Abstract
The lack of mechanisms made to check reliability of information on social networks is evidenced by the spread of misinformation and rumors in this kind of system. Given this scenario, the provision of tools to assist users with information auditability on social networks needs an emergencial approach. This article describes a catalog, followed by a guide of features that provide auditability on social networks. The guide contains guidelines for development of funcionalities in order to promote the adoption of auditability and enable users to identify false information and validate content on social networks. © 2016 for this paper by its authors.

Abstract
Digital accessibility is recognized as a fundamental tool for an egalitarian society. Nevertheless, software accessibility is an under addressed topic in the discipline of software engineering and the academy in general. As a result, its development and implementation is compromised. This problem is depicted here with the help of some experiments that shows the poor attention which is dedicated to this topic. Some hypotheses that try to explain this problem are formulated, and some possible solutions are debated. As a conclusion, some insights are given and a new possible researched avenue is presented.

Abstract
Conflict-free Replicated Data Types (CRDTs) can simplify the design of deterministic eventual consistency. Considering the several CRDTs that have been deployed in production systems, counters are among the first. Counters are apparently simple, with a straightforward inc/dec/read API, but can require complex implementations and several variants have been specified and coded. Unlike sets and registers, that can be adapted to operate inside maps, current counter approaches exhibit anomalies when embedded in maps. Here, we illustrate the anomaly and propose a solution, based on a new counter model and implementation.

Abstract

Abstract
Smartphones are everywhere, and they are a very attractive platform to perform unobtrusive monitoring of users. In this work, we use common features of modern smartphones to build a human activity recognition (HAR) system for elderly care. We have built a classifier that detects the transport mode of the user including whether an individual is inactive, walking, in bus, in car, in train or in metro. We evaluated our approach using over 24 hours of transportation data from a group of 15 individuals. Our tests show that our classifier can detect the transportation mode with over 90% accuracy.

Abstract
People in modern societies have increasingly sedentary lifestyles. They usually do not have time to take part in physical activity on a regular basis. Additionally, due to time constraints, people are consuming more processed and junk foods. This behavior may lead to health issues, such as obesity or cardiovascular disease. On the other hand people are becoming more aware and more interested in doing physical activities, which has resulted in an increase of memberships at gymnasiums. People usually obtain better results in training by having a personal trainer, especially in the beginning, because personal trainers can recommend safer and more effective exercises, as well as provide motivation. Moreover, personal trainers can also play the roles of life coaches or nutritionists. Despite the benefits, having a personal trainer can be difficult. Due to time constraints, it might not be simple to combine both schedules of the personal trainer and the client. In this paper we present a novel health training platform to maximize the personal trainer and client relationship and, therefore, increase the client's well-being. The health training platform allows clients to have sensors connected to their smartphones and send their exercise data to their personal trainer. It also allows personal trainers to observe their clients' evolution and provide feedback. The health training platform has an architecture that allows multiple configurations involving personal trainers, clients and gymnasiums. We have built and tested a prototype of a health training platform.