2,293 research outputs found

    The ‘danmu’ phenomenon and media participation: Intercultural understanding and language learning through ‘The Ministry of Time’

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    While research on Western multimedia platforms, such as YouTube, is prolific and interdisciplinary, Asian portals remain unknown. We explore this field by analyzing the juvenile and intercultural uses of a popular visualization system in Japan and China, known as “danmaku” or “danmu”. This technology inserts dynamic and contextualized comments on a photogram, with several typographical possibilities. Based on a corpus of 1,590 comments on “The Ministry of Time,” collected from a fandom platform with millions of users, we analyzed the topics that arouse the most interest among Chinese fans. We combine content analysis, which incorporates coding and counting techniques of the categories with the most interventions (n>16), with multimodal discourse analysis (TV series, Asian platform and user comments). Results show that the viewers are most interested in the film genre (time travel), the characters, the plot, certain sociocultural contents, and the Spanish language. Their discussions address issues of interculturality, some topics that are taboo in China and the fandom culture in Asia. Our study illustrates the potential of participation, communication, and learning in Asian social media, and constitutes an interesting and innovative contribution to the field of media and digital literacy, with various suggestions to promote intercultural competence with the use of popular culture

    Enrichment of the Phenotypic and Genotypic Data Warehouse analysis using Question Answering systems to facilitate the decision making process in cereal breeding programs

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    Currently there are an overwhelming number of scientific publications in Life Sciences, especially in Genetics and Biotechnology. This huge amount of information is structured in corporate Data Warehouses (DW) or in Biological Databases (e.g. UniProt, RCSB Protein Data Bank, CEREALAB or GenBank), whose main drawback is its cost of updating that makes it obsolete easily. However, these Databases are the main tool for enterprises when they want to update their internal information, for example when a plant breeder enterprise needs to enrich its genetic information (internal structured Database) with recently discovered genes related to specific phenotypic traits (external unstructured data) in order to choose the desired parentals for breeding programs. In this paper, we propose to complement the internal information with external data from the Web using Question Answering (QA) techniques. We go a step further by providing a complete framework for integrating unstructured and structured information by combining traditional Databases and DW architectures with QA systems. The great advantage of our framework is that decision makers can compare instantaneously internal data with external data from competitors, thereby allowing taking quick strategic decisions based on richer data.This paper has been partially supported by the MESOLAP (TIN2010-14860) and GEODAS-BI (TIN2012-37493-C03-03) projects from the Spanish Ministry of Education and Competitivity. Alejandro Maté is funded by the Generalitat Valenciana under an ACIF grant (ACIF/2010/298)

    RTST Trend Report: lead theme Contextualisation

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    Specht, M., Börner, D., Tabuenca, B., Ternier, S., De Vries, F., Kalz, M., Drachsler, H., & Schmitz, B. (2012). RTST Trend Report: lead theme Contextualisation. Deliverable 1.7 of STELLAR network of excellence. Heerlen, The Netherlands.In summary this trend-scouting report highlights different design dimensions of contextualizing learning. On the one hand designing educational context: the components and constituents of the educational setting, which also have to be orchestrated in an instructional design or the process of orchestration (Luckin, 2010, Specht, 2009) on the other hand bridging and linking learning contexts for seamless learning support: Wong et al. define design dimensions of seamless learning experiences and which gaps they identify and what challenges must be tackled to create seamless learning experiences (Wong, 2011).STELLAR Network of Excellence, Grant 23191

    Diversified Usages of Big Data : Scope and Challenges

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    During the last few decades, novel trends in terms of advancement in computational power, increase in storage capacity, growing usage of Web and mass availability of smart devices are leading towards the collection and storage of enormous amount of Data. Big Data Analytics are applied to derive gainful insights and knowledge from this data. The present paper aims to characterize Big Data and then delves in various application domains where Big Data techniques can potentially be applied. The researchers in computer science and allied areas have several research challenges. To address these challenges, new tools and techniques need to be developed and leveraged to solve problems for people, industry and the world at large. DOI: 10.17762/ijritcc2321-8169.150517

    From Social Data Mining to Forecasting Socio-Economic Crisis

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    Socio-economic data mining has a great potential in terms of gaining a better understanding of problems that our economy and society are facing, such as financial instability, shortages of resources, or conflicts. Without large-scale data mining, progress in these areas seems hard or impossible. Therefore, a suitable, distributed data mining infrastructure and research centers should be built in Europe. It also appears appropriate to build a network of Crisis Observatories. They can be imagined as laboratories devoted to the gathering and processing of enormous volumes of data on both natural systems such as the Earth and its ecosystem, as well as on human techno-socio-economic systems, so as to gain early warnings of impending events. Reality mining provides the chance to adapt more quickly and more accurately to changing situations. Further opportunities arise by individually customized services, which however should be provided in a privacy-respecting way. This requires the development of novel ICT (such as a self- organizing Web), but most likely new legal regulations and suitable institutions as well. As long as such regulations are lacking on a world-wide scale, it is in the public interest that scientists explore what can be done with the huge data available. Big data do have the potential to change or even threaten democratic societies. The same applies to sudden and large-scale failures of ICT systems. Therefore, dealing with data must be done with a large degree of responsibility and care. Self-interests of individuals, companies or institutions have limits, where the public interest is affected, and public interest is not a sufficient justification to violate human rights of individuals. Privacy is a high good, as confidentiality is, and damaging it would have serious side effects for society.Comment: 65 pages, 1 figure, Visioneer White Paper, see http://www.visioneer.ethz.c

