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This paper presents a method to localize a robot in a global coordinate frame based on a sparse 2D map containing outlines of building and road network information and no location prior information. Its input is a single 3D laser scan of the surroundings of the robot. The approach extends the generic chamfer matching template matching technique from image processing by including visibility analysis in the cost function. Thus, the observed building planes are matched to the expected view of the corresponding map section instead of to the entire map, which makes a more accurate matching possible. Since this formulation operates on generic edge maps from visual sensors, the matching formulation can be expected to generalize to other input data, e.g., from monocular or stereo cameras. The method is evaluated on two large datasets collected in different real-world urban settings and compared to a baseline method from literature and to the standard chamfer matching approach, where it shows considerable performance benefits, as well as the feasibility of global localization based on sparse building outline data.

Powers are properties defined by what they do. The focus of the large majority of the powers literature has been mainly put on explicating the (multifaceted) results of the production of a power in certain (multifaceted) initial conditions: but all this causal complexity is bound to be—and, in fact, it has proved to be—quite difficult to handle. In this paper we take a different approach by focusing on the very activity of producing those multifaceted manifestations themselves. In this paper, we propose an original account of what the essence of a power consists in which stems from a radical reconceptualisation of power-causation according to which counterfactuals are to be explained away by powers, and not vice-versa. We call this approach the dynamical operator account of powers. According to this account, the causal role of powers consists in their ensuring that the ontological transition from a stimulus S to a manifestation M happens. Powers thus have a dynamical essence which consists in the fundamental activity of generating the counterfactuals typically associated with them. We show that if one conceptualises this functional activity as the metaphysical fulcrum around which counterfactual-based causation revolves, one is granted not only an improved methodology to individuate powers but also a better understanding of their knowability, modality and directedness.

Within the Topical Collection, this paper represents an introductory contribution aimed at describing and discussing the research questions and the sampling criteria in the field of mortars, plasters and pigments studies. The paper is divided into three parts. In the first part, some terminological issues are clarified and the building archaeology is introduced as an indispensable method for sampling and interpreting archaeometric results. In the second part, the most common research questions are presented and discussed. Some case studies are also reported to clarify what the expected results may be. The sampling problem is faced in the third part, where the criteria for a representative, functional and suitable selection are provided.

In the development of computer-based systems, modelling is often advocated in addition to programming, in that it helps in reflecting the application domain and that it makes the design and experiment activities of development more efficient. However, there is disagreement about what models are and how they can be used in software systems development. In this paper, we present the Scandinavian approach to modelling, which makes a clear distinction between models and model descriptions. This paper explains the connections between models, descriptions, systems, and executions. Combining the Scandinavian approach with the Kiel notion of model, we establish that both descriptions and executions are closely connected instruments with different roles. The paper argues that (program) executions are the models of dynamic systems, not their descriptions in terms of diagrams and text. So in a general sense programming is about writing descriptions for systems. In particular the paper clarifies when programming is also modelling.

[Abstract] Residential location choice (RLC) predicts where and how people choose their residential location in the framework of land use–transport interaction models (LUTI). This paper seeks an efficient RLC model in the context of irregular zoning of location alternatives. The main current proposals in the field are discrete choice models. In RLC modeling, the alternatives are spatial units, and spatially correlated logit (SCL) is an efficient approach when the analyst cannot pre-define groups of alternatives that efficiently reflect the systematic substitution patterns among the alternatives. The SCL uses the spatial information on the contiguity of the zones to determine spatial correlation among the alternatives. Urban residential location choice usually uses administrative zoning, which is very irregular in many cities (mainly historic cities); however, SCL is not efficient in this context owing to the limitations of the binary contiguity spatial variable employed as a spatial correlation metric (SCM). This paper proposes an extension of the mixed SCL model, with an SCM based on the proportion of common border length in contiguous zones, which is more efficient in the irregular urban zoning context. The proposed model is applied to an urban case study of LUTI RLC modeling with irregular zoning, based on the administrative divisions of the city of Santander (Spain) and is shown to be empirically more efficient than the previous approaches. The authors acknowledge the financial support provided by the Government of Spain under the projects TRA2012-37659 and RTI2018-097924-B-I00 MCIU/AEI/FEDER, UE

In 1950, Nash’s seminal paper introduced the axiomatic approach to the analysis of bargaining situations. Since then, many bargaining solutions have been proposed and axiomatically analyzed. The fact that agents, when face with a bargaining problem, can come up with different solution concepts (that is, different notions of fairness and equity) was first introduced by van Damme (J Econ Theory 38:78–100, 1986) with the meta-bargaining model. In this paper we present and axiomatically analyze a procedure for solving meta-bargaining problems, which we call Unanimous–Concession. As an example, we show that the Nash solution is the result of the meta-bargaining process we define, when agents have dual egalitarian criteria. Finally, we compare, from an axiomatic point of view, our proposal with other meta-bargaining procedures. Financial support from Spanish Ministry of Economy and Competitiveness under Project ECO2016-77200-P is gratefully acknowledged.

Historically, cities and their citizens have led the largest changes that have been taking place continuously, especially since the transition from an agricultural economy to an industrial one. This phenomenon is especially significant from the mid-eighteenth century and it will become more intense if the predictions that establish that, around the year 2050, approximately 70% of the world population will concentrate in some type of city finally come true. With these boundary conditions, it is evident that the achievement of more efficient and sustainable cities is an unavoidable objective for which politicians, managers and technicians must work in order to guarantee the quality of life of their citizens. Although this paradigm of sustainability and efficiency has always been present in the managers of cities, it has not been until very recently that technology has made available to the responsible parties a plethora of possibilities that, when properly employed, translate into significant savings. At the same time, the day-to-day improvement of the citizens is consolidating a new urban concept in which the different processes and systems that occur in it are continuously monitored in both time and space. This paper reviews the evolution of one of the pioneering examples of such cities, Santander, where an Internet of the Things infrastructure was deployed a decade ago. In this time, multiple technologies and services have been developed and deployed in smart city pilots. The paper discusses the key lessons learnt from the digitalization of the city and the new challenges that have arisen as we were paving the way for a smarter and more liveable city. This work has been funded by the Spanish Government (MINECO) under Grant Agreement No. RTI2018-093475-A-I00 FIERCE (Future Internet Enabled Resilient smart CitiEs) project.

