940 research outputs found

    A BIM - GIS Integrated Information Model Using Semantic Web and RDF Graph Databases

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    In recent years, 3D virtual indoor and outdoor urban modelling has become an essential geospatial information framework for civil and engineering applications such as emergency response, evacuation planning, and facility management. Building multi-sourced and multi-scale 3D urban models are in high demand among architects, engineers, and construction professionals to achieve these tasks and provide relevant information to decision support systems. Spatial modelling technologies such as Building Information Modelling (BIM) and Geographical Information Systems (GIS) are frequently used to meet such high demands. However, sharing data and information between these two domains is still challenging. At the same time, the semantic or syntactic strategies for inter-communication between BIM and GIS do not fully provide rich semantic and geometric information exchange of BIM into GIS or vice-versa. This research study proposes a novel approach for integrating BIM and GIS using semantic web technologies and Resources Description Framework (RDF) graph databases. The suggested solution's originality and novelty come from combining the advantages of integrating BIM and GIS models into a semantically unified data model using a semantic framework and ontology engineering approaches. The new model will be named Integrated Geospatial Information Model (IGIM). It is constructed through three stages. The first stage requires BIMRDF and GISRDF graphs generation from BIM and GIS datasets. Then graph integration from BIM and GIS semantic models creates IGIMRDF. Lastly, the information from IGIMRDF unified graph is filtered using a graph query language and graph data analytics tools. The linkage between BIMRDF and GISRDF is completed through SPARQL endpoints defined by queries using elements and entity classes with similar or complementary information from properties, relationships, and geometries from an ontology-matching process during model construction. The resulting model (or sub-model) can be managed in a graph database system and used in the backend as a data-tier serving web services feeding a front-tier domain-oriented application. A case study was designed, developed, and tested using the semantic integrated information model for validating the newly proposed solution, architecture, and performance

    Design of an E-learning system using semantic information and cloud computing technologies

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    Humanity is currently suffering from many difficult problems that threaten the life and survival of the human race. It is very easy for all mankind to be affected, directly or indirectly, by these problems. Education is a key solution for most of them. In our thesis we tried to make use of current technologies to enhance and ease the learning process. We have designed an e-learning system based on semantic information and cloud computing, in addition to many other technologies that contribute to improving the educational process and raising the level of students. The design was built after much research on useful technology, its types, and examples of actual systems that were previously discussed by other researchers. In addition to the proposed design, an algorithm was implemented to identify topics found in large textual educational resources. It was tested and proved to be efficient against other methods. The algorithm has the ability of extracting the main topics from textual learning resources, linking related resources and generating interactive dynamic knowledge graphs. This algorithm accurately and efficiently accomplishes those tasks even for bigger books. We used Wikipedia Miner, TextRank, and Gensim within our algorithm. Our algorithm‘s accuracy was evaluated against Gensim, largely improving its accuracy. Augmenting the system design with the implemented algorithm will produce many useful services for improving the learning process such as: identifying main topics of big textual learning resources automatically and connecting them to other well defined concepts from Wikipedia, enriching current learning resources with semantic information from external sources, providing student with browsable dynamic interactive knowledge graphs, and making use of learning groups to encourage students to share their learning experiences and feedback with other learners.Programa de Doctorado en Ingeniería Telemática por la Universidad Carlos III de MadridPresidente: Luis Sánchez Fernández.- Secretario: Luis de la Fuente Valentín.- Vocal: Norberto Fernández Garcí

    Application of knowledge management principles to support maintenance strategies in healthcare organisations

