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The Web is the main source of information for almost all human activities. Webpages are growing exponentially and becoming more sophisticated, presenting a serious challenge to search engines, recommender systems and Web directories. To organize this complex and vast content, webpage classification is the basic technique, usually based on textual analysis of HTML code. However, the visual appearance of a webpage plays an important role and can be a new alternative to distinguish between categories. In a previous paper, we implemented a Deep Learning model to classify webpages into certain categories using only screenshots, where the results demonstrated a very hard multi-class problem. In the present work, we address the same problem under a new approach, applying One vs. Rest strategy, using regularization techniques, redefining the prediction mechanism, and generating a more reliable dataset. Thus, we have obtained interesting improvements in accuracy and reduction of overfitting. Also, we have developed an online system for classifying webpages that can help designers, website owners, webmasters, and users in general.

As a result of an aging population and an increase in life expectancy, de-mentia is now a serious problem in public health. In elderly populations, this is a syndrome often caused by neurodegenerative diseases that currently lack curative treatment. Dementia has an enormous impact on patients, their families, and society. In a disease management model with no curative treatments, only a care program can be provided to fully treat people with dementia, considering improvement or, at least, maintenance of their quality of life (QoL) a priority of care. Therefore, determining the standard of QoL in a patient and monitoring this over time requires the use of instruments to measure this construct. In line with the biopsychosocial models of medicine and patient-centered care, there is a theoretical and practical interest in including patient-reported outcomes, such as QoL, into patient care. In dementia, QoL has intrinsic importance due to the type of information it provides, the complexity of progression in dementia, and the difficulty of evaluating aspects closely related to neuropsychological changes in patients. The concept of QoL is complex, multidimensional, and includes both objective and subjective aspects. The theoretical models of QoL in dementia include components that are different from those of the general population, requiring specific instruments to measure and monitoring this construct in subjects who experience problems of under-standing, communication, insight, and interpretation. The objective of this chapter is to revise the concept, determinants and instruments of QoL in dementia. A narrative review was performed. This chapter summarizes the theoretical evidence concerning QoL of patients with dementia and attempts to identify its significant predictors. A search of the literature was conducted using electronic databases (Medline, EMBASE, Web of Science) using the search terms “quality of life”, “dementia” and “older people”. Different conceptual models of quality of life in dementia, determinants and instruments of QoL were found by severity level of dementia.

This chapter builds upon the related research that grapples with determinants of TFP, as the driving force of potential growth. In particular, we empirically estimate, in a homogenous and systematic manner, cross-country contributions of cyclical and structural determinants of aggregate TFP growth. Under a growth accounting framework, we compute TFP growth estimates for 41 economies over the 1992–2014 period. After selecting its main drivers by means of a Bayesian Model Averaging (BMA) approach, we exploit panel estimates to conclude that a substantial share of the growth underperformance in recent years was related to cyclical factors, mainly the output gap, but also: (i) over-indebtedness for advanced economies; and (ii) the decline in commodity prices for commodity exporters. In addition, the growth of IT capital and the convergence towards the technological frontier appear to be significant structural drivers of TFP productivity growth in emerging market economies.

The world’s population is ageing and, with that, new social issues arise, especially in terms of healthcare and daily activities. Despite the preference for human professional healthcare, the new socio-economic situation and the decrease in care personnel make necessary to give support to the process of caregiving. In this context, Robotics can be considered as a solution since it can provide healthcare support, help in performing daily tasks, and/or increase the feeling of autonomony and self management. This paper is an overview of the existing robotic technologies for elderly care, analysing their benefits for the elderly.

