9,195 research outputs found

    Future craft:research exposition

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    ICS Materials. Towards a re-Interpretation of material qualities through interactive, connected, and smart materials.

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    The domain of materials for design is changing under the influence of an increased technological advancement, miniaturization and democratization. Materials are becoming connected, augmented, computational, interactive, active, responsive, and dynamic. These are ICS Materials, an acronym that stands for Interactive, Connected and Smart. While labs around the world are experimenting with these new materials, there is the need to reflect on their potentials and impact on design. This paper is a first step in this direction: to interpret and describe the qualities of ICS materials, considering their experiential pattern, their expressive sensorial dimension, and their aesthetic of interaction. Through case studies, we analyse and classify these emerging ICS Materials and identified common characteristics, and challenges, e.g. the ability to change over time or their programmability by the designers and users. On that basis, we argue there is the need to reframe and redesign existing models to describe ICS materials, making their qualities emerge

    Traceability Links Recovery among Requirements and BPMN models

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    Tesis por compendio[EN] Throughout the pages of this document, I present the results of the research that was carried out in the context of my PhD studies. During the aforementioned research, I studied the process of Traceability Links Recovery between natural language requirements and industrial software models. More precisely, due to their popularity and extensive usage, I studied the process of Traceability Links Recovery between natural language requirements and Business Process Models, also known as BPMN models. In order to carry out the research, I focused my work on two main objectives: (1) the development of the Traceability Links Recovery techniques between natural language requirements and BPMN models, and (2) the validation and analysis of the results obtained by the developed techniques in industrial domain case studies. The results of the research have been redacted and published in forums, conferences, and journals specialized in the topics and context of the research. This thesis document introduces the topics, context, and objectives of the research, presents the academic publications that have been published as a result of the work, and then discusses the outcomes of the investigation.[ES] A través de las páginas de este documento, presento los resultados de la investigación realizada en el contexto de mis estudios de doctorado. Durante la investigación, he estudiado el proceso de Recuperación de Enlaces de Trazabilidad entre requisitos especificados en lenguaje natural y modelos de software industriales. Más concretamente, debido a su popularidad y uso extensivo, he estudiado el proceso de Recuperación de Enlaces de Trazabilidad entre requisitos especificados en lenguaje natural y Modelos de Procesos de Negocio, también conocidos como modelos BPMN. Para llevar a cabo esta investigación, mi trabajo se ha centrado en dos objetivos principales: (1) desarrollo de técnicas de Recuperación de Enlaces de Trazabilidad entre requisitos especificados en lenguaje natural y modelos BPMN, y (2) validación y análisis de los resultados obtenidos por las técnicas desarrolladas en casos de estudio de dominios industriales. Los resultados de la investigación han sido redactados y publicados en foros, conferencias y revistas especializadas en los temas y contexto de la investigación. Esta tesis introduce los temas, contexto y objetivos de la investigación, presenta las publicaciones académicas que han sido publicadas como resultado del trabajo, y expone los resultados de la investigación.[CA] A través de les pàgines d'aquest document, presente els resultats de la investigació realitzada en el context dels meus estudis de doctorat. Durant la investigació, he estudiat el procés de Recuperació d'Enllaços de Traçabilitat entre requisits especificats en llenguatge natural i models de programari industrials. Més concretament, a causa de la seua popularitat i ús extensiu, he estudiat el procés de Recuperació d'Enllaços de Traçabilitat entre requisits especificats en llenguatge natural i Models de Processos de Negoci, també coneguts com a models BPMN. Per a dur a terme aquesta investigació, el meu treball s'ha centrat en dos objectius principals: (1) desenvolupament de tècniques de Recuperació d'Enllaços de Traçabilitat entre requisits especificats en llenguatge natural i models BPMN, i (2) validació i anàlisi dels resultats obtinguts per les tècniques desenvolupades en casos d'estudi de dominis industrials. Els resultats de la investigació han sigut redactats i publicats en fòrums, conferències i revistes especialitzades en els temes i context de la investigació. Aquesta tesi introdueix els temes, context i objectius de la investigació, presenta les publicacions acadèmiques que han sigut publicades com a resultat del treball, i exposa els resultats de la investigació.Lapeña Martí, R. (2020). Traceability Links Recovery among Requirements and BPMN models [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/149391TESISCompendi

