830 resultados para Research communities


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Recently, we have seen an explosion of interest in ontologies as artifacts to represent human knowledge and as critical components in knowledge management, the semantic Web, business-to-business applications, and several other application areas. Various research communities commonly assume that ontologies are the appropriate modeling structure for representing knowledge. However, little discussion has occurred regarding the actual range of knowledge an ontology can successfully represent.

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The Models@run.time (MRT) workshop series offers a discussion forum for the rising need to leverage modeling techniques for the software of the future. The main goals are to explore the benefits of models@run.time and to foster collaboration and cross-fertilization between different research communities like for example like model-driven engineering (e.g. MODELS), self-adaptive/autonomous systems communities (e.g., SEAMS and ICAC), the control theory community and the artificial intelligence community. © 2012 Authors.

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Purpose – The purpose of this paper is to report the state-of-the-art of servitization by presenting a clinical review of literature currently available on the topic. The paper aims to define the servitization concept, report on its origin, features and drivers and give examples of its adoption along with future research challenges. Design/methodology/approach – In determining the scope of this study, the focus is on articles that are central and relevant to servitization within a wider manufacturing context. The methodology consists of identifying relevant publication databases, searching these using a wide range of key words and phrases associated with servitization, and then fully reviewing each article in turn. The key findings and their implications for research are all described. Findings – Servitization is the innovation of an organisation's capabilities and processes to shift from selling products to selling integrated products and services that deliver value in use. There are a diverse range of servitization examples in the literature. These tend to emphasize the potential to maintain revenue streams and improve profitability. Practical implications – Servitization does not represent a panacea for manufactures. However, it is a concept of significant potential value, providing routes for companies to move up the value chain and exploit higher value business activities. There is little work to date that can be used to help practitioners. Originality/value – This paper provides a useful review of servitization and a platform on which to base more in-depth research into the broader topic of service-led competitive strategy by drawing on the work from other related research communities.

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Purpose: The servitization of manufacturing is a diverse and complex field of research interest. The purpose of this paper is to provide an integrative and organising lens for viewing the various contributions to knowledge production from those research communities addressing servitization. To achieve this, the paper aims to set out to address two principal questions, namely where are the knowledge stocks and flows amongst the research communities? And what are generic research concerns being addressed by these communities? Design/methodology/approach: Using an evidenced-based approach, the authors have performed a systematic review of the research literature associated with the servitization of manufacturing. This investigation incorporates a descriptive and thematic analysis of 148 academic and scholarly papers from 103 different lead authors in 68 international peer-reviewed journals. Findings: The work proposes support for the existence of distinct researcher communities, namely services marketing, service management, operations management, product-service systems and service science management and engineering, which are contributing to knowledge production in the servitization of manufacturing. Knowledge stocks within all communities associated with research in the servitization of manufacturing have dramatically increased since the mid-1990s. The trends clearly reveal that the operations community is in receipt of the majority of citations relating to the servitization of manufacturing. In terms of knowledge flows, it is apparent that the more mature communities are drawing on more locally produced knowledge stocks, whereas the emergent communities are drawing on a knowledge base more evenly distributed across all the communities. The results are indicative of varying degrees of interdependency amongst the communities. The generic research concerns being addressed within the communities are associated with the concepts of product-service differentiation, competitive strategy, customer value, customer relationships and product-service configuration. Originality/value: This research has further developed and articulated the identities of distinct researcher communities actively contributing to knowledge production in the servitization of manufacturing, and to what extent they are pursuing common research agendas. This study provides an improved descriptive and thematic awareness of the resulting body of knowledge, allowing the field of servitization to progress in a more informed and multidisciplinary fashion. © Emerald Group Publishing Limited.

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Uncertainty can be defined as the difference between information that is represented in an executing system and the information that is both measurable and available about the system at a certain point in its life-time. A software system can be exposed to multiple sources of uncertainty produced by, for example, ambiguous requirements and unpredictable execution environments. A runtime model is a dynamic knowledge base that abstracts useful information about the system, its operational context and the extent to which the system meets its stakeholders' needs. A software system can successfully operate in multiple dynamic contexts by using runtime models that augment information available at design-time with information monitored at runtime. This chapter explores the role of runtime models as a means to cope with uncertainty. To this end, we introduce a well-suited terminology about models, runtime models and uncertainty and present a state-of-the-art summary on model-based techniques for addressing uncertainty both at development- and runtime. Using a case study about robot systems we discuss how current techniques and the MAPE-K loop can be used together to tackle uncertainty. Furthermore, we propose possible extensions of the MAPE-K loop architecture with runtime models to further handle uncertainty at runtime. The chapter concludes by identifying key challenges, and enabling technologies for using runtime models to address uncertainty, and also identifies closely related research communities that can foster ideas for resolving the challenges raised. © 2014 Springer International Publishing.

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Timeline generation is an important research task which can help users to have a quick understanding of the overall evolution of any given topic. It thus attracts much attention from research communities in recent years. Nevertheless, existing work on timeline generation often ignores an important factor, the attention attracted to topics of interest (hereafter termed "social attention"). Without taking into consideration social attention, the generated timelines may not reflect users' collective interests. In this paper, we study how to incorporate social attention in the generation of timeline summaries. In particular, for a given topic, we capture social attention by learning users' collective interests in the form of word distributions from Twitter, which are subsequently incorporated into a unified framework for timeline summary generation. We construct four evaluation sets over six diverse topics. We demonstrate that our proposed approach is able to generate both informative and interesting timelines. Our work sheds light on the feasibility of incorporating social attention into traditional text mining tasks. Copyright © 2013 ACM.

