Abstract
Some industries have critical areas (dangerous or hazardous) where the presence of a human must be reduced or avoided. In some cases, there are areas where humans should be replaced by robots. The present work uses a robot with differential drive to scan an environment with known and unknown obstacles, defined in 3D simulation. It is important that the robot be able to make the right decisions about its way without the need of an operator. A solution to this challenge will be presented in this paper. The control application and its communication module with a simulator or a real robot are proposed. The robot can perform the scan, passing through all the waypoints arranged in a grid. The results are presented, showcasing the robot’s capacity to perform a viable trajectory without human intervention. © Springer International Publishing AG 2018.

Abstract
In smart grid, demand response (DR) programs can be deployed to encourage electricity consumers towards scheduling their controllable demands to off-peak periods. Motivating the consumers to participate in a DR program is a challenging task, as they experience a confidential discomfort cost by modifying their load demand from the desirable pattern to the scheduled pattern. Meanwhile, to balance the load and generation, the independent system operator (ISO) requires to motivate the suppliers towards modifying their generation profiles to follow the changes in the load demands. Additionally, to protect the entities' privacy, the ISO needs to apply an effective well-designed pricing scheme. In this paper, we focus on proposing a decentralized DR framework considering the operating constraints of the grid. In our proposed framework, each individual entity responds to the control signals called conjectured prices from the ISO to modify its demand or generation profile with the locally-available information. We formulate the centralized problem of the ISO that jointly minimizes the suppliers' generation cost and the consumers' discomfort cost. We also discuss how the ISO determines the conjectured prices to motivate the entities toward an operating point that coincides with the solution to the centralized problem. The performance of the proposed algorithm is evaluated on a modified IEEE 14-bus in reducing the suppliers' and consumers' cost, as well as the transmission lines congestion.

Abstract
Nowadays, web applications play an important role in our society and in the business world. Many companies earn a large part of their revenues through web applications that provide support services that must be maintained and improved over time. Most of these services operate on a large scale and are in constant change due to the environment in which they operate and due to the rapid technological evolution as we strive to improve our everyday lives. Due to this constantly changing environment, it is difficult to estimate the impact of changes; to maintain the software requirements documents updated; and to build and maintain a test suit for regression testing. Regression tests must be updated continually in order to test the current behavior after requested changes are implemented. REQAnalytics is a tool that aims to solve these problems. This paper presents REQAnalytics and an extension to generate test cases from the usage of a SaaS platform in order to diminish the effort in building and maintaining regression tests that are useful to check if the SaaS platform remains working as expected.

Abstract
Transport systems and buildings are among the bigger energy users inside cities. Abundant research has been developed about these systems (facilities and transport). However, synergies among them are commonly overlooked, not taking advantage of the possible benefits of their joint coordination and management. This paper presents a linear programming model to find the optimal operation and planning of distributed energy resources (DER) in a residential district, while considering electric private and public transport systems, in particular electric vehicles and metro. Hence, the main contribution of this paper is the analysis of synergies of such an interconnected scheme. It has been assumed that part of the metro regenerative braking energy can be stored into electric vehicles' (EVs') batteries, so that it can be used later for other trains or for the EV itself. Several case studies have been proposed using data from a residential district and a metro line in Madrid. The obtained results show important cost savings in the overall system, especially a significant power cost reduction for the metro system.

Abstract
In the context of SaaS (Software as a Service) where software has to be up and running 7 days a week and 24 h a day, keeping the requirements specification up to date can be difficult. Managing requirements in this context have additional challenges that need to be taken into account, for instance, re-prioritize requirements continuously and identify/update new dependencies among them. We claim that extracting and analyzing the usage of the SaaS can help to maintain requirements updated and contribute to improve the overall quality of the services provided. This paper presents REQAnalytics, a recommendation system that collects the information about the usage of a SaaS, analyses it and generates recommendations more readable than reports generated by web analytic tools. The overall approach has been applied on several case studies with promising results. © Springer International Publishing AG, part of Springer Nature 2018.

Abstract
Systems are error-prone. Big systems have lots of errors. The Internet-of-Things poses us one of the biggest and widespread systems, where errors directly impact people's lives. Testing and validating is how one deals with errors; but testing and validating a planetary-scale, heterogeneous, and ever-growing ecosystem has its own challenges and idiosyncrasies. As of today, the solutions available for testing these systems are insufficient and fragmentary. In this paper we provide an overview on test approaches, tools and methodologies for the Internet-of-Things, its software and its devices. Our conclusion is that we are still lagging behind on the best practices and lessons learned from the Software Engineering community in the past decades.