Children’s access to beneficial information in Arab states: Implementation of Article 17 of the Convention on the Rights of the Child in Egypt, Morocco and the United Arab Emirates

In theory, the multiple platforms and transnational nature of digital media, along with a related proliferation of diverse forms of content, make it easier for children’s right to access socially and culturally beneficial information and material to be realised, as required by Article 17 of the UN Convention on the Rights of the Child (CRC). Drawing on data collected during research on children’s screen content in the Arab world, combined with scrutiny of documents collated by the Committee on the Rights of the Child, which monitors compliance with the CRC, this paper explores how three Arab countries, Egypt, Morocco and the United Arab Emirates, presented their efforts to implement Article 17 as part of their periodic reporting on their overall performance in putting the CRC into effect. It uncovers tensions over the relationship between provision, participation and protection in relation to media, reveals that Article 17 is liable to get less attention than it deserves in contexts where governments keep a tight grip on media, and that, by appearing to give it a lower priority, all parties neglect the intersection between human rights in relation to media and children’s rights.

A model for information retrieval driven by conceptual spaces

A retrieval model describes the transformation of a query into a set of documents. The question is: what drives this transformation? For semantic information retrieval type of models this transformation is driven by the content and structure of the semantic models. In this case, Knowledge Organization Systems (KOSs) are the semantic models that encode the meaning employed for monolingual and cross-language retrieval. The focus of this research is the relationship between these meanings’ representations and their role and potential in augmenting existing retrieval models effectiveness. The proposed approach is unique in explicitly interpreting a semantic reference as a pointer to a concept in the semantic model that activates all its linked neighboring concepts. It is in fact the formalization of the information retrieval model and the integration of knowledge resources from the Linguistic Linked Open Data cloud that is distinctive from other approaches. The preprocessing of the semantic model using Formal Concept Analysis enables the extraction of conceptual spaces (formal contexts)that are based on sub-graphs from the original structure of the semantic model. The types of conceptual spaces built in this case are limited by the KOSs structural relations relevant to retrieval: exact match, broader, narrower, and related. They capture the definitional and relational aspects of the concepts in the semantic model. Also, each formal context is assigned an operational role in the flow of processes of the retrieval system enabling a clear path towards the implementations of monolingual and cross-lingual systems. By following this model’s theoretical description in constructing a retrieval system, evaluation results have shown statistically significant results in both monolingual and bilingual settings when no methods for query expansion were used. The test suite was run on the Cross-Language Evaluation Forum Domain Specific 2004-2006 collection with additional extensions to match the specifics of this model.

SecGOD - Google Docs: Now I Feel Safer!

This paper presents SecGOD. A tool that protects the privacy of documents created with online office suites. SecGOD is implemented as a Greasemonkey java-script making it deployable on all popular greesemonkey compatible browsers and utilizes symmetric key encryption. All operations run on the client side, with SecGOD operating invisibly as concerned by the cloud, with no changes needed to the code that is provided to the cloud server provider. Finally, the effectiveness of SecGOD is demonstrated by conducting extensive experiments measuring the processing time for the three versions of AES (128, 192, 256 bits).

Predictive Risk Modelling for Integrated Care: a Structured Review

If patients at risk of admission or readmission to hospital or other forms of care could be identified and offered suitable early interventions then their lives and long-term health may be improved by reducing the chances of future admission or readmission to care, and hopefully, their cost of care reduced. Considerable work has been carried out in this subject area especially in the USA and the UK. This has led for instance to the development of tools such as PARR, PARR-30, and the Combined Predictive Model for prediction of emergency readmission or admission to acute care. Here we perform a structured review the academic and grey literature on predictive risk tools for social care utilisation, as well as admission and readmission to general hospitals and psychiatric hospitals. This is the first phase of a project in partnership with Docobo Ltd and funded by Innovate UK,in which we seek to develop novel predictive risk tools and dashboards to assist commissioners in Clinical Commissioning Groups with the triangulation of the intelligence available from routinely collected data to optimise integrated care and better understand the complex needs of individuals.