Browsing by Type "book part"

Now showing 1 - 20 of 198
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    Advanced analytics for modern mining
    (Springer International Publishing, 2022-02-23) Galar, Diego; Kumar, Uday; Tecnalia Research & Innovation
    Technology is growing very fast, and we are facing the Fourth Revolution in industry. Digital transformation has found its way in to many different traditional and modern industries. Digitalization and automation are two common words in mining these days. However, there are many challenges in the mining industry to reach the appropriate maturity level for Industry 4.0. Data collection systems, cloud-based storage, intelligent data architecture, creating online data hubs are some examples of digitalization challenges. Moreover, it is essential to use advanced analytics models applying artificial intelligence and machine learning models for automation, prediction, and optimization. Mine managers need an intelligent indigent virtual assistant to make better decisions and develop smart mines. This chapter some key components of intelligent mining and helps researchers understand Industry 4.0 in the mining context.
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    Advanced mobility communication
    (Institution of Engineering and Technology, 2020-01-01) Kurano, Jorge Alfonso; Bermejo, David Jiménez; Fraile-Ardanuy, Jesús; Castanõ, Sandra; Merino, Julia; Álvaro-Hermana, Roberto; Tecnalia Research & Innovation
    The urban and interurban mobility environment has been evolving in recent decades. Traditional factors that have been pushing these changes have been changes in motorisation, residential and urban sprawl, and the spatial distribution of the population, the workplaces and other societal relevant locations. Currently, more than a half of the world population is living in cities, reaching almost 72% in the European Union (EU), and it is estimated that over 80% of the European population will live in urban areas by 2020. The growth of the cities will also generate new city mobility challenges to be solved.
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    Adversarial sample crafting for time series classification with elastic similarity measures
    (Springer Verlag, 2018) Oregi, Izaskun; Del Ser, Javier; Perez, Aritz; Lozano, Jose A.; Quantum
    Adversarial Machine Learning (AML) refers to the study of the robustness of classification models when processing data samples that have been intelligently manipulated to confuse them. Procedures aimed at furnishing such confusing samples exploit concrete vulnerabilities of the learning algorithm of the model at hand, by which perturbations can make a given data instance to be misclassified. In this context, the literature has so far gravitated on different AML strategies to modify data instances for diverse learning algorithms, in most cases for image classification. This work builds upon this background literature to address AML for distance based time series classifiers (e.g., nearest neighbors), in which attacks (i.e. modifications of the samples to be classified by the model) must be intelligently devised by taking into account the measure of similarity used to compare time series. In particular, we propose different attack strategies relying on guided perturbations of the input time series based on gradient information provided by a smoothed version of the distance based model to be attacked. Furthermore, we formulate the AML sample crafting process as an optimization problem driven by the Pareto trade-off between (1) a measure of distortion of the input sample with respect to its original version; and (2) the probability of the crafted sample to confuse the model. In this case, this formulated problem is efficiently tackled by using multi-objective heuristic solvers. Several experiments are discussed so as to assess whether the crafted adversarial time series succeed when confusing the distance based model under target.
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    Airline Application Security in the Digital Economy: Tackling Security Challenges for Distributed Applications in Lufthansa Systems
    (Springer Nature, 2019) Somoskői, Balázs; Spahr, Stefan; Rios, Erkuden; Ripolles, Oscar; Dominiak, Jacek; Cserveny, Tamás; Bálint, Péter; Matthews, Peter; Iturbe, Eider; Muntés-Mulero, Victor; CIBERSEC&DLT
    (a)Situation faced: In the era of pervasive digitalization, the airline IT software industry is facing a number of challenges from the combination of new distribution channels, social media, Big data, Cloud Computing, etc. One of the major challenges in creating smart and scalable software applications is how to tackle security challenges when components are distributed and operated in hybrid and multiple clouds, whose providers may be independent and heterogeneous. The difficulties reside not only in identifying and expressing the desired level of security in the application, but also in how the security guarantees are influenced by the cloud services used.(b)Action taken: We exemplify the case with a flight scheduling application prototype developed by Lufthansa Systems and explain how novel approaches are used to address security issues during the development of such a prototype by following the MUSA approach. MUSA stands for Multi-cloud Secure Applications and refers to an EU-funded research project that is developing an integrated solution for the development and operation of secure multi-cloud applications accounting for those security aspects from the beginning. We introduce the MUSA Security DevOps framework and lessons learned from using it.(c)Results achieved: Lufthansa Systems tested MUSA tools in an exercise to create, deploy and control a new secure application prototype. We describe how these tools were used in the context of the case study presented in this paper. We also analyze the impact that they had in the development, deployment, and operation of the multi-cloud prototype. This analysis is done by means of a user-centered evaluation using questionnaires and informal interviews.(d)Lessons learned: The most important lesson is the importance of a sound risk analysis from which the security decisions are taken. MUSA framework supports the automation of the risk analysis in a per component basis, helping to systematize the creation of the application risk profile. Another important aspect is how implementing a SecDevOps approach in a multi-cloud scenario proves that it is highly valuable to include security topics together with the regular DevOps methodology. Finally, we must underline the need for cloud standards which enable homogeneous cloud service descriptions that ease the comparison of the services and the offered security controls.
