The aim of the study is to analyse the opportunities and challenges of emergency remote teaching based on experiences of the COVID-19 emergency. A qualitative research method was undertaken in two steps. In the first step, a thematic analysis of an online discussion forum with international experts from different sectors and countries was carried out. In the second step (an Italian case study), both the data and the statements of opinion leaders from secondary online sources, including web articles, statistical data and legislation, were analysed. The results reveal several technological, pedagogical and social challenges. The technological challenges are mainly related to the unreliability of Internet connections and many students’ lack of necessary electronic devices. The pedagogical challenges are principally associated with teachers’ and learners’ lack of digital skills, the lack of structured content versus the abundance of online resources, learners’ lack of interactivity and motivation and teachers’ lack of social and cognitive presence (the ability to construct meaning through sustained communication within a community of inquiry). The social challenges are mainly related to the lack of human interaction between teachers and students as well as among the latter, the lack of physical spaces at home to receive lessons and the lack of support of parents who are frequently working remotely in the same spaces. Based on the lessons learned from this worldwide emergency, challenges and proposals for action to face these same challenges, which should be and sometimes have been implemented, are provided.
The paper gives an overview of the different sentiment classification approaches and tools used for sentiment analysis. Starting from this overview the paper provides a classification of (i) approaches with respect to features/techniques and advantages/limitations and (ii) tools with respect to the different techniques used for sentiment analysis. Different application fields of application of sentiment analysis such as: business, politic, public actions and finance are also discussed in the paper.
Abstract. The EU Flood Risk Management Directive 2007/60/EC aims at an active involvement of interested parties in the setting up of flood risk management plans and thus calls for more governance-related decision-making. This requirement has two perspectives. On the one hand, there is (1) the question of how decision-makers can improve the quality of their governance process. On the other hand, there is (2) the question of how the public shall be appropriately informed and involved. These questions were the centre of the ERA-Net CRUE-funded project IMRA (integrative flood risk governance approach for improvement of risk awareness) that aimed at an optimisation of the flood risk management process by increasing procedural efficiency with an explicit involvement strategy. To reach this goal, the IMRA project partners developed two new approaches that were implemented in three case study areas for the first time in flood risk management:1. risk governance assessment tool: An indicator-based benchmarking and monitoring tool was used to evaluate the performance of a flood risk management system in regard to ideal risk governance principles;2. social milieu approach: The concept of social milieus was used to gain a picture of the people living in the case study regions to learn more about their lifestyles, attitudes and values and to use this knowledge to plan custom-made information and participation activities for the broad public.This paper presents basic elements and the application of two innovative approaches as a part of an "involvement strategy" that aims at the active involvement of all interested parties (stakeholders) for assessing, reviewing and updating flood risk management plans, as formulated in the EU Flood Risk Management Directive 2007/60/EC.
Abstract. Italy's recent history is punctuated with devastating flood disasters claiming high death toll and causing vast but underestimated economic, social and environmental damage. The responses to major flood and landslide disasters such as the Polesine (1951), Vajont (1963), Firenze (1966), Valtelina (1987, Piedmont (1994), Crotone (1996), Sarno (1998), Soverato (2000, and Piedmont (2000) events have contributed to shaping the country's flood risk governance. Insufficient resources and capacity, slow implementation of the (at that time) novel risk prevention and protection framework, embodied in the law 183/89 of 18 May 1989, increased the reliance on the response and recovery operations of the civil protection. As a result, the importance of the Civil Protection Mechanism and the relative body of norms and regulation developed rapidly in the 1990s. In the aftermath of the Sarno (1998) and Soverato (2000) disasters, the Department for Civil Protection (DCP) installed a network of advanced early warning and alerting centres, the cornerstones of Italy's preparedness for natural hazards and a best practice worth following. However, deep convective clouds, not uncommon in Italy, producing intense rainfall and rapidly developing localised floods still lead to considerable damage and loss of life that can only be reduced by stepping up the risk prevention efforts. The implementation of the EU Floods Directive (2007/60/EC) provides an opportunity to revise the model of flood risk governance and confront the shortcomings encountered during more than 20 yr of organised flood risk management. This brief communication offers joint recommendations towards this end from three projects funded by the 2nd CRUE ERA-NET (http://www.crue-eranet.net/) Funding Initiative: FREEMAN, IMRA and URFlood.
The high complexity of natural language and the huge amount of human and temporal resources necessary for producing the grammars lead several researchers in the area of Natural Language Processing to investigate various solutions for automating grammar generation and updating processes. Many algorithms for Context-Free Grammar inference have been developed in the literature. This paper provides a survey of the methodologies for inferring context-free grammars from examples, developed by researchers in the last decade. After introducing some preliminary definitions and notations concerning learning and inductive inference, some of the most relevant existing grammatical inference methods for Natural Language are described and classified according to the kind of presentation (if text or informant) and the type of information (if supervised, unsupervised, or semi-supervised). Moreover, the state of the art of the strategies for evaluation and comparison of different grammar inference methods is presented. The goal of the paper is to provide a reader with introduction to major concepts and current approaches in Natural Language Learning research.
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