A Transparent, Reputation-Based Architecture for Semantic Web Annotation

New forms of conceiving the web such as web 2.0 and the semantic web have emerged for numerous purposes ranging from professional activities to leisure. The semantic web is based on associating concepts with web pages, rather than only identifying hyperlinks and repeated literals. ITACA is a project whose aim is to add semantic annotations to web pages, where semantic annotations are Wikipedia URLs. Therefore, users can write, read and vote on semantic annotations of a webpage. Semantic annotations of a webpage are ranked according to users' votes. Building upon the ITACA project, we propose a transparent, reputation-based architecture. With this proposal, semantic annotations are stored in the users' local machines instead of web servers, so that web servers transparency is preserved. To achieve transparency, an indexing server is added to the architecture to locate semantic annotations. Moreover, users are grouped into reputation domains, providing accurate semantic annotation ranking when retrieving annotations of a web page. Cache copies of semantic annotations in annotation servers are done to improve eficiency of the algorithm, reducing the number of sent messages

A Transparent, Reputation-Based Architecture for Semantic Web Annotation

New forms of conceiving the web such as web 2.0 and the semantic web have emerged for numerous purposes ranging from professional activities to leisure. The semantic web is based on associating concepts with web pages, rather than only identifying hyperlinks and repeated literals. ITACA is a project whose aim is to add semantic annotations to web pages, where semantic annotations are Wikipedia URLs. Therefore, users can write, read and vote on semantic annotations of a webpage. Semantic annotations of a webpage are ranked according to users' votes. Building upon the ITACA project, we propose a transparent, reputation-based architecture. With this proposal, semantic annotations are stored in the users' local machines instead of web servers, so that web servers transparency is preserved. To achieve transparency, an indexing server is added to the architecture to locate semantic annotations. Moreover, users are grouped into reputation domains, providing accurate semantic annotation ranking when retrieving annotations of a web page. Cache copies of semantic annotations in annotation servers are done to improve eficiency of the algorithm, reducing the number of sent messages

Real-time multimodal emotion classification system in E-Learning context

Emotions of learners are crucial and important in e-learning as they promote learning. To investigate the effects of emotions on improving and optimizing the outcomes of e-learning, machine learning models have been proposed in the literature. However, proposed models so far are suitable for offline mode, where data for emotion classification is stored and can be accessed boundlessly. In contrast, when data arrives in a stream, the model can see the data once and real-time response is required for real-time emotion classification. Additionally, researchers have identified that single data modality is incapable of capturing the complete insight of the learning experience and emotions. So, multi-modal data streams such as electroencephalogram (EEG), Respiratory Belt (RB), electrodermal activity data (EDA), etc., are utilized to improve the accuracy and provide deeper insights in learners’ emotion and learning experience. In this paper, we propose a Real-time Multimodal Emotion Classification System (ReMECS) based on Feed-Forward Neural Network, trained in an online fashion using the Incremental Stochastic Gradient Descent algorithm. To validate the performance of ReMECS, we have used the popular multimodal benchmark emotion classification dataset called DEAP. The results (accuracy and F1-score) show that the ReMECS can adequately classify emotions in real-time from the multimodal data stream in comparison to the state-of-the-art approaches.Work partially funded by ACCIO under the project TutorIA.Peer ReviewedPostprint (author's final draft

Citclops: Data Interpretation and Knowledge-based Systems Integration

Measuring the optical properties of water bodies (as indicators of, e.g., sewage impact, dissolved organic matter, sediment load or gross biological activity) is a way to assess their environmental status. The Citclops European project, in 2012-2015, developed systems to retrieve and use data on natural-water colour, transparency and fluorescence, using low-cost sensors combined with contextual information, taking into account existing experiences. This paper describes the general interpretation of data and delivery of information as carried out via the development of a decision support system named 'Citclops Data Explorer' and available from the main portal of the project

A Collaborative Protocol for Private Retrieval of Location-Based Information

Privacy and security are paramount for the proper deployment of location-based services (LBSs). We present a novel protocol based on user collaboration to privately retrieve location-based information from an LBS provider. Our approach neither assumes that users or the LBS can be completely trusted with regard to privacy, nor relies on a trusted third party. In addition, user queries, containing accurate locations, remain unchanged, and the collaborative protocol does not impose any special requirements on the query-response function of the LBS. The protocol is analyzed in terms of privacy, network traffic, and LBS processing overhead. We show that our proposal provides exponential scalability in the probability of guaranteed privacy breach, at the expense of a linear relative network cost.Preprin

La Campanya contra el Quart Cinturó : un moviment social urbà

This article is a case study of what is known as urban social movements. The term refers to the threat that is represented by urbanistic action. We present an analysis of the internal and external aspects of the urban social movements as seen specifically in the Vallès Oriental and Occidental. This urban social movement began as a reaction to the construction of the Quart Cinturó, initiated in 1994, and is still active.En este artículo se hace referencia a los movimientos sociales urbanos, con especial incidencia en los que son motivados por la amenaza que representa la acción urbanística. Concretamente, se presenta un análisis de los aspectos internos y externos del movimiento social urbano originado en el Vallès Oriental y Occidental como reacción al proyecto de construcción del Cuarto Cinturón, redactado en 1966. Este movimiento se articulará a través de la Campaña contra el Cuarto Cinturón, iniciada en 1994 y todavia hoy activa

Monitoring and Prognosis System Based on the ICF for People with Traumatic Brain Injury

