Abstract
Demand response is known as one of the basic components of smart grids that plays an important role in shaping load curves. In most of the prior reports on applying demand response programs, reactive power and load dependency to voltage magnitude have been ignored in distribution grids. In this paper, firstly, we show that the ignorance of the mentioned phenomena can cause a mismatch between the expected value of demand response and the experimental value. This mismatch is known as the demand response mismatch (DRM), which is dependent on some parameters such as load type, load reduction percentage, and network power factor. To overcome this problem, this paper presents a reactive power control model. In addition, a mixed integer nonlinear program is proposed to find the optimal size and location of STATCOMs and the optimal transformer tap settings that minimize the DRM. In this paper, the 16-bus U.K. generic distribution system (UKGDS) is employed to prove the capability of the presented method in DRM reduction.

Abstract
Taking the case of the University of Aveiro, we herein analyse why students choose to abandon their higher education degrees. To date, and as a result of focus group and brainstorming interactions, as well as of an analysis performed at the highest levels in the university, the following twelve causes for abandonment were identified: 1. Difficulty in adapting to the first year at university; 2. Financial difficulty and not being granted, as requested, a student scholarship; 3. Not being able to finish a satisfactory number of subjects, in the first year at university; 4. Missing a lot of lectures, which makes passing more difficult; 5. Being somewhat immature and subsequently not adapting to the challenges, often a long way from home; 6. Entering the university in a later recruitment stage, later than everyone else, and thus experiencing added difficulty in accompanying the syllabus; 7. Not being in a degree which was the first study choice, as the student's marks were not good enough, leading to low motivation levels; 8. Being one of the lower-end students in class, and thus having difficulty in keeping up; 9. Being a part-time student, while maintaining a full-time working job, which makes passing subjects harder; 10. Doing an internship, and subsequently being offered a job, which the student accepts, due to current financial priorities, leading to premature abandonment of university; 11. Having difficulty in passing one subject in particular (e.g. Calculus or Statistics), leading to the student abandoning higher education altogether; 12. Thinking that higher education is too theoretical, and therefore not worthwhile, and preferring to go right into the job market, to gain work experience. We also performed three interviews with students from various Higher Education Institutions (HEI), who dropped out of higher education, the data collected having confirmed what was stated above. Being aware of these issues and taking action (from a relationship marketing and services perspective) at the highest levels in a HEI is a good path towards success, as is occurring at the University of Aveiro. However, it will ultimately be up to the students, in the end, to decide whether studying is worthwhile thus keeping dropout to a minimum.

Abstract
This chapter presents the process of developing a Metadata Application Profile for the Social and Solidarity Economy (DCAP-SSE) using Me4MAP, a method for developing Application Profiles that was being put forth by the authors. The DCAPSSE and Me4MAP were developed iteratively, feeding new developments into each other. This paper presents how the DCAP-SSE was developed showing the steps followed through the development of the activities and the techniques used, and the final deliverables obtained at the end of each activity. It also presents the work-team and how each profile of the team contributed for the DCAP-SSE development process. The DCAP-SSE has been endorsed by the SSE community and new perspectives of SSE activities have been defined for future enlargement of the DCAP-SSE. At the time of writing this chapter, Linked Open SSE Data is being published, they are the first examples of use of the DCAP-SSE. © 2017, IGI Global.

Abstract
Inventory management can be considered as one of the main components of planning and production control. In the literature numerous mathematical models are presented for inventory management, which approach different aspects related to this management. The development of efficient inventory models and the adoption of appropriate optimization methods for solving these models are needed to support in making decisions to inventory management. In this paper, we propose an inventory model that works with multiple products and multiple resource constraints, deciding between the continuous review and periodic review systems. This model is formulated as a nonlinear mixed integer optimization problem. It explores for the resolution of this model, an approach based on Branch-And-Bound method and interior point method. In order to propose this model and choose the method for its resolution, initially an investigation in the literature review on the topic is done. Then, the concept of continuous review and periodic review systems is explored. Finally, two computational tests are proposed, one to compare the results of proposed nonlinear model with the linear model and the other to verify its efficiency and applicability. The results show the potential of the model and solution method used to work with inventory system.

Abstract
A long-period grating (LPG) written on a standard single mode fiber is investigated as a fiber optic sensor for vibration and magnetic field sensing. It is demonstrated the high sensitivity of the device to applied curvature and the possibility to monitor vibration in a wide range of frequencies from 30 Hz to 2000 Hz. The system was tested using intensity-based interrogation scheme, providing a frequency discrimination of 913 mHz. The goal of these tests was to evaluate the sensor as a passive vibration monitor in the detection of changes in resonant vibration frequencies of support infrastructures can provide information on its degradation. Furthermore, taking advantage of the intrinsic sensitivity to micro strain, alternating magnetic fields were also measured using an intensity-based interrogation scheme by coupling a Terfenol-D magnetostrictive rod to a pre-strained LPG sensor, providing a resolution below 5.61 mu T-rms/root Hz from 1.22 mT(rms) up to 2.53 mT(rms).

Abstract
In the dynamic scenarios faced nowadays, when handling non stationary data streams it is of utmost importance to perform change detection tests. In this work, we propose the Intrinsic Page Hinkley Test (iPHT), which enhances the Page Hinkley Test (PHT) eliminating the user-defined parameter (the allowed magnitude of change of the data that are not considered real distribution change of the data stream) by using the second order intrinsic mode function (IMF) which is a data dependent value reflecting the intrinsic data variation. In such way, the PHT change detection method is expected to be more robust and require less tunes. Furthermore, we extend the proposed iPHT to a blockwise approach. Computing the IMF over sliding windows, which is shown to be more responsive to changes and suitable for online settings. The iPHT is evaluated using artificial and real data, outperforming the PHT. © Springer International Publishing AG 2017.