The crowd as a cameraman : on-stage display of crowdsourced mobile video at large-scale events

Recording videos with smartphones at large-scale events such as concerts and festivals is very common nowadays. These videos register the atmosphere of the event as it is experienced by the crowd and offer a perspective that is hard to capture by the professional cameras installed throughout the venue. In this article, we present a framework to collect videos from smartphones in the public and blend these into a mosaic that can be readily mixed with professional camera footage and shown on displays during the event. The video upload is prioritized by matching requests of the event director with video metadata, while taking into account the available wireless network capacity. The proposed framework's main novelty is its scalability, supporting the real-time transmission, processing and display of videos recorded by hundreds of simultaneous users in ultra-dense Wi-Fi environments, as well as its proven integration in commercial production environments. The framework has been extensively validated in a controlled lab setting with up to 1 000 clients as well as in a field trial where 1 183 videos were collected from 135 participants recruited from an audience of 8 050 people. 90 % of those videos were uploaded within 6.8 minutes

Data linking for the Semantic Web

By specifying that published datasets must link to other existing datasets, the 4th linked data principle ensures a Web of data and not just a set of unconnected data islands. The authors propose in this paper the term data linking to name the problem of finding equivalent resources on the Web of linked data. In order to perform data linking, many techniques were developed, finding their roots in statistics, database, natural language processing and graph theory. The authors begin this paper by providing background information and terminological clarifications related to data linking. Then a comprehensive survey over the various techniques available for data linking is provided. These techniques are classified along the three criteria of granularity, type of evidence, and source of the evidence. Finally, the authors survey eleven recent tools performing data linking and we classify them according to the surveyed techniques

Project-Team RMoD 2013 Activity Report

Activity Report 2013 Project-Team RMOD Analyses and Languages Constructs for Object-Oriented Application Evolutio

AutoOC: Automated multi-objective design of deep autoencoders and one-class classifiers using grammatical evolution

One-Class Classification (OCC) corresponds to a subclass of unsupervised Machine Learning (ML) that is valuable when labeled data is non-existent. In this paper, we present AutoOC, a computationally efficient Grammatical Evolution (GE) approach that automatically searches for OCC models. AutoOC assumes a multi-objective optimization, aiming to increase the OCC predictive performance while reducing the ML training time. AutoOC also includes two execution speedup mechanisms, a periodic training sampling, and a multi-core fitness evaluation. In particular, we study two AutoOC variants: a pure Neuroevolution (NE) setup that optimizes two types of deep learning models, namely dense Autoencoder (AE) and Variational Autoencoder (VAE); and a general Automated Machine Learning (AutoML) ALL setup that considers five distinct OCC base learners, specifically Isolation Forest (IF), Local Outlier Factor (LOF), One-Class SVM (OC-SVM), AE and VAE. Several experiments were conducted, using eight public OpenML datasets and two validation scenarios (unsupervised and supervised). The results show that AutoOC requires a reasonable amount of execution time and tends to obtain lightweight OCC models. Moreover, AutoOC provides quality predictive results, outperforming a baseline IF for all analyzed datasets and surpassing the best supervised OpenML human modeling for two datasets.- (undefined

The metric tide: report of the independent review of the role of metrics in research assessment and management

This report presents the findings and recommendations of the Independent Review of the Role of Metrics in Research Assessment and Management. The review was chaired by Professor James Wilsdon, supported by an independent and multidisciplinary group of experts in scientometrics, research funding, research policy, publishing, university management and administration. This review has gone beyond earlier studies to take a deeper look at potential uses and limitations of research metrics and indicators. It has explored the use of metrics across different disciplines, and assessed their potential contribution to the development of research excellence and impact. It has analysed their role in processes of research assessment, including the next cycle of the Research Excellence Framework (REF). It has considered the changing ways in which universities are using quantitative indicators in their management systems, and the growing power of league tables and rankings. And it has considered the negative or unintended effects of metrics on various aspects of research culture. The report starts by tracing the history of metrics in research management and assessment, in the UK and internationally. It looks at the applicability of metrics within different research cultures, compares the peer review system with metric-based alternatives, and considers what balance might be struck between the two. It charts the development of research management systems within institutions, and examines the effects of the growing use of quantitative indicators on different aspects of research culture, including performance management, equality, diversity, interdisciplinarity, and the ‘gaming’ of assessment systems. The review looks at how different funders are using quantitative indicators, and considers their potential role in research and innovation policy. Finally, it examines the role that metrics played in REF2014, and outlines scenarios for their contribution to future exercises