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    Aluminides
    (Elsevier, 2017-01-01) Agote, Iñigo; Lagos, Miguel A.; EXTREMAT
    Combustion synthesis methods can be used to obtain different aluminides starting from elemental powders. Combustion synthesis of the aluminides typically begins when the system reaches the initiation temperature, and a SHS reaction begins at the metal interface. Because of its high specific mechanical properties and corrosion resistant behavior, TiAl is one of the most attractive aluminides, however because of the low adiabatic temperature of the Ti+Al reaction (Tad=1244°C), the system needs additional activation energy to support the synthesis process in self-sustaining mode.
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    Appropriate spherical coordinate model for trocar port constraint in robotic surgery
    (Springer Verlag, 2018) Remazeilles, Anthony; Prada, Miguel; Rasines, Irati; Robótica Médica
    This article deals with the representation of the pivot point created when inserting an endoscope in the human body during a surgery application. Several robotic-based surgical solutions use the well-known spherical coordinates to define the pose of the robotic endoscope tip, since it can only represents motions that satisfy this single insertion point constraint. We demonstrate in this article that the traditional spherical model may not be totally suitable for surgical applications. First of all, such model presents a representation singularity within the work space. Furthermore, control strategies based on that model may not produce optimal motions of the robotic arm holding the endoscope. We propose an adjustment of the traditional spherical model to alleviate these two issues. We also propose a very simple but efficient control task for servoing a robotic arm holding an endoscopic camera to center an instrument in the camera field of view. Simulations are provided for demonstrating the correctness and efficiency of the proposed model and control approach.
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    Architectures and concepts for smart decentralised energy systems
    (Elsevier, 2021-01-01) Morch, Andrei Z.; Caerts, Chris; Mutule, Anna; Merino, Julia; Tecnalia Research & Innovation
    The idea of creation of more decentralized power system has been circulating for a while, but started to materialise only during the recent years, when massive introduction of support schemes for RES has started to move more and more generation into the distribution network. Apart from the environmental benefits, this has created several challenges for planning and operation of the conventional power system. Furthermore, the growing recognition of necessity for optimization across different energy carriers for example “ETIP SNET Vision 2050" is also pointing towards more and more decentralized system. This chapter presents an overview of the main architectures and concepts for smart decentralized energy systems, through the critical analysis of recent documents such as Pan-European roadmaps (ETIP-SNET) and scenarios (TYNDP2020), results of R&D projects and regulatory documents (“Clean Energy for all Europeans”). The chapter is organized in four parts and starts with background for decentralization: driving forces, trends, and foreseen benefits as well as potential challenges and pitfalls. The second section starts with an overview of different levels of decentralization. The decentralized architecture combined with new ICT infrastructure (including machine learning), opens possibility for new and more efficient control approaches (balancing and voltage). This issue has been studied for example in ELECTRA IRP project, elaborating a cellular structure with dedicated set of novel controls for the power system. This section will further look at the market alternatives and the areas with several unresolved issues and gaps, which must be explored further and require an immediate attention from the research community. The following section will present views of several key stakeholders on decentralization of the power system. It appears that transformation to partially or fully decentralized power system will require certain changes of the present and creation of new roles and responsibilities among actors on the power market. Some of these modifications has been already introduced and formalised in the most recent recast of “Clean Energy for all Europeans.” The section will further present somewhat different opinions about this among the involved stakeholders, which have been expressed in several position papers. The final section makes conclusions and links the content to other chapters of the book.