The paper departs from the general problem of knowledge integration and the basic strategies that can be adopted to confront this challenge. With the purpose of providing a sound meta-theoretical framework to facilitate knowledge conceptualization and integration, as well as assessment criteria to evaluate achievements regarding knowledge integration, the paper first reviews the previous work in the field of conceptual spaces. It subsequently gives an overview of structural tools and mechanisms for knowledge representation, recapped in the modal stratified bond model of global knowledge. On these groundings, a novel formalized representation of conceptual systems, structures, spaces and algebras is developed through a set of definitions which goes beyond the exploration of mental knowledge representation and the semantics of natural languages. These two components provide a sound framework for the development of the glossaLAB international project with respect to its two basic objectives, namely (i) facilitating knowledge integration in general and particularly in the context of the general study of information and systems; (ii) facilitating the assessment of the achievements as regards knowledge integration in interdisciplinary settings. An additional article tackles the solutions adopted to integrate these results in the elucidation of the conceptual network of the general study of information and systems. 2019-20

The paper describes the glossaLAB international project as a contribution to confront the urgent need of knowledge integration frameworks, as required to face global challenges that overwhelm disciplinary knowledge capacity. Under this scope, glossaLAB is devised to make contributions in three main aspects of such endeavor: (i) development of a sound theoretical framework for the unification of knowledge, (ii) establishment of broadly accepted methodologies and tools to facilitate the integration of knowledge, (iii) development of assessment criteria for the qualification of interdisciplinarity undertakings. The paper discusses the main components of the project and the solutions adopted to achieve the intended objectives at three different levels: at the technical level, glossaLAB aims at developing a platform for knowledge integration based on the elucidation of concepts, metaphors, theories and problems, including a semantically- operative recompilation of valuable scattered encyclopedic contents devoted to two entangled transdisciplinary fields: the sciences of systems and information. At the theoretical level, the goal is reducing the redundancy of the conceptual system (defined in terms of “intensional performance” of the contents recompiled), and the elucidation of new concepts. Finally, at the meta-theoretical level, the project aims at assessing the knowledge integration achieved through the co-creation process based on (a) the diversity of the disciplines involved and (b) the integration properties of the conceptual network stablished through the elucidation process. 2019-20

Although reuse is generally considered a good practice within software engineering, several problems dissuade its industrial application and a new viewpoint is needed. This paper presents a new perspective of reuse based on improved retrieval techniques for semantic content (knowledge). This approach, called Universal Knowledge Reuse Methodology (UKRM), drops the investment costs needed in systematic reuse, including the cost of traceability in the process, and reduces the chaos of ad-hoc reuse. UKRM makes reuse independent of the type of content, the context where it will be reused, and even the user that demands it. The paper includes an incremental experiment in order to validate the feasibility of this proposal.

Computational methods for protein structure prediction allow us to determine a three-dimensional structure of a protein based on its pure amino acid sequence. These methods are a very important alternative to costly and slow experimental methods, like X-ray crystallography or Nuclear Magnetic Resonance. However, conventional calculations of protein structure are time-consuming and require ample computational resources, especially when carried out with the use of ab initio methods that rely on physical forces and interactions between atoms in a protein. Fortunately, at the present stage of the development of computer science, such huge computational resources are available from public cloud providers on a pay-as-you-go basis. We have designed and developed a scalable and extensible system, called Cloud4PSP, which enables predictions of 3D protein structures in the Microsoft Azure commercial cloud. The system makes use of the Warecki-Znamirowski method as a sample procedure for protein structure prediction, and this prediction method was used to test the scalability of the system. The results of the efficiency tests performed proved good acceleration of predictions when scaling the system vertically and horizontally. In the paper, we show the system architecture that allowed us to achieve such good results, the Cloud4PSP processing model, and the results of the scalability tests. At the end of the paper, we try to answer which of the scaling techniques, scaling out or scaling up, is better for solving such computational problems with the use of Cloud computing.

This paper proposes the use of a randomized kinodynamic planning technique to synthesize dynamic motions for cable-suspended parallel robots. Given two mechanical states of the robot, both with a prescribed position and velocity, the method attempts to connect them by a collision-free trajectory that respects the joint and force limits of the actuators, keeps the cables in tension, and takes the robot dynamics into account. The method is based on the construction of a bidirectionalrapidly-exploring random tree over the state space. Remarkably, the technique can be used to cross forward singularities of the robot in a predictable manner, which extends the motion capabilities beyond those demonstrated in previous work. The paper describes experiments that show the performance of the method in point-to-point operations with specific cable-driven robots, but the overall strategy remains applicable to other mechanism designs., This research has been partially funded by project DPI2014-57220-C2-2-P.

Annotation watermarking is a technique that allows to associate content descriptions with digital images in a persistent and format independent manner. It is commonly used in medical applications and, hence, existing schemes have been designed to meet rigorous watermark transparency requirements. As a result, the effective capacity of such schemes is severely limited. In this paper, we present a new approach to annotation watermarking. We adopt the fountain coding paradigm and design a convenient watermark communication architecture which resembles a traditional packet network. Our approach allows for straightforward incorporation of content adaptivity, robustness against cropping and support for multiple data streams. In our study, we focus on high-capacity annotations and we assume different requirements with respect to the fidelity of the watermarked images. Our scheme is robust against lossy JPEG compression and cropping. This paper describes the principles of the proposed approach and presents the results of it's experimental evaluation.

