A non-intrusive estimation for high-quality Internet TV services

This paper presents a non-intrusive estimator for Internet TV services based on streaming technology. Analyzing the video packets received by the client application, the estimator is capable of selecting the most suitable encoding bitrate for the available bandwidth in the end-to-end path. The estimator has been integrated in a real client/server architecture and evaluated with different network traffic situations. The results of the performed evaluation have revealed the stability and adaptation speed as the best qualities of our proposal.     

An online tool to identify white-collar worker profiles in relation to their ICT skills and mental strain

The introduction of Internet and Information and communication Technologies (ICT) in offices is a global phenomenon that transformed white-collar worker job demands. Although there are several studies of e-skills and mental workload for central countries, there is a lack of similar studies for the Latin American context. An online snowball sampled (n = 352) survey was developed and validated by the authors (internal consistency = 0.7). We characterized ICT worker profiles from e-skills and these dimensions: attitudes toward, resources usage and technology dependency. Mental Strain was assessed with raw task load index (RTLX) and correlated with the proposed profiles by means of paired T-tests and Mann–Whitney Tests. The sample was characterized by 7.2% of non visual display terminal users and 92.8% of visual display terminal, ICT skilled users. Of the latter, 30.7% were ICT practitioners, 30.4% were ICT Users and 27.2% were E-Business Users. Non VDT users’ mental strain was statistically meaningful smaller than VDT–ICT skilled users’ mental workload. No statistical differences were found in RTLX results when comparing ICT skilled user profiles. Non VDT users can be identified from ICT skilled Users by their lower ITC Dependency and minor use of ICT resources. There were no differences in those dimensions among ICT skilled Profiles. Attitude toward these technologies was a distinct factor for ICT Users in relation to ICT Practitioners and ITC Business Users. The application of this tool in peripheral and central countries would allow a complete ergonomical characterization of white-collar workers within the Information Society.     

An experiment for improving students performance in secondary and tertiary education by means of m-learning auto-assessment

Mobile learning is considered an evolution of e-learning that embraces the ubiquitous nature of current computational systems in order to improve teaching and learning. Within this context it is possible to develop mobile applications oriented to learning, but it is also important to assess to what extent such applications actually work. In this paper we present a new tool designed to reinforce students’ knowledge by means of self-assessment. Improvement in student achievement was evaluated and an attitudinal survey was also carried out to measure student attitudes towards this new tool. Three different experimental groups were selected for this research, with students aged from 14 to 21 years old, including high-school and university students. Results show that this kind of tool improves student achievement, especially amongst younger learners, with a relatively low impact on current teaching activities and methodology.     

Simultaneous learning of perception and action in mobile robots

One of the main problems of robots is the lack of adaptability and the need for adjustment every time the robot changes its working place. To solve this, we propose a learning approach for mobile robots using a reinforcement-based strategy and a dynamic sensor-state mapping. This strategy, practically parameterless, minimises the adjustments needed when the robot operates in a different environment or performs a different task.Our system will simultaneously learn the state space and the action to execute on each state. The learning algorithm will attempt to maximise the time before a robot failure in order to obtain a control policy suited to the desired behaviour, thus providing a more interpretable learning process. The state representation will be created dynamically, starting with an empty state space and adding new states as the robot finds new situations that has not seen before. A dynamic creation of the state representation will avoid the classic, error-prone and cyclic process of designing and testing an ad hoc representation. We performed an exhaustive study of our approach, comparing it with other classic strategies. Unexpectedly, learning both perception and action does not increase the learning time.     

