462 research outputs found

    Federated Robust Embedded Systems: Concepts and Challenges

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    The development within the area of embedded systems (ESs) is moving rapidly, not least due to falling costs of computation and communication equipment. It is believed that increased communication opportunities will lead to the future ESs no longer being parts of isolated products, but rather parts of larger communities or federations of ESs, within which information is exchanged for the benefit of all participants. This vision is asserted by a number of interrelated research topics, such as the internet of things, cyber-physical systems, systems of systems, and multi-agent systems. In this work, the focus is primarily on ESs, with their specific real-time and safety requirements. While the vision of interconnected ESs is quite promising, it also brings great challenges to the development of future systems in an efficient, safe, and reliable way. In this work, a pre-study has been carried out in order to gain a better understanding about common concepts and challenges that naturally arise in federations of ESs. The work was organized around a series of workshops, with contributions from both academic participants and industrial partners with a strong experience in ES development. During the workshops, a portfolio of possible ES federation scenarios was collected, and a number of application examples were discussed more thoroughly on different abstraction levels, starting from screening the nature of interactions on the federation level and proceeding down to the implementation details within each ES. These discussions led to a better understanding of what can be expected in the future federated ESs. In this report, the discussed applications are summarized, together with their characteristics, challenges, and necessary solution elements, providing a ground for the future research within the area of communicating ESs

    Fuzzy Logic

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    Fuzzy Logic is becoming an essential method of solving problems in all domains. It gives tremendous impact on the design of autonomous intelligent systems. The purpose of this book is to introduce Hybrid Algorithms, Techniques, and Implementations of Fuzzy Logic. The book consists of thirteen chapters highlighting models and principles of fuzzy logic and issues on its techniques and implementations. The intended readers of this book are engineers, researchers, and graduate students interested in fuzzy logic systems

    High-level Architecture and Compelling Technologies for an Advanced Web-based Vehicle Routing and Scheduling System for Urban Freight Transportation

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    The search for a more efficient routing and scheduling, the improvement of serviceā€™s level and the increasing complexity of real-world distributive contexts are contingent variables that generate the need for a systemā€™s architecture that may be holistic, innovative, scalable and reliable. Hence, new technologies and a lucid awareness of involved actors and infrastructures, provide the basis to create a more efficient routing and scheduling architecture for enterprises

    Behaviour monitoring: investigation of local and distributed approaches

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    Nowadays, the widespread availability of cheap and eļ¬ƒcient unmanned systems (either aerial, ground or surface) has led to signiļ¬cant opportunities in the ļ¬eld of remote sensing and automated monitoring. On the one hand, the deļ¬nition of eļ¬ƒcient approaches to information collection, ļ¬ltering and fusion has been the focus of extremely relevant research streams over the last decades. On the other hand, far less attention has been given to the problem of ā€˜interpretingā€™ the data, thus implementing inference processes able to, e.g., spot anomalies and possible threats in the monitored scenario. It is easy to understand how the automation of the ā€˜target assessmentā€™ process could bring a great impact on monitoring applications since it would allow sensibly alleviating the analysis burden for human operators. To this end, the research project proposed in this thesis addresses the problem of behaviour assessment leading to the identiļ¬cation of targets that exhibit features ā€œof interestā€. Firstly, this thesis has addressed the problem of distributed target assessment based on behavioural and contextual features. The assessment problem is analysed making reference to a layered structure and a possible implementation approach for the middle-layer has been proposed. An extensive analysis of the ā€˜featureā€™ concept is provided, together with considerations about the target assessment process. A case study considering a road-traļ¬ƒc monitoring application is then introduced, suggesting a possible implementation for a set of features related to this particular scenario. The distributed approach has been implemented employing a consensus protocol, which allows achieving agreement about high-level, non-measurable, characteristics of the monitored vehicles. Two diļ¬€erent techniques, ā€˜Beliefā€™ and ā€˜Averageā€™ consensus, for distributed target assessment based on features are ļ¬nally presented, enabling the comparison of consensus eļ¬€ects when implemented at diļ¬€erent level of the considered conceptual hierarchy. Then, the problem of identifying targets concerning features is tackled using a diļ¬€erent approach: a probabilistic description is adopted for the target characteristics of interest and a hypothesis testing technique is applied to the feature probability density functions. Such approach is expected to allow discerning whether a given vehicle is a target of interest or not. The assessment process introduced is also able to account for information about the context of the vehicle, i.e. the environment where it moves or is operated. In so doing the target assessment process can be eļ¬€ectively adapted to the contour conditions. Results from simulations involving a road monitoring scenario are presented, considering both synthetic and real-world data. Lastly, the thesis addresses the problem of manoeuvre recognition and behaviour anomalies detection for generic targets through pattern matching techniques. This problem is analysed considering motor vehicles in a multi-lane road scenario. The proposed approach, however, can be easily extended to signiļ¬cantly diļ¬€erent monitoring contexts. The overall proposed solution consists in a trajectory analysis tool, which classiļ¬es the target position over time into a sequence of ā€˜driving modesā€™, and a string-matching technique. This classiļ¬cation allows, as result of two diļ¬€erent approaches, detecting both a priori deļ¬ned patterns of interest and general behaviours standing out from those regularly exhibited from the monitored targets. Regarding the pattern matching process, two techniques are introduced and compared: a basic approach based on simple strings and a newly proposed method based on ā€˜regular expressionsā€™. About reference patterns, a technique for the automatic deļ¬nition of a dictionary of regular expressions matching the commonly observed target manoeuvres is presented. Its assessment results are then compared to those of a classic multi-layered neural network. In conclusion, this thesis proposes some novel approaches, both local and distributed, for the identiļ¬cation of the ā€˜targets of interestā€™ within a multi-target scenario. Such assessment is solely based on the behaviour actually exhibited by a target and does not involve any speciļ¬c knowledge about the targets (analytic dynamic models, previous data, signatures of any type, etc.), being thus easily applicable to diļ¬€erent scenarios and target types. For all the novel approaches described in the thesis, numerical results from simulations are reported: these results, in all the cases, conļ¬rm the eļ¬€ectiveness of the proposed techniques, even if they appear to be open to interpretation because of the inherent subjectivity of the assessment process

