Abstract
In classification, when there is a disproportion in the number of observations in each class, the data is said to be class imbalance. Class imbalance is pervasive in real world applications of data classification and has been the focus of much research. The minority class contributes too little to the decision boundary because the learning process learns from each observation in isolation. In this paper, we discuss the application of learning pairwise rankers as a solution to class imbalance. We compare ranking models to alternatives from the literature.

Abstract
Object representation is one of the most challenging tasks in robotics because it must provide reliable information in real-time to enable the robot to physically interact with the objects in its environment. To ensure reliability, a global object descriptor must be computed based on a unique and repeatable object reference frame. Moreover, the descriptor should contain enough information enabling to recognize the same or similar objects seen from different perspectives. This paper presents a new object descriptor named Global Orthographic Object Descriptor (GOOD) designed to be robust, descriptive and efficient to compute and use. The performance of the proposed object descriptor is compared with the main state-of-the-art descriptors. Experimental results show that the overall classification performance obtained with GOOD is comparable to the best performances obtained with the state-ofthe-art descriptors. Concerning memory and computation time, GOOD clearly outperforms the other descriptors. Therefore, GOOD is especially suited for real-time applications.

Abstract
Transmission Expansion Planning (TEP) is an optimization problem that has a non-convex and combinatorial search space so that several solution algorithms may converge to local optima. Therefore, many works have been proposed to solve the TEP problem considering its relaxation or reducing its search space. In any case, relaxation and reduction approaches should not compromise the quality of the final solution. This paper aims at analyzing the performance of a search space technique using a Constructive Heuristic Algorithm (CHA) admitting that the TEP problem is then solved using a Discreet Evolutionary Particle Swarm Optimization (DEPSO). On one hand the reduction quality is performed by analyzing whether the optimal expansion routes are included in the CHA constrained set and, on the other hand, the relaxation quality of the DC model is analyzed by checking if the optimal solution obtained with it violates any constraint using the AC model. The simulations were performed using three different test systems. The results suggest that the proposed CHA provides very good results in reducing the TEP search space and that the adoption of the DC model originates several violations if the full AC model is used to model the operation of the power system.

Abstract
One of the main constraints for Renewable Energy Sources (RES) integration in LV networks are overvoltages caused by changing the normal power flow of the network. In favourable weather conditions high voltages may lead to overvoltage trips thus preventing the injection of renewable energy into the grid. An optimized management of power injection from controlled RES to keep the grid voltage within regulatory limits enables a larger energy output and deployment of distributed generation. The SuSTAINABLE project developed a centralized algorithm based on a hierarchical methodology to control distributed power injection and solve the identified issue. A decentralized algorithm based on a coordinated droop control embedded in the inverters was developed as well. In order to evaluate the proposed algorithms a controllable PV µG and batteries were installed at the end of the feeder of a real LV network operated by EDP Distribuicao. The obtained results are presented in this paper and show that a hierarchical methodology to control power injection could optimize RES energy production while maintaining voltages within bounds, thus enabling a larger deployment of RES at the LV levels.

Abstract
Solving nesting problems involves the waste minimisation in cutting processes, and therefore it is not only economically relevant for many industries but has also an important environmental impact, as the raw materials that are cut are usually a natural resource. However, very few exact approaches have been proposed in the literature for the nesting problem (also known as irregular packing problem), and the majority of the known approaches are heuristic algorithms, leading to suboptimal solutions. The few mathematical programming models known for this problem can be divided into discrete and continuous models, based on how the placement coordinates of the pieces to be cut are dealt with. In this paper, we propose an innovative semi-continuous mixed-integer programming model for two-dimensional cutting and packing problems with irregular shaped pieces. The model aims to exploit the advantages of the two previous classes of approaches and discretises the [GRAPHICS] -axis while keeping the [GRAPHICS] -coordinate continuous. The board can therefore be seen as a set of stripes. Computational results show that the model, when solved by a commercial solver, can deal with large problems and determine the optimal solution for smaller instances, but as it happens with discrete models, the optimal solution value depends on the discretisation step that is used.

Abstract
The IEC 61499 standard proposes an event driven execution model for component based (in terms of Function Blocks), distributed industrial automation applications. However, the standard provides only an informal execution semantics, thus in consequence behavior and correctness relies on the design decisions made by the tool vendor. In this paper we present the formalization of a subset of the IEC 61499 standard in order to provide an underpinning for the static verification of Function Block models by means of deductive reasoning. Specifically, we contribute by addressing verification at the component, algorithm, and ECC levels. From Function Block descriptions, enriched with formal contracts, we show that correctness of component compositions, as well as functional and transitional behavior can be ensured. Feasibility of the approach is demonstrated by manually encoding a set of representative use-cases in WhyML, for which the verification conditions are automatically derived (through the Why3 platform) and discharged (using automatic SMT-based solvers). Furthermore, we discuss opportunities and challenges towards deriving certified executables for IEC 61499 models. © 2016 IEEE.