International audience; We present in this paper a study on fault management in a grid middleware. The middleware is our home-grown software called P2P-MPI. This framework is MPJ compliant, allows users to execute message passing parallel programs, and its objective is to support environments using commodity hardware. Hence, running programs is failure prone and a particular attention must be paid to fault management. The fault management covers two issues: fault-tolerance and fault detection. Fault-tolerance deals with the program execution: P2P-MPI provides a transparent fault tolerance facility based on replication of computations. Fault detection concerns the monitoring of the program execution by the system. The monitoring is done through a distributed set of modules called failure detectors. The contribution of this paper is twofold. The first contribution is the evaluation of the failure probability of an application depending on the replication degree. The failure probability depends on the execution length, and we propose a model to evaluate the duration of a replicated parallel program. Then, we give an expression of the replication degree required to keep the failure probability of an execution under a given threshold. The second contribution is a study of the advantages and drawbacks of several fault detection systems found in the literature. The criteria of our evaluation are the reliability of the failure detection service and the failure detection speed. We retain the binary round-robin protocol for its failure detection speed, and we propose a variant of this protocol which is more reliable than the application execution in any case. Experiments involving of up to 256 processes, carried out on Grid'5000, show that the real detection times closely match the predictions.

Data acquisition during storage tank inspection is one of the most important aspects for petrochemical storage tank owners. Mobile inspection robots designed to enter inside a storage tanks without taking the tank out of service are required to enter through manholes on the roof of the tank with openings as small as 300-millimetre diameter. These robots are controlled via an umbilical cable which supplies power to the robot, sends and receives signals to control robot motion, and transfers inspection data acquired by non-destructive testing (NDT) sensors back to NDT inspectors. It is important to localize a robot inside the tank so that NDT data indicating a defect such as corrosion pitting in tank floors or weld cracks can be mapped for subsequent monitoring and repair. Wireless communication with the robot for NDT data acquisition and localization would enable the minimization of umbilical size and its effective management which is important when a small mobile robot is supplied with a very long umbilical. This paper presents results of a study to develop a wireless communication system that uses radio frequency (RF) signals with low power (< 1W) sent by a transceiver on a robot operating inside an oil storage tank which travel through an oil medium, are transmitted through steel tank walls and are captured by receivers placed in air outside the tank. Simulations using Feko software have been performed to assess the feasibility of using RF for communication in oil storage tanks with laboratory experiments conducted using vegetable oil to validate the simulations. RF signals transmitted by a robot operating inside an oil tank and received by a number of receivers placed in air around the tank has potential application as a robot localization system.

To reduce the impact of droughts and increase the resilience of regional water systems, various competing demands, such as hydropower, supply, irrigation and river ecosystems, need to be reconciled. In this perspective, for a sustainable and efficient management of the water resources, planners and practitioners would benefit from using the most recent data and easily accessible analysis tools, that can make hydrological model applications easier to apply. In this paper, a web-based open-source geoinformation tool for estimating Flow Duration Curves (FDCs) in ungauged basins is presented. The FDC estimation derives from a regional statistical model, that relates basin topographic parameters, climatic characteristic and other environmental factors to FDC features via multivariate regression. The software tool has the primary function of simplifying the GIS-intensive application of the multivariate methodology, allowing computation of the necessary basin features through web services. These are developed in compliance with the OGC specifications for geospatial Web Processing Service (WPS), while scripting and model implementation are developed server-side, which ensures the user access to always updated data, and to procedures free from software client compatibility issues. An operational application is available for the North-Western Italy.

This paper proposes to enrich robot motion data with trajectory curvature information. To do so, we use an approximate implementation of a topological feature named writhe, which measures the curling of a closed curve around itself, and its analog feature for two closed curves, namely the linking number. Despite these features have been established for closed curves, their definition allows for a discrete calculation that is well-defined for non-closed curves and can thus provide information about how much a robot trajectory is curling around a line in space. Such lines can be predefined by a user, observed by vision or, in our case, inferred as virtual lines in space around which the robot motion is curling. We use these topological features to augment the data of a trajectory encapsulated as a Movement Primitive (MP). We propose a method to determine how many virtual segments best characterize a trajectory and then find such segments. This results in a generative model that permits modulating curvature to generate new samples, while still staying within the dataset distribution and being able to adapt to contextual variables., Thiswork has been carried out within the projectCLOTHILDE (“CLOTH manIpulation Learning from DEmonstrations”) funded by the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (Advanced Grant agreementNo 741930).Research at IRI is also supported by the Spanish State Research Agency through theMaría de Maeztu Seal of Excellence to IRI MDM-2016-0656.

This is a post-peer-review, pre-copyedit version of an article published in International Journal of Parallel Programming. The final authenticated version is available online at: https://doi.org/10.1007/s10766-021-00709-y. [Abstract] The Divide-and-conquer (D&C) pattern appears in a large number of problems and is highly suitable to exploit parallelism. This has led to much research on its easy and efficient application both in shared and distributed memory parallel systems. One of the most successful approaches explored in this area consists of expressing this pattern by means of parallel skeletons which automate and hide the complexity of the parallelization from the user while trying to provide good performance. In this paper, we tackle the development of a skeleton oriented to the efficient parallel resolution of D&C problems with a high degree of imbalance among the subproblems generated and/or a deep level of recurrence. The skeleton achieves in our experiments average speedups between 11 and 18% higher than those of other solutions, reaching a maximum speedup of 78% in some tests. Nevertheless, the new proposal requires an average of between 13 and 29% less programming effort than the usual alternatives. Ministerio de Ciencia e Innovación de España; TIN2016-75845-P Ministerio de Ciencia e Innovación de España; PID2019-104184RB-I00 Ministerio de Ciencia e Innovación de España; PID2019-104834GB-I00 Ministerio de Ciencia e Innovación de España; 10.13039/501100011033 Ministerio de Ciencia e Innovación de España; BES-2017-081320 Xunta de Galicia; ED431C 2017/04 Xunta de Galicia; ED431C 2018/19 Xunta de Galicia; ED431G 2019/01 Xunta de Galicia; ED431G 2019/04

In this paper, we present a robotic workcell for task automation in footwear manufacturing such as sole digitization, glue dispensing, and sole manipulation from different places within the factory plant. We aim to make progress towards shoe industry 4.0. To achieve it, we have implemented a novel sole grasping method, compatible with soles of different shapes, sizes, and materials, by exploiting the particular characteristics of these objects. Our proposal is able to work well with low density point clouds from a single RGBD camera and also with dense point clouds obtained from a laser scanner digitizer. The method computes antipodal grasping points from visual data in both cases and it does not require a previous recognition of sole. It relies on sole contour extraction using concave hulls and measuring the curvature on contour areas. Our method was tested both in a simulated environment and in real conditions of manufacturing at INESCOP facilities, processing 20 soles with different sizes and characteristics. Grasps were performed in two different configurations, obtaining an average score of 97.5% of successful real grasps for soles without heel made with materials of low or medium flexibility. In both cases, the grasping method was tested without carrying out tactile control throughout the task. Research work was completely funded by the European Commission and FEDER through the COMMANDIA project (SOE2/P1/F0638), supported by Interreg-V Sudoe. Part of the facilities used were provided by the Footwear Technological Institute (INESCOP).