    Audio beacon technologies, surveillance and social order

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    This thesis explores audio beacon technology with the aim of elucidating the implications of this technology for the individual in contemporary society. Audio beacons are hidden inside digital devices. They emit and receive high frequency audio signals which are inaudible to the human ear, thereby generating and transmitting data without our knowledge. The motivation for this research is to raise awareness of the prevalence of audio beacon technologies and to explore their implications for contemporary society. The research takes an interdisciplinary approach involving ā€“ 1) a survey of audio beacon technology, 2) a contextualization in terms of contemporary theories of surveillance and control and 3) an interpretation in terms of 20th century dystopian literature. The hidden surveillance and privacy of this technology is examined mainly through the humanistic perspective of George Orwellā€™s book Nineteen Eighty-Four. The general conclusion formed is that audio beacon technologies can serve as a surveillance method enhancing authoritarian and exploitative regimes. To mitigate the negative impacts of audio beacons, this research proposes two types of solutions ā€“ 1) individual actions that will have an immediate effect and 2) governmental legislation that can improve privacy in the longer term. Both of these solutions cannot happen without a raised public awareness, towards which this research hopes to make a contribution. Finally, this research introduces the notion of a \u27digital paradox\u27 in which the dystopian worlds of George Orwell and Aldous Huxley are brought together in order to characterize surveillance and control in contemporary society

    Sound event detection in the DCASE 2017 Challenge

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    International audienceEach edition of the challenge on Detection and Classification of Acoustic Scenes and Events (DCASE) contained several tasks involving sound event detection in different setups. DCASE 2017 presented participants with three such tasks, each having specific datasets and detection requirements: Task 2, in which target sound events were very rare in both training and testing data, Task 3 having overlapping events annotated in real-life audio, and Task 4, in which only weakly-labeled data was available for training. In this paper, we present the three tasks, including the datasets and baseline systems, and analyze the challenge entries for each task. We observe the popularity of methods using deep neural networks, and the still widely used mel frequency based representations, with only few approaches standing out as radically different. Analysis of the systems behavior reveals that task-specific optimization has a big role in producing good performance; however, often this optimization closely follows the ranking metric, and its maximization/minimization does not result in universally good performance. We also introduce the calculation of confidence intervals based on a jackknife resampling procedure, to perform statistical analysis of the challenge results. The analysis indicates that while the 95% confidence intervals for many systems overlap, there are significant difference in performance between the top systems and the baseline for all tasks

    Assessment and support of error recognition in automated driving

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    Potential impacts of advanced aerodynamic technology on air transportation system productivity

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    Summaries of a workshop held at NASA Langley Research Center in 1993 to explore the application of advanced aerodynamics to airport productivity improvement are discussed. Sessions included discussions of terminal area productivity problems and advanced aerodynamic technologies for enhanced high lift and reduced noise, emissions, and wake vortex hazard with emphasis upon advanced aircraft configurations and multidisciplinary solution options

    Music in Evolution and Evolution in Music

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    Music in Evolution and Evolution in Music by Steven Jan is a comprehensive account of the relationships between evolutionary theory and music. Examining the ā€˜evolutionary algorithmā€™ that drives biological and musical-cultural evolution, the book provides a distinctive commentary on how musicality and music can shed light on our understanding of Darwinā€™s famous theory, and vice-versa. Comprised of seven chapters, with several musical examples, figures and definitions of terms, this original and accessible book is a valuable resource for anyone interested in the relationships between music and evolutionary thought. Jan guides the reader through key evolutionary ideas and the development of human musicality, before exploring cultural evolution, evolutionary ideas in musical scholarship, animal vocalisations, music generated through technology, and the nature of consciousness as an evolutionary phenomenon. A unique examination of how evolutionary thought intersects with music, Music in Evolution and Evolution in Music is essential to our understanding of how and why music arose in our species and why it is such a significant presence in our lives
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