Issues related to piezocone sleeve friction measurement accuracy in soft sensitive clays

Over the past decades, the piezocone testing has been increasingly adopted for field investigation as it offers a quick and cost-effective methodology for subsoil profiling and geotechnical parameters estimation. Although the piezocone testing has revealed good applicability worldwide, difficulties are encountered in complex soil conditions, such as soft sensitive clays. One of the key issues in such soils is represented by the poor quality of the sleeve friction (fs) measurement due to inaccuracy and poor resolution of the sleeve sensor. This paper investigates the influence of fs data quality on soil parameters determination with particular emphasis on the soil behavior type (SBT) chart classification. The field investigation was conducted in a soft sensitive clay site located in Finland using two different penetrometers: a standard piezocone and an advanced piezocone characterized by enhance accuracy sleeve friction sensor. Results show that the use of high-resolution piezocone plays a key role in soft clays to avoid misleading soil type classification.publishedVersionPeer reviewe

Piezocone testing in Nordic soft clays : Comparison of high-quality databases

Soft and sensitive clays are widespread in Scandinavia. Piezocone correlations for Norwegian clays have been previously proposed based on high-quality block samples from several sites. Recently, a large database of Finnish soft clays was compiled by Tampere University from piezocone measurements as well as high-quality laboratory tests on specimens from large tube samples. Finnish and Norwegian clays exhibit some differences in terms of basic properties. Norwegian clays show lower water content, lower organic content, higher silt content and lower plasticity than the clays from Finland. This may be linked to the source of the materials, their depositional and post-depositional processes that in turn impact on the mechanical behaviour. This paper aims to compare piezocone Norwegian and Finnish data with focus on strength and stress history. The database trends are compared for relevant engineering parameters. The data and its variability are critically discussed considering differences in geological history, basic properties, sampling techniques and disturbance.publishedVersionPeer reviewe

AI in Education: learner choice and fundamental rights

This article examines benefits and risks of Artificial Intelligence (AI) in education in relation to fundamental human rights. The article is based on an EU scoping study [Berendt, B., A. Littlejohn, P. Kern, P. Mitros, X. Shacklock, and M. Blakemore. 2017. Big Data for Monitoring Educational Systems. Luxembourg: Publications Office of the European Union. https://publications.europa.eu/en/publication-detail/-/publication/94cb5fc8-473e-11e7-aea8-01aa75ed71a1/]. The study takes into account the potential for AI and ‘Big Data’ to provide more effective monitoring of the education system in real-time, but also considers the implications for fundamental human rights and freedoms of both teachers and learners. The analysis highlights a need to balance the benefits and risks as AI tools are developed, marketed and deployed. We conclude with a call to embed consideration of the benefits and risks of AI in education as technology tools into the development, marketing and deployment of these tools. There are questions around who – which body or organisation – should take responsibility for regulating AI in education, particularly since AI impacts not only data protection and privacy, but on fundamental rights in general. Given AI’s global impact, it should be regulated at a trans-national level, with a global organisation such as the UN taking on this role

COSMO-SkyMed Dual-Use and Multi-National Experienced Challenges and Operational Implications

COSMO-SkyMed is an Earth Observation space program funded by the Italian Ministry of Research and Italian Ministry of Defence (It-MoD) and conducted by the Italian Space Agency (ASI) in conjunction with It-MoD, which was designed in order to fulfill Dual-Use requirements in terms of different needs of Defence and Civilian Users, such as different requirements in data products, system performances, security needs, response time, request priority management and data accessibility/confidentiality, being a pioneer program in the frame of the Civil and Military Space Duality and representing a reference for future Earth Observation space programs. Furthermore, COSMO-SkyMed was designed in order to achieve Interoperability, Expandability with respect to additional Defence and Civilian Partners and Multi-Mission features, which are the bases for the establishment of international cooperation programs that have been set up by ASI and It-MoD or are going-on, such as the Italian-French cooperation named ORFEO (Optical and Radar Federated Earth Observation) and the Italian-Argentinean cooperation named SIASGE (Sistema Ítalo Argentino de Satélites para la Gestión de Emergencias). In such a context, a significant example of successful COSMO-SkyMed international partnership is the recent French Defence User Ground Segment (F-DUGS) integration within COSMO-SkyMed system. The aim of this paper is to show the COSMO-SkyMed conceived architecture, the experienced operational implications collected in operating the system from the launch of the first COSMO-SkyMed satellite until the completion of the constellation and the integration of the French Partner into the system, highlighting the lessons learned and the experienced challenges to fulfill very innovative and demanding requirements

Visualizing Junk: Big Data Visualizations and the need for Feminist Data Studies

The datafication of culture has led to an increase in the circulation of data visualizations. In their production, visualizers draw on historical antecedents which define what constitutes a good visualization. In their reception, audiences similarly draw on experiences with visualizations and other visual forms to categorize them as good or bad. Whilst there are often sound reasons for such assessments, the gendered dimensions of judgements of cultural artefacts like data visualizations cannot be ignored. In this paper, we highlight how definitions of visualizations as bad are sometimes gendered. In turn, this gendered derision is often entangled with legitimate criticisms of poor visualization execution, making it hard to see and so normalised. This, we argue, is a form of what Gill (2011) calls flexible sexism, and it is why there is a need not just for feminist critiques of big data, but for feminist data studies – that is, feminists doing big data and data visualization