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- Magni - a framework for developing context-aware mobile applicationsPublication . Queirós, Ricardo; Portela, Filipe; Machado, JoséThe advent of Internet and ubiquitous technologies has been fostering the appearance of intelligent mobile applications aware of their environment and the objects nearby. Despite its popularity, mobile developers are often required to write large and disorganized amounts of code, mixing UI with business logic and interact, in a ad-hoc fashion, with sensor devices and services. These habits hinder the code maintenance, refactoring and testing, while negatively influencing the consistency and performance of mobile applications. In this paper we present Magni as an abstract framework for the design and implementation of personalized and context-aware mobile applications. The corner stone of the framework is its architectural pattern based on the Model–View–Presenter pattern in the UI layer relying in REST services the majority of the app features. This paradigm fosters the modular design, implementing the separation of concerns concept and allowing an easier implementation of unit tests. In order to validate the framework, we present a prototype for an healthcare automotive app. The main goal of the app is to facilitate the access to health related points of interest such as hospitals, clinics and pharmacies.
- Introdução ao desenvolvimento moderno para a WebPublication . Portela, Carlos Filipe; Queirós, Ricardo
- A benchmarking analysis of open-source business intelligence tools in healthcare environmentsPublication . Brandão, Andreia; Pereira, Eliana; Esteves, Marisa; Portela, Carlos Filipe; Santos, Manuel Filipe; Abelha, António; Machado, JoséIn recent years, a wide range of Business Intelligence (BI) technologies have been applied to different areas in order to support the decision-making process. BI enables the extraction of knowledge from the data stored. The healthcare industry is no exception, and so BI applications have been under investigation across multiple units of different institutions. Thus, in this article, we intend to analyze some open-source/free BI tools on the market and their applicability in the clinical sphere, taking into consideration the general characteristics of the clinical environment. For this purpose, six BI tools were selected, analyzed, and tested in a practical environment. Then, a comparison metric and a ranking were defined for the tested applications in order to choose the one that best applies to the extraction of useful knowledge and clinical data in a healthcare environment. Finally, a pervasive BI platform was developed using a real case in order to prove the tool viability.