Associative classifiers have been widely used in many domains due to their inherent interpretability. They are built in steps, one of them aimed at ranking the rules, usually performed through objective measures. Works aim to modify this step in order to obtain a classifier with better performance. Among them are those that use multiple measures simultaneously in order to consider different points of view for a given rule. However, these works present problems regarding execution time and interpretability. Here we show the use of ranking aggregation methods, specifically Borda’s methods, to rank the rules through a set of measures. Our results demonstrate that our solution is fast to execute and still guarantee the interpretability of the models, since they contain a statistically significant smaller number of rules.
Due to the amount of software that is produced every day in the automotive industry, improve software quality became a necessity, especially in areas where safety is a critical point, such as autonomous driving. Following on from this, continuous inspection of software is important, timely and central, to guarantee software quality and avoid the worst scenarios related to the automotive industry, particularly with autonomous driving. Even so, this proposal is motivated by the huge number of failures associated with low quality software. In this way, the main objective of this research is to achieve a solution for continuous inspection of software quality in the context of the company Bosch Car Multimedia.
Facebook Papers refers to an investigative project, conducted by a consortium of seventeen US media outlets, that had access to thousands of internal Facebook documents the set of documents was leaked by a former employee and whistleblower. This article aims to understand the research that was conducted internally by Facebook teams focusing on Body image and appearance on Instagram. The methodology employed combines bibliographic and documentary research, with descriptive analysis of research reports on Body Image, appearance, and social comparison promoted by the research teams of the company Facebook and released internally between the years 2019, 2020 and 2021. The documents were made available in 2021 by The Wall Street Journal. Thus, this paper describes i) the methodologies employed and the research findings; ii) what suggestions were made for improvement in the safety and wellbeing of individuals on Instagram.
Consumers are increasingly aware of issues related to food safety and fraud, as well as environmental and ecological impacts due to food production. Besides the quality of the products, there is currently also a growing concern about the origin of the products and the path they take to reach the final consumers. Consumers are demanding transparency across the entire value chain of the products they consume. That’s why it’s necessary to design and develop traceability platforms for these products. The platform must be able to collect information at all stages of the supply chain and store it in a system external and shared by all operators in the value chain. This information must be available to all participants in the supply chain, including farmers, health authorities, government industries, sellers, retailer, final consumers, and any other actor involved in the value chain. This article describes the planning and implementation of a platform that allows to trace back and forth fruits and vegetables. This platform would be decentralized by using a blockchain-based approach. The proposed platform would provide an easy way to visualize information about products to any participant in this supply chain.
Virtual Learning Environments began to be adopted more frequently due to the demands generated by the pandemic and the need for new teaching and assessment methodologies, especially in Higher Education. Many evaluative practices today are directly associated with Online Teaching, and it is necessary to point out elements that indicate the appropriate choice of the Assessment Instrument in Online Teaching. The research aims to propose a distributed system that helps in the adequate indication of the choice of the Assessment Instrument that will be applied, based on the student’s Learning Style. To do so, we will use a Multiagent System that reasons and proposes the indication of the Assessment Instrument being closer to the student's Learning Style so that the best use of the results obtained in the assessment is obtained, contributing with metric indicators that represent the understanding of the skills and skills achieved. Thus, our study, still under development, is a Systematic Literature Review and seeks to survey the state of the art of research related to Online Assessment.