A real-time versatile roadway path extraction and tracking on an FPGA platform

This paper presents an algorithm for roadway path extraction and tracking and its implementation in a Field Programmable Gate Array (FPGA) device. The implementation is particularly suitable for use as a core component of a Lane Departure Warning (LDW) system, which requires high-performance digital image processing as well as low-cost semiconductor devices, appropriate for the high volume production of the automotive market. The FPGA technology proved to be a proper platform to meet these two contrasting requirements. The proposed algorithm is specifically designed to be completely embedded in FPGA hardware to process wide VGA resolution video sequences at 30 frames per second. The main contributions of this work lie in (i) the proper selection, customization and integration of the main functions for road extraction and tracking to cope with the addressed application, and (ii) the subsequent FPGA hardware implementation as a modular architecture of specialized blocks. Experiments on real road scenario video sequences running on the FPGA device illustrate the good performance of the proposed system prototype and its ability to adapt to varying common roadway conditions, without the need for a per-installation calibration procedure.     

Sensitivity analysis of the rice model WARM in Europe: Exploring the effects of different locations,climates and methods of analysis on model sensitivity to crop parameters

Sensitivity analysis studies how the variation in model outputs can be due to different sources of variation. This issue is addressed, in this study, as an application of sensitivity analysis techniques to a crop model in the Mediterranean region. In particular, an application of Morris and Sobol' sensitivity analysis methods to the rice model WARM is presented. The output considered is aboveground biomass at maturity, simulated at five rice districts of different countries (France, Greece, Italy, Portugal, and Spain) for years characterized by low, intermediate, and high continentality. The total effect index of Sobol' (that accounts for the total contribution to the output variation due a given parameter) and two Morris indices (mean μ and standard deviation σ of the ratios output changes/parameter variations) were used as sensitivity metrics. Radiation use efficiency (RUE), optimum temperature (T_opt), and leaf area index at emergence (LAI_ini) ranked in most of the combinations site × year as first, second and third most relevant parameters. Exceptions were observed, depending on the sensitivity method (e.g. LAI_ini resulted not relevant by the Morris method), or site-continentality pattern (e.g. with intermediate continentality in Spain, LAI_ini and T_opt were second and third ranked; with low continentality in Portugal, RUE was outranked by T_opt). Low σ values associated with the most relevant parameters indicated limited parameter interactions. The importance of sensitivity analyses by exploring site × climate combinations is discussed as pre-requisite to evaluate either novel crop-modelling approaches or the application of known modelling solutions to conditions not explored previously. The need of developing tools for sensitivity analysis within the modelling environment is also emphasized.     

Video Surveillance Online Repository (ViSOR): an integrated framework

The availability of new techniques and tools for Video Surveillance and the capability of storing huge amounts of visual data acquired by hundreds of cameras every day call for a convergence between pattern recognition, computer vision and multimedia paradigms. A clear need for this convergence is shown by new research projects which attempt to exploit both ontology-based retrieval and video analysis techniques also in the field of surveillance. This paper presents the ViSOR (Video Surveillance Online Repository) framework, designed with the aim of establishing an open platform for collecting, annotating, retrieving, and sharing surveillance videos, as well as evaluating the performance of automatic surveillance systems. Annotations are based on a reference ontology which has been defined integrating hundreds of concepts, some of them coming from the LSCOM and MediaMill ontologies. A new annotation classification schema is also provided, which is aimed at identifying the spatial, temporal and domain detail level used. The ViSOR web interface allows video browsing, querying by annotated concepts or by keywords, compressed video previewing, media downloading and uploading. Finally, ViSOR includes a performance evaluation desk which can be used to compare different annotations.     

Bond graph based control of a three-phase inverter with LC filter – Connection to passive and active loads

This paper proposes a model of a three phase electrical inverter with a LC output filter in delta connection used in a renewable energy supply system. The concept of inverse bond graph via bicausality is used for the control law design. The control law robustness is tested by connecting passive and active (induction machine) loads.     

A hybrid particle swarm optimization approach for the sequential ordering problem

The sequential ordering problem is a version of the asymmetric travelling salesman problem where precedence constraints on vertices are imposed. A tour is feasible if these constraints are fulfilled, and the objective is to find a feasible solution with minimum cost.