Abstract
MicroGrids represent a new paradigm for the operation of distribution systems and there are several advantages as well as challenges regarding their development. One of the advantages is related with the participation of MicroGrid agents in electricity markets and in the provision of ancillary services. This paper describes two optimization models to allocate three ancillary services among MicroGrid agents - reactive power/voltage control, active loss balancing and demand interruption. These models assume that MicroGrid agents participate in the day-ahead market sending their bids to the MicroGrid Central Controller, MGCC, that acts as an interface with the Market Operator. Once the Market Operator returns the economic dispatch of the MicroGrid agents, the MGCC checks its technical feasibility (namely voltage magnitude and branch flow limits) and activates an adjustment market to change the initial schedule and to allocate these three ancillary services. One of the models has crisp nature considering that voltage and branch flow limits are rigid while the second one admits that voltage and branch flow limits are modeled in a soft way using Fuzzy Set concepts. Finally, the paper illustrates the application of these models with a Case Study using a 55 node MV/LV network.

Abstract
The automatic detection and segmentation of the pectoral muscle in the medio-lateral oblique view of mammograms is essential for further analysis of breast anormalies. However, it is still a very difficult task since the sizes, shapes and intensity contrasts of pectoral muscles change greatly from image to image. In this paper, an algorithm based on the shortest path on a graph is proposed to automatically detect the pectoral muscle contour. To overcome the difficulties of searching for the path between a lateral and the top margins of the image, this is first transformed, using polar coordinates. In the transformed image, the muscle boundary in amongst the shortest paths between the top and the bottom rows. A comprehensive comparison with manually-drawn contours reveals the strength of the proposed method.

Abstract
It is shown how the design possibilities offered by double-layer uniform-waist tapered optical fibers (DLUWTs) permit to move the wavelength detection range to adapt the response of the sensors to varied conditions. In particular, we have obtained very good experimental curves showing that we can achieve plasmon resonances in the C-band of the optical communications, around 1.5 mu m, for the range of refractive indices of aqueous media, highly interesting in the biosensors field. Also, we show results for other interesting wavelength region, around 500 nm, where we can take advantage of the absorption peaks of the analytes. Finally, we explore the possibilities of using InN as a dielectric material for the second layer of the deposition. These results contribute to considerably expand the applicability and performance of SPR fiber sensors.

Abstract
The fitting of physical dynamical models to stimulus-response data such as the chemical concentration measured after a gas has been released to the environment, or the plasma concentration measured after an intravenous or oral input of a drug, are important problems in the area of system identification. Using models of different structures, one can obtain relevant statistical information on the parameters of the model from an array of software packages available in the literature. A meaningful interpretation of these parameters requires that in the presence of error-free data and an error-free model structure, a unique solution for the model parameters is guaranteed. This problem is known as a priori identifiability. Once the model is deemed identifiable, the parameters are then obtained, usually via a nonlinear least squares technique. In addition to identifiability, there is the problem of convergence of the parameters to the true values. It is a known fact that nonlinear parameter estimation algorithms do not always converge to the true parameter set. This is due to the fact that estimating the parameters of a nonlinear model can at times be an ill-conditioned problem. In this paper we use the same state space analysis techniques used to determine identifiability, to estimate the model parameters in a linear fashion. We approach the problem from a system identification point of view and then take advantage of the similarity transformation between the physical model and the identified model. We formulate the similarity relations and then transform them into a null space problem whose solution leads to the physical parameters. The novelty of our approach is in the use of a state space system identification algorithm to identify a black-box system, followed by a physical parameter extraction step using robust numerical tools such as the singular value decomposition.

Abstract
In this work we propose a new problem, that we have named hop-constrained minimum cost flow spanning tree problem, and develop an exact solution methodology. This problem is an extension of the well know NP-hard hop-constrained Minimum Spanning Tree problem (MST), since in addition to finding the arcs to be used we also must find the amount of flow that is to be routed through each arc. The hop-constrained MST has numerous practical applications in the design of communication networks. The hop constraints are usually used to guarantee a certain quality of service with respect to availability, reliability and lower delays, since they limit the number of arcs in each path from the central service provider. Including the flows, as we propose, allows for different levels of service requirements. A further extension is considered: the cost functions may have any type or form, may be neither convex nor concave, and need not to be differentiable or continuous. We develop a dynamic programming approach, which extends the scope of application of a previous work, to solve to optimality such problems. Computational experiments are performed using randomly generated test problems. Results showing the robustness of the method are reported.

Abstract
The e-Framework is arguably the most prominent e-learning framework currently in use. For this reason it was selected as basis for modelling a programming exercises evaluation service. The purpose of this type of evaluator is to mark and grade exercises in computer programming courses and in programming contests. By exposing its functions as services a programming exercise evaluator is able to participate in business processes integrating different system types, such as Programming Contest Management Systems, Learning Management Systems, Integrated Development Environments and Learning Object Repositories. This paper formalizes the approaches to be used in the implementation of a programming exercise evaluator as a service on the e-Framework.