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    ArmAssist: An integrated solution for telerehabilitation of post-stroke arm impairment
    (Springer International Publishing, 2013) Perry, Joel C.; Zabaleta, Haritz; Belloso, Aitor; Rodríguez-de-Pablo, Cristina; Cavallaro, Francesca I.; Keller, Thierry; Tecnalia Research & Innovation
    There is growing consensus that new technologies in rehabilitation robotics and telerehabilitation systems can lessen the strain on the healthcare system by shifting the focus toward at-home rehabilitation and providing patients with more training autonomy. In this paper, a recently developed integrated solution for providing at-home telerehabilitation is presented. The system combines a low-cost mobile device and table mat for arm reach support, a large touchscreen PC, and a web-based telerehabilitation platform with serious games for assessment and training. The ArmAssist system represents a new generation of tools for reducing the burden of hands-on supervision in clinical stroke rehabilitation and has been met with initial praise for its ease of use in the clinical setting and motivational benefits for the patient.
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    Artificial skin and electrotactile stimulation for advanced tactile feedback in myoelectric prostheses
    (River Publishers, 2020-11-30) Seminara, Lucia; Strbac, Matija; Amin, Youssef; Valle, Maurizio; Dosen, Strahinja; SG
    Modern prosthetic arms and hands are sophisticated robotic devices that can provide some of the motor functions lost due to an amputation. However, none of the commonly used commercial systems restores somatosensory feedback to its user. In principle, the latter can be achieved by recording data from prosthesis sensors and conveying this information by stimulating the sensory structures of the amputee using invasive and noninvasive interfaces. Many such systems have been presented in the literature with promising results; however, they all rely on using only a few discrete stimulation points to transmit information and hence suffer from a limited information bandwidth. In this chapter, we propose a novel concept of a high-bandwidth feedback interface that relies on advanced sensing and stimulation to convey a large amount of information to the prosthesis user. The interface comprises an artificial skin covering the prosthesis with a dense network of tactile sensors (taxels) and a compact stimulation device delivering electrical current pulses through a matrix electrode with many conductive pads. The state-ofthe- art in the two technologies that are required for the implementation of the proposed concept are reviewed. This includes biomimetic e-skins that are suitable for the application in a wearable scenario, stimulation systems integrating a demultiplexing circuit to distribute electrical pulses, and flexible electrodes that can be produced with arbitrary shape, size, and distribution of conductive pads. Finally, the challenges in selecting feedback variables (raw signals versus high-level features) and mapping of these variables into stimulation parameters are addressed.
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    Assessment of the Potential of Commercial Buildings for Energy Management in Energy Performance Contracts
    (Springer Science and Business Media Deutschland GmbH, 2024) Garrido-Marijuan, Antonio; Garay-Martinez, Roberto; de Agustín, Pablo; Eguiarte, Olaia; EDIFICACIÓN DE ENERGÍA POSITIVA; LABORATORIO DE TRANSFORMACIÓN URBANA
    The Energy Performance Building Directive encourages Member States to establish clear long-term renovation strategies, highlighting the value of energy renovation for both the envelope and the smart services application in buildings. There is, however, a lack of works that effectively examine the cost-effectiveness linked to both the envelope retrofitting and the smartness of the building, which could hinder the effective implementation and prevent building owners, occupants, and stakeholders from taking full advantage of these strategies. This study presents a methodology to assess the most suitable “target” market across Europe for energy renovation. The work focuses on different typologies of commercial buildings, evaluating their potential for energy renovation under different boundary conditions such as climate or demand response market maturity. The assessment is performed in two stages: qualitative identification of those countries with the highest interest for renovation and energy management and quantitative assessment of the top candidates regarding their potential for renovation under different retrofitting scenarios in energy and economic terms. The study aims to serve as a decision-making process to explore and identify the potential for energy performance contracts for different typologies at the European level.
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    Automated Driving Vehicle Functionality as Guardian Angel
    (Springer, 2024) Sarabia, Joseba; Diaz, Sergio; Marcano, Mauricio; Mirnig, Alexander; Venkitachalam, Bharat Krishna; CCAM
    The concept of the Guardian Angel system represents a pivotal advancement in vehicular safety, with a focus on enhancing the driving experience for individuals with diminished driving skills, particularly elderly drivers seeking to retain their mobility. This system functions as an unobtrusive co-pilot, intervening only when necessary, and empowering drivers to maintain control while ensuring their safety. By actively monitoring both the external environment and the interior of the vehicle, the Guardian Angel system adeptly identifies potential hazards and triggers interventions in response to imminent collisions, road departures, or internal factors such as driver distraction or drowsiness. Through a comprehensive array of Human–Machine Interfaces (HMIs), the Guardian Angel system communicates critical information to the driver, enhancing situational awareness and facilitating seamless cooperation between humans and machine. The holistic design ensures that the system operates unobtrusively in the background, engaging only in safety–critical situations and providing clear explanations for its interventions. This paper presents a detailed exposition of the Guardian Angel system's architecture, its controller design, and the diverse range of HMIs employed to relay information to the driver. The focus here lies in articulating the system's conceptual foundation, design principles, and the potential it holds for transforming the driving experience into a safer and more empowering endeavor for drivers of varying skills.
