5,567 research outputs found

    Towards a framework for the study of ongoing socio-technical transitions: explored through the UK self-driving car paradigm

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    The UK government set out to see self-driving cars on roads by 2021. The idea of a self-driving car has been around for almost a century, and more recent technological developments have made self-driving cars a real-life possibility. While a fully self-driving automobility system is some distance away, real-life testing is bringing autonomous driving closer to consumers. Some claim this to be the biggest disruption to mobility systems since the invention of the car. Claims about the potential of self-driving mobility range from economic and social benefits to environmental improvements. A significant ambiguity however remains concerning how they will be deployed and how the technological innovation will affect mobility aims and related transport and infrastructure systems. So far, the vast majority of studies on AVs have focused on the technology aspect of this transition lacking contributions that address this from a broader socio-technical perspective. With the accelerated adoption of new technologies, Sustainability Transitions has come to prominence as a research area that seeks to understand and guide socio-technical transitions toward sustainable trajectories. Socio-technical transitions theoretical framework has been used to understand historical transitions in the majority of empirical applications. The ability to apply the same framework to ongoing transitions and to guide these towards sustainable outcomes remains unsubstantiated. To address this gap this thesis examines the foundations of multi-level perspective (MLP) – a socio-technical transitions analytical framework – and develops an analytical framework (SRPM – System Rules Pathways Mechanisms) that is appropriate for the study of ongoing transitions. The refocused framework incorporates critical realism to focus analysis on causation and causal mechanisms. It is used to analyse the ongoing socio-technical transition to self-driving cars in the UK through a four-step analytical process. The study is framed as a case-based process mechanism study. The four steps are: i) contextualisation of the ongoing transition to AVs in the UK as a socio-technical transition based on the MLP theoretical framework; ii) identification of internal and external structural relations within the transition through the notion of rules and the morphogenetic cycle; iii) aligning observed processes with transition pathways to theorise about the trajectories of the transition; iv) identification of causal mechanisms in the observed processes through identification of demi-regularities through data analysis of grey literature and theorisation about mechanisms through the development of mechanism sketches and schemata. The thesis makes two contributions to knowledge: i) methodological and ii) empirical. The methodological contribution is the development of the SRPM analytical framework to study an ongoing socio-technical transition, and the empirical contribution is the application of this framework to the study of the ongoing transition to driverless cars in the UK

    A Data-driven Approach to Large Knowledge Graph Matching

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    In the last decade, a remarkable number of open Knowledge Graphs (KGs) were developed, such as DBpedia, NELL, and YAGO. While some of such KGs are curated via crowdsourcing platforms, others are semi-automatically constructed. This has resulted in a significant degree of semantic heterogeneity and overlapping facts. KGs are highly complementary; thus, mapping them can benefit intelligent applications that require integrating different KGs such as recommendation systems, query answering, and semantic web navigation. Although the problem of ontology matching has been investigated and a significant number of systems have been developed, the challenges of mapping large-scale KGs remain significant. KG matching has been a topic of interest in the Semantic Web community since it has been introduced to the Ontology Alignment Evaluation Initiative (OAEI) in 2018. Nonetheless, a major limitation of the current benchmarks is their lack of representation of real-world KGs. This work also highlights a number of limitations with current matching methods, such as: (i) they are highly dependent on string-based similarity measures, and (ii) they are primarily built to handle well-formed ontologies. These features make them unsuitable for large, (semi/fully) automatically constructed KGs with hundreds of classes and millions of instances. Another limitation of current work is the lack of benchmark datasets that represent the challenging task of matching real-world KGs. This work addresses the limitation of the current datasets by first introducing two gold standard datasets for matching the schema of large, automatically constructed, less-well-structured KGs based on common KGs such as NELL, DBpedia, and Wikidata. We believe that the datasets which we make public in this work make the largest domain-independent benchmarks for matching KG classes. As many state-of-the-art methods are not suitable for matching large-scale and cross-domain KGs that often suffer from highly imbalanced class distribution, recent studies have revisited instance-based matching techniques in addressing this task. This is because such large KGs often lack a well-defined structure and descriptive metadata about their classes, but contain numerous class instances. Therefore, inspired by the role of instances in KGs, we propose a hybrid matching approach. Our method composes an instance-based matcher that casts the schema-matching process as a text classification task by exploiting instances of KG classes, and a string-based matcher. Our method is domain-independent and is able to handle KG classes with imbalanced populations. Further, we show that incorporating an instance-based approach with the appropriate data balancing strategy results in significant results in matching large and common KG classes