    Utilising radio-frequency identification technologies as knowledge management enablers in academic libraries: a case study of the University of South Africa

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    The quest to generate, preserve and utilise knowledge is driving firms and organisations towards a knowledge-based approach to managing organisational knowledge assets. Therefore, knowledge management (KM) is becoming increasingly important for organisations such as academic libraries to enhance their competitive edge in performance, to become more effective and to keep the organisation’s knowledge for future use. The importance of KM cannot be overemphasised in terms of how academic libraries can find meaningful and effective ways to manage knowledge resources to improve the services rendered to information users. Pressure is mounting for academic libraries to attain, retain and share knowledge for strategic planning, decision-making and remaining competitive. The adoption of radio-frequency identification (RFID) technologies is one of the preferred approaches to managing organisational knowledge assets; therefore, this was the motivation for undertaking this study in order to understand how these new technologies can change the knowledge management landscape in academic libraries. A qualitative research methodology, informed by the interpretivist research philosophy, was adopted in this study. Data were collected from a sample of 12 participants using non-probability purposive and convenience sampling techniques. The use of purposive and convenience techniques was ideal for this study because the participants were readily available and possessed the relevant data required to address the research questions and research problem of the study. Open-ended questions were designed to form an interview guide, which was the main data collection instrument. Annual reports, system manuals and user manuals were consulted to augment the primary data collected to address the problem at hand. The findings from the study showed that RFID technologies improved efficiency, tracking and tracing, inventory management and assisted with planning. It was revealed that users of RFID technologies required further training and development to fully utilise these systems for the benefit of the organisation. The study was conducted using a small sample of 12 participants; therefore, it was recommended that further studies could be conducted with large sample sizes using different research strategies. It was suggested that further research should be conducted to establish how change programmes have been managed before in other departments or sections and how the staff exodus was managed. An organisation-wide research would be recommended to ascertain the views and opinions of a larger population so that findings can be generalisable.Information ScienceM. Inf. (Information Science

    The Ends of Knowledge Sharing in Networks: Using Information Technology to Start Knowledge Protection

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    Organisations need networks to leverage external knowledge, particularly for SMEs with their limited resources. Organisations use networks for knowledge sharing to foster innovation. This use of networks bears risks like the unwanted spill-over of knowledge. Consequently, organisa-tions need to balance sharing and protecting knowledge. While scholars have extensively inves-tigated the sharing perspective, they have so far neglected knowledge protection in network set-tings and especially the interplay between sharing and protection. This paper illuminates the motives and practices of network members switching from open sharing to stronger protection on the basis of 53 interviews with members from 10 SME networks. We describe three patterns of switching behaviour and explain how the interviewees adapt the use of collaborative IT to manage the switches. Employees switch from sharing to being open to (a) a certain extent, (b) a certain group, or (c) a certain topic. We find that the three types of switching behaviour are re-lated to network characteristics and to corresponding adaptions in using collaborative IT. Col-laborative IT does not necessarily hamper knowledge protection, but adapted use can support both knowledge sharing and knowledge protection. We argue that organisations should develop protection capabilities to manage the switches

