Abstract
In order to detect network motifs we need to evaluate the exceptionality of subgraphs in a given network. This is usually done by comparing subgraph frequencies on both the original and an ensemble of random networks keeping certain structural properties. The classical null model implies preserving the degree sequence. In this paper our focus is on a richer model that approximately fixes the frequency of subgraphs of size K - 1 to compute motifs of size K. We propose a method for generating random graphs under this model, and we provide algorithms for its efficient computation. We show empirical results of our proposed methodology on neurobiological networks, showcasing its efficiency and its differences when comparing to the traditional null model.

Abstract
This paper proposes a comprehensive model for the interactions of the plug-in electric vehicles (PEVs) involved parties. An aggregator with mixed resources is assumed to be the interface between the parking lot (PL) and the upstream energy and reserve markets. On the other hand, the interactions of the PEV owners and the PL are also modeled as they impose restrictions to the PL's behavior. Therefore, a bilevel problem is constructed where in the upper level the objective of the aggregator is to maximize its profit through its interactions, and in the lower level the PL maximizes its own profit limited to the preferences of PEVs. The objectives of the upper and lower levels are contradictory; hence, an equilibrium point should be found to solve the problem. In this regard, the duality theorem is employed to convert the bilevel model to a mathematical program with equilibrium constraints. The model is implemented on the IEEE 37-bus network with added distributed generations. Various cases are thoroughly investigated and conclusions are duly drawn.

Abstract
The visual impaired are a specific minority group that can benefit from specific assistive systems in order to mitigate their mobility and accessibility constrains. In the last decade, our research group has been integrating and developing assistive technologies, focused in human-computer interaction, artificial vision, assisted navigation, pervasive computing, among others. Several projects and prototypes have been developed with the main objective of improving the blind's autonomy, mobility, and quality of life. Currently the technology has reached a maturation point that allows the development of systems based on video capturing, image recognition and location referencing, which are key for providing features of artificial vision, assisted navigation and spatial perception. The miniaturization of electronics can be used to create devices such as electronic canes that equipped with sensors can provide so much more contextual information to a blind user. The adoption of these systems is dependent of an information catalogue regarding points of interest and their physical location reference. In this paper we describe the current work on assistive systems for the blind and propose a new perspective on using the base information of those systems to provide new services to the general public. By bridging the gap between the two groups, we expect to further advance the development of the current systems and contribute to their economic sustainability.

Abstract
Formal methods technologies have the potential to verify the usability and safety of user interface (UI) software design in medical devices, enabling significant reductions in use errors and consequential safety incidents with such devices. This however depends on comprehensive and verifiable safety requirements to leverage these techniques for detecting and preventing flaws in UI software that can induce use errors. This paper presents a hazard analysis method that extends Leveson’s System Theoretic Process Analysis (STPA) with a comprehensive set of causal factor categories, so as to provide developers with clear guidelines for systematic identification of use-related hazards associated with medical devices, their causes embedded in UI software design, and safety requirements for mitigating such hazards. The method is evaluated with a case study on the Gantry-2 radiation therapy system, which demonstrates that (1) as compared to standard STPA, our method allowed us to identify more UI software design issues likely to cause use-related hazards; and (2) the identified UI software design issues facilitated the definition of precise, verifiable safety requirements for UI software, which could be readily formalized in verification tools such as Prototype Verification System (PVS).

Abstract

Abstract
Magnetic Resonance Imaging (MRI) exams suffer from undesirable structure replicating and overlapping effects on certain acquisition settings. These are called Spatial Aliasing Artefacts (SAA) and their presence interferes with the segmentation of other anatomical structures. This paper addresses the segmentation of the SAA in T1-weighted MRI image sets, in order to effectively remove their influence over the legitimately positioned body structures. The proposed method comprises an initial thresholding, employing the Triangle method, an aggregation of neighboring voxels through Region Growing. Further refinement of the objects contour is obtained with Convex Hull and a Minimum Path algorithm applied to two orthogonal planes (Sagittal and Axial). Some experiments concerning the extension of the pipeline used are reported and the results seem promising. The average contour distance concerning the Ground Truth (GT) rounds 2.5mm and area metrics point out average overlaps above 64% with the GT. Some issues concerning the fusion between the output from the two planes are to be perfected. Nevertheless, the results seems sufficient to neutralize the influence of SAA and expedite the downstream anatomical segmentation tasks.