    Subsidiary Entrepreneurial Alertness: Antecedents and Outcomes

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    This thesis brings together concepts from both international business and entrepreneurship to develop a framework of the facilitators of subsidiary innovation and performance. This study proposes that Subsidiary Entrepreneurial Alertness (SEA) facilitates the recognition of opportunities (the origin of subsidiary initiatives). First introduced by Kirzner (1979) in the context of the individual, entrepreneurial alertness (EA) is the ability to notice an opportunity without actively searching. Similarly, to entrepreneurial alertness at the individual level, this study argues that SEA enables the subsidiary to best select opportunities based on resources available. The research further develops our conceptualisation of SEA by drawing on work by Tang et al. (2012) identifying three distinct activities of EA: scanning and search (identifying opportunities unseen by others due to their awareness gaps), association and connection of information, and evaluation and judgement to interpret or anticipate future viability of opportunities. This study then hypothesises that SEA leads to opportunity recognition at the subsidiary level and further hypothesises innovation and performance as outcomes of opportunity recognition. This research brings these arguments together to develop and test a comprehensive theoretical model. The theoretical model is tested through a mail survey of the CEOs/MDs of foreign subsidiaries within the Republic of Ireland (an innovative hub for foreign subsidiaries). This method was selected as the best method to reach the targeted respondent, and due to the depth of knowledge the target respondent holds, the survey can answer the desired question more substantially. The results were examined using partial least squares structural equation modelling (PLS-SEM). The study’s findings confirm two critical aspects of subsidiary context, subsidiary brokerage and subsidiary credibility are positively related to SEA. The study establishes a positive link between SEA and both the generation of innovation and the subsidiary’s performance. This thesis makes three significant contributions to the subsidiary literature as it 1) introduces and develops the concept of SEA, 2) identifies the antecedents of SEA, and 3) demonstrates the impact of SEA on subsidiary opportunity recognition. Implications for subsidiaries, headquarters and policy makers are discussed along with the limitations of the study