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    Healthcare is a vital service that touches people's lives on a daily basis by providing treatment and resolving patients' health problems through the staff. Human lives are ultimately dependent on the skilled hands of the staff and those who manage the infrastructure that supports the daily operations of the service, making it a compelling reason for a dedicated research study. However, the UK healthcare sector is undergoing rapid changes, driven by rising costs, technological advancements, changing patient expectations, and increasing pressure to deliver sustainable healthcare. With the global rise in healthcare challenges, the need for sustainable healthcare delivery has become imperative. Sustainable healthcare delivery requires the integration of various practices that enhance the efficiency and effectiveness of healthcare infrastructural assets. One critical area that requires attention is the management of healthcare facilities. Healthcare facilitiesis considered one of the core elements in the delivery of effective healthcare services, as shortcomings in the provision of facilities management (FM) services in hospitals may have much more drastic negative effects than in any other general forms of buildings. An essential element in healthcare FM is linked to the relationship between action and knowledge. With a full sense of understanding of infrastructural assets, it is possible to improve, manage and make buildings suitable to the needs of users and to ensure the functionality of the structure and processes. The premise of FM is that an organisation's effectiveness and efficiency are linked to the physical environment in which it operates and that improving the environment can result in direct benefits in operational performance. The goal of healthcare FM is to support the achievement of organisational mission and goals by designing and managing space and infrastructural assets in the best combination of suitability, efficiency, and cost. In operational terms, performance refers to how well a building contributes to fulfilling its intended functions. Therefore, comprehensive deployment of efficient FM approaches is essential for ensuring quality healthcare provision while positively impacting overall patient experiences. In this regard, incorporating knowledge management (KM) principles into hospitals' FM processes contributes significantly to ensuring sustainable healthcare provision and enhancement of patient experiences. Organisations implementing KM principles are better positioned to navigate the constantly evolving business ecosystem easily. Furthermore, KM is vital in processes and service improvement, strategic decision-making, and organisational adaptation and renewal. In this regard, KM principles can be applied to improve hospital FM, thereby ensuring sustainable healthcare delivery. Knowledge management assumes that organisations that manage their organisational and individual knowledge more effectively will be able to cope more successfully with the challenges of the new business ecosystem. There is also the argument that KM plays a crucial role in improving processes and services, strategic decision-making, and adapting and renewing an organisation. The goal of KM is to aid action – providing "a knowledge pull" rather than the information overload most people experience in healthcare FM. Other motivations for seeking better KM in healthcare FM include patient safety, evidence-based care, and cost efficiency as the dominant drivers. The most evidence exists for the success of such approaches at knowledge bottlenecks, such as infection prevention and control, working safely, compliances, automated systems and reminders, and recall based on best practices. The ability to cultivate, nurture and maximise knowledge at multiple levels and in multiple contexts is one of the most significant challenges for those responsible for KM. However, despite the potential benefits, applying KM principles in hospital facilities is still limited. There is a lack of understanding of how KM can be effectively applied in this context, and few studies have explored the potential challenges and opportunities associated with implementing KM principles in hospitals facilities for sustainable healthcare delivery. This study explores applying KM principles to support maintenance strategies in healthcare organisations. The study also explores the challenges and opportunities, for healthcare organisations and FM practitioners, in operationalising a framework which draws the interconnectedness between healthcare. The study begins by defining healthcare FM and its importance in the healthcare industry. It then discusses the concept of KM and the different types of knowledge that are relevant in the healthcare FM sector. The study also examines the challenges that healthcare FM face in managing knowledge and how the application of KM principles can help to overcome these challenges. The study then explores the different KM strategies that can be applied in healthcare FM. The KM benefits include improved patient outcomes, reduced costs, increased efficiency, and enhanced collaboration among healthcare professionals. Additionally, issues like creating a culture of innovation, technology, and benchmarking are considered. In addition, a framework that integrates the essential concepts of KM in healthcare FM will be presented and discussed. The field of KM is introduced as a complex adaptive system with numerous possibilities and challenges. In this context, and in consideration of healthcare FM, five objectives have been formulated to achieve the research aim. As part of the research, a number of objectives will be evaluated, including appraising the concept of KM and how knowledge is created, stored, transferred, and utilised in healthcare FM, evaluating the impact of organisational structure on job satisfaction as well as exploring how cultural differences impact knowledge sharing and performance in healthcare FM organisations. This study uses a combination of qualitative methods, such as meetings, observations, document analysis (internal and external), and semi-structured interviews, to discover the subjective experiences of healthcare FM employees and to understand the phenomenon within a real-world context and attitudes of healthcare FM as the data collection method, using open questions to allow probing where appropriate and facilitating KM development in the delivery and practice of healthcare FM. The study describes the research methodology using the theoretical concept of the "research onion". The qualitative research was conducted in the NHS acute and non-acute hospitals in Northwest England. Findings from the research study revealed that while the concept of KM has grown significantly in recent years, KM in healthcare FM has received little or no attention. The target population was fifty (five FM directors, five academics, five industry experts, ten managers, ten supervisors, five team leaders and ten operatives). These seven groups were purposively selected as the target population because they play a crucial role in KM enhancement in healthcare FM. Face-to-face interviews were conducted with all participants based on their pre-determined availability. Out of the 50-target population, only 25 were successfully interviewed to the point of saturation. Data collected from the interview were coded and analysed using NVivo to identify themes and patterns related to KM in healthcare FM. The study is divided into eight major sections. First, it discusses literature findings regarding healthcare FM and KM, including underlying trends in FM, KM in general, and KM in healthcare FM. Second, the research establishes the study's methodology, introducing the five research objectives, questions and hypothesis. The chapter introduces the literature on methodology elements, including philosophical views and inquiry strategies. The interview and data analysis look at the feedback from the interviews. Lastly, a conclusion and recommendation summarise the research objectives and suggest further research. Overall, this study highlights the importance of KM in healthcare FM and provides insights for healthcare FM directors, managers, supervisors, academia, researchers and operatives on effectively leveraging knowledge to improve patient care and organisational effectiveness

