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- Quality Management: Concepts and Approaches for Software ProjectsPublication . Gonçalves, Dulce; Varajão, João; Martinho, Ricardo; Cruz, José BulasIn a world of growing competitiveness, “quality” is a main subject. On recent years, there has been a trend towards the improvement of software projects’ quality. This means improving not only the final software products, but especially the quality of leadership and of project management. It is now recognized that the quality of software products and services can be improved if quality management is accomplished according to the unique characteristics and complexity of each project. In this paper we present the main concepts of quality management, as also some approaches of software quality assurance. We then gather them around and, using the Deming’s philosophy, present the Total Quality Management paradigm. We also discuss the rules and standards of Quality Management Systems (ISO 9000 and CMMI), and identify some misfits regarding the specific context of software development.
- Decision support system using mobile app statisticsPublication . Constante, Fabian; Guevara, Juan; Silva, Catarina; Gonçalves, Dulce; Marcelino, LuisNowadays to make the right decision about where and how to request or buy a service, a user is often supported by a mobile device that offers more than simple descriptive data. Nevertheless, not all information on services is fully accessible. The difficulty in keeping track of changes in services’ costs causes delays and can result in waste of time and money. In fact, the decision of which service to use usually involves some level of uncertainty and risk. Hence, the user should have access to some form of decision support system that could be easily available through mobile applications. The power of these devices allows to apply knowledge areas already developed, carrying statistics with dynamic and interactive graphics, thus allowing for a more systematic control of services and corresponding expenses. In this work we analyze the existing related work on mobile decision support systems and propose an architecture of a decision support system using Mobile App Statistics. Tests were carried out with a car fuel app to support the decision of choosing the gas station at each point. Results show that using the additional statistical information provided users can take better decisions during the request of a service.
- Energy consumption behaviour characterization with mobile gamificationPublication . Toasa, Renato; Silva, Carlos; Silva, Catarina; Gonçalves, Dulce; Neves, Luis; Marcelino, LuisExcessive electric energy consumption results in high costs for consumers, and often on using non-renewable resources. Additionally, in many cases, it is difficult for the consumer or for the energy provider to determine if one or more equipment is being used efficiently. Therefore, the main objective of this work is to promote awareness about energy consumption. For that purpose, a mobile application with a gamification approach was designed to identify users’ behaviors towards the use of energy and, based on the user’s answers, offer advices to save energy and promote ecological awareness. The outcome of using gamification on a mobile application with such goals results in a streamlined data collection application that combines information and entertainment. The collected information is being gathered to potentially create consumer profiles that better reflect the user’s energy consumption.
- How Health Literacy impacts Polytechnic of Leiria Students?Publication . Teixeira Ascenso, Rita Margarida; Luis, Luis; Dias, Sara; Gonçalves, DulceIn 2021, aHealth Literacy(HL) evaluation among university students revealed notable limitations in HL. To assess the general HL of populations comprehensively, the European HLSurvey Questionnaire (HLS-EU-Q) was developed, encompassing 12 subdomains to provide a broad perspective on public health. In 2014, the questionnaire was adapted for use in Portugal, resulting in the HLS-EU-PT version, validated through a 16-question survey (HLS-EU-PT-Q16).Global HL andthreedomains’ indexes and levelswere determined, namely Healthcare (HC), Disease prevention (DP), and Health Promotion (HP). The HLSEU-Q16-PT assessment demonstrated satisfactory internal consistency, with 0.8834Cronbach's alpha coefficient.In this study, an online survey distributedbetween 2020-2021among Polytechnic of Leiria academia allowed data collection from various stakeholders, including 251 students, 109 professors, 15 researchers, and 55 other staff. From the430 responses,75 questions were analysed. The saved data wasthefocus of this work, regarding a thesis of the first edition of the master’s in data science to analysethe 251 surveyed studentsand their HL. The results revealed that thesestudents have lower HL index, and, in this case study,health areadegreeor school impactsHL.
- Health Literacy of the Polytechnic of Leiria StudentsPublication . Ascenso, Rita Margarida Teixeira; Dias, Sara Simões; Luis, Luis; Gonçalves, DulceHealth Literacy (HL) has several definitions and numerous HL assessment tools. Several systematic reviews on HL identified tools for HL assessment. Health Literacy Survey with 47 questions (HLS-EU-Q47) for Europe was adapted for 16 questions (HLS-EU-Q16), and for only 6 questions (HLS-EU-Q6). These are already in Portuguese and have been used to assess HL since 2017. The studies involved the Portuguese population, and recently, in 2021, the HL evaluation in university students identified limitations in HL. The HLS-EU-Q16_Pt used showed adequate internal consistency (Cronbach's alpha = 0.778, [0.737, 0.816]). Among 251 students from the Polytechnic of Leiria there was a statistically significant association of HL scores with the health area, and more evident when students had a previous degree in health.
- Decision Support System to Diagnosis and Classification of Epilepsy in ChildrenPublication . Rijo, Rui; Silva, Catarina; Pereira, Luis; Gonçalves, Dulce; Agostinho, MargaridaClinical decision support systems play an important role in organizations. They have a tight relation with the information systems. Our goal is to develop a system to support the diagnosis and the classification of epilepsy in children. Around 50 million people in the world have epilepsy. Epilepsy diagnosis can be an extremely complex process, demanding considerable time and effort from physicians and healthcare infrastructures. Exams such as electroencephalograms and magnetic resonances are often used to create a more accurate diagnosis in a short amount of time. After the diagnosis process, physicians classify epilepsy according to the International Classification of Diseases, ninth revision (ICD-9). Physicians need to classify each specific type of epilepsy based on different data, e.g., types of seizures, events and exams' results. The classification process is time consuming and, in some cases, demands for complementary exams. This work presents a text mining approach to support medical decisions relating to epilepsy diagnosis and ICD-9-based classification in children. We put forward a text mining approach using electronically processed medical records, and apply the K-Nearest Neighbor technique as a white-box multiclass classifier approach to classify each instance, mapping it to the corresponding ICD-9-based standard code. Results on real medical records suggest that the proposed framework shows good performance and clear interpretations, albeit the reduced volume of available training data. To overcome this hurdle, in this work we also propose and explore ways of expanding the dataset.