Accessible Ubiquitous Services for Supporting Daily Activities: A Case Study with Young Adults with Intellectual Disabilities

ABSTRACT

Ubiquitous environments have considerable potential to provide services supporting daily activities (using public transportation to and from workplace, using ATM machines, selecting and purchasing goods in ticketing or vending machines, etc.) in order to assist people with disabilities. Nevertheless, the ubiquitous service providers generally supply generic user interfaces which are not usually accessible for all potential end users. In this article, a case study to verify the adequacy of the user interfaces automatically generated by the Egoki system for two supporting ubiquitous services adapted to young adults with moderate intellectual disabilities was presented. The task completion times and the level of assistance required by participants when using the interfaces were analyzed. Participants were able to access services through a tablet and successfully complete the tasks, regardless of their level of expertise and familiarity with the service. Moreover, results indicate that their performance and confidence improved with practice, as they required fewer direct verbal and pointer cues to accomplish tasks. By applying observational methods during the experimental sessions, several potential improvements for the automated interface generation process were also detected.     

Transfer learning with Partially Constrained Models: Application to reinforcement learning of linked multicomponent robot system control

Transfer learning is a hierarchical approach to reinforcement learning of complex tasks modeled as Markov Decision Processes. The learning results on the source task are used as the starting point for the learning on the target task. In this paper we deal with a hierarchy of constrained systems, where the source task is an under-constrained system, hence called the Partially Constrained Model (PCM). Constraints in the framework of reinforcement learning are dealt with by state-action veto policies. We propose a theoretical background for the hierarchy of training refinements, showing that the effective action repertoires learnt on the PCM are maximal, and that the PCM-optimal policy gives maximal state value functions. We apply the approach to learn the control of Linked Multicomponent Robotic Systems using Reinforcement Learning. The paradigmatic example is the transportation of a hose. The system has strong physical constraints and a large state space. Learning experiments in the target task are realized over an accurate but computationally expensive simulation of the hose dynamics. The PCM is obtained simplifying the hose model. Learning results of the PCM Transfer Learning show an spectacular improvement over conventional Q-learning on the target task.     

Integration of service robots in the smart home by means of UPnP: A surveillance robot case study

Despite the large number of electronic devices that coexist in homes, only a few of them can be easily integrated in the same network. Given that smart home applications are based on the integration of many heterogeneous devices in the same network, the lack of interoperability can become a major issue in the development of advanced services. In this paper we tackle this issue developing an adapter to integrate the service robot Rovio into a smart home by means of Universal Plug and Play (UPnP). Different advanced services are designed to explore the possibilities derived from the integration of service robots in the smart home.     

Dynamic Accessibility using Big Data: The Role of the Changing Conditions of Network Congestion and Destination Attractiveness

Accessibility is essentially a dynamic concept. However, most studies on urban accessibility take a static approach, overlooking the fact that accessibility conditions change dramatically throughout the day. Due to their high spatial and temporal resolution, the new data sources (Big Data) offer new possibilities for the study of accessibility. The aim of this paper is to analyse urban accessibility considering its two components –the performance of the transport network and the attractiveness of the destinations– using a dynamic approach using data from TomTom and Twitter respectively. This allows us to obtain profiles that highlight the daily variations in accessibility in the city of Madrid, and identify the influence of congestion and the changes in location of the population. These profiles reveal significant variations according to transport zones. Each transport zone has its own accessibility profile, and thus its own specific problems, which require solutions that are also specific.     

Energy-based monitoring and correction to enhance the accuracy and stability of explicit co-simulation

Multibody System Dynamics - The simulation of complex engineering applications often requires the consideration of component-level dynamics whose nature and time-scale differ across the elements of...     

FE Modeling of Strain Localization in Soft Rock

A finite-element (FE) model of localized deformation in soft rock taking a strong discontinuity approach is presented. The model is formulated within the context of rate-independent, nonassociated Drucker-Prager plasticity with nonlinear cohesion hardening∕softening. Strain localization is modeled as a jump in the displacement field and simulated within the framework of the FE method using the standard Galerkin approximation. The model is used to simulate the load-displacement behavior of Gosford sandstone deforming in plane strain, focusing on the prediction of the stress levels necessary to initiate strain localization, based on the strong and weak discontinuity criteria (jumps in displacement and strain, respectively), and on the demonstration of mesh-independence of the FE solutions in the bifurcated state. For the sandstone, the onset of weak discontinuity is detected first, before the onset of strong discontinuity, suggesting a possible coupling of the two types of discontinuities in the strain-softening regime.     

Towards the automation of address identification

A new semi-automatic method is presented to standardize or codify addresses, in order to produce bibliometric indicators from bibliographic databases. The hypothesis is that this new method is very trustworthy to normalize authors’ addresses, easy and quick to obtain. As a way to test the method, a set of already hand-coded data is chosen to verify its reliability: 136,821 Spanish documents (2006–2008) downloaded previously from the Web of Science database. Unique addresses from this set were selected to produce a list of keywords representing various institutional sectors. Once the list of terms is obtained, addresses are standardized with this information and the result is compared to the previous hand-coded data. Some tests are done to analyze possible association between both systems (automatic and hand-coding), calculating measures of recall and precision, and some statistical directional and symmetric measures. The outcome shows a good relation between both methods. Although these results are quite general, this overview of institutional sectors is a good way to develop a second approach for the selection of particular centers. This system has some new features because it provides a method based on the previous non-existence of master lists or tables and it has a certain impact on the automation of tasks. The validity of the hypothesis has been proved taking into account not only the statistical measures, but also considering that the obtaining of general and detailed scientific output is less time-consuming and will be even less due to the feedback of these master tables reused for the same kind of data. The same method could be used with any country and/or database creating a new master list taking into account their specific characteristics.     

Milk thermization by pulsed electric fields (PEF) and electrically induced heat

Whole milk was processed using selected combinations of pulsed electric fields (PEF) and thermal treatments to inactivate Listeria innocua. Electric field intensities of 30 and 40 kV/cm were applied at selected number of pulses (1–30) and temperatures (20–72 °C) for less than 10 s. A maximum microbial reduction of 4.3 log cycles was achieved using 10, 17.5, 20 and 25 pulses, when processing milk at 30 kV/cm and initial temperatures of 43, 33, 23 and 13 °C, respectively. Around 4.3 log cycles of L. innocua was observed when treating milk at 40 kV/cm using 3, 10, 12.5, 15, and 20 pulses and 53, 33, 23, 15, and 3 °C, respectively. Milk treated with 40 kV/cm of electric field intensity, few pulses, and initial temperature close to 55 °C showed the best balance between L. innocua inactivation and energy-consumption. An energy expenditure of around 244 J/mL was achieved, which can be further reduced to 44 J/mL using a thermal regeneration system.     

Infrared Lock-in Thermography Crack Localization on Metallic Surfaces for Industrial Diagnosis

Optical lock-in thermography with a modulated laser excitation is used for the qualitative assessment of surface cracks in metallic samples. In order to identify and localize an open defect, a novel dedicated image processing of the recorded IR amplitude sequence is proposed. The obtained results demonstrate the potentiality of active lock-in thermography as a contactless measurement tool for the localization of breaking cracks located into specific regions difficult to reach by other conventional non-destructive testing (NDT) techniques such as eddy currents or ultrasound techniques. Crack localization without a prior preparation of the inspected surface can be a possible alternative to penetrant inspection in industrial processes. Various applications illustrating the proposed procedure are presented.