    Knowledge Brokering and Organizational Innovation: Founder Imprinting Effects

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    We empirically examine the innovation consequences of organizational knowledge brokering, the ability to effectively apply knowledge from one technical domain to innovate in another. We investigate how organizational innovation outcomes vary by founders’ initial mode of venture ideation. We then compare how firms established with knowledge-brokering-based ideation differ in their methods of sustaining ongoing knowledge-brokering capacity compared with firms not established in such a manner. We do so by tracking all the start-up biotechnology firms founded to commercialize the then-emergent recombinant DNA technology (the sample of initial knowledge brokers) together with a contemporaneously founded sample of biotechnology firms that did not license the DNA technology (the sample of initial nonbrokers). Our results suggest that (a) ongoing knowledge brokering has an inverted U-shaped relationship with innovative performance in general; (b) initial knowledge brokers have a positive imprinting effect on their organizations’ search patterns over time, resulting in superior performance relative to nonbrokers; and (c) initial nonbrokers rely more on external channels of sourcing knowledge, such as hiring technical staff, relative to initial brokers, reinforcing the imprinting interpretation. The described imprinting mechanism differs from extant mechanisms such as partner affiliation- and trigger-based mechanisms in explaining entrepreneurial performance differentials

    Proceedings of the Salford Postgraduate Annual Research Conference (SPARC) 2011

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    These proceedings bring together a selection of papers from the 2011 Salford Postgraduate Annual Research Conference(SPARC). It includes papers from PhD students in the arts and social sciences, business, computing, science and engineering, education, environment, built environment and health sciences. Contributions from Salford researchers are published here alongside papers from students at the Universities of Anglia Ruskin, Birmingham City, Chester,De Montfort, Exeter, Leeds, Liverpool, Liverpool John Moores and Manchester

    Preserving the Quality of Architectural Tactics in Source Code

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    In any complex software system, strong interdependencies exist between requirements and software architecture. Requirements drive architectural choices while also being constrained by the existing architecture and by what is economically feasible. This makes it advisable to concurrently specify the requirements, to devise and compare alternative architectural design solutions, and ultimately to make a series of design decisions in order to satisfy each of the quality concerns. Unfortunately, anecdotal evidence has shown that architectural knowledge tends to be tacit in nature, stored in the heads of people, and lost over time. Therefore, developers often lack comprehensive knowledge of underlying architectural design decisions and inadvertently degrade the quality of the architecture while performing maintenance activities. In practice, this problem can be addressed through preserving the relationships between the requirements, architectural design decisions and their implementations in the source code, and then using this information to keep developers aware of critical architectural aspects of the code. This dissertation presents a novel approach that utilizes machine learning techniques to recover and preserve the relationships between architecturally significant requirements, architectural decisions and their realizations in the implemented code. Our approach for recovering architectural decisions includes the two primary stages of training and classification. In the first stage, the classifier is trained using code snippets of different architectural decisions collected from various software systems. During this phase, the classifier learns the terms that developers typically use to implement each architectural decision. These ``indicator terms\u27\u27 represent method names, variable names, comments, or the development APIs that developers inevitably use to implement various architectural decisions. A probabilistic weight is then computed for each potential indicator term with respect to each type of architectural decision. The weight estimates how strongly an indicator term represents a specific architectural tactics/decisions. For example, a term such as \emph{pulse} is highly representative of the heartbeat tactic but occurs infrequently in the authentication. After learning the indicator terms, the classifier can compute the likelihood that any given source file implements a specific architectural decision. The classifier was evaluated through several different experiments including classical cross-validation over code snippets of 50 open source projects and on the entire source code of a large scale software system. Results showed that classifier can reliably recognize a wide range of architectural decisions. The technique introduced in this dissertation is used to develop the Archie tool suite. Archie is a plug-in for Eclipse and is designed to detect wide range of architectural design decisions in the code and to protect them from potential degradation during maintenance activities. It has several features for performing change impact analysis of architectural concerns at both the code and design level and proactively keep developers informed of underlying architectural decisions during maintenance activities. Archie is at the stage of technology transfer at the US Department of Homeland Security where it is purely used to detect and monitor security choices. Furthermore, this outcome is integrated into the Department of Homeland Security\u27s Software Assurance Market Place (SWAMP) to advance research and development of secure software systems
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