    From the conception to the definition of a new service: the case of the European GeoPKDD project”

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    La tesi affronta il processo che parte dalla generazione di un nuovo servizio di tipo technology push ed arriva fino alla sua definizione, attraverso l’analisi del lavoro svolto per WIND Telecomunicazioni s.p.a. nell’ambito del progetto Europeo GeoPKDD. Dopo un inquadramento teorico sulle metodologie di sviluppo di nuovi servizi e sulle peculiarità di uno sviluppo technology push rispetto al caso market pull, il lavoro si concentra sul processo che, partendo dalla generazione di nuove idee basate sulla tecnologia GeoPKDD, si ù concluso con la definizione delle specifiche finali da implementare nel servizio finale

    Investigating Potential Interventions on disruptive impacts of Industry 4.0 technologies in Circular Supply chains: Evidence from SMEs of an Emerging Economy

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    As a transversal theme, the intertwining of digitalization and sustainability has crossed all Supply Chains (SCs) levels dealing with widespread environmental and societal concerns. This paper investigates the potential interventions and disruptive impacts that Industry 4.0 technologies may have on pharmaceutical Circular SCs (CSCs). To accomplish this, a novel method involving a literature review and Pythagorean fuzzy-Delphi has initially been employed to identify and screen categorized lists of Industry 4.0 Disruptive Technologies (IDTs) and their impacts on pharmaceutical CSC. Subsequently, the weight of finalized impacts and the performance score of finalized IDTs have simultaneously been measured via a novel version of Pythagorean fuzzy SECA (Simultaneously Evaluation of Criteria and Alternatives). Then, the priority of each intervention for disruptive impacts of Industry 4.0 has been determined via the Hanlon method. This is one of the first papers to provide in-depth insights into advancing the study of the disruptive action of Industry 4.0 technologies cross-fertilizing CE throughout pharmaceutical SCs in the emerging economy of Iran. The results indicate that digital technologies such as Big Data Analytics, Global Positioning Systems, Enterprise Resource Planning, and Digital Platforms are quite available in the Irans' pharmaceutical industry. These technologies, along with four available interventions, e.g., environmental regulations, subsidy, fine, and reward, would facilitate moving towards a lean, agile, resilient, and sustainable supply chain through the efficient utilization of resources, optimized waste management, and substituting the human workforce by machines

    AIGC In China: Current Developments And Future Outlook

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    The increasing attention given to AI Generated Content (AIGC) has brought a profound impact on various aspects of daily life, industrial manufacturing, and the academic sector. Recognizing the global trends and competitiveness in AIGC development, this study aims to analyze China's current status in the field. The investigation begins with an overview of the foundational technologies and current applications of AIGC. Subsequently, the study delves into the market status, policy landscape, and development trajectory of AIGC in China, utilizing keyword searches to identify relevant scholarly papers. Furthermore, the paper provides a comprehensive examination of AIGC products and their corresponding ecosystem, emphasizing the ecological construction of AIGC. Finally, this paper discusses the challenges and risks faced by the AIGC industry while presenting a forward-looking perspective on the industry's future based on competitive insights in AIGC

    Selection of third party software in Off-The-Shelf-based software development: an interview study with industrial practitioners

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    The success of software development using third party components highly depends on the ability to select a suitable component for the intended application. The evidence shows that there is limited knowledge about current industrial OTS selection practices. As a result, there is often a gap between theory and practice, and the proposed methods for supporting selection are rarely adopted in the industrial practice. This paper's goal is to investigate the actual industrial practice of component selection in order to provide an initial empirical basis that allows the reconciliation of research and industrial endeavors. The study consisted of semi-structured interviews with 23 employees from 20 different software-intensive companies that mostly develop web information system applications. It provides qualitative information that help to further understand these practices, and emphasize some aspects that have been overlooked by researchers. For instance, although the literature claims that component repositories are important for locating reusable components; these are hardly used in industrial practice. Instead, other resources that have not received considerable attention are used with this aim. Practices and potential market niches for software-intensive companies have been also identified. The results are valuable from both the research and the industrial perspectives as they provide a basis for formulating well-substantiated hypotheses and more effective improvement strategies.Peer ReviewedPostprint (author's final draft
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