Abstract
The introduction of plug-in electric vehicles (PEVs) in the electrical system is bringing various challenges. One of the recent solutions to deploy the potentials of PEVs in the system is through PEV parking lots (PL). The PLs not only provide a place for the PEVs charging requirements, but also give the possibility of exploiting the vehicle-to-gird (V2G) potential of PEVs in a more efficient manner comparing to PEV aggregators. On the other hand, the V2G mode gives the reserve market possibility to the PL operator, which can be a source of income other than selling energy to the PEV owners. However, the willingness of participating in the V2G mode may be low due to exposing battery degradation and not sufficient departure state of charge (SOC). As a result, this study investigates the behavior of PL on deploying the V2G mode of PEVs in reserve market participation considering the PEVs' traffic behavior.

Abstract
The research activities in a Higher Education Institution (HEI) is highly dependent of the development of research projects. Most times, these projects have, at the core of their workforce, scholarship fellows financed by the project budget and responsible for the execution of very specific research tasks. The procurement process, leading to the contracting of these fellows, evolves several internal bureaus, from several organic units of the HEI, in a complex and long process. This work reports on the development of system to support this process. The solution was integrated in the HEI ecosystem in a harmonious manner, by implementing the necessary features and using the other HEI systems features when possible. After a year, the scholarship management system has proved a success, providing the user features to conduct the process as well as the management analytics to proper support the governance of the research area.

Abstract
This research proposes new approaches to deal with the production planning and scheduling problem in brewery facilities. Two real situations found in factories are addressed, which differ by considering (or not) the setup operations in tanks that provide liquid for bottling lines. Depending on the technology involved in the production process, the number of tank swaps is relevant (Case A) or it can be neglected (Case B). For both scenarios, new MIP (Mixed Integer Programming) formulations and heuristic solution methods based on these formulations are proposed. In order to evaluate the approach for Case A, we compare the results of a previous study with the results obtained in this paper. For the solution methods and the result analysis of Case B, we propose adaptations of Case A approaches yielding an alternative MIP formulation to represent it. Therefore, the main contributions of this article are twofold: (i) to propose alternative MIP models and solution methods for the problem in Case A, providing better results than previously reported, and (ii) to propose new MIP models and solution methods for Case B, analyzing and comparing the results and benefits for Case B considering the technology investment required.

Abstract
The development of interferometric methodologies for deformation monitoring that are able to deal with long time series of synthetic aperture radar (SAR) images made the detection of seasonal effects possible by decomposing the differential SAR phase. In the case of monitoring of man-made structures, particularly bridges, the use of high-resolution X-band SAR data allows the determination of three major components with significant influence on the SAR phase: the linear deformation trend, the height of structures over terrain, and the thermal expansion. In the case of stable metallic or (reinforced) concrete structures, this last effect can reach a magnitude comparable to or even exceeding the other phase components. In this review, we present two case studies that confirm the feasibility of InSAR techniques for bridge deformation monitoring and our original approach to refine the thermal expansion component.

Abstract
Searching for health information is one of the most popular activities on the web. In this domain, users often misspell or lack knowledge of the proper medical terms to use in queries. To overcome these difficulties and attempt to retrieve higher-quality content, we developed a query suggestion system that provides alternative queries combining the Portuguese or English language with lay or medico-scientific terminology. Here we evaluate this system's impact on the medical accuracy of the knowledge acquired during the search. Evaluation shows that simply providing these suggestions contributes to reduce the quantity of incorrect content. This indicates that even when suggestions are not clicked, they are useful either for subsequent queries' formulation or for interpreting search results. Clicking on suggestions, regardless of type, leads to answers with more correct content. An analysis by type of suggestion and user characteristics showed that the benefits of certain languages and terminologies are more perceptible in users with certain levels of English proficiency and health literacy. This suggests a personalization of this suggestion system toward these characteristics. Overall, the effect of language is more preponderant than the effect of terminology. Clicks on English suggestions are clearly preferable to clicks on Portuguese ones.

Abstract
Given the large volumes and dynamics of data that recommender systems currently have to deal with, we look at online stream based approaches that are able to cope with high throughput observations. In this paper we describe work on incremental neighborhood based and incremental matrix factorization approaches for binary ratings, starting with a general introduction, looking at various approaches and describing existing enhancements. We refer to recent work on forgetting techniques and multidimensional recommendation. We will also focus on adequate procedures for the evaluation of online recommender algorithms.