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There are great interests of designing research metrics and indices to measure the research impacts in research institutes. Unfortunately, most of those indices ignore critical design issues, e.g. the disparity between domains, the impact of journals or conferences in which papers are published, normalising the range of the index values to certain intervals, and the scalability of using the index to rank different research entities. In this paper, a new normalised fuzzy index, (NFindex), is proposed as a fuzzy-based research impact metric. The proposed index is a scalable index whose values are normalised to the percentage levels. NFindex achieves both inter-discipline normalisation and intra-discipline consistency. The capability of NFindex to achieve the inter-discipline normalisation enables fair comparison between different research domains regardless their nature in terms of influence and contribution to other research areas, e.g. natural science. Therefore, NFindex gives a universal normalised single-number metric that can be used by research institutes to solve the problem of inter-discipline scholar ranking. Moreover, it can help universal ranking of universities and research institutes according to their research capabilities and impacts. The obtained results, on diverse research areas, prove the potential of NFindex in terms of both intra-discipline consistency and inter-discipline normalisation. [ABSTRACT FROM AUTHOR]

The aim of this study is to provide insights concerning the effects of the ubiquitous digital environment on the way people think and the subsequent need to equip young individuals with the necessary skills. Several studies focus on defining the so-called digital skills, also providing indications that higher cognitive skills are required. However, they do not examine how young individuals could perform better to adapt to the continuously evolving digital environment. To address this gap, the study introduces and analyses the construct of digital intelligence, representing the new way of thinking and behaviour in the digital environment. For the purposes of the study, a set of tests was given to students at Greek high schools, targeting 15–16 years old students and employing original tests to assess digital intelligence. According to the findings, digital intelligence is composed of: (1) logical reasoning, algorithms, and evaluation, (2) abstraction, decomposition, and patterns and generalisation, (3) digital emotional intelligence and communication, (4) digital safety and security, and (5) digital identity, use, literacy, and rights. Assessing digital intelligence, as proposed in this study, could be used to assist vocational guidance, employee selection and evaluation, and development of revised school curricula. [ABSTRACT FROM AUTHOR]

People increasingly use microblogging platforms such as Twitter during natural disasters and emergencies. Research studies have revealed the usefulness of the data available on Twitter for several disaster response tasks. However, making sense of social media data is a challenging task due to several reasons such as limitations of available tools to analyse high-volume and high-velocity data streams, dealing with information overload, among others. To eliminate such limitations, in this work, we first show that textual and imagery content on social media provide complementary information useful to improve situational awareness. We then explore ways in which various Artificial Intelligence techniques from Natural Language Processing and Computer Vision fields can exploit such complementary information generated during disaster events. Finally, we propose a methodological approach that combines several computational techniques effectively in a unified framework to help humanitarian organisations in their relief efforts. We conduct extensive experiments using textual and imagery content from millions of tweets posted during the three major disaster events in the 2017 Atlantic Hurricane season. Our study reveals that the distributions of various types of useful information can inform crisis managers and responders and facilitate the development of future automated systems for disaster management. [ABSTRACT FROM AUTHOR]