Abstract
Unmanned aerial vehicles (UAVs) have become popular in recent years and are now used in a wide variety of applications. This is the logical result of certain technological developments that occurred over the last two decades, allowing UAVs to be equipped with different types of sensors that can provide high-resolution data at relatively low prices. However, despite the success and extraordinary results achieved by the use of UAVs, traditional remote sensing platforms such as satellites continue to develop as well. Nowadays, satellites use sophisticated sensors providing data with increasingly improving spatial, temporal and radiometric resolutions. This is the case for the Sentinel-2 observation mission from the Copernicus Programme, which systematically acquires optical imagery at high spatial resolutions, with a revisiting period of five days. It therefore makes sense to think that, in some applications, satellite data may be used instead of UAV data, with all the associated benefits (extended coverage without the need to visit the area). In this study, Sentinel-2 time series data performances were evaluated in comparison with high-resolution UAV-based data, in an area affected by a fire, in 2017. Given the 10-m resolution of Sentinel-2 images, different spatial resolutions of the UAV-based data (0.25, 5 and 10 m) were used and compared to determine their similarities. The achieved results demonstrate the effectiveness of satellite data for post-fire monitoring, even at a local scale, as more cost-effective than UAV data. The Sentinel-2 results present a similar behavior to the UAV-based data for assessing burned areas.

Abstract
To study how emotions affect people in expressive writing, scientists require tools to aid them in their research. The researchers at M-BW use an Experiment Management System, called HandSpy to store and analyze the hand-written productions of participants. The input is stored as digital ink and then displayed on a web-based interface. To assist the project, HandSpy integrates with new sources of information to help researchers visualize the link between psychophysiological data and written input. The newly acquired data is synchronized with the existing burst-pause interval model and represented on the user interface of the platform together with the already existing information.

Abstract
The choice of password composition policy to enforce on a password-protected system represents a critical security decision, and has been shown to significantly affect the vulnerability of user-chosen passwords to guessing attacks. In practice, however, this choice is not usually rigorous or justifiable, with a tendency for system administrators to choose password composition policies based on intuition alone. In this work, we propose a novel methodology that draws on password probability distributions constructed from large sets of real-world password data which have been filtered according to various password composition policies. Password probabilities are then redistributed to simulate different user password reselection behaviours in order to automatically determine the password composition policy that will induce the distribution of user-chosen passwords with the greatest uniformity, a metric which we show to be a useful proxy to measure overall resistance to password guessing attacks. Further, we show that by fitting power-law equations to the password probability distributions we generate, we can justify our choice of password composition policy without any direct access to user password data. Finally, we present Skeptic - -a software toolkit that implements this methodology, including a DSL to enable system administrators with no background in password security to compare and rank password composition policies without resorting to expensive and time-consuming user studies. Drawing on 205,176,321 passwords across 3 datasets, we lend validity to our approach by demonstrating that the results we obtain align closely with findings from a previous empirical study into password composition policy effectiveness. © 2020 ACM.

Abstract
Nowadays the use of container technologies is ubiquitous and thus the need to make them secure arises. Container technologies such as Docker provide several options to better improve container security, one of those is the use of a Seccomp profile. A major problem with these profiles is that they are hard to maintain because of two different factors: they need to be updated quite often and present a complex and time consuming task to determine exactly what to update, therefore not many people use them. The research goal of this paper is to make Seccomp profiles a viable technique in a production environment by proposing a reliable method to generate custom Seccomp profiles for arbitrary containerized application. This research focused on developing a solution with few requirements allowing for an easy integration with any environment with no human intervention. Results show that using a custom Seccomp profile can mitigate several attacks and even some zero day vulnerabilities on containerized applications. This represents a big step forward on using Seccomp in a production environment, which would benefit users worldwide.

Abstract
This paper presents an action research study aiming to motivate undergraduate students to develop their computer programming learning skills, particularly within the transition from beginner to proficient level. The SimProgramming motivational approach is presented as a didactic proposal for this context. From the results of this iterative research process, we concluded that SimProgramming is a promising tool for teaching computer programming skills in intermediate classes, with potential to be used and/or applied in other educational contexts. © 2021, Springer Nature Switzerland AG.

Abstract
Augmented Reality (AR) is a field of knowledge that emerged in the middle of the last century, and its use has been spreading because of its usefulness, but also because of mobile platforms, accessible to most users. AR characteristics are valued in several fields of human activity, and also in the field of Education and Training, being AR pointed out as useful to the learning process. In this paper we search and analyse surveys and reviews of AR. We present a AR’s definition, and we create a classification scheme of two dimensions for AR: the dimension of the fields of application of AR, and the dimension of the technologies of AR. © 2021, Springer Nature Switzerland AG.