Towards Interoperable Research Infrastructures for Environmental and Earth Sciences

This open access book summarises the latest developments on data management in the EU H2020 ENVRIplus project, which brought together more than 20 environmental and Earth science research infrastructures into a single community. It provides readers with a systematic overview of the common challenges faced by research infrastructures and how a ‘reference model guided’ engineering approach can be used to achieve greater interoperability among such infrastructures in the environmental and earth sciences. The 20 contributions in this book are structured in 5 parts on the design, development, deployment, operation and use of research infrastructures. Part one provides an overview of the state of the art of research infrastructure and relevant e-Infrastructure technologies, part two discusses the reference model guided engineering approach, the third part presents the software and tools developed for common data management challenges, the fourth part demonstrates the software via several use cases, and the last part discusses the sustainability and future directions

European Union Law and Mitigation of Artificial Intelligence-Related Discrimination Risks in the Private Sector: With Special Focus on the Proposed Artificial Intelligence Act

Integrating AI systems into decision-making processes in the private sector may place the right to non-discrimination in danger. In order to illustrate this threat, risky fields in the private sector, namely employment, banking, advertising, pricing and insurance, were investigated in this paper with authentic examples of AI-related discrimination. Then, the current EU non-discrimination laws and data protection laws were examined, and it was found out that these EU laws do not have the necessary tools to tackle specific risks arising from AI-related discrimination in the private sector. Therefore, there is an immediate need for new EU legislation equipped with tools which explicitly target AI-related discrimination risks in the private sector. The proposed AI Act may provide new tools against AI-related discrimination in the private sector. Thus, this paper analyzes the proposed AI Act in terms of its potential impacts on mitigating AI-related discrimination risks. Due to the cradle-to-grave approach adopted by the proposed AI Act, providers and users of high-risk AI systems are required to comply with various specific ex-ante and ex-post obligations. It is found out that these obligations can contribute to the mitigation of AI-related discrimination by providing new legal tools. However, these tools are not sufficient in the face of AI-related discrimination risks. Therefore, it is concluded that the crucial need for specific legislation to mitigate AI-related discrimination risks in the private sector is still present

The Value of New Scientific Communication Models for Chemistry

This paper is intended as a starting point for discussion on the possible future of scientific communication in chemistry, the value of new models of scientific communication enabled by web based technologies, and the necessary future steps to achieve the benefits of those new models. It is informed by a NSF sponsored workshop that was held on October 23-24, 2008 in Washington D.C. It provides an overview on the chemical communication system in chemistry and describes efforts to enhance scientific communication by introducing new web-based models of scientific communication. It observes that such innovations are still embryonic and have not yet found broad adoption and acceptance by the chemical community. The paper proceeds to analyze the reasons for this by identifying specific characteristics of the chemistry domain that relate to its research practices and socio-economic organization. It hypothesizes how these may influence communication practices, and produce resistance to changes of the current system similar to those that have been successfully deployed in other sciences and which have been proposed by pioneers within chemistry.National Science Foundation, Microsof

Internet based molecular collaborative and publishing tools

The scientific electronic publishing model has hitherto been an Internet based delivery of electronic articles that are essentially replicas of their paper counterparts. They contain little in the way of added semantics that may better expose the science, assist the peer review process and facilitate follow on collaborations, even though the enabling technologies have been around for some time and are mature. This thesis will examine the evolution of chemical electronic publishing over the past 15 years. It will illustrate, which the help of two frameworks, how publishers should be exploiting technologies to improve the semantics of chemical journal articles, namely their value added features and relationships with other chemical resources on the Web. The first framework is an early exemplar of structured and scalable electronic publishing where a Web content management system and a molecular database are integrated. It employs a test bed of articles from several RSC journals and supporting molecular coordinate and connectivity information. The value of converting 3D molecular expressions in chemical file formats, such as the MOL file, into more generic 3D graphics formats, such as Web3D, is assessed. This exemplar highlights the use of metadata management for bidirectional hyperlink maintenance in electronic publishing. The second framework repurposes this metadata management concept into a Semantic Web application called SemanticEye. SemanticEye demonstrates how relationships between chemical electronic articles and other chemical resources are established. It adapts the successful semantic model used for digital music metadata management by popular applications such as iTunes. Globally unique identifiers enable relationships to be established between articles and other resources on the Web and SemanticEye implements two: the Document Object Identifier (DOI) for articles and the IUPAC International Chemical Identifier (InChI) for molecules. SemanticEye’s potential as a framework for seeding collaborations between researchers, who have hitherto never met, is explored using FOAF, the friend-of-a-friend Semantic Web standard for social networks