The ability to grasp is a fundamental requirement for service robots in order to perform meaningful tasks in ordinary environments. However, its robustness can be compromised by the inaccuracy (or lack) of tactile and proprioceptive sensing, especially in the presence of unforeseen slippage. As a solution, vision can be instrumental in detecting grasp errors. In this paper, we present an RGB-D visual application for discerning the success or failure in robot grasping of unknown objects, when a poor proprioceptive information and/or a deformable gripper without tactile information is used. The proposed application is divided into two stages: the visual gripper detection and recognition, and the grasping assessment (i.e. checking whether a grasping error has occurred). For that, three different visual cues are combined: colour, depth and edges. This development is supported by the experimental results on the Hobbit robot which is provided with an elastically deformable gripper.

Population aging is growing and, consequently, has attracted great interest in knowledge on the promotion of health and quality of life (QoL) in old age. In this context, a multidisciplinary team designed the CadeViMa Study, a cross-sectional study to assess the QoL of community-dwelling older people and to identify its associated factors. It incorporated a representative sample of 1106 people aged 60 years or older in Spain. QoL was assessed by means of a generic instrument for measuring health-related QoL (HRQoL), the EQ-5D, and a global QoL rating scale, the Personal Well-Being Index (PWI). The survey also gathered information on the sociodemographic, health-related, psychosocial, financial, and contextual characteristics of the participants. Results indicated that QoL of community-dwelling older adults was influenced by age, health status, loneliness, social support and disability. People aged 78 years or more reported a significantly lower QoL (PWI) than younger counterparts did. Logistic regression models showed that some chronic health conditions, such as osteoarticular or mental health disorders, and disability have a great impact on HRQoL and global QoL. Perceived loneliness and social support strongly influenced global QoL. Loneliness, in turn, was negatively associated to residential satisfaction. We also found that a high sense of coherence, a concept related to successful aging, is also associated to better QoL in old age. These results reflect the importance of the functional, social, mental, and contextual dimensions in the QoL of community-dwelling older adults, and may help to set the priorities of interventions addressed to preserve their QoL.

Animat Approach and Methodology.- A Role for Sleep in Artificial Cognition through Deferred Restructuring of Experience in Autonomous Machines.- Time in Consciousness, Memory and Human-Robot Interaction.- Non-representational Sensorimotor Knowledge.- Perception and Motor Control.- Self-exploration of the Stumpy Robot with Predictive Information Maximization.- Detecting the Vibration in the Artificial Web Inspired by the Spider.- Modelling Reaction Times in Non-linear Classification Tasks.- Multiple Decoupled CPGs with Local Sensory Feedback for Adaptive Locomotion Behaviors of Bio-inspired Walking Robots.- Poramate Manoonpong.- The Role of a Cerebellum-Driven Perceptual Prediction within a Robotic Postural Task.- Biomimetic Agent Based Modelling Using Male Frog Calling Behaviour as a Case Study.- Navigation and Internal World Models Snapshot Homing Navigation Based on Edge Features.- Ground-Nesting Insects Could Use Visual Tracking for Monitoring Nest Position during Learning Flights.- Adaptive Landmark-Based Navigation System Using Learning Techniques.- Robustness Study of a Multimodal Compass Inspired from HD-Cells and Dynamic Neural Fields.- Learning and Adaptation.- Developmental Dynamics of RNNPB: New Insight about Infant Action Development.- Simulating the Emergence of Early Physical and Social Interactions: A Developmental Route through Low Level Visuomotor Learning.- Intrinsically Motivated Decision Making for Situated, Goal-Driven Agents.- An Anti-hebbian Learning Rule to Represent Drive Motivations for Reinforcement Learning.- Unsupervised Learning of Sensory Primitives from Optical Flow Fields.- Reinforcement-Driven Shaping of Sequence Learning in Neural Dynamics.- Rapid Humanoid Motion Learning through Coordinated, Parallel Evolution.- Evolution.- Programmable Self-assembly with Chained Soft Cells: An Algorithm to Fold into 2-D Shapes.- Voxel Robot: A Pneumatic Robot with Deformable Morphology.- Task-Driven Evolution of Modular Self-reconfigurable Robots.- A Bacterial-Based Algorithm to Simulate Complex Adaptive Systems.- Online Evolution of Deep Convolutional Network for Vision-Based Reinforcement Learning.- Collective and Social Behavior.- A Swarm Robotics Approach to Task Allocation under Soft Deadlines and Negligible Switching Costs.- Supervised Robot Groups with Reconfigurable Formation: Theory and Simulations.- Coupling Learning Capability and Local Rules for the Improvement of the Objects' Aggregation Task by a Cognitive Multi-Robot System.- Honeybee-Inspired Quality Monitoring of Routing Paths in Mobile Ad Hoc Networks.- Human Inspiration and Comparison for Monitoring Strategies in a Robotic Convoy Task.- Animal Social Behaviour: A Visual Analysis.- Crowd Emotion Detection Using Dynamic Probabilistic Models.