    Methodological approaches and techniques for designing ontologies in information systems requirements engineering

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    Programa doutoral em Information Systems and TechnologyThe way we interact with the world around us is changing as new challenges arise, embracing innovative business models, rethinking the organization and processes to maximize results, and evolving change management. Currently, and considering the projects executed, the methodologies used do not fully respond to the companies' needs. On the one hand, organizations are not familiar with the languages used in Information Systems, and on the other hand, they are often unable to validate requirements or business models. These are some of the difficulties encountered that lead us to think about formulating a new approach. Thus, the state of the art presented in this paper includes a study of the models involved in the software development process, where traditional methods and the rivalry of agile methods are present. In addition, a survey is made about Ontologies and what methods exist to conceive, transform, and represent them. Thus, after analyzing some of the various possibilities currently available, we began the process of evolving a method and developing an approach that would allow us to design ontologies. The method we evolved and adapted will allow us to derive terminologies from a specific domain, aggregating them in order to facilitate the construction of a catalog of terminologies. Next, the definition of an approach to designing ontologies will allow the construction of a domain-specific ontology. This approach allows in the first instance to integrate and store the data from different information systems of a given organization. In a second instance, the rules for mapping and building the ontology database are defined. Finally, a technological architecture is also proposed that will allow the mapping of an ontology through the construction of complex networks, allowing mapping and relating terminologies. This doctoral work encompasses numerous Research & Development (R&D) projects belonging to different domains such as Software Industry, Textile Industry, Robotic Industry and Smart Cities. Finally, a critical and descriptive analysis of the work done is performed, and we also point out perspectives for possible future work.A forma como interagimos com o mundo à nossa volta está a mudar à medida que novos desafios surgem, abraçando modelos empresariais inovadores, repensando a organização e os processos para maximizar os resultados, e evoluindo a gestão da mudança. Atualmente, e considerando os projetos executados, as metodologias utilizadas não respondem na totalidade às necessidades das empresas. Por um lado, as organizações não estão familiarizadas com as linguagens utilizadas nos Sistemas de Informação, por outro lado, são muitas vezes incapazes de validar requisitos ou modelos de negócio. Estas são algumas das dificuldades encontradas que nos levam a pensar na formulação de uma nova abordagem. Assim, o estado da arte apresentado neste documento inclui um estudo dos modelos envolvidos no processo de desenvolvimento de software, onde os métodos tradicionais e a rivalidade de métodos ágeis estão presentes. Além disso, é efetuado um levantamento sobre Ontologias e quais os métodos existentes para as conceber, transformar e representar. Assim, e após analisarmos algumas das várias possibilidades atualmente disponíveis, iniciou-se o processo de evolução de um método e desenvolvimento de uma abordagem que nos permitisse conceber ontologias. O método que evoluímos e adaptamos permitirá derivar terminologias de um domínio específico, agregando-as de forma a facilitar a construção de um catálogo de terminologias. Em seguida, a definição de uma abordagem para conceber ontologias permitirá a construção de uma ontologia de um domínio específico. Esta abordagem permite em primeira instância, integrar e armazenar os dados de diferentes sistemas de informação de uma determinada organização. Num segundo momento, são definidas as regras para o mapeamento e construção da base de dados ontológica. Finalmente, é também proposta uma arquitetura tecnológica que permitirá efetuar o mapeamento de uma ontologia através da construção de redes complexas, permitindo mapear e relacionar terminologias. Este trabalho de doutoramento engloba inúmeros projetos de Investigação & Desenvolvimento (I&D) pertencentes a diferentes domínios como por exemplo Indústria de Software, Indústria Têxtil, Indústria Robótica e Smart Cities. Finalmente, é realizada uma análise critica e descritiva do trabalho realizado, sendo que apontamos ainda perspetivas de possíveis trabalhos futuros

