Abstract
Temporal abnormalities in events and gait phases of human walking can be potentially applied in the gait performance analysis. In this study is presented a novel real-time gait events detector that continuously considers the previous gait motions in order to improve this gait analysis. The detection of heel-strike and toe-off events is performed by a finite state machine (FSM), through decision rules and adaptive thresholds. The proposed algorithm stands out of the state-of-the-art by using adaptive thresholds in the FSM's decision rules, making the proposed gait event detector robust to sporadic perturbations, and adaptive to locomotion mode changes. For such, three stages were considered: thresholds' calibration, real-time detection of gait events and thresholds' update. Anatomical differences between lower limbs demanded independent FSMs for each limb. The algorithm was validated in a simulated biped model, and on a real DARwIn-OP robot, what shows up the generality of the proposed approach. Results highlight that the proposed algorithm correctly detects the gait events (accuracy of 100% and 84.348% in simulated and real conditions, respectively), with average time delays from 15.5 to 34ms. Thus, the proposed detector is an adaptive, accurate and versatile tool for real-time analysis of the feet movements along gait cycle.

Abstract
The news industry has gone through seismic shifts in the past decade with digital content and social media completely redefining how people consume news. Readers check for accurate fresh news from multiple sources throughout the day using dedicated apps or social media on their smartphones and tablets. At the same time, news publishers rely more and more on social networks and citizen journalism as a frontline to breaking news. In this new era of fastflowing instant news delivery and consumption, publishers and aggregators have to overcomea great number of challenges. These include the verification or assessment of a source's reliability; the integration of news with other sources of information; real-time processing of both news content and social streams in multiple languages, in different formats and in high volumes; deduplication; entity detection and disambiguation; automatic summarization; and news recommendation. Although Information Retrieval (IR) applied to news has been a popular research area for decades, fresh approaches are needed due to the changing type and volume of media content available and the way people consume this content. Hence, the first international workshop on recent trends in News Information Retrieval (NewsIR) was held in conjunction with ECIR 2016. As part of the workshop, we released a new dataset consisting of one million news articles to the research community. The workshop was very well attended with around 70 registered participants. We received a healthy number of 19 submissions in total of which 12 were accepted for presentation. In addition to that, we were pleased to have two keynote talks by well-known experts in the field - on with an industry background (Jochen Leidner) and one from academia (Julio Gonzalo). The workshop also included a breakout session to discuss ideas for a future data challenge in news IR and closed with a focused panel discussion to reflect on the day. Throughout the day the workshop stimulated discussions around new and powerful uses of IR applied to news sources and the intersection of multiple IR tasks to solve real user problems. In particular, several ideas were presented on solving complex information needs for media monitoring, event detection and summarisation. Moreover, and going forward, the workshop concluded with a long list of suggestions for shared tasks, and dataset requirements.

Abstract
Estimating the outer scale profile, L0(h) in the context of current very large and future extremely large telescopes is crucial, as it impacts the on-line estimation of turbulence parameters (Cn2(h), r0, ?0 and t0) and the performance of Wide Field Adaptive Optics (WFAO) systems. We describe an on-line technique that estimates L0(h) using AO loop data available at the facility instruments. It constructs the cross-correlation functions of the slopes of two or more wavefront sensors, which are fitted to linear combinations of theoretical responses for individual layers with different altitudes and outer scale values. We analyze some restrictions found in the estimation process, which are general to any measurement technique. The insensitivity of the instrument to large values of outer scale is one of them, as the telescope becomes blind to outer scales larger than its diameter. Another problem is the contradiction between the length of data and the stationarity assumption of the turbulence (turbulence parameters may change during the data acquisition time). Our method effectively deals with problems such as noise estimation, asymmetric correlation functions and wavefront propagation effects. It is shown that the latter cannot be neglected in high resolution AO systems or strong turbulence at high altitudes. The method is applied to the Gemini South MCAO system (GeMS) that comprises five wavefront sensors and two DMs. Statistical values of L0(h) at Cerro Pachón from data acquired with GeMS during three years are shown, where some interesting resemblance to other independent results in the literature are shown.

Abstract
Welcome to SGAMES 2015, the 5th International Conference on Serious Games, Interaction and Simulation. This conference is a multidisciplinary approach to the presentation of research, theory, application, practice and validation in the fields of Serious Games, Interaction and Simulation. As such it covers areas like cognition, psychology, technology-enhanced education, evaluation and assessment, multimedia and information technology. It is the place to show and to see new scientific approaches and results from experiments and real-life applications. © ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2016.

Abstract
The steel industry is the world's largest industrial source of CO2 emissions. Recent UK economic policies have led to reduced domestic steel production giving an apparent reduction in national emissions. However, demand for goods made from steel has not reduced. Emissions have thus been transferred not reduced and implementation of UK climate policies may in future expand this 'carbon leakage.' This paper explores how future UK demand for goods made from steel might be supplied while satisfying national climate policies, and how this will influence global CO2 emissions. Current flows and stocks of steel are estimated from existing databases. Evidence from other developed economies suggests that per capita stocks are tending towards a saturation level so future demand is forecast from population growth and the expected rate of replacement of a stable stock. The carbon intensities of five different steel-making routes are used to predict the allowed scale of future domestic steel production within the industrial emissions allowances set in four energy pathways defined by the UK Government. The remaining requirement for steel must be sourced offshore and the associated emissions are predicted, to give an estimate of the global emissions arising from final demand in the UK. The results show that current UK climate strategy may have a limited effect in reducing the CO2 emissions of the global steel industry, unless the UK shifts towards producing more of its own steel products with domestic secondary steel-making. This option would also increase the security of UK supply and support an expansion of UK manufacturing.

Abstract
The role of human in the Industrie 4.0 vision is still considered as irreplaceable. Therefore, user interfaces of cyber-physical systems involved in the production automation need to be well designed and taking into consideration the industrial application requirements. With the advances in augmented and virtual reality data visualization and novel interaction techniques like mid-air gestures, these approaches seem to be suitable for integration into the industry environment. This paper describes the implementation of an augmented reality application for smart glasses with mid- air gestures and smart phone with touch interaction to compare and evaluate the usage of such interfaces in a production cell comprising an industrial robot.