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    Automatic fitting of feature points for border detection of skin lesions in medical images with bat algorithm
    (Springer Verlag, 2018) Gálvez, Akemi; Fister, Iztok; Fister, Iztok; Osaba, Eneko; Del Ser, Javier; Iglesias, Andrés; Quantum; IA
    This paper addresses the problem of automatic fitting of feature points for border detection of skin lesions. This problem is an important task in segmentation of dermoscopy images for semi-automatic early diagnosis of melanoma and other skin lesions. Given a set of feature points selected by a dermatologist, we apply a powerful nature-inspired metaheuristic optimization method called bat algorithm to obtain the free-form parametric Bézier curve that fits the points better in the least-squares sense. Our experimental results on two examples of skin lesions show that the method performs quite well and might be applied to automatic fitting of feature points for border detection in medical images.
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    The BerbaTek project for Basque: Promoting a less-resourced language via language technology for translation, content management and learning
    (Language Science Press, 2016-12-12) Leturia, Igor; Sarasola, Kepa; Arregi, Xabier; de Ilarraza, Arantza Diaz; Navas, Eva; Sainz, Iñaki; del Pozo, Arantza; Baranda, David; Iturraspe, Urtza; SWT; HPA
    Basque is both a minority language (only a small proportion of the population of the Basque Country speaks it) and also a less-resourced language. Fortunately, the Basque regional government is committed to its recovery, and has adopted policies for funding, among other things, language technologies, a field which a language aiming to survive cannot dispense with. BerbaTek was a 3-year (2009-2011) strategic research project on language, speech and multimedia technologies for Basque carried out by a consortium of five members, all prominent local organizations dedicated to research in the above-mentioned areas, and partially funded by the Departments for Industry and Culture of the Basque Government. Collaboration in BerbaTek allowed to carry out a great amount of both basic and applied research. In addition, various prototypes were developed to show the potential of integrating the developed technologies to the language industry sector.
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    Best practice in the general use of data in a city
    (River Publishers, 2022-11-11) Autero, Annina; Bourmpos, Michail; Quero, Iván Carrillo; Geri, Emanuele; Groléas, Hervé; Jashari, Alisa; Karaberi, Christina N.; Osa, María Jose Lopez; Maenpaa, Sari; Pejstrup, Esben; Palmisano, Elena; Pazzaglia, Fabio; Sapyska, Minna; HPA
    This chapter gives a "bird's eye view" of a variety of examples of how some of the "EU CITIES MISSION's 100 climate neutral and smart cities by 2030" are already using data from a wide variety of sources. They collectively will bring a wide range of experiences to ensure that the identified good practices in data usage might be shared and built upon, in the drive to make data work to drive forward the climate-neutral agenda.1 The examples come from a wide range of application areas and reflect the variety of the emerging data spaces, with the majority coming from the "100 climate-neutral cities". Whilst useful in its own right to be able to see the variety of uses data is being put to in a city, to stimulate ideas and potential replication elsewhere, the main purpose is for it to be used as a building block. The following chapter will concentrate on how cities have used personal data in the process of running their city. But in addition to providing these examples, we will also try to indicate how, by adding personal data to the data currently being used in the cases described in this chapter, added value might be demonstrated.
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    Beyond human–computer interaction: Metadesign in support of human problem–domain interaction
    (Taylor and Francis, 2011-01-01) Carmien, Stefan Parry; Fischer, Gerhard; Tecnalia Research & Innovation
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    Big Data in Railway O&M: A Dependability Approach
    (IGI Global, 2022-01-01) Galar, Diego; Seneviratne, Dammika; Kumar, Uday; Tecnalia Research & Innovation; INDUSTRY_THINGS
    Railway systems are complex with respect to technology and operations with the involvement of a wide range of human actors, organizations and technical solutions. For the operations and control of such complexity, a viable solution is to apply intelligent computerized systems, for instance, computerized traffic control systems for coordinating airline transportation, or advanced monitoring and diagnostic systems in vehicles. Moreover, transportation assets cannot compromise the safety of the passengers by only applying operation and maintenance activities. Indeed, safety is a more difficult goal to achieve using traditional maintenance strategies and computerized solutions come into the picture as the only option to deal with complex systems interacting among them and trying to balance the growth in technical complexity together with stable and acceptable dependability indexes. Big data analytics are expected to improve the overall performance of the railways supported by smart systems and Internetbased solutions. Operation and Maintenance will be application areas, where benefits will be visible as a consequence of big data policies due to diagnosis and prognosis capabilities provided to the whole network of processes. This chapter shows the possibilities of applying the big data concept in the railway transportation industry and the positive effects on technology and operations from a systems perspective.