    Making Presentation Math Computable

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    This Open-Access-book addresses the issue of translating mathematical expressions from LaTeX to the syntax of Computer Algebra Systems (CAS). Over the past decades, especially in the domain of Sciences, Technology, Engineering, and Mathematics (STEM), LaTeX has become the de-facto standard to typeset mathematical formulae in publications. Since scientists are generally required to publish their work, LaTeX has become an integral part of today's publishing workflow. On the other hand, modern research increasingly relies on CAS to simplify, manipulate, compute, and visualize mathematics. However, existing LaTeX import functions in CAS are limited to simple arithmetic expressions and are, therefore, insufficient for most use cases. Consequently, the workflow of experimenting and publishing in the Sciences often includes time-consuming and error-prone manual conversions between presentational LaTeX and computational CAS formats. To address the lack of a reliable and comprehensive translation tool between LaTeX and CAS, this thesis makes the following three contributions. First, it provides an approach to semantically enhance LaTeX expressions with sufficient semantic information for translations into CAS syntaxes. Second, it demonstrates the first context-aware LaTeX to CAS translation framework LaCASt. Third, the thesis provides a novel approach to evaluate the performance for LaTeX to CAS translations on large-scaled datasets with an automatic verification of equations in digital mathematical libraries. This is an open access book

    Situating Data: Inquiries in Algorithmic Culture

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    Taking up the challenges of the datafication of culture, as well as of the scholarship of cultural inquiry itself, this collection contributes to the critical debate about data and algorithms. How can we understand the quality and significance of current socio-technical transformations that result from datafication and algorithmization? How can we explore the changing conditions and contours for living within such new and changing frameworks? How can, or should we, think and act within, but also in response to these conditions? This collection brings together various perspectives on the datafication and algorithmization of culture from debates and disciplines within the field of cultural inquiry, specifically (new) media studies, game studies, urban studies, screen studies, and gender and postcolonial studies. It proposes conceptual and methodological directions for exploring where, when, and how data and algorithms (re)shape cultural practices, create (in)justice, and (co)produce knowledge

