587 research outputs found

    Federated Query Processing over Heterogeneous Data Sources in a Semantic Data Lake

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    Data provides the basis for emerging scientific and interdisciplinary data-centric applications with the potential of improving the quality of life for citizens. Big Data plays an important role in promoting both manufacturing and scientific development through industrial digitization and emerging interdisciplinary research. Open data initiatives have encouraged the publication of Big Data by exploiting the decentralized nature of the Web, allowing for the availability of heterogeneous data generated and maintained by autonomous data providers. Consequently, the growing volume of data consumed by different applications raise the need for effective data integration approaches able to process a large volume of data that is represented in different format, schema and model, which may also include sensitive data, e.g., financial transactions, medical procedures, or personal data. Data Lakes are composed of heterogeneous data sources in their original format, that reduce the overhead of materialized data integration. Query processing over Data Lakes require the semantic description of data collected from heterogeneous data sources. A Data Lake with such semantic annotations is referred to as a Semantic Data Lake. Transforming Big Data into actionable knowledge demands novel and scalable techniques for enabling not only Big Data ingestion and curation to the Semantic Data Lake, but also for efficient large-scale semantic data integration, exploration, and discovery. Federated query processing techniques utilize source descriptions to find relevant data sources and find efficient execution plan that minimize the total execution time and maximize the completeness of answers. Existing federated query processing engines employ a coarse-grained description model where the semantics encoded in data sources are ignored. Such descriptions may lead to the erroneous selection of data sources for a query and unnecessary retrieval of data, affecting thus the performance of query processing engine. In this thesis, we address the problem of federated query processing against heterogeneous data sources in a Semantic Data Lake. First, we tackle the challenge of knowledge representation and propose a novel source description model, RDF Molecule Templates, that describe knowledge available in a Semantic Data Lake. RDF Molecule Templates (RDF-MTs) describes data sources in terms of an abstract description of entities belonging to the same semantic concept. Then, we propose a technique for data source selection and query decomposition, the MULDER approach, and query planning and optimization techniques, Ontario, that exploit the characteristics of heterogeneous data sources described using RDF-MTs and provide a uniform access to heterogeneous data sources. We then address the challenge of enforcing privacy and access control requirements imposed by data providers. We introduce a privacy-aware federated query technique, BOUNCER, able to enforce privacy and access control regulations during query processing over data sources in a Semantic Data Lake. In particular, BOUNCER exploits RDF-MTs based source descriptions in order to express privacy and access control policies as well as their automatic enforcement during source selection, query decomposition, and planning. Furthermore, BOUNCER implements query decomposition and optimization techniques able to identify query plans over data sources that not only contain the relevant entities to answer a query, but also are regulated by policies that allow for accessing these relevant entities. Finally, we tackle the problem of interest based update propagation and co-evolution of data sources. We present a novel approach for interest-based RDF update propagation that consistently maintains a full or partial replication of large datasets and deal with co-evolution

    A safety assessment framework for Automatic Dependent Surveillance Broadcast (ADS-B) and its potential impact on aviation safety

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    The limitations of the current civil aviation surveillance systems include a lack of coverage in some areas and low performance in terms of accuracy, integrity, continuity and availability particularly in high density traffic areas including airports, with a negative impact on capacity and safety. Automatic Dependent Surveillance Broadcast (ADS-B) technology has been proposed to address these limitations by enabling improved situational awareness for all stakeholders and enhanced airborne and ground surveillance, resulting in increased safety and capacity. In particular, its scalability and adaptability should facilitate its use in general aviation and in ground vehicles. This should, in principle, provide affordable, effective surveillance of all air and ground traffic, even on airport taxiways and runways, and in airspace where radar is ineffective or unavailable. The success of the progressive implementation of ADS-B has led to numerous programmes for its introduction in other parts of the World where the operational environment is considerably different from that of Australia. However, a number of critical issues must be addressed in order to benefit from ADS-B, including the development and execution of a safety case that addresses both its introduction into legacy and new systems’ operational concepts, the latter including the Single European Sky (SES) / Single European Sky ATM Research (SESAR) and the US’ Next Generation Air Transportation System (NexGEN). This requires amongst others, a good understanding of the limitations of existing surveillance systems, ADS-B architecture and system failures and its interfaces to the existing and future ATM systems. Research on ADS-B to date has not addressed in detail the important questions of limitations of existing systems and ADS-B failure modes including their characterisation, modelling and assessment of impact. The latter is particularly important due to the sole dependency of ADS-B on GNSS for information on aircraft state and its reliance on communication technologies such as Mode-S Extended Squitter, VHF Data Link Mode-4 (VDLM4) or Universal Access Transceiver (UAT), to broadcast the surveillance information to ground-based air traffic control (ATC) and other ADS-B equipped aircraft within a specified range, all of which increase complexity and the potential for failures. This thesis proposes a novel framework for the assessment of the ADS-B system performance to meet the level of safety required for ground and airborne surveillance operations. The framework integrates various methods for ADS-B performance assessment in terms of accuracy, integrity, continuity, availability and latency, and reliability assessment using probabilistic safety assessment methods; customized failure mode identification approach and fault tree analysis. Based on the framework, the thesis develops a failure mode register for ADS-B, identifies and quantifies the impact of a number of potential hazards for the ADS-B. Furthermore, this thesis identifies various anomalies in the onboard GNSS system that feeds aircraft navigation information into the ADS-B system. Finally, the thesis maps the ADS-B data availability and the quantified system performance to the envisioned airborne surveillance application’s requirements. The mapping exercise indicates that, the quantified ADS-B accuracy is sufficient for all applications while ADS-B integrity is insufficient to support the most stringent application: Airborne Separation (ASEP). In addition, some of the required performance parameters are unavailable from aircraft certified to DO-260 standard. Therefore, all aircraft must be certified to DO-260B standard to support the applications and perform continuous monitoring, to ensure consistency in the system performance of each aircraft.Open Acces

