8,688 research outputs found

    With the Participatory Consumer Audience in mind: exploring and developing professional brand identity designers reflexive practice

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    This PhD reflects upon first-hand unidirectional and passive consumer audience experience approaches prevalent in professional UK brand identity design. It explores: How brand identity designers might move towards an improved reflexive practice in the design of consumer audience experiences. This practice-led research focuses on the ideas generation stage of their design process. An ongoing constructivist audience paradigm shift signals that when thinking about and using their positionality in relation to their consumer audience experiences, designers need reflexive practice to support critical reflection of themselves, their biases and assumptions. This research uncovered a lack of relevant theory regarding reflexive practice specific to the context of brand identity design. This insufficiency throws into doubt designers' relational, participatory and equitable approaches in their working practices and their abilities to address market imperatives, including client requirements connected to the ongoing audience paradigm shift. Aligned with John Dewey's ethical pragmatism and drawing from Creswell, Tashakkori and Teddlie, my study adopts a mixed methods methodology. Alongside established qualitative and quantitative methods, this includes my practice via design visualisations, as discussed by Drucker, and builds upon Carl DiSalvo's approach of practice used to do inquiry and design as a method of inquiry. My practice enabled me to critically reflect, evaluate and construct reflexive practice knowledge, including the development of reflexive practice communications, to advance understanding of and improve other designers' reflexive practice, and to communicate my process of reflexive design practice research. Thirty UK-based professional brand identity designers participated in this research: nineteen participants in Phase One, a questionnaire, and six in Phase Two semi-structured interviews. Phase One and Two findings identified a gap in that designers are not employing a reflexive design practice and lack the resources to do so. Seeking to improve these shortcomings, eighteen initial reflexive design practice principles were explored and tested in Phase Three, a workshop involving five design participants. Results showed that the principles facilitated participants to advance prior thinking and engage in a reflexive design practice. Further reflections and insights from the same five Phase Three participants uncovered a need to refine and reduce the principles and communicate them in a guide. Eight revised overarching and eighteen sub-principles in a prototype guide were explored in Phase Four in applied practice by three brand identity designers involved in Phase Three. Results corroborated workshop findings and provided further recommendations. Contributions of this research are three-fold. First, offering an advanced understanding of professional brand identity designers' reflexive practice and process knowledge. Second, it produced a reflexive design guide with eight overarching and eighteen sub-reflexive design principles and corresponding digital app, thereby offering a preliminary new design practice method. This method offers a way to improve designers' thinking about and operation of their relational positionality, participatory consumer audience experience approaches, and reflexive design practice actions. Third, it provides a contribution to knowledge via its methodology, which integrates design visualisation practice into a mixed methods approach

    An extracellular receptor tyrosine kinase motif orchestrating intracellular STAT activation

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    The ErbB4 receptor isoforms JM-a and JM-b differ within their extracellular juxtamembrane (eJM) domains. Here, ErbB4 isoforms are used as a model to address the effect of structural variation in the eJM domain of receptor tyrosine kinases (RTK) on downstream signaling. A specific JM-a-like sequence motif is discovered, and its presence or absence (in JM-b-like RTKs) in the eJM domains of several RTKs is demonstrated to dictate selective STAT activation. STAT5a activation by RTKs including the JM-a like motif is shown to involve interaction with oligosaccharides of N-glycosylated cell surface proteins such as β1 integrin, whereas STAT5b activation by JM-b is dependent on TYK2. ErbB4 JM-a- and JM-b-like RTKs are shown to associate with specific signaling complexes at different cell surface compartments using analyses of RTK interactomes and super-resolution imaging. These findings provide evidence for a conserved mechanism linking a ubiquitous extracellular motif in RTKs with selective intracellular STAT signaling

    Conversations on Empathy

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    In the aftermath of a global pandemic, amidst new and ongoing wars, genocide, inequality, and staggering ecological collapse, some in the public and political arena have argued that we are in desperate need of greater empathy — be this with our neighbours, refugees, war victims, the vulnerable or disappearing animal and plant species. This interdisciplinary volume asks the crucial questions: How does a better understanding of empathy contribute, if at all, to our understanding of others? How is it implicated in the ways we perceive, understand and constitute others as subjects? Conversations on Empathy examines how empathy might be enacted and experienced either as a way to highlight forms of otherness or, instead, to overcome what might otherwise appear to be irreducible differences. It explores the ways in which empathy enables us to understand, imagine and create sameness and otherness in our everyday intersubjective encounters focusing on a varied range of "radical others" – others who are perceived as being dramatically different from oneself. With a focus on the importance of empathy to understand difference, the book contends that the role of empathy is critical, now more than ever, for thinking about local and global challenges of interconnectedness, care and justice

    Software Design Change Artifacts Generation through Software Architectural Change Detection and Categorisation