    Improving interoperability on industrial standards through ontologies

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    Interoperability refers to the effective exchange of information and understanding to collectively pursue common objectives. System developers commonly use ontologies to enhance semantic and syntactic interoperability within this context. This work aims to evaluate the contribution of ontology in making explicit the meaning of the entities described in a Piping and Instrumentation Diagram (P&ID) model and to provide an architecture that allows the representation of a P&ID in ontological knowledge bases. To understand the semantics of the P&ID entities and relations, we map each class of the P&ID to the corresponding entity of the Offshore Petroleum Production Plant Ontology (O3PO). The ontology describes the definition of each vocable associated with the axioms that clarify and regulate the meaning and utilization of this vocabulary. We intend to guarantee that the integration of P&ID with other models respects the original semantics and avoids unintended data exchanges. We follow this ontological analysis with a case study of a model that conforms to the Data Exchange in the Process Industry (DEXPI) specification, intended to provide homogeneous data interchange between CAD systems from diverse vendors. The ontological analysis of the DEXPI P&ID specification, to build a relation with a well-founded ontology, raises a set of desirable properties for a model intended for use in interoperability. While achieving technical interoperability between DEXPI P&IDs and ontologies represented in OWL is evident, we identified several challenges within the realm of semantic interoperability, specifically concerning clarity/intelligibility, conciseness, extendibility, consistency, and essence. These issues present significant hurdles to achieving seamless systems integration. Moreover, if the DEXPI standard were to evolve into a de facto standard for representing P&IDs across a broader range of domains than initially intended, these highlighted issues could potentially bottleneck its adoption and hinder its integration into different systems.Interoperabilidade se refere à troca efetiva de informação e entendimento na busca por objetivos comuns. Neste contexto, desenvolvedores de sistemas comumente utilizam ontologias para aprimorar a interoperabilidade semântica e sintática. O objetivo deste trabalho é avaliar a contribuição da ontologia para tornar explícito o significado das entidades descritas em um modelo de Diagrama de Tubulação e Instrumentação (DTI) e fornecer uma arquitetura que permita a representação de um DTI em bases de conhecimento ontológicas. Para entender a semântica das entidades e relações do DTI, mapeamos cada classe do DTI para a entidade correspondente da Ontologia de Planta de Produção de Petróleo Offshore (O3PO). A ontologia descreve a definição de cada vocábulo associado com os axiomas que esclarecem e regulam o significado e a utilização desse vocabulário. Pretendemos garantir que a integração do DTI com outros modelos respeite a semântica original e, assim, evite trocas de dados não intencionais. Seguimos essa análise ontológica com um estudo de caso de um modelo que se conforma à especificação "Data Exchange in the Process Industry" (DEXPI), destinada a fornecer uma troca de dados homogênea entre sistemas CAD de diversos fabricantes. A análise ontológica da especificação DEXPI DTI, para construir uma relação com uma ontologia bem fundamentada, levanta um conjunto de propriedades desejáveis para um modelo destinado a ser usado na interoperabilidade. Embora a conquista da interoperabilidade técnica entre DTIs DEXPI e ontologias representadas em OWL seja evidente, diversos desafios foram identificados no âmbito da interoperabilidade semântica, especificamente em relação à clareza/inteligibilidade, concisão, extensibilidade, consistência e essência. Essas questões representam obstáculos significativos para alcançar uma integração de sistemas perfeita. Além disso, se o padrão DEXPI evoluir para um padrão de facto para a representação de DTIs em um conjunto mais amplo de domínios do que inicialmente pretendido, essas questões destacadas poderiam potencialmente atrasar sua adoção e dificultar sua integração em sistemas diferentes

    Vers l’élaboration d’un système d’organisation des connaissances en allergologie : l’analyse des documents et des pratiques informationnelles des acteurs