In this paper we analyse the performance of machine learning methods in predicting patient information such as age or sex solely from retinal imaging modalities in a heterogeneous clinical population. Our dataset consists of N = 135,667 fundus images and N = 85,536 volumetric OCT scans. Deep learning models were trained to predict the patient’s age and sex from fundus images, OCT cross sections and OCT volumes. For sex prediction, a ROC AUC of 0.80 was achieved for fundus images, 0.84 for OCT cross sections and 0.90 for OCT volumes. Age prediction mean absolute errors of 6.328 years for fundus, 5.625 years for OCT cross sections and 4.541 for OCT volumes were observed. We assess the performance of OCT scans containing different biomarkers and note a peak performance of AUC = 0.88 for OCT cross sections and 0.95 for volumes when there is no pathology on scans. Performance drops in case of drusen, fibrovascular pigment epitheliuum detachment and geographic atrophy present. We conclude that deep learning based methods are capable of classifying the patient’s sex and age from color fundus photography and OCT for a broad spectrum of patients irrespective of underlying disease or image quality. Non-random sex prediction using fundus images seems only possible if the eye fovea and optic disc are visible.

NoSQL technologies have become a common component in many information systems and software applications. These technologies are focused on performance, enabling scalable processing of large volumes of structured and unstructured data. Unfortunately, most developments over NoSQL technologies consider security as an afterthought, putting at risk personal data of individuals and potentially causing severe economic loses as well as reputation crisis. In order to avoid these situations, companies require an approach that introduces security mechanisms into their systems without scrapping already in-place solutions to restart all over again the design process. Therefore, in this paper we propose the first modernization approach for introducing security in NoSQL databases, focusing on access control and thereby improving the security of their associated information systems and applications. Our approach analyzes the existing NoSQL solution of the organization, using a domain ontology to detect sensitive information and creating a conceptual model of the database. Together with this model, a series of security issues related to access control are listed, allowing database designers to identify the security mechanisms that must be incorporated into their existing solution. For each security issue, our approach automatically generates a proposed solution, consisting of a combination of privilege modifications, new roles and views to improve access control. In order to test our approach, we apply our process to a medical database implemented using the popular document-oriented NoSQL database, MongoDB. The great advantages of our approach are that: (1) it takes into account the context of the system thanks to the introduction of domain ontologies, (2) it helps to avoid missing critical access control issues since the analysis is performed automatically, (3) it reduces the effort and costs of the modernization process thanks to the automated steps in the process, (4) it can be used with different NoSQL document-based technologies in a successful way by adjusting the metamodel, and (5) it is lined up with known standards, hence allowing the application of guidelines and best practices. This work was supported in part by the Spanish Ministry of Science, Innovation and Universities through the Project ECLIPSE under Grants RTI2018-094283-BC31 and RTI2018-094283- B-C32. Furthermore, it has been funded by the AETHER-UA (PID2020-112540RB-C43) Project from the Spanish Ministry of Science and Innovation.

Optical fibre networks are advancing rapidly to meet growing traffic demands. Security issues, including attack management, have become increasingly important for optical communication networks because of the vulnerabilities associated with tapping light from optical fibre links. Physical layer security often requires restricting access to channels and periodic inspections of link performance. In this paper, we report how quantum communication techniques can be utilized to detect a physical layer attack. We present an efficient method for monitoring the physical layer security of a high-data-rate classical optical communication network using a modulated continuous-variable quantum signal. We describe the theoretical and experimental underpinnings of this monitoring system and the monitoring accuracy for different monitored parameters. We analyse its performance for both unamplified and amplified optical links. The technique represents a novel approach for applying quantum signal processing to practical optical communication networks and compares well with classical monitoring methods. We conclude by discussing the challenges facing its practical application, its differences with respect to existing quantum key distribution methods, and its usage in future secure optical transport network planning., Optical communication security: Sound the quantum alarm A quantum alarm system can detect eavesdropping on optical communication links faster than classical methods. The system was developed by Yupeng Gong and colleagues at the University of Cambridge, UK, and involves transmitting two modes that are indistinguishable to an eavesdropper over the same channel and at the same wavelength. One mode sends a classical data signal and the other sends the security-monitoring quantum modulated signal. The alarm system is low-cost and can easily be used with high data-rate communication links that are hundreds of kilometers long. It can also be used with other encryption methods. The quantum alarm overcomes issues in other attack detection techniques, including quantum key distribution, which is challenging to implement in high data-rate optical communication networks.

Unequal area facility layout problem is an important issue in the design of industrial plants, as well as other fields such as hospitals or schools, among others. While participating in an interactive designing process, the human user is required to evaluate a high number of proposed solutions, which produces them fatigue both mental and physical. In this paper, the use of eye-tracking to estimate user’s evaluations from gaze behavior is investigated. The results show that, after a process of training and data taking, it is possible to obtain a good enough estimation of the user’s evaluations which is independent of the problem and of the users as well. These promising results advice to use eye-tracking as a substitute for the mouse during users’ evaluations.