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    Software is solely designed, implemented, tested, and inspected by expert people, unlike other engineering projects where they are mostly implemented by workers (non-experts) after designing by engineers. Researchers and practitioners have linked software bugs, security holes, problematic integration of changes, complex-to-understand codebase, unwarranted mental pressure, and so on in software development and maintenance to inconsistent and complex design and a lack of ways to easily understand what is going on and what to plan in a software system. The unavailability of proper information and insights needed by the development teams to make good decisions makes these challenges worse. Therefore, software design documents and other insightful information extraction are essential to reduce the above mentioned anomalies. Moreover, architectural design artifacts extraction is required to create the developer’s profile to be available to the market for many crucial scenarios. To that end, architectural change detection, categorization, and change description generation are crucial because they are the primary artifacts to trace other software artifacts. However, it is not feasible for humans to analyze all the changes for a single release for detecting change and impact because it is time-consuming, laborious, costly, and inconsistent. In this thesis, we conduct six studies considering the mentioned challenges to automate the architectural change information extraction and document generation that could potentially assist the development and maintenance teams. In particular, (1) we detect architectural changes using lightweight techniques leveraging textual and codebase properties, (2) categorize them considering intelligent perspectives, and (3) generate design change documents by exploiting precise contexts of components’ relations and change purposes which were previously unexplored. Our experiment using 4000+ architectural change samples and 200+ design change documents suggests that our proposed approaches are promising in accuracy and scalability to deploy frequently. Our proposed change detection approach can detect up to 100% of the architectural change instances (and is very scalable). On the other hand, our proposed change classifier’s F1 score is 70%, which is promising given the challenges. Finally, our proposed system can produce descriptive design change artifacts with 75% significance. Since most of our studies are foundational, our approaches and prepared datasets can be used as baselines for advancing research in design change information extraction and documentation

    A Prototype “Debugger” for Search Strategies

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    Knowledge workers such as healthcare information professionals, legal researchers, and librarians need to create and execute search strategies that are effective, efficient and error-free. The traditional solution is to use command-line query builders offered by proprietary database vendors. However, these are based on an archaic approach that offers limited support for the validation and optimisation of their output. Consequently, there are often errors in search strategies reported in the literature that prevent them from being effectively reused or extended. In this paper, we demonstrate a new approach that takes inspiration from software development practice and applies it to the challenge of search strategy formulation. We demonstrate a prototype ‘debugger’ which provides insight into the construction and semantics of search strategies, allowing users to inspect, understand and validate their behaviour and effects. This has the potential to eliminate many sources of error and offers new ways to validate, optimise and re-use search strategies and best practices

    Current and Future Challenges in Knowledge Representation and Reasoning

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    Knowledge Representation and Reasoning is a central, longstanding, and active area of Artificial Intelligence. Over the years it has evolved significantly; more recently it has been challenged and complemented by research in areas such as machine learning and reasoning under uncertainty. In July 2022 a Dagstuhl Perspectives workshop was held on Knowledge Representation and Reasoning. The goal of the workshop was to describe the state of the art in the field, including its relation with other areas, its shortcomings and strengths, together with recommendations for future progress. We developed this manifesto based on the presentations, panels, working groups, and discussions that took place at the Dagstuhl Workshop. It is a declaration of our views on Knowledge Representation: its origins, goals, milestones, and current foci; its relation to other disciplines, especially to Artificial Intelligence; and on its challenges, along with key priorities for the next decade

    Sociotechnical Imaginaries, the Future and the Third Offset Strategy

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    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

    “So what if ChatGPT wrote it?” Multidisciplinary perspectives on opportunities, challenges and implications of generative conversational AI for research, practice and policy

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    Transformative artificially intelligent tools, such as ChatGPT, designed to generate sophisticated text indistinguishable from that produced by a human, are applicable across a wide range of contexts. The technology presents opportunities as well as, often ethical and legal, challenges, and has the potential for both positive and negative impacts for organisations, society, and individuals. Offering multi-disciplinary insight into some of these, this article brings together 43 contributions from experts in fields such as computer science, marketing, information systems, education, policy, hospitality and tourism, management, publishing, and nursing. The contributors acknowledge ChatGPT’s capabilities to enhance productivity and suggest that it is likely to offer significant gains in the banking, hospitality and tourism, and information technology industries, and enhance business activities, such as management and marketing. Nevertheless, they also consider its limitations, disruptions to practices, threats to privacy and security, and consequences of biases, misuse, and misinformation. However, opinion is split on whether ChatGPT’s use should be restricted or legislated. Drawing on these contributions, the article identifies questions requiring further research across three thematic areas: knowledge, transparency, and ethics; digital transformation of organisations and societies; and teaching, learning, and scholarly research. The avenues for further research include: identifying skills, resources, and capabilities needed to handle generative AI; examining biases of generative AI attributable to training datasets and processes; exploring business and societal contexts best suited for generative AI implementation; determining optimal combinations of human and generative AI for various tasks; identifying ways to assess accuracy of text produced by generative AI; and uncovering the ethical and legal issues in using generative AI across different contexts
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