    2019 EC3 July 10-12, 2019 Chania, Crete, Greece

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    Proceedings, MSVSCC 2018

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    Proceedings of the 12th Annual Modeling, Simulation & Visualization Student Capstone Conference held on April 19, 2018 at VMASC in Suffolk, Virginia. 155 pp

    State-of-the-Art Sensors Technology in Spain 2015: Volume 1

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    This book provides a comprehensive overview of state-of-the-art sensors technology in specific leading areas. Industrial researchers, engineers and professionals can find information on the most advanced technologies and developments, together with data processing. Further research covers specific devices and technologies that capture and distribute data to be processed by applying dedicated techniques or procedures, which is where sensors play the most important role. The book provides insights and solutions for different problems covering a broad spectrum of possibilities, thanks to a set of applications and solutions based on sensory technologies. Topics include: • Signal analysis for spectral power • 3D precise measurements • Electromagnetic propagation • Drugs detection • e-health environments based on social sensor networks • Robots in wireless environments, navigation, teleoperation, object grasping, demining • Wireless sensor networks • Industrial IoT • Insights in smart cities • Voice recognition • FPGA interfaces • Flight mill device for measurements on insects • Optical systems: UV, LEDs, lasers, fiber optics • Machine vision • Power dissipation • Liquid level in fuel tanks • Parabolic solar tracker • Force sensors • Control for a twin roto

    Linked Open Data - Creating Knowledge Out of Interlinked Data: Results of the LOD2 Project

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    Database Management; Artificial Intelligence (incl. Robotics); Information Systems and Communication Servic

    Semantic-driven modeling and reasoning for enhanced safety of cyber-physical systems

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    This dissertation is concerned with the development of new methodologies and semantics for model-based systems engineering (MBSE) procedures for the behavior modeling of cyber-physical systems (CPS). Our main interest is to enhance system-level safety through effective reasoning capabilities embedded in procedures for CPS design. This class of systems is defined by a tight integration of software and physical processes, the need to satisfy stringent constraints on performance, safety and a reliance on automation for the management of system functionality. Our approach employs semantic–driven modeling and reasoning : (1) for the design of cyber that can understand the physical world and reason with physical quantities, time and space, (2) to improve synthesis of component-based CPS architectures, and (3) to prevent under-specification of system requirements (the main cause of safety failures in software). We investigate and understand metadomains, especially temporal and spatial theories, and the role ontologies play in deriving formal, precise models of CPS. Description logic-based semantics and metadomain ontologies for reasoning in CPS and an integrated approach to unify the semantic foundations for decision making in CPS are covered. The research agenda is driven by Civil Systems design and operation applications, especially the dilemma zone problem. Semantic models of time and space supported respectively by Allen’s Temporal Interval Calculus (ATIC) and Region Connectedness Calculus (RCC-8) are developed and demonstrated thanks to the capabilities of Semantic Web technologies. A modular, flexible, and reusable reasoning-enabled semantic-based platform for safety-critical CPS modeling and analysis is developed and demonstrated. The platform employs formal representations of domains (cyber, physical) and metadomains (temporal and spatial) entities using decidable web ontology language (OWL) formalisms. Decidable fragments of temporal and spatial calculus are found to play a central role in the development of spatio-temporal algorithms to assure system safety. They rely on formalized safety metrics developed in the context of cyber-physical transportation systems and collision avoidance for autonomous systems. The platform components are integrated together with Whistle, a small scripting language (under development) able to process complex datatypes including physical quantities and units. The language also enables the simulation, visualization and analysis of safety tubes for collision prediction and prevention at signalized and non-signalized traffic intersections

    2013 Annual Research Symposium Abstract Book

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    2013 annual volume of abstracts for science research projects conducted by students at Trinity College
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