Trabajo presentado en el 4th Iberian Robotics Conference, celebrado en Oporto (Portugal) en noviembre de 2019, This paper proposes a Social Reward Sources (SRS) design for a Human-Robot Collaborative Navigation (HRCN) task: human-robot collaborative search. It is a flexible approach capable of handling the collaborative task, human-robot interaction and environment restrictions, all integrated on a common environment. We modelled task rewards based on unexplored area observability and isolation and evaluated the model through different levels of human-robot communication.The models are validated through quantitative evaluation against both agents¿ individual performance and qualitative surveying of participants¿ perception. After that, the three proposed communication levels are com-pared against each other using the previous metrics., Work supported under projects ColRobTransp (DPI2016-78957-RAEI/FEDER EU), TERRINet (H2020-INFRAIA-2017-1-two-stage-730994) and by the Spanish State Research Agency through the Maria de Maeztu Seal of Excellence to IRI (MDM-2016-0656).

Recent advances in generative adversarial networks (GANs) have shown impressive results for the task of facial expression synthesis. The most successful architecture is StarGAN (Choi et al. in CVPR, 2018), that conditions GANs’ generation process with images of a specific domain, namely a set of images of people sharing the same expression. While effective, this approach can only generate a discrete number of expressions, determined by the content and granularity of the dataset. To address this limitation, in this paper, we introduce a novel GAN conditioning scheme based on action units (AU) annotations, which describes in a continuous manifold the anatomical facial movements defining a human expression. Our approach allows controlling the magnitude of activation of each AU and combining several of them. Additionally, we propose a weakly supervised strategy to train the model, that only requires images annotated with their activated AUs, and exploit a novel self-learned attention mechanism that makes our network robust to changing backgrounds, lighting conditions and occlusions. Extensive evaluation shows that our approach goes beyond competing conditional generators both in the capability to synthesize a much wider range of expressions ruled by anatomically feasible muscle movements, as in the capacity of dealing with images in the wild. The code of this work is publicly available at https://github.com/albertpumarola/GANimation., This work is partially supported by an Amazon Research Award, by the Spanish Ministry of Economy and Competitiveness under Projects HuMoUR TIN2017-90086-R, ColRobTransp DPI2016-78957 and María de Maeztu Seal of Excellence MDM-2016-0656; by the EU Project AEROARMS ICT-2014-1-644271; and by the Grant R01-DC- 014498 of the National Institute of Health. We also thank Nvidia for hardware donation under the GPU Grant Program.

13 p.-6 fig.-5 tab., Alzheimer's disease is one of the most common neurodegenerative disorders in elder population. The β-site amyloid cleavage enzyme 1 (BACE1) is the major constituent of amyloid plaques and plays a central role in this brain pathogenesis, thus it constitutes an auspicious pharmacological target for its treatment. In this paper, a QSAR model for identification of potential inhibitors of BACE1 protein is designed by using classification methods. For building this model, a database with 215 molecules collected from different sources has been assembled. This dataset contains diverse compounds with different scaffolds and physical-chemical properties, covering a wide chemical space in the drug-like range. The most distinctive aspect of the applied QSAR strategy is the combination of hybridization with backward elimination of models, which contributes to improve the quality of the final QSAR model. Another relevant step is the visual analysis of the molecular descriptors that allows guaranteeing the absence of information redundancy in the model. The QSAR model performances have been assessed by traditional metrics, and the final proposed model has low cardinality, and reaches a high percentage of chemical compounds correctly classified., This work is kindly supported by CONICET, grant PIP 112–2012–0100471, by UNS, grants PGI 24/N042 and PGI 24/ZM17, Ministerio de Economía y Competitividad (CTQ2015-66313-R) and by MINCYT, for their economic support given to IP in the “6° Programa de Movilidad Docente a Madrid”.

The scarcity of labeled data often limits the application of supervised deep learning techniques for medical image segmentation. This has motivated the development of semi-supervised techniques that learn from a mixture of labeled and unlabeled images. In this paper, we propose a novel semi-supervised method that, in addition to supervised learning on labeled training images, learns to predict segmentations consistent under a given class of transformations on both labeled and unlabeled images. More specifically, in this work we explore learning equivariance to elastic deformations. We implement this through: 1) a Siamese architecture with two identical branches, each of which receives a differently transformed image, and 2) a composite loss function with a supervised segmentation loss term and an unsupervised term that encourages segmentation consistency between the predictions of the two branches. We evaluate the method on a public dataset of chest radiographs with segmentations of anatomical structures using 5-fold cross-validation. The proposed method reaches significantly higher segmentation accuracy compared to supervised learning. This is due to learning transformation consistency on both labeled and unlabeled images, with the latter contributing the most. We achieve the performance comparable to state-of-the-art chest X-ray segmentation methods while using substantially fewer labeled images.

Mediation is a process in which two parties agree to resolve their dispute by negotiating over alternative solutions presented by a mediator. In order to construct such solutions, the mediator brings more information and knowledge, and, if possible, resources to the negotiation table. In order to do so, the mediator faces the challenge of determining which information is relevant to the current problem, given a vast database of knowledge. The contribution of this paper is the automated mediation machinery to resolve this issue. We define the concept of a Mediation Problem and show how it can be described in Game Description Language (GDL). Furthermore, we present an algorithm that allows the mediator to efficiently determine which information is relevant to the problem and collect this information from the negotiating agents. We show with several experiments that this algorithm is much more efficient than the naive solution that simply takes all available knowledge into account., This work was sponsored by Endeavour Research Fellowship 4577_2015 awarded by the Australian Department of Education.

Trabajo presentado en el 4th Iberian Robotics Conference, celebrado en Oporto (Portugal) en noviembre de 2019, In this paper is proposed an inclusion of the Social Force Model (SFM) into a concrete Deep Reinforcement Learning (RL) framework for robot navigation. These types of techniques have demonstrated to be useful to deal with different types of environments to achieve a goal. In Deep RL, a description of the world to describe the states and a reward adapted to the environment are crucial elements to get the desire behaviour and achieve a high performance. For this reason, this work adds a dense reward function based on SFM and uses the forces in the states like an additional description. Furthermore, obstacles are added to improve the behaviour of works that only consider moving agents. This SFM inclusion can offer a better description of the obstacles for the navigation. Several simulations have been done to check the effects of these modifications in the average performance., Work supported by the Spanish Ministry of Science and Innovation under project ColRobTransp (DPI2016-78957-RAEI/FEDER EU) and by the Spanish State Research Agency through the María de Maeztu Seal of Excellence to IRI (MDM-2016-0656). Óscar Gil is also supported by Spanish Ministry of Science and Innovation under a FPI-grant, BES-2017-082126.