The EFFECT (End-oF-liFE-CommunicaTion) Study: The Acceptability, Feasibility, and Potential Impact of Using Mortality Prediction Scores for Initiating End-of-Life Goals of Care Communication in the Adult Intensive Care Unit

Purpose: The purpose of this dissertation was to determine the acceptability, feasibility, and potential impact of using Severity of Illness (SOI) mortality risk prediction scores for initiating end-of-life (EOL) goals-of-care communication in the adult Intensive Care Unit (ICU). First, an integrative review was conducted to evaluate the psychometric properties of existing SOI scoring systems and their ability to predict mortality in the adult ICU population as the basis for clinical care and provider-patient/family communication. Next, an integrative review of interventions that can guide researchers in reducing surrogate burden was conducted as the basis for conducting research that may impact surrogates of dying patients in the ICU. Finally, a mixed-methods study was conducted to determine the acceptability and feasibility of having providers use SOI mortality prediction scores for their patients as part of routine care and investigate providers’ intentions to change practice related to goals-of-care communication as a result of awareness of the scores. Problem: While healthcare teams recognize that profoundly ill patients in adult ICUs may die, many families are caught by surprise when their loved one dies in a setting with the most advanced technology and intense care available. ICU deaths account for about 20% of patient deaths in US hospitals and this rate is increasing due in part to deficiencies in EOL care communication that can compromise quality of EOL care and increase resource utilization. Previous studies suggest that communication about EOL goals-of-care is infrequent among healthcare providers, patients, and families; often occurs late in the course of illness; and relies on family members to act as patient surrogates in discussions. Furthermore, despite advances in healthcare quality, family members remain more dissatisfied with communication in the ICU than with other aspects of care. Mechanisms for increasing the timeliness and frequency of discussions about EOL goals-of-care are needed. Specific Aims: Aim 1. Evaluate four valid SOI instruments to determine which instrument, or combination of instruments, is the best fit for the study site, given providers’ perceived feasibility of use. Aim 2. Evaluate the acceptability and feasibility of having providers use SOI mortality prediction scores for their patients as part of routine workflow and practice. Aim 3. Evaluate providers’ intentions to change their practice related to goals-of-care communication with patients and/or their families as a result of awareness of SOI mortality prediction scores. Design: First, an integrative review was conducted to evaluate the psychometric properties of existing SOI scoring systems and their ability to predict mortality in the adult ICU. This review provided the foundational knowledge needed in the selection of SOI systems that were used in aim 1. Next, an integrative review of interventions that can guide researchers in reducing surrogate burden was conducted. This review provided foundational knowledge needed for designing a study that may impact surrogates of dying patients in the ICU. Lastly, an explanatory mixed-methods study was conducted to determine the acceptability and feasibility of having providers use SOI mortality prediction scores for their patients as part of routine care and investigate providers’ intentions to change practice related to goals-of-care communication as a result of awareness of the scores. Self-efficacy theory was used as the theoretical underpinning for the design of this study, specifically aim 3. Findings: Based on discrimination alone, the first integrative review found APACHE IV to be superior, but the VA ICU, SICULA, and SOFA Max were close with ‘very good’ discrimination. The second integrative review revealed six levels of intervention, from the personal ‘Direct Care of the Surrogate’ to the population-based ‘Legal/Regulatory’ and provided a framework to assist researchers when designing and conducting research that involves surrogates. The dissertation study found the use of mortality risk prediction scores as part of routine workflow and practice to be acceptable and feasible – providers agreed to participate, patient mortality risk were evaluated by the instrument chosen by the providers (i.e., the Sequential Organ Failure Assessment - SOFA), and overall, participants found use of daily mortality prediction scores possible in their setting. However, there was some disagreement related to the use of SOFA scores as an effective way for determining patient mortality risk. Based on themes that emerged from interviews, providers with limited ICU experience were eager and accepting of the mortality risk scores while those with vast experience found the scores to be an adjunct to their own intuition; though all acknowledged the benefit of looking at daily scores or ‘trends’. The most substantial of all themes identified was the need to consider SOFA scores in relation to patient context; a number alone should not determine mortality risk and whether a goals-of-care conversation needs to occur. Conclusion: This dissertation study found that overall, participants indicated that using mortality prediction scores as part of their daily workflow was acceptable and feasible. Use of SOFA scores for potentially increasing EOL goals-of-care conversations appears to be most beneficial for providers with limited ICU experience. Large-scale studies are needed to determine the effect of using mortality risk predictions on patient EOL outcomes