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    Big data in road transport and mobility research
    (Elsevier, 2017-01-01) Campos-Cordobés, Sergio; del Ser, Javier; Laña, Ibai; Olabarrieta, Ignacio Iñaki; Sánchez-Cubillo, Javier; Sánchez-Medina, Javier J.; Torre-Bastida, Ana I.; LABORATORIO DE TRANSFORMACIÓN URBANA; SMART_TRANSPORT; IA; Tecnalia Research & Innovation; HPA
    Ubiquitous computing has changed the acquisition of mobility data, with two aspects contributing: the high penetration rate and the ability to capture and share information on a continuous basis. This applies to geolocation information, operational mobile phone data, and also, social network crowdsourced information. Additionally, under the umbrella of the Internet of Things trend, the deployment of the Connected Vehicle (Car-as-a-sensor) concept, supported by advanced V2X communications, provides massive data volume. For all these cases, data are open to never before seen opportunities to analyze and predict individual and aggregated mobility patterns. Big Data refers to the processsing capabilities of such an explosion in the amount, quality, and heterogeneity of available data. This chapter will review the most relevant data sources, introduce the underlying techniques supporting the BigData paradigm and, finally, provide a list of some relevant applications in the transport and mobility domain.
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    Biomass Pretreatment Strategies (Technologies, Environmental Performance, Economic Considerations, Industrial Implementation)
    (Elsevier Inc., 2016-03-01) Peral, Carlota; Alimentación Sostenible
    Agricultural wastes are the most abundant and renewable resources in the world. These wastes, commonly called lignocellulosic biomass, are composed mainly of cellulose, hemicellulose, and lignin. Both the cellulose and hemicellulose fractions are polymers of sugars and thereby a potential source for fermentation processes. Lignin can be used for many purposes, including production of chemicals, heat, and energy. Lignocellulosic biomass is recalcitrant to hydrolysis with cellulolytic enzymes. Therefore, a pretreatment step is necessary for the production of fermentable sugars. Various pretreatment methods, such as physical, chemical, physicochemical, biological, and combinations of them are available. Selection of the best pretreatment depends on factors as foreseen utilization of the main biomass components, efficiency in separation, environmental concerns, compatibility with subsequent fermentation, energy requirements, and costs that must be taken into account for commercial implementation.
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    Biomedical applications of ceramic nanocomposites
    (Elsevier Inc., 2013-07) Garmendia, N.; Olalde, B.; Obieta, I.; Biomateriales; Tecnalia Research & Innovation
    Bioceramics and bioceramic composites have been widely used for biomedical applications for the last 50 years. This chapter discusses the advantages of using ceramic nanocomposites. The application of both inert and bioactive ceramics for orthopaedic and dental implants, as well as in the novel field of tissue engineering, is discussed and future trends are presented.
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    Bottom-up technologies for reuse: A framework to support extractive software product line adoption activities
    (Springer International Publishing, 2022-11-22) Martinez, Jabier; Ziadi, Tewfik; Bissyandé, Tegawendé F.; Klein, Jaques; le Traon, Yves; SWT
    Bottom-Up Technologies for Reuse (BUT4Reuse) is a generic and extensible framework for helping in Software Product Line (SPL) adoption from existing artefacts. It supports the re-engineering of source code variants, models, requirements, or other structured formats. Currently 17 adapters are available for different artefact types. The framework covers the most relevant re-engineering activities towards extractive SPL adoption, i.e., the same framework can support feature identification and location, feature constraints discovery, feature model synthesis, and the construction of reusable assets. Well-defined extension points are provided for integrating algorithms and techniques for the mentioned activities. Similar to the case of the adapters, more than 20 state-of-the-art algorithms and techniques are currently integrated. The target users are both SPL adopters and integrators of adapters and techniques. In addition, two integrated benchmarks are proposed towards reproducible and comparable results for feature location research. This chapter presents the framework principles, supported activities, and an overview of the currently available functionalities.