57 research outputs found

    The interpretation of noun noun compounds

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    This thesis looks at conceptual combination, in particular it investigates how noun noun compounds are interpreted. Several themes run throughout the work. Real compounds (e.g. coat hanger, crab apple) are compared to novel ones (e.g. banjo cactus, zip violin). Also, compounds are examined in each of the possible permutations of artefacts (A) (e.g. coat, banjo) and natural kinds (N) (e.g. crab, cactus), (AA, AN, NA and NN).Experiments 1 - 4 examine noncompositionality in noun noun compounds. Possible sources of noncompositionality are investigated using both feature listing and feature rating tasks. Although some differences were found, results were similar between different types of compound, evidence of noncompositionality being found in each. The results also confirm that most of the meaning of a noun noim compound is derived from the second constituent (noun2).Experiments 5 and 6 look at two different types of compoimd interpretation - slot filling and property mapping. In experiment 5, slot filling is found to be the preferred interpretation type overall, but property mapping is more common in compounds composed of two natural kinds (NN). Experiment 6 examines possible factors influencing the choice between slot filling and property mapping interpretations. It was found that constituent similarity plays an important role, and also that this interacts with whether or not the constituents have important properties which clash. Experiment 7 looks at compound identification. Results suggest that the first constituent (nounl) may be critical in such tasks. Experiment 8 compares the importance of nounl and noun2 in determining the type of interpretation given to a compound. Neither position is found to be more influential than the other, although relational information does seem to be associated with specific nouns in each position. Throughout the thesis findings are related to current theories of conceptual combination, such as prototype models, the concept specialisation model and theories of compound interpretation by analogy

    Representing archaeological uncertainty in cultural informatics

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    This thesis sets out to explore, describe, quantify, and visualise uncertainty in a cultural informatics context, with a focus on archaeological reconstructions. For quite some time, archaeologists and heritage experts have been criticising the often toorealistic appearance of three-dimensional reconstructions. They have been highlighting one of the unique features of archaeology: the information we have on our heritage will always be incomplete. This incompleteness should be reflected in digitised reconstructions of the past. This criticism is the driving force behind this thesis. The research examines archaeological theory and inferential process and provides insight into computer visualisation. It describes how these two areas, of archaeology and computer graphics, have formed a useful, but often tumultuous, relationship through the years. By examining the uncertainty background of disciplines such as GIS, medicine, and law, the thesis postulates that archaeological visualisation, in order to mature, must move towards archaeological knowledge visualisation. Three sequential areas are proposed through this thesis for the initial exploration of archaeological uncertainty: identification, quantification and modelling. The main contributions of the thesis lie in those three areas. Firstly, through the innovative design, distribution, and analysis of a questionnaire, the thesis identifies the importance of uncertainty in archaeological interpretation and discovers potential preferences among different evidence types. Secondly, the thesis uniquely analyses and evaluates, in relation to archaeological uncertainty, three different belief quantification models. The varying ways that these mathematical models work, are also evaluated through simulated experiments. Comparison of results indicates significant convergence between the models. Thirdly, a novel approach to archaeological uncertainty and evidence conflict visualisation is presented, influenced by information visualisation schemes. Lastly, suggestions for future semantic extensions to this research are presented through the design and development of new plugins to a search engine

    Management of data quality when integrating data with known provenance

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    Foundations of Fuzzy Logic and Semantic Web Languages

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    This book is the first to combine coverage of fuzzy logic and Semantic Web languages. It provides in-depth insight into fuzzy Semantic Web languages for non-fuzzy set theory and fuzzy logic experts. It also helps researchers of non-Semantic Web languages get a better understanding of the theoretical fundamentals of Semantic Web languages. The first part of the book covers all the theoretical and logical aspects of classical (two-valued) Semantic Web languages. The second part explains how to generalize these languages to cope with fuzzy set theory and fuzzy logic

    Foundations of Fuzzy Logic and Semantic Web Languages

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    This book is the first to combine coverage of fuzzy logic and Semantic Web languages. It provides in-depth insight into fuzzy Semantic Web languages for non-fuzzy set theory and fuzzy logic experts. It also helps researchers of non-Semantic Web languages get a better understanding of the theoretical fundamentals of Semantic Web languages. The first part of the book covers all the theoretical and logical aspects of classical (two-valued) Semantic Web languages. The second part explains how to generalize these languages to cope with fuzzy set theory and fuzzy logic