The final publication is available at Springer via http://dx.doi.org/10.1007/s10922-018-9484-x Network slicing is one of the key enabling technologies for 5G networks. It allows infrastructure owners to assign resources to service providers (tenants), which will afterwards use them to satisfy their end-user demands. This paradigm, which changes the way networks have been traditionally managed, was initially proposed in the wired realm (core networks). More recently, the scientific community has paid attention to the integration of network slicing in wireless cellular technologies (LTE). However, there are not many works addressing the challenges that appear when trying to exploit slicing techniques over WiFi networks, in spite of their growing relevance. In this paper we propose a novel method of proportionally distributing resources in WiFi networks, by means of the airtime. We develop an analytical model, which shed light on how such resources could be split. The validity of the proposed model is assessed by means of simulation-based evaluation over the ns-3 framework This work has been supported in part by the European Commission and the Spanish Government (Fondo Europeo de desarrollo Regional, FEDER) by means of the EU H2020 NECOS (777067) and ADVICE (TEC2015-71329) projects, respectively.

Trabajo presentado en la 20th Annual Conference Towards Autonomous Robotic Systems (TAROS), celebrada en Londres (Reino Unido), del 3 al 5 de julio de 2019, Probabilistic planning is very useful for handling uncertainty in planning tasks to be carried out by robots. ROSPlan is a framework for task planning in the Robot Operating System (ROS), but until now it has not been possible to use probabilistic planners within the framework. This systems paper presents a standardized integration of probabilistic planners into ROSPlan that allows for reasoning with non-deterministic effects and is agnostic to the probabilistic planner used. We instantiate the framework in a system for the case of a mobile robot performing tasks indoors, where probabilistic plans are generated and executed by the PROST planner. We evaluate the effectiveness of the proposed approach in a real-world robotic scenario., This work has been supported by the ERC project Clothilde (ERC-2016-ADG-741930), the HuMoUR project (Spanish Ministry of Science and Innovation TIN2017-90086-R) and by the Spanish State Research Agency through the María de Maeztu Seal of Excellence to IRI (MDM-2016-0656). G. Canal is also supported by the Spanish Ministry of Education, Culture and Sport by the FPU15/00504 doctoral grant and the mobility grant EST17/00371. The research from KCL was partly supported by Korea Evaluation Institute of Industrial Technology (KEIT) funded by the Ministry of Trade, Industry & Energy (MOTIE) (No. 1415158956).

In this paper we first consider the problem of extending fuzzy (weak and strict) preference relations, represented by fuzzy preorders on a set to a fuzzy preferences on subsets, and we characterise different possibilities. Based on their properties, we then semantically define and axiomatize several two-tiered graded modal logics to reason about the corresponding different notions of fuzzy preferences., Esteva and Godo acknowledges partial support by the Spanish FEDER/MINECO project TIN2015-71799-C2-1-P. Vidal acknowledges partial support by the joint project of the Austrian Science Fund (FWF) I1897-N25 and the Czech Science Foundation (GACR) 15-34650L, and by the institutional grant RVO:67985807.

The home care crew scheduling (HCCS) problem is a planning task whose goal is to allocate a set of professional caregivers in the most efficient way to perform a number of assistencial and health care visits to the customers private homes. This is part of an important trend in advanced health care systems, to promote "independent living" specially in situations of dependency on long-term care. This not only ensures a higher quality of life but also a lower cost for society. Real instances of the HCCS problem are large and highly constrained due to both caregivers' contract limitations and customers' needs. This paper presents an advanced parallel model that solves HCCS problems using a grid-based asynchronous evolutionary algorithm (EA). Our approach has been tested using a grid computing facility of up to 300 nodes. The algorithm is a modified (1 + lambda) EA, parallelized using a master/worker model that minimizes communication requirements and processor bottlenecks by distributing both the execution of the EA operators and the evaluation of solutions. We have used three large real-world instances provided by a private company to perform experimentation with different configurations of the EA and number of workers. Results show that our algorithm achieves solutions that clearly outperform the solution provided by the company and the grid-based algorithm is able to handle real world HCCS problems The work of Francisco Luna and Juan F. Valenzuela is funded by the Spanish Ministry of Economy, Industry and Competitiveness under contract TIN2016-75097-P. The work of Alejandro Cervantes and Pedro Isasi is funded by the Spanish Ministry of Science and Innovation under contract TIN2011-28336.

The elderly in the future will use smart house technology, sensors, and robots to stay at home longer. Privacy at home for these elderly is important. In this exploratory paper, we examine different understandings of privacy and use Palen and Dourish's framework to look at the negotiation of privacy along boundaries between a human at home, the robot, and its sensors. We select three dilemmas: turning sensors on and off, the robot seeing through walls, and machine learning. We discuss these dilemmas and also discuss ways the robot can help make the elderly more aware of privacy issues and to build trust.

Visual topological localization is a process typically required by varied mobile autonomous robots, but it is a complex task if long operating periods are considered. This is because of the appearance variations suffered in a place: dynamic elements, illumination or weather. Due to these problems, long-term visual place recognition across seasons has become a challenge for the robotics community. For this reason, we propose an innovative method for a robust and efficient life-long localization using cameras. In this paper, we describe our approach (ABLE), which includes three different versions depending on the type of images: monocular, stereo and panoramic. This distinction makes our proposal more adaptable and effective, because it allows to exploit the extra information that can be provided by each type of camera. Besides, we contribute a novel methodology for identifying places, which is based on a fast matching of global binary descriptors extracted from sequences of images. The presented results demonstrate the benefits of using ABLE, which is compared to the most representative state-of-the-art algorithms in long-term conditions., Ministerio de Economía y Competitividad, Comunidad de Madrid

Although business model innovation (BMI) is essential to remaining competitive, many firms fail at it. A promising approach is building on reoccurring successful solutions – business model patterns (BMP) – as a blueprint for BMI. However, existing patterns face constraints subject to a high diversity and overlaps among patterns. In addition, literature do not consider relations among BMPs, which limits their potential for BMI. This paper develops a hierarchical taxonomy of BMPs including generalizations and specializations based on inheritance. We conduct a literature review to identify patterns and a cluster analysis to create an inductive structure, followed by a qualitative analysis. The resulting hierarchical taxonomy includes 194 elements. It is the first hierarchical taxonomy of BMPs. The hierarchy addresses the diversity of patterns and overlaps with inheritance. It aids research to structure and understand BMPs. For practice, the taxonomy allows for the application of patterns and supports BMI.

