Abstract
Tone mapping operators (TMOs) allow the visual appearance of High Dynamic Range (HDR) video to be reproduced on Low Dynamic Range (LDR) displays. While several studies have been made to compare the performance of different TMOs on standard displays, there is only one preliminary study that takes into account the characteristics of Small Screen Devices (SSDs) which are common on mobile platforms that are growing rapidly in popularity. Due to the unique characteristics of mobile devices, the variety of viewing conditions where they are used, and the fact that they are becoming so widespread, it is important to identify what is the best method to deliver HDR video content to these devices. This paper presents an evaluation of HDR video on mobile devices using an HDR display as reference. Six state-of-the-art HDR video tone mappers are evaluated by conducting a psychophysical experiment where participants were asked to rank the tone mappers applied to different HDR video footage. A comparison was made between tone mapped HDR video footage shown on a tablet and an LCD display compared with the same HDR video footage shown simultaneously on an HDR display. This study shows there is a subtle but statistically significant difference in the preference of TMOs between SSD and LDR even though the overall ordering of TMOs is the same across both displays.

Abstract
UNIX-based operative systems were always empowered by scriptable shell interfaces, with a core set of powerful tools to perform manipulation over files and data streams. However those tools can be difficult to manage at the hands of a non-expert programmer. This paper proposes the creation of a Collaborative Web Platform to easily create workflows using common UNIX command line tools for processing Big Data through a collaborative web GUI.

Abstract
With the increase of the Information and Communication Technologies in all aspects and sectors of our life, a world of unprecedented scenarios is arising. Some of these scenarios are the explosions of new and different Healthcare projects that intend to decrease the economical and social costs of the real ageing population phenomenon, through the delocalization of healthcare services delivery and management to the home. These Ambient Assisted Living environments, which we have taken a step forward with the introduction of proactive techniques for better adapting to its users, usually elderly or chronic patients, are now entering a new phase: users with no special help needs also need to have a healthier Active Ageing. Since the direct correlation between physical activity and health is well established, we present here an idea to better achieve this goal. © Springer International Publishing Switzerland 2014.

Abstract
Due to the large amount of pages in Websites it is important to collect knowledge about users' previous visits in order to provide patterns that allow the customization of the Website. In previous work we proposed a multi-agent approach using agents with two different algorithms (associative rules and collaborative filtering) and showed the results of the offline tests. Both algorithms are incremental and work with binary data. In this paper we present the results of experiments held online. Results show that this multi-agent approach combining different algorithms is capable of improving user's satisfaction.

Abstract
The traditional approach for specifying adaptive behavior in embedded applications requires developers to engage in error-prone programming tasks. This results in long design cycles and in the inherent inability to explore and evaluate a wide variety of alternative adaptation behaviors, critical for systems exposed to dynamic operational and situational environments. In this paper, we introduce a domain-specific language (DSL) for specifying and implementing run-time adaptable application behavior. We illustrate our approach using a real-life stereo navigation application as a case study, highlighting the impact and benefits of dynamically adapting algorithm parameters. The experiments reveal our approach effective, as such run-time adaptations are easily specified in a higher level by the DSL, and thus at a lower programming effort than when using a general-purpose language such as C.

Abstract
Due to the large number of optimizations provided in modern compilers and to compiler optimization specific opportunities, a Design Space Exploration (DSE) is necessary to search for the best sequence of compiler optimizations for a given code fragment (e. g., function). As this exploration is a complex and time consuming task, in this paper we present DSE strategies to select optimization sequences to both improve the performance of each function and reduce the exploration time. The DSE is based on a clustering approach which groups functions with similarities and then explore the reduced search space provided by the optimizations previously suggested for the functions in each group. The identification of similarities between functions uses a data mining method which is applied to a symbolic code representation of the source code. The DSE process uses the reduced set identified by clustering in two ways: as the design space or as the initial configuration. In both ways, the adoption of a pre-selection based on clustering allows the use of simple and fast DSE algorithms. Our experiments for evaluating the effectiveness of the proposed approach address the exploration of compiler optimization sequences considering 49 compilation passes and targeting a Xilinx MicroBlaze processor, and were performed aiming performance improvements for 41 functions. Experimental results reveal that the use of our new clustering-based DSE approach achieved a significant reduction on the total exploration time of the search space (18 x over a Genetic Algorithm approach for DSE) at the same time that important performance speedups (43% over the baseline) were obtained by the optimized codes.