    Identification of Emerging Scientific Topics in Bibliometric Databases

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    Bibliometrie, Maschinelles Lernen, LDA, Clustering, Neue Themen Abstract = Frühzeitiges Erkennen von aufkommenden Themengebieten in der Wissenschaft unterstützt sowohl Entscheidungen auf individueller als auch öffentlicher Ebene. Viele bestehende Verfahren beschränken sich auf eine retrospektive (Zitations-)Analyse der Publikationsdaten. Das Ziel der vorliegenden Arbeit war deshalb die Entwicklung eines Verfahrens, das zeitnah und neutral sogenannte "emerging topic candidates" aus einem Set von wissenschaftlichen Publikationen auswählt

    Identification of Emerging Scientific Topics in Bibliometric Databases

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    Bibliometrie, Maschinelles Lernen, LDA, Clustering, Neue Themen Abstract = Frühzeitiges Erkennen von aufkommenden Themengebieten in der Wissenschaft unterstützt sowohl Entscheidungen auf individueller als auch öffentlicher Ebene. Viele bestehende Verfahren beschränken sich auf eine retrospektive (Zitations-)Analyse der Publikationsdaten. Das Ziel der vorliegenden Arbeit war deshalb die Entwicklung eines Verfahrens, das zeitnah und neutral sogenannte "emerging topic candidates" aus einem Set von wissenschaftlichen Publikationen auswählt

    SEISMIC ATTRIBUTES ASSISTED QUANTITATIVE UNCONVENTIONAL RESERVOIRS CHARACTERIZATION

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    Unconventional reservoirs cover a wide range of hydrocarbon-bearing formations and reservoir types that generally do not produce economic rates of hydrocarbons without stimulation. The focus of this dissertation is to develop and calibrate workflows to aid in the characterization of the highly heterogeneous Mississippi Limestone reservoir play of northern Oklahoma. Because natural fractures and faults are the primary pathways for hydrocarbon migration and production in many reservoirs, naturally fractured reservoirs represent a significant percentage of oil and gas reservoirs throughout the world. In 2012, unconventional shale gas productions were accounting for 34% of the total natural gas production in the U.S. (0.68 trillion m3). Because of their complexity and commercial significance, naturally fractured reservoirs have been extensively studied showing that the in-situ stress field, lithology, formation thickness, structural setting and other geological factors all play a role. The understanding of the magnitude, timing, and distribution of these controlling factors could lead to an improvement in the characterization of fractures in reservoirs. Although, the geomechanical history of the rocks is elusive and often speculative, one can infer the magnitude and orientation of paleostresses and thereby hypothesize the degree of fracturing given current structure. Reservoir structure are mapped using petrophysical logs and seismic techniques where seismic attributes such as coherence and curvature are commonly used to map deformation in the subsurface. This dissertation introduces a new edge-detecting seismic attribute, aberrancy that quantitatively estimates the orientation and magnitude of poorly resolved faults as well as flexures in the subsurface. The rate of penetration (ROP) measures drilling speed, which is indicative of the overall time and in general, the cost of the drilling operation process. ROP depends on many engineering factors; however, if these parameters are held constant, ROP is a function of the geology. This dissertation is the first study that links ROP to seismic data and seismic-related attributes using proximal support vector machine. By using this workflow, we anticipate that this process can help better predict a budget or even reduce the cost of drilling when an ROP assessment is made in conjunction with reservoir quality and characteristics. Due to the complexity of fracture characterization, fracture prediction is more commonly the product of comprehensive integration of software, data, and specialize measurements specific to unconventional reservoirs. To calibrate volumetric aberrancy. I integrate seismic attributes and borehole image logs as the input to neural network. The findings on the use of volumetric aberrancy as an aid to structural interpretation and quantitative fracture prediction

