Abstract
Programmers and support engineers typically rely on log data to narrow down the root cause of unexpected behaviors in dependable distributed systems. Unfortunately, the inherently distributed nature and complexity of such distributed executions often leads to multiple independent logs, scattered across different physical machines, with thousands or millions entries poorly correlated in terms of event causality. This renders log-based debugging a tedious, time-consuming, and potentially inconclusive task. We present Falcon, a tool aimed at making log-based analysis of distributed systems practical and effective. Falcon's modular architecture, designed as an extensible pipeline, allows it to seamlessly combine several distinct logging sources and generate a coherent space-time diagram of distributed executions. To preserve event causality, even in the presence of logs collected from independent unsynchronized machines, Falcon introduces a novel happens-before symbolic formulation and relies on an off-the-shelf constraint solver to obtain a coherent event schedule. Our case study with the popular distributed coordination service Apache Zookeeper shows that Falcon eases the log-based analysis of complex distributed protocols and is helpful in bridging the gap between protocol design and implementation.

Abstract
Replanning is often used to optimize results of an activity in an ever changing world. To address the challenge of preparing future engineers for success, a special course was created for all engineering freshmen of the Faculty of Engineering of the University of Porto, in Portugal. Presented as a case study, this special course underwent a careful replanning as a result of several years of experience in teaching practice alongside with a theoretical deepening in pedagogical and technological issues, under the aegis of the action-research methodology. Within the context of the case study course, the mentioned replanning was also based on a theoretical approach that clearly identifies teaching-learning-assessment methodologies that promote regulation from those that foster emancipation, using a specific instrument: a taxonomy of educational processes. The replanning was designed to globally boost results regarding the educational aims of the course such as furthering freshmen's integration into work environment and preparing them for success by fostering transversal skills (needed for study and work). Technology is seen as a mean of education enrichment as well as a productivity tool. The introduced innovations include fun-but-educational activities, several types of assessment over time and specific technological tools which were critical for the educational impact/achievement of this course. Success is demonstrated by encouraging feedback from the stakeholders, high students' classifications and a steady reduction in retention. It is advocated that large portions of the reasoning behind the replanning can be extrapolated to other courses.

Abstract
The IoT area has grown significantly in the last few years and is expected to reach a gigantic amount of 50 billion devices by 2020. The appearance of serverless architectures, specifically highlighting FaaS, raises the question of the suitability of using them in IoT environments. Combining IoT with a serverless architectural design can be effective when trying to make use of the local processing power that exists in a local network of IoT devices and creating a fog layer that leverages computational capabilities that are closer to the end-user. In this approach, which is placed between the device and the serverless function, when a device requests for the execution of a serverless function will decide based on previous metrics of execution if the serverless function should be executed locally, in the fog layer of a local network of IoT devices, or if it should be executed remotely, in one of the available cloud servers. Therefore, this approach allows dynamically allocating functions to the most suitable layer.

Abstract
In this paper we analyze the subsidence behavior of a coastal area in the province of Málaga (Costa del Sol), southern Spain, in the period 1992-2018 using C-band SAR interferometry. The area comprises several zones of interest where continuous deformation has happened during the analyzed period. Using SAR data from ESA's ERS-1/2, Envisat, and Sentinel-1A/B satellites, and Multi-Temporal InSAR methods we detect and monitor subsidence in highly populated and industrial areas, airport, harbor, as well as local instabilities over a railway line and a highway. In a previous work, we reported a subsidence due to intensive use of groundwater in some populated towns in the period 1992-2009 with maximum line-of-sight (LOS) rates of the order of -11 mm/yr. In this contribution, we confirm the subsidence trend. Furthermore, we detect an increase in the deformation rates for the most recent period (2014-2018), suggesting that the overexploitation of the aquifers has not ceased. © 2018 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license.

Abstract
This work presents a novel multimodal database comprising 3D face, 2D face, thermal face, visible iris, finger and hand veins, voice and anthropometrics. This dataset will constitute a valuable resource to the field with its number and variety of biometric traits. Acquired in the context of the EU PROTECT project, the dataset allows several combinations of biometric traits and envisages applications such as border control. Based upon the results of the unimodal data, a fusion scheme was applied to ascertain the recognition potential of combining these biometric traits in a multimodal approach. Due to the variability on the discriminative power of the traits, a leave the n-best out fusion technique was applied to obtain different recognition results. © 2018 Gesellschaft fuer Informatik.

Abstract