In new product development, the rapid proposal of innovative solutions represents an important phase. This in turn relies on creative ideas, their evaluation, refinement and embodiment of worthwhile directions. This study aims to describe a CBDT based process model for product conceptual design that concentrates on rapidly generating innovations with the support of decision-making rationale. Case-based decision theory (CBDT), derived from case-based reasoning, is applied in this paper as a core method to aid design engineers to make an informed decision quickly, thus accelerating the design process. In the process of utilizing CBDT to support a decision, as for the similarity function, the proper value assignment methods to the selected attribute set for calculation are discussed. In order to assist with innovative solution, aspects of the theory of inventive problem solving (TRIZ) are integrated into the case-based reasoning process. Accordingly, a CBDT-TRIZ model is developed. Quality-function deployment is used to translate customer wants into relevant engineering design requirements and thus formulating the design specification. Image-Scale is used to offer an orthogonal coordinates system to aid evaluation. Finally, a case study is used to demonstrate the validity of the proposed process model based on the design of a cordless hand-tool for garden and lawn applications.

Dark-field imaging is a scattering-based X-ray imaging method that can be performed with laboratory X-ray tubes. The possibility to obtain information about unresolvable structures has already seen a lot of interest for both medical and material science applications. Unlike conventional X-ray attenuation, orientation dependent changes of the dark-field signal can be used to reveal microscopic structural orientation. To date, reconstruction of the three-dimensional dark-field signal requires dedicated, highly complex algorithms and specialized acquisition hardware. This severely hinders the possible application of orientation-dependent dark-field tomography. In this paper, we show that it is possible to perform this kind of dark-field tomography with common Talbot-Lau interferometer setups by reducing the reconstruction to several smaller independent problems. This allows for the reconstruction to be performed with commercially available software and our findings will therefore help pave the way for a straightforward implementation of orientation-dependent dark-field tomography.

Trabajo presentado a la Third Iberian Robotics Conference, celebrada en Sevilla del 22 al 24 de noviembre de 2017., In this paper, we present an on-line adaptive side-by-side human-robot companion to approach a moving person to interact with. Our framework makes the pair robot-human capable of overpass, in a joint way, the dynamic and static obstacles of the environment while they reach a moving goal, which is the person who wants to interact with the pair. We have defined a new moving final goal that depends on the environment, the movement of the group and the movement of the interacting person. Moreover, we modified the Extended Social Force model to include this new moving goal. The method has been validated over several situations in simulation. This work is an extension of the On-line adaptive side-by-side human robot companion in dynamic urban environments, IROS2017.

Trabajo presentado a la Third Iberian Robotics Conference, celebrada en Sevilla del 22 al 24 de noviembre de 2017., This paper presents an approach for plan generation, seletion and pruning of trajectories for autonomous driving, capable of dealing with dynamic complex environments, such as driving in urban scenarios. The planner rst discretizes the plan space and searches for the best trajectory and velocity prole of the vehicle. The main contributions of this work are the use of G2-splines for path generation and a method that takes into account accelerations and passenger comfort for generating and pruning velocity profiles based on 3rd order splines, both fulfilling kino-dynamic constraints. The proposed methods have been implemented in a motion planner in MATLAB and tested through simulation in different representative scenarios, involving obstacles and other moving vehicles. The simulations show that the planner performs correctly in different dynamic scenarios, maintaining the passenger comfort.

Trabajo presentado al 4th International Workshop on Parallelism in Bioinformatics (euro-Par), celebrado del 22 al 26 de agosto de 2016 en Grenoble, France., Next-generation sequencing (NGS) technologies initiated a revolution in genomics, producing massive amounts of biological data and the consequent need for adapting current computing infrastructures. Multiple alignment of genomes, analysis of variants or phylogenetic tree construction, with quadratic polynomial complexity in the best case are tools that can take days or weeks to complete in conventional computers. Most of these analysis, involving several tools integrated in workflows, present the possibility of dividing the computational load in independent tasks allowing parallel execution. Determining adequate load balancing, data partitioning, granularity and I/O tuning are key factors for achieving suitable speedups. In this paper we present a coarse-grain parallelization of GH caller (Genotype/Haplotype caller), a tool used in population genomics workflows that performs a probabilistic identification process to account for the frequency of variants present between population individuals. It implements a master-worker model, using the standard Message Passing Interface (MPI), and concurrently and iteratively distributes the data among the available worker processes by mapping subsets of data and leaving the orchestration to the master process. Our results show a performance gain factor of 260x using 64 processes and additional optimizations with regard to the initial non-parallelized version., This work was supported by Ministerio de Ciencia y Tecnología (Spain) under project number TIN2014-53234-C2-1-R, and Ministerio de Economía y Competitividad (grant AGL2013-41834-R) to S.E.R.-O.

This paper addresses the analysis of aircraft control capabilities during the cruise phase (flying at the established level with practically constant configuration and speed) in the presence of windshears. The study uses a point-mass aircraft model describing flight in a vertical plane. The problem is formulated as a differential game against wind disturbances. The first player, autopilot, controls the angle of attack and the power setting, whereas the second player, wind, produces dangerous gusts. The state variables of the model are subjected to constraints expressing aircraft safety conditions. Namely, the altitude, path inclination, and velocity are constrained. Viability theory is used to find the so-called viability kernel, the maximal subset of the state constraint where the aircraft trajectories can remain arbitrary long if the first player utilizes an appropriate feedback control, and the second player generates any admissible disturbances. The computations are based on grid methods developed by the authors and implemented on a multiprocessor computer system.