    Knowledge Representation in Engineering 4.0

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    This dissertation was developed in the context of the BMBF and EU/ECSEL funded projects GENIAL! and Arrowhead Tools. In these projects the chair examines methods of specifications and cooperations in the automotive value chain from OEM-Tier1-Tier2. Goal of the projects is to improve communication and collaborative planning, especially in early development stages. Besides SysML, the use of agreed vocabularies and on- tologies for modeling requirements, overall context, variants, and many other items, is targeted. This thesis proposes a web database, where data from the collaborative requirements elicitation is combined with an ontology-based approach that uses reasoning capabilities. For this purpose, state-of-the-art ontologies have been investigated and integrated that entail domains like hardware/software, roadmapping, IoT, context, innovation and oth- ers. New ontologies have been designed like a HW / SW allocation ontology and a domain-specific "eFuse ontology" as well as some prototypes. The result is a modular ontology suite and the GENIAL! Basic Ontology that allows us to model automotive and microelectronic functions, components, properties and dependencies based on the ISO26262 standard among these elements. Furthermore, context knowledge that influences design decisions such as future trends in legislation, society, environment, etc. is included. These knowledge bases are integrated in a novel tool that allows for collabo- rative innovation planning and requirements communication along the automotive value chain. To start off the work of the project, an architecture and prototype tool was developed. Designing ontologies and knowing how to use them proved to be a non-trivial task, requiring a lot of context and background knowledge. Some of this background knowledge has been selected for presentation and was utilized either in designing models or for later immersion. Examples are basic foundations like design guidelines for ontologies, ontology categories and a continuum of expressiveness of languages and advanced content like multi-level theory, foundational ontologies and reasoning. Finally, at the end, we demonstrate the overall framework, and show the ontology with reasoning, database and APPEL/SysMD (AGILA ProPErty and Dependency Descrip- tion Language / System MarkDown) and constraints of the hardware / software knowledge base. There, by example, we explore and solve roadmap constraints that are coupled with a car model through a constraint solver.Diese Dissertation wurde im Kontext des von BMBF und EU / ECSEL gefördertem Projektes GENIAL! und Arrowhead Tools entwickelt. In diesen Projekten untersucht der Lehrstuhl Methoden zur Spezifikationen und Kooperation in der Automotive Wertschöp- fungskette, von OEM zu Tier1 und Tier2. Ziel der Arbeit ist es die Kommunikation und gemeinsame Planung, speziell in den frühen Entwicklungsphasen zu verbessern. Neben SysML ist die Benutzung von vereinbarten Vokabularen und Ontologien in der Modellierung von Requirements, des Gesamtkontextes, Varianten und vielen anderen Elementen angezielt. Ontologien sind dabei eine Möglichkeit, um das Vermeiden von Missverständnissen und Fehlplanungen zu unterstützen. Dieser Ansatz schlägt eine Web- datenbank vor, wobei Ontologien das Teilen von Wissen und das logische Schlussfolgern von implizitem Wissen und Regeln unterstützen. Diese Arbeit beschreibt Ontologien für die Domäne des Engineering 4.0, oder spezifischer, für die Domäne, die für das deutsche Projekt GENIAL! benötigt wurde. Dies betrifft Domänen, wie Hardware und Software, Roadmapping, Kontext, Innovation, IoT und andere. Neue Ontologien wurden entworfen, wie beispielsweise die Hardware-Software Allokations-Ontologie und eine domänen-spezifische "eFuse Ontologie". Das Ergebnis war eine modulare Ontologie-Bibliothek mit der GENIAL! Basic Ontology, die es erlaubt, automotive und mikroelektronische Komponenten, Funktionen, Eigenschaften und deren Abhängigkeiten basierend auf dem ISO26262 Standard zu entwerfen. Des weiteren ist Kontextwissen, welches Entwurfsentscheidungen beinflusst, inkludiert. Diese Wissensbasen sind in einem neuartigen Tool integriert, dass es ermöglicht, Roadmapwissen und Anforderungen durch die Automobil- Wertschöpfungskette hinweg auszutauschen. On tologien zu entwerfen und zu wissen, wie man diese benutzt, war dabei keine triviale Aufgabe und benötigte viel Hintergrund- und Kontextwissen. Ausgewählte Grundlagen hierfür sind Richtlinien, wie man Ontologien entwirft, Ontologiekategorien, sowie das Spektrum an Sprachen und Formen von Wissensrepresentationen. Des weiteren sind fort- geschrittene Methoden erläutert, z.B wie man mit Ontologien Schlußfolgerungen trifft. Am Schluss wird das Overall Framework demonstriert, und die Ontologie mit Reason- ing, Datenbank und APPEL/SysMD (AGILA ProPErty and Dependency Description Language / System MarkDown) und Constraints der Hardware / Software Wissensbasis gezeigt. Dabei werden exemplarisch Roadmap Constraints mit dem Automodell verbunden und durch den Constraint Solver gelöst und exploriert
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