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The field of Semantic Web Services (SWS) has been recognized as one of the most promising areas of emergent research within the Semantic Web initiative, exhibiting an extensive commercial potential and attracting significant attention from both industry and the research community. Currently, there exist several different frameworks and languages for formally describing a Web Service: Web Ontology Language for Services (OWL-S), Web Service Modelling Ontology (WSMO) and Semantic Annotations for the Web Services Description Language (SAWSDL) are the most important approaches. To the inexperienced user, choosing the appropriate platform for a specific SWS application may prove to be challenging, given a lack of clear separation between the ideas promoted by the associated research communities. In this paper, we systematically compare OWL-S, WSMO and SAWSDL from various standpoints, namely, that of the service requester and provider as well as the broker-based view. The comparison is meant to help users to better understand the strengths and limitations of these different approaches to formalizing SWS, and to choose the most suitable solution for a given application. Copyright © 2015 John Wiley & Sons, Ltd.

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Full text: With the rapid development of the aerospace industry, manufacturing technologies have to continuously develop and adjust themselves to ever-growing demands coming from more complex component designs and the use of highly engineered materials. Today there is an increased number of manufacturers contributing to the realization of final products, i.e. avionics, so it is easy to perceive the truly globalized dimension of the aerospace manufacturing business. With this comes the demand for further engineering developments on which the academic/industrial research institutes need to deliver solutions to real aerospace manufacturing problems. This is a challenging task since aerospace manufacturing technologies have to cover a wide range of materials (from composites to advanced Ni/Ti alloys), processes (from forging to non-traditional machining and assembly), and parts’ dimensions/batch sizes (from airframes to turbine blades). In this wide context, this Special Issue includes high quality theoretical and experimental scientific contributions on the following topics related to the aerospace manufacturing technology: (a) machining of advance aerospace alloys; (b) abrasive processes applied to aerospace components; (c) surface treatments to enhance fatigue performance of aerospace components; (d) joining and assembly of aerospace components; (e) laser machining of aerospace alloys; (f) automated/supervised manufacture of aerospace components; (g) quality supervision of aerospace manufacturing routes. The breadth of topics in this Special Issue is perhaps indicative of the complexity and challenges that the research related to aerospace manufacturing technology can offer. We hope that this issue will act as a catalyst for the development of further research, academic and industrial interactions, and publications related to aerospace manufacturing technologies for the benefit of the academic and industrial research communities.

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The field of Semantic Web Services (SWS) has been recognized as one of the most promising areas of emergent research within the Semantic Web (SW) initiative, exhibiting an extensive commercial potential, and attracting significant attention from both industry and the research community. Currently, there exist several different frameworks and languages for formally describing a Web Service: OWL-S (Web Ontology Language for Services), WSMO (Web Service Modeling Ontology) and SAWSDL (Semantic Annotations for the Web Services Description Language) are the most important approaches. To the inexperienced user, choosing the appropriate paradigm for a specific SWS application may prove to be challenging, given a lack of clear separation between the ideas promoted by the associated research communities. In this paper, we systematically compare OWL-S, WSMO and SAWSDL from various standpoints, namely that of the service requester and provider as well as the broker based view. The comparison is meant to help users to better understand the strengths and limitations of these different approaches to formalising SWS, and to choose the most suitable solution for a given use case. © 2013 IEEE.

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Biobanks represent key resources for clinico-genomic research and are needed to pave the way to personalised medicine. To achieve this goal, it is crucial that scientists can securely access and share high-quality biomaterial and related data. Therefore, there is a growing interest in integrating biobanks into larger biomedical information and communication technology (ICT) infrastructures. The European project p-medicine is currently building an innovative ICT infrastructure to meet this need. This platform provides tools and services for conducting research and clinical trials in personalised medicine. In this paper, we describe one of its main components, the biobank access framework p-BioSPRE (p-medicine Biospecimen Search and Project Request Engine). This generic framework enables and simplifies access to existing biobanks, but also to offer own biomaterial collections to research communities, and to manage biobank specimens and related clinical data over the ObTiMA Trial Biomaterial Manager. p-BioSPRE takes into consideration all relevant ethical and legal standards, e.g., safeguarding donors’ personal rights and enabling biobanks to keep control over the donated material and related data. The framework thus enables secure sharing of biomaterial within open and closed research communities, while flexibly integrating related clinical and omics data. Although the development of the framework is mainly driven by user scenarios from the cancer domain, in this case, acute lymphoblastic leukaemia and Wilms tumour, it can be extended to further disease entities.

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The job of a historian is to understand what happened in the past, resorting in many cases to written documents as a firsthand source of information. Text, however, does not amount to the only source of knowledge. Pictorial representations, in fact, have also accompanied the main events of the historical timeline. In particular, the opportunity of visually representing circumstances has bloomed since the invention of photography, with the possibility of capturing in real-time the occurrence of a specific events. Thanks to the widespread use of digital technologies (e.g. smartphones and digital cameras), networking capabilities and consequent availability of multimedia content, the academic and industrial research communities have developed artificial intelligence (AI) paradigms with the aim of inferring, transferring and creating new layers of information from images, videos, etc. Now, while AI communities are devoting much of their attention to analyze digital images, from an historical research standpoint more interesting results may be obtained analyzing analog images representing the pre-digital era. Within the aforementioned scenario, the aim of this work is to analyze a collection of analog documentary photographs, building upon state-of-the-art deep learning techniques. In particular, the analysis carried out in this thesis aims at producing two following results: (a) produce the date of an image, and, (b) recognizing its background socio-cultural context,as defined by a group of historical-sociological researchers. Given these premises, the contribution of this work amounts to: (i) the introduction of an historical dataset including images of “Family Album” among all the twentieth century, (ii) the introduction of a new classification task regarding the identification of the socio-cultural context of an image, (iii) the exploitation of different deep learning architectures to perform the image dating and the image socio-cultural context classification.