depression over pregnancy. 56 healthy pregnant women self reported physical activity, HRQoL and depression at 10-15 and 19-24 weeks of pregnancy and physical activity before pregnancy. Whereas vigorous leisure physical activity decreased after conception, moderate leisure physical activity and work related physical activity remained stable over time. The prevalence of recommended physical activity was 39.3% and 12.5% in the 1st and 2nd trimesters of pregnancy respectively, and 14.3% pre-pregnancy. From the 1st to the 2nd pregnancy trimester, most physical HRQoL dimensions scores decreased and only mental component increased, independently of physical activity status. No changes in mean depression scores were observed. These data suggest that physical activity patterns change with pregnancy and that physical and mental components are differentially affected by pregnancy course, independently of physical activity status.