Date of Conference: 22-25 July, 2014 Conference name: International Conference on Simulation of Adaptive Behavior. SAB 2014: From Animals to Animats Ants, bees and wasps are central place foragers. They leave their nests to forage and routinely return to their home-base. Most are guided by memories of the visual panorama and the visual appearance of the local nest environment when pinpointing their nest. These memories are acquired during highly structured learning walks or flights that are performed when leaving the nest for the first time or whenever the insects had difficulties finding the nest during their previous return. Ground-nesting bees and wasps perform such learning flights daily when they depart for the first time. During these flights, the insects turn back to face the nest entrance and subsequently back away from the nest while flying along ever increasing arcs that are centred on the nest. Flying along these arcs, the insects counter-turn in such a way that the nest entrance is always seen in the frontal visual field at slightly lateral positions. Here we asked how the insects may achieve keeping track of the nest entrance location given that it is a small, inconspicuous hole in the ground, surrounded by complex natural structures that undergo unpredictable perspective transformations as the insect pivots around the area and gains distance from it. We reconstructed the natural visual scene experienced by wasps and bees during their learning flights and applied a number of template-based tracking methods to these image sequences. We find that tracking with a fixed template fails very quickly in the course of a learning flight, but that continuously updating the template allowed us to reliably estimate nest direction in reconstructed image sequences. This is true even for later sections of learning flights when the insects are so far away from the nest that they cannot resolve the nest entrance as a visual feature. We discuss why visual goal-anchoring is likely to be important during the acquisition of visual-spatial memories and describe experiments to test whether insects indeed update nest-related templates during their learning flights. © 2014 Springer International Publishing Switzerland.

Social activities are among the most striking of animal behaviours, providing knowledge about their intelligence, cognition and evolution. However, their observation in the field can be especially arduous. To address this, image processing methods have been developed. However, despite the extensively research on this topic, multiple object tracking still remains a very hard problem due to the wide variety of issues to be overcome (e.g. changes in illumination conditions, stopped colony member, occlusions, etc.). In this paper, we contribute a novel visual tracking application addressing the challenge of detecting and simultaneously tracking hundreds of animals in their habitat. For that, motion is used as primary cue. The system was validated in experiments with laboratory colonies of micro-robots and several example analysis of dewlap lizard’s behaviour.

Cognitive impaired population face with innumerable problems in their daily life. Surprisingly, they are not provided with any help to perform those tasks for which they have difficulties. As a consequence, it is necessary to develop systems that allow those people to live independently and autonomously. Living in a technological era, people could take advantage of the available technology, being provided with some solutions to their needs. This paper presents a platform that assists users with remembering where their possessions are. Mainly, an object recognition process together with an intelligent scheduling applications are integrated in an Ambient Assisted Living (AAL) environment.

On the way to autonomous service robots, spatial reasoning plays a main role since it properly deals with problems involving uncertainty. In particular, we are interested in knowing people’s pose to avoid collisions. With that aim, in this paper, we present a qualitative acceleration model for robotic applications including representation, reasoning and a practical application.