The objective of this research is to provide a standardized platform to monitor and predict indicators of people with traumatic brain injury using the International Classification of Functioning, Disability and Health, and analyze its potential benefits for people with disabilities, health centers and administrations. We developed a platform that allows automatic standardization and automatic graphical representations of indicators of the status of individuals and populations. We used data from 730 people with acquired brain injury performing periodic comprehensive evaluations in the years 2006-2013. Health professionals noted that the use of color-coded graphical representation is useful for quickly diagnose failures, limitations or restrictions in rehabilitation. The prognosis System achieves 41% of accuracy and sensitivity in the prediction of emotional functions, and 48% of accuracy and sensitivity in the prediction of executive functions. This monitoring and prognosis system has the potential to: (1) save costs and time, (2) provide more information to make decisions, (3) promote interoperability, (4) facilitate joint decision-making, and (5) improve policies of socioeconomic evaluation of the burden of disease. Professionals found the monitoring system useful because it generates a more comprehensive understanding of health oriented to the profile of the patients, instead of their diseases and injuries

Influence of COVID-19 confinement on students' performance in higher education

This study analyzes the effects of COVID-19 confinement on the autonomous learning performance of students in higher education. Using a field experiment with 458 students from three different subjects at Universidad Autónoma de Madrid (Spain), we study the differences in assessments by dividing students into two groups. The first group (control) corresponds to academic years 2017/2018 and 2018/2019. The second group (experimental) corresponds to students from 2019/2020, which is the group of students that had their face-to-face activities interrupted because of the confinement. The results show that there is a significant positive effect of the COVID-19 confinement on students' performance. This effect is also significant in activities that did not change their format when performed after the confinement. We find that this effect is significant both in subjects that increased the number of assessment activities and subjects that did not change the student workload. Additionally, an analysis of students' learning strategies before confinement shows that students did not study on a continuous basis. Based on these results, we conclude that COVID-19 confinement changed students' learning strategies to a more continuous habit, improving their efficiency. For these reasons, better scores in students' assessment are expected due to COVID-19 confinement that can be explained by an improvement in their learning performanceThis research was funded by ADeAPTIVE (Advanced Design of e-Learning Applications Personalizing Teaching to Improve Virtual Education) project with the support of the Erasmus + programme of the European Union (grant number 2017-1-ES01-KA203-038266). This study was also funded by ACCIO´, Spain (Pla d’Actuacio´ de Centres Tecnològics 2019) under the project Augmented Workplace. This study was also funded by the Fondo Supera COVID-19 (Project: Development of tools for the assessment in higher education in the COVID-19 confinemen

Sex and gender differences and biases in artificial intelligence for biomedicine and healthcare

Precision Medicine implies a deep understanding of inter-individual differences in health and disease that are due to genetic and environmental factors. To acquire such understanding there is a need for the implementation of different types of technologies based on artificial intelligence (AI) that enable the identification of biomedically relevant patterns, facilitating progress towards individually tailored preventative and therapeutic interventions. Despite the significant scientific advances achieved so far, most of the currently used biomedical AI technologies do not account for bias detection. Furthermore, the design of the majority of algorithms ignore the sex and gender dimension and its contribution to health and disease differences among individuals. Failure in accounting for these differences will generate sub-optimal results and produce mistakes as well as discriminatory outcomes. In this review we examine the current sex and gender gaps in a subset of biomedical technologies used in relation to Precision Medicine. In addition, we provide recommendations to optimize their utilization to improve the global health and disease landscape and decrease inequalities.This work is written on behalf of the Women’s Brain Project (WBP) (www.womensbrainproject.com/), an international organization advocating for women’s brain and mental health through scientific research, debate and public engagement. The authors would like to gratefully acknowledge Maria Teresa Ferretti and Nicoletta Iacobacci (WBP) for the scientific advice and insightful discussions; Roberto Confalonieri (Alpha Health) for reviewing the manuscript; the Bioinfo4Women programme of Barcelona Supercomputing Center (BSC) for the support. This work has been supported by the Spanish Government (SEV 2015–0493) and grant PT17/0009/0001, of the Acción Estratégica en Salud 2013–2016 of the Programa Estatal de Investigación Orientada a los Retos de la Sociedad, funded by the Instituto de Salud Carlos III (ISCIII) and European Regional Development Fund (ERDF). EG has received funding from the Innovative Medicines Initiative 2 (IMI2) Joint Undertaking under grant agreement No 116030 (TransQST), which is supported by the European Union’s Horizon 2020 research and innovation programme and the European Federation of Pharmaceutical Industries and Associations (EFPIA).Peer ReviewedPostprint (published version

A Transparent, Reputation-Based Architecture for Semantic Web Annotation

New forms of conceiving the web such as web 2.0 and the semantic web have emerged for numerous purposes ranging from professional activities to leisure. The semantic web is based on associating concepts with web pages, rather than only identifying hyperlinks and repeated literals. ITACA is a project whose aim is to add semantic annotations to web pages, where semantic annotations are Wikipedia URLs. Therefore, users can write, read and vote on semantic annotations of a webpage. Semantic annotations of a webpage are ranked according to users' votes. Building upon the ITACA project, we propose a transparent, reputation-based architecture. With this proposal, semantic annotations are stored in the users' local machines instead of web servers, so that web servers transparency is preserved. To achieve transparency, an indexing server is added to the architecture to locate semantic annotations. Moreover, users are grouped into reputation domains, providing accurate semantic annotation ranking when retrieving annotations of a web page. Cache copies of semantic annotations in annotation servers are done to improve eficiency of the algorithm, reducing the number of sent messages