This paper investigates the resilience of an elementary electricity system (machine-generator) under proportional and derivative (PD) control when subject to large perturbations. A particular attention is paid to small power grids, representative of power grid structure in some developing countries. The considered elementary electricity system consists of a consumer (machine), a power plant (generator) and a transmission line. Both Runge-Kutta and Newton methods are used to solve the dynamical equations and the characteristic equations for stability. It is found that the controller increases the resilience of the system. We also show that time delays associated to the feedback loop of the controller have a negative impact on the performance. It is also shown that the asymmetry due to energy demand of different consumers to power plant increases the stability of the system.

The European Grid Infrastructure (EGI) is providing a sustainable pan---European Computing Grid to support e---Science, integrating more than 350 computing resource centers worldwide. One of its main challenges is that the middleware driving this production infrastructure is constantly evolving, as it adapts to the changing needs of the EGI Community. Since the software is provided by external technology providers, it needs to pass through a quality verification process before it is included in the EGI official release called Unified Middleware Distribution (UMD). Therefore, all software components undergo a release process covering the definition of the functionality and quality criteria, the verification of those criteria, and the testing under production environments. This paper details the design, development and implementation of this software validation process. An analysis is performed on several metrics to evaluate the process impact on the stability of the production infrastructure, by capturing malfunctions and other issues at the initial testing phases.

The motivation of this work fits with the general vision to enable e-health for European citizens, irrespective of their social and financial status and their place of residence. Services to be provided include access to a high-quality early diagnostic and prognostic service for the Alzheimer Disease and other forms of dementia, based both on the European Research and Education Networks and the European Grid Infrastructure. The present paper reports on the architecture and services of a Science Gateway developed in the context of the DECIDE project, which aims to support the medical community in its daily duties of patients’ examination and diagnosis. The implementation of the Science Gateway is described with particular focus on the standard technologies adopted to ease the access by non IT-.expert users. The work leverages on an authentication and authorization infrastructure based on Identity Federations and robot certificates and on the adoption of the SAGA standard for middleware-independent Grid interaction. The architecture and the functionalities of the digital repository for medical image storage and analysis are also presented.

Science Gateways are web portal environments targeted for a given community and dedicated to specific scientific needs. Scientists require a different set of tools, applications, visualizations, data integration patterns, to be able to satisfy unique requirements of different research domains. To enable users to benefit from remote computational and storage resources, a web portal framework should support an easy integration and access to the e-Infrastructure. In this paper we present results of our research and development activities leading to the release of the Vine Toolkit framework integrated with Adobe Flex/BlazeDs technologies. It offers a set of unified and abstract APIs for different Grid middleware and a rich graphic presentation layer. Additionally, it automates the integration process with portal frameworks, such as Liferay or GridSphere. Vine Toolkit introduces a concept of subprojects which extend core APIs or define new low level components and web applications. This way, a Science Gateway prototyping process is definitely shortened. Consequently, it allows programmers to build software components that can be reused in a simple manner for different Science Gateways.

Within the field of ocean science there is a long history of using controlled vocabularies and other Semantic Web techniques to provide a common and easily exchanged description of datasets. As an activity within the European Union, United States, Australian-funded project "Ocean Data Interoperability Platform", a workshop took place in June 2014 at Rensselaer Polytechnic Institute to further the use of these Semantic Web techniques with the aim of producing a set Linked Data publication patterns which describe many parts of a marine science dataset. During the workshop, a Semantic Web development methodology was followed which promoted the use of a team with mixed skills (computer, data and marine science experts) to rapidly prototype a model ontology which could be iterated in the future. In this paper we outline the methodology employed in the workshop, and examine both the technical and sociological outcomes of a workshop of this kind.

One way to reduce the computational load of the agents is the distribution of their services. To achieve this goal, the functionality of a MAS (multiagent system) should not reside in the agents themselves, but ubiquitously be distributed so that allows the system to perform tasks in parallel avoiding an additional computational cost. The distribution of services that offers SCODA (Distributed and Specialized Agent Communities) allows an intelligent management of these services provided by agents of the system and the parallel execution of threads that allow to respond to requests asynchronously, which implies an improvement in the performance of the system at both the computational level as the level of quality of service in the control of these services. The comparison carried out in the case of study that is presented in this paper demonstrates the existing improvement in the distribution of services on systems based on SCODA.

This paper presents the design and implementation of dedicated hardware IP modules for background subtraction, which are suitable to be implemented in embedded vision systems and are efficient in terms of performance, resource consumption, and operational speed. To achieve this goal, a comprehensive experimental study of different algorithms has been carried out by evaluating a wide range of quality parameters. From the results of this analysis, five candidate algorithms were selected and implemented using a model-based design methodology supported by Matlab and Xilinx FPGA tools. Using only the internal block memory available in the FPGA, they provide adequate solutions for processing low-resolution images with CIF and QCIF formats., This work was partially supported by TEC2011-24319 from the Spanish Government (with support from FEDER). E. Calvo-Gallego is funded by a FPU fellowship from the Spanish Government and P. Brox is supported by the ‘V Plan Propio de Investigación’ of the University of Seville.

Scientists continuously generate research data but only a few of them are published. If these data were accessible and reusable, researchers could examine them and generate new knowledge. Our purpose is to determine whether there is a relationship between the impact factor and the policies concerning open availability of raw research data in journals of Information Science and Library Science (ISLS) subject category from the Web of Science database. We reviewed the policies related to public availability of papers and data sharing in the 85 journals included in the ISLS category of the Journal Citation Reports in 2012. The relationship between public availability of published data and impact factor of journals is analysed through different statistical tests. The variable “statement of complementary material” was accepted in 50 % of the journals; 65 % of the journals support “reuse”; 67 % of the journals specified “storage in thematic or institutional repositories”; the “publication of the manuscript in a website” was accepted in 69 % of the journals. We have found a 50 % of journals that include the possibility to deposit data as supplementary material, and more than 60 % accept reuse, storage in repositories and publication in websites. There is a clear positive relationship between being a top journal in impact factor ranking of JCR and having an open policy., This work has benefited from assistance by the National R+D+I of the Ministry of Economy and Competitiveness of the Spanish Government (CSO2012-39632-C02).