Quantitative analysis of RFID’ publications from 2006 to 2016

Sensitivity Analysis by the PROMETHEE-GAIA method: Algorithms evaluation for COVID-19 prediction

With the expansion of coronavirus in the World, the search for technology solutions based on the analysis and prospecting of diseases has become constant. The paper addresses a machine learning algorithms analysis used to predict and identify infected patients. For analysis, we use a multicriteria approach using the PROMETHEE-GAIA method, providing the structuring of alternatives respective to a set of criteria, thus enabling the obtaining of their importance degree under the perspective of multiple criteria. The study approaches a sensitivity analysis, evaluating the alternatives using the PROMETHEE I and II methods, along with the GAIA plan, both implemented by the Visual PROMETHEE computational tool, exploring numerical and graphical resources. The analysis model proves to be effective, guaranteeing the ranking of alternatives by inter criterion evaluation and local results with intra criterion evaluation, providing a transparent analysis concerning the selection of prediction algorithms to combat the COVID-19 pandemic.

Strategic support for the distribution of vaccines against Covid-19 to Brazilian remote areas: A multicriteria approach in the light of the ELECTRE-MOr method

The pandemic caused by the new coronavirus has brought to light a series of concerns for the Brazilian population and government departments due to the different costly consequences that it has generated. It has also mobilized different strategic fronts that plan and implement several mitigating measures against the virus. Besides, the search for solutions for adequate care for individuals in need of support has been constant. This work uses ELECTRE-MOr, a Multi-Criteria Decision Aid (MCDA) method, to support the logistic plan for the vaccine distribution throughout Brazil, essentially to remote areas. The method allows an objective and structured classification of ideal types of thermal boxes for the storage of immunobiological inside the Cold Chain, presenting the best alternative that maintains the quality of materials until the final destination and has the best cost-benefit. Currently, the ELECTRE-MOr model is under development in a computational tool in Python, allowing the use of the method intuitively and clearly, enabling professionals of any area of expertise to apply it.

Worldwide Research on Low Cost Technologies through Bibliometric Analysis

It is essential to address research into low-cost technologies, as those employed on a wide scale demand a great amount of resources. The main goal of this work was to analyze the research on low cost technologies worldwide by studying the scientific output recorded in the Scopus database. This analysis makes it possible to determine the evolution of research into low cost technologies. In particular, we analyzed the distribution of this research by the different scientific categories, the categories’ evolution over time, the types of publications, the geographical distribution throughout different countries, the main institutions in each scientific category, and the areas of research identified through the main keywords indexed in the publications. A remarkable finding of this work has been that the universities that are most active in low-cost technologies are those in the most technologically advanced countries. There is only one exception to the above statement and it is in the field of medicine, where the most technologically developed countries are not always the most interested in this field. Given the trends observed in recent years, there is a need for a major change and for low-cost technologies to become an area of interest in countries with emerging economies.