    Examples of works to practice staccato technique in clarinet instrument

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    Klarnetin staccato tekniğini güçlendirme aşamaları eser çalışmalarıyla uygulanmıştır. Staccato geçişlerini hızlandıracak ritim ve nüans çalışmalarına yer verilmiştir. Çalışmanın en önemli amacı sadece staccato çalışması değil parmak-dilin eş zamanlı uyumunun hassasiyeti üzerinde de durulmasıdır. Staccato çalışmalarını daha verimli hale getirmek için eser çalışmasının içinde etüt çalışmasına da yer verilmiştir. Çalışmaların üzerinde titizlikle durulması staccato çalışmasının ilham verici etkisi ile müzikal kimliğe yeni bir boyut kazandırmıştır. Sekiz özgün eser çalışmasının her aşaması anlatılmıştır. Her aşamanın bir sonraki performans ve tekniği güçlendirmesi esas alınmıştır. Bu çalışmada staccato tekniğinin hangi alanlarda kullanıldığı, nasıl sonuçlar elde edildiği bilgisine yer verilmiştir. Notaların parmak ve dil uyumu ile nasıl şekilleneceği ve nasıl bir çalışma disiplini içinde gerçekleşeceği planlanmıştır. Kamış-nota-diyafram-parmak-dil-nüans ve disiplin kavramlarının staccato tekniğinde ayrılmaz bir bütün olduğu saptanmıştır. Araştırmada literatür taraması yapılarak staccato ile ilgili çalışmalar taranmıştır. Tarama sonucunda klarnet tekniğin de kullanılan staccato eser çalışmasının az olduğu tespit edilmiştir. Metot taramasında da etüt çalışmasının daha çok olduğu saptanmıştır. Böylelikle klarnetin staccato tekniğini hızlandırma ve güçlendirme çalışmaları sunulmuştur. Staccato etüt çalışmaları yapılırken, araya eser çalışmasının girmesi beyni rahatlattığı ve istekliliği daha arttırdığı gözlemlenmiştir. Staccato çalışmasını yaparken doğru bir kamış seçimi üzerinde de durulmuştur. Staccato tekniğini doğru çalışmak için doğru bir kamışın dil hızını arttırdığı saptanmıştır. Doğru bir kamış seçimi kamıştan rahat ses çıkmasına bağlıdır. Kamış, dil atma gücünü vermiyorsa daha doğru bir kamış seçiminin yapılması gerekliliği vurgulanmıştır. Staccato çalışmalarında baştan sona bir eseri yorumlamak zor olabilir. Bu açıdan çalışma, verilen müzikal nüanslara uymanın, dil atış performansını rahatlattığını ortaya koymuştur. Gelecek nesillere edinilen bilgi ve birikimlerin aktarılması ve geliştirici olması teşvik edilmiştir. Çıkacak eserlerin nasıl çözüleceği, staccato tekniğinin nasıl üstesinden gelinebileceği anlatılmıştır. Staccato tekniğinin daha kısa sürede çözüme kavuşturulması amaç edinilmiştir. Parmakların yerlerini öğrettiğimiz kadar belleğimize de çalışmaların kaydedilmesi önemlidir. Gösterilen azmin ve sabrın sonucu olarak ortaya çıkan yapıt başarıyı daha da yukarı seviyelere çıkaracaktır

    Bibliographic Control in the Digital Ecosystem

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    With the contributions of international experts, the book aims to explore the new boundaries of universal bibliographic control. Bibliographic control is radically changing because the bibliographic universe is radically changing: resources, agents, technologies, standards and practices. Among the main topics addressed: library cooperation networks; legal deposit; national bibliographies; new tools and standards (IFLA LRM, RDA, BIBFRAME); authority control and new alliances (Wikidata, Wikibase, Identifiers); new ways of indexing resources (artificial intelligence); institutional repositories; new book supply chain; “discoverability” in the IIIF digital ecosystem; role of thesauri and ontologies in the digital ecosystem; bibliographic control and search engines

    Technologies and Applications for Big Data Value

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    This open access book explores cutting-edge solutions and best practices for big data and data-driven AI applications for the data-driven economy. It provides the reader with a basis for understanding how technical issues can be overcome to offer real-world solutions to major industrial areas. The book starts with an introductory chapter that provides an overview of the book by positioning the following chapters in terms of their contributions to technology frameworks which are key elements of the Big Data Value Public-Private Partnership and the upcoming Partnership on AI, Data and Robotics. The remainder of the book is then arranged in two parts. The first part “Technologies and Methods” contains horizontal contributions of technologies and methods that enable data value chains to be applied in any sector. The second part “Processes and Applications” details experience reports and lessons from using big data and data-driven approaches in processes and applications. Its chapters are co-authored with industry experts and cover domains including health, law, finance, retail, manufacturing, mobility, and smart cities. Contributions emanate from the Big Data Value Public-Private Partnership and the Big Data Value Association, which have acted as the European data community's nucleus to bring together businesses with leading researchers to harness the value of data to benefit society, business, science, and industry. The book is of interest to two primary audiences, first, undergraduate and postgraduate students and researchers in various fields, including big data, data science, data engineering, and machine learning and AI. Second, practitioners and industry experts engaged in data-driven systems, software design and deployment projects who are interested in employing these advanced methods to address real-world problems

    Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries

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    This two-volume set LNCS 12962 and 12963 constitutes the thoroughly refereed proceedings of the 7th International MICCAI Brainlesion Workshop, BrainLes 2021, as well as the RSNA-ASNR-MICCAI Brain Tumor Segmentation (BraTS) Challenge, the Federated Tumor Segmentation (FeTS) Challenge, the Cross-Modality Domain Adaptation (CrossMoDA) Challenge, and the challenge on Quantification of Uncertainties in Biomedical Image Quantification (QUBIQ). These were held jointly at the 23rd Medical Image Computing for Computer Assisted Intervention Conference, MICCAI 2020, in September 2021. The 91 revised papers presented in these volumes were selected form 151 submissions. Due to COVID-19 pandemic the conference was held virtually. This is an open access book

    Good Issues and bad tidying: what GitHub can tell us about agency in project-based group modelling work for higher education

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    Collaborative project work in technology-enabled environments at university is essential for learners to become ready for an increasingly global, complex, and virtualised workplace. Research on effective pedagogical and technical design for computer supported collaborative learning in higher education (CSCL) has often taken place in synchronous contexts, using specialised technology platforms. However, large-scale changes to work and education resulting from the COVID-19 pandemic necessitate the development of pedagogical and research approaches that support students working asynchronously, in distributed teams, using collaboration platforms that extend beyond institutional infrastructure. Within the field of CSCL, knowledge building research has shown collaboration to be a complex systems phenomenon, involving the intersection of individual and collective efforts to actively advance the group’s shared knowledge, but studies analysing interaction data have been resource-intensive to conduct. Contemporary workplace platforms such as professional knowledge environments have multiple design affordances consistent with knowledge building principles, as well as the capacity to generate rich data about user activity. However, we have little understanding to date as to how these environments can support knowledge building pedagogies and facilitate associated research. This study uses a case study approach and thematic analysis to investigate the activity of three university groups engaged in a collaborative modelling task over time. It investigates how agency emerges during project work in professional knowledge environments, and how the system interaction data can extend our understanding of effective collaboration processes. The results show that the GitHub platform can support knowledge building pedagogical designs in facilitating individual and collective agency in higher education group work, and provide insights into epistemic, regulative and relational aspects of learner behaviour at individual and group levels. These findings extend our understanding of effective learning design to novel environments of a type likely to be used by our students in the workplace, and make design and methodological contributions to research on computer-supported collaborative learning

    From wallet to mobile: exploring how mobile payments create customer value in the service experience

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    This study explores how mobile proximity payments (MPP) (e.g., Apple Pay) create customer value in the service experience compared to traditional payment methods (e.g. cash and card). The main objectives were firstly to understand how customer value manifests as an outcome in the MPP service experience, and secondly to understand how the customer activities in the process of using MPP create customer value. To achieve these objectives a conceptual framework is built upon the Grönroos-Voima Value Model (Grönroos and Voima, 2013), and uses the Theory of Consumption Value (Sheth et al., 1991) to determine the customer value constructs for MPP, which is complimented with Script theory (Abelson, 1981) to determine the value creating activities the consumer does in the process of paying with MPP. The study uses a sequential exploratory mixed methods design, wherein the first qualitative stage uses two methods, self-observations (n=200) and semi-structured interviews (n=18). The subsequent second quantitative stage uses an online survey (n=441) and Structural Equation Modelling analysis to further examine the relationships and effect between the value creating activities and customer value constructs identified in stage one. The academic contributions include the development of a model of mobile payment services value creation in the service experience, introducing the concept of in-use barriers which occur after adoption and constrains the consumers existing use of MPP, and revealing the importance of the mobile in-hand momentary condition as an antecedent state. Additionally, the customer value perspective of this thesis demonstrates an alternative to the dominant Information Technology approaches to researching mobile payments and broadens the view of technology from purely an object a user interacts with to an object that is immersed in consumers’ daily life
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