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    The aim of the present thesis, funded by the Occitanie Region (2019-2023), is to construct a knowledge organization system (KOS) for the Allergy Unit of the Montpellier University Hospital (France), to represent and organize the complexity of allergy knowledge. Currently, there is no KOS that might be used by allergy professionals and researchers for their information processing and seeking activities. Allergy knowledge, produced by different actors, is abundant and heterogeneous, and keeps developing in parallel with the massification of health data. To allow and provide access to this knowledge, it is crucial to identify and characterize it, first by focusing on what might be useful for professionals’ daily activities and then by structuring it in a system of organization and documentary representation possibly linking the different ways of representing knowledge by different actors in this domain. Therefore, we propose a KOS in allergy, reached through a contextualized approach that relies, on one hand, on the analysis of the context of use of specialized knowledge, by the study of the informational practices of professionals who seek, produce, and mobilize knowledge in the domain; and on the other hand, on the analysis of a corpus of documents that professionals use in their daily activities. Through our work, we perform an epistemological reflection within the Information & Communication Sciences, by showing how the analysis of informational practices contributes to the construction of a KOS for a medical domain. Moreover, we try to answer a methodological question, linked with the development of a KOS in allergy, and evaluate if our conception method, oriented by a contextualized approach, allows to propose a useful KOS for the practices of the actors in this domain

    Exploring vocabulary learning strategy using online learning management system among TESL trainee teachers

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    Vocabulary learning strategy (VLS) is a very significant process for the second language learner (L2) in acquiring wide vocabulary especially for TESL teacher trainees for their future usage. However, VLSs are not being emphasized and specified in the structure of the TESL programme at Institute of Teacher Education (ITE) of the study. So, online learning management system (LMS), Schoology becomes a major platform in exploring VLSs in this study. The study aims to (i) examine the types of VLSs used by the TESL trainee teachers; (ii) explore on how an LMS helps TESL trainee teachers in enhancing their VLSs; and (iii) investigate the issues or challenges faced by the TESL trainee teachers in using LMS. This qualitative study used multiple methods such as interviews, online postings and discussion via LMS Schoology and field notes. It involved 14 research participants in three phases within 15- week interactions. During the phases, they had to write online reflections based on the tasks given via the LMS which were analysed using CEFR Text Analyzer. The structured online interviews, field notes and face-to-face interviews were analysed thematically using ATLAS.ti Software. The findings indicated the research participants had used VLSs similarly that had been highlighted in Gu and Johnson's (1996) vocabulary learning domain, metacognitive and cognitive strategies. In this study, online and modification strategies are two strategies used by the research participants that had been explored through the LMS. This study depicts how LMS helps the TESL trainee teachers in enhancing their VLSs and presents some issues and challenges faced by the research participants. This study was significant for trainee teachers, teacher trainers, the curriculum developers, and L2 researchers. There is a need to maximize the use of LMS in increasing TESL trainee teachers’ vocabulary learning through more VLSs for successful teaching and learning process

    Linguistically-Informed Neural Architectures for Lexical, Syntactic and Semantic Tasks in Sanskrit

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    The primary focus of this thesis is to make Sanskrit manuscripts more accessible to the end-users through natural language technologies. The morphological richness, compounding, free word orderliness, and low-resource nature of Sanskrit pose significant challenges for developing deep learning solutions. We identify four fundamental tasks, which are crucial for developing a robust NLP technology for Sanskrit: word segmentation, dependency parsing, compound type identification, and poetry analysis. The first task, Sanskrit Word Segmentation (SWS), is a fundamental text processing task for any other downstream applications. However, it is challenging due to the sandhi phenomenon that modifies characters at word boundaries. Similarly, the existing dependency parsing approaches struggle with morphologically rich and low-resource languages like Sanskrit. Compound type identification is also challenging for Sanskrit due to the context-sensitive semantic relation between components. All these challenges result in sub-optimal performance in NLP applications like question answering and machine translation. Finally, Sanskrit poetry has not been extensively studied in computational linguistics. While addressing these challenges, this thesis makes various contributions: (1) The thesis proposes linguistically-informed neural architectures for these tasks. (2) We showcase the interpretability and multilingual extension of the proposed systems. (3) Our proposed systems report state-of-the-art performance. (4) Finally, we present a neural toolkit named SanskritShala, a web-based application that provides real-time analysis of input for various NLP tasks. Overall, this thesis contributes to making Sanskrit manuscripts more accessible by developing robust NLP technology and releasing various resources, datasets, and web-based toolkit.Comment: Ph.D. dissertatio
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