Interoperable services based on activity monitoring in ambient assisted living environments

Ambient Assisted Living (AAL) is considered as the main technological solution that will enable the aged and people in recovery to maintain their independence and a consequent high quality of life for a longer period of time than would otherwise be the case. This goal is achieved by monitoring human’s activities and deploying the appropriate collection of services to set environmental features and satisfy user preferences in a given context. However, both human monitoring and services deployment are particularly hard to accomplish due to the uncertainty and ambiguity characterising human actions, and heterogeneity of hardware devices composed in an AAL system. This research addresses both the aforementioned challenges by introducing 1) an innovative system, based on Self Organising Feature Map (SOFM), for automatically classifying the resting location of a moving object in an indoor environment and 2) a strategy able to generate context-aware based Fuzzy Markup Language (FML) services in order to maximize the users’ comfort and hardware interoperability level. The overall system runs on a distributed embedded platform with a specialised ceiling- mounted video sensor for intelligent activity monitoring. The system has the ability to learn resting locations, to measure overall activity levels, to detect specific events such as potential falls and to deploy the right sequence of fuzzy services modelled through FML for supporting people in that particular context. Experimental results show less than 20% classification error in monitoring human activities and providing the right set of services, showing the robustness of our approach over others in literature with minimal power consumption

Human behavioural analysis with self-organizing map for ambient assisted living

This paper presents a system for automatically classifying the resting location of a moving object in an indoor environment. The system uses an unsupervised neural network (Self Organising Feature Map) fully implemented on a low-cost, low-power automated home-based surveillance system, capable of monitoring activity level of elders living alone independently. The proposed system runs on an embedded platform with a specialised ceiling-mounted video sensor for intelligent activity monitoring. The system has the ability to learn resting locations, to measure overall activity levels and to detect specific events such as potential falls. First order motion information, including first order moving average smoothing, is generated from the 2D image coordinates (trajectories). A novel edge-based object detection algorithm capable of running at a reasonable speed on the embedded platform has been developed. The classification is dynamic and achieved in real-time. The dynamic classifier is achieved using a SOFM and a probabilistic model. Experimental results show less than 20% classification error, showing the robustness of our approach over others in literature with minimal power consumption. The head location of the subject is also estimated by a novel approach capable of running on any resource limited platform with power constraints

A Novel QoS provisioning Scheme for OBS networks

This paper presents Classified Cloning, a novel QoS provisioning mechanism for OBS networks carrying real-time applications (such as video on demand, Voice over IP, online gaming and Grid computing). It provides such applications with a minimum loss rate while minimizing end-to-end delay and jitter. ns-2 has been used as the simulation tool, with new OBS modules having been developed for performance evaluation purposes. Ingress node performance has been investigated, as well as the overall performance of the suggested scheme. The results obtained showed that new scheme has superior performance to classical cloning. In particular, QoS provisioning offers a guaranteed burst loss rate, delay and expected value of jitter, unlike existing proposals for QoS implementation in OBS which use the burst offset time to provide such differentiation. Indeed, classical schemes increase both end-to-end delay and jitter. It is shown that the burst loss rate is reduced by 50% reduced over classical cloning

Sex Differences in Elite Swimming with Advanced Age Are Less Than Marathon Running

The sex difference in marathon performance increases with finishing place and age of the runner but whether this occurs among swimmers is unknown. The purpose was to compare sex differences in swimming velocity across world record place (1st–10th), age group (25–89 years), and event distance. We also compared sex differences between freestyle swimming and marathon running. The world\u27s top 10 swimming times of both sexes for World Championship freestyle stroke, backstroke, breaststroke, and butterfly events and the world\u27s top 10 marathon times in 5-year age groups were obtained. Men were faster than women for freestyle (12.4 ± 4.2%), backstroke (12.8 ± 3.0%), and breaststroke (14.5 ± 3.2%), with the greatest sex differences for butterfly (16.7 ± 5.5%). The sex difference in swimming velocity increased across world record place for freestyle (P \u3c 0.001), breaststroke, and butterfly for all age groups and distances (P  \u3c 0.001) because of a greater relative drop-off between first and 10th place for women. The sex difference in marathon running increased with the world record place and the sex difference for marathon running was greater than for swimming (P \u3c 0.001). The sex difference in swimming increased with world record place and age, but was less than for marathon running. Collectively, these results suggest more depth in women\u27s swimming than marathon running

New Limits on Local Lorentz Invariance in Mercury and Cesium

We report new bounds on Local Lorentz Invariance (LLI) violation in Cs and Hg. The limits are obtained through the observation of the the spin- precession frequencies of 199Hg and 133Cs atoms in their ground states as a function of the orientation of an applied magnetic field with respect to the fixed stars. We measure the amplitudes of the dipole couplings to a preferred direction in the equatorial plane to be 19(11) nHz for Hg and 9(5) microHz for Cs. The upper bounds established here improve upon previous bounds by about a factor of four. The improvement is primarily due to mounting the apparatus on a rotating table. New bounds are established on several terms in the standard model extension including the first bounds on the spin-couplings of the neutron and proton to the z direction, <7e-30 GeV and <7e-29 GeV, respectively.Comment: 17 pages, 6 figure

Force Steadiness During a Cognitively Challenging Motor Task Is Predicted by Executive Function in Older Adults

Motor performance and cognitive function both decline with aging. Older adults for example are usually less steady for a constant-force task than young adults when performing low-intensity contractions with limb muscles. Healthy older adults can also show varying degrees of cognitive decline, particularly in executive function skills. It is not known, however, whether age-related changes in steadiness of low-force tasks and cognitive function are independent of one another. In this study, we determined if executive function skills in aging are associated with the steadiness during a low-force muscle contraction performed with and without the imposition of a cognitive challenge. We recruited 60 older adults (60–85 years old, 34 women, 26 men) and 48 young adults (19–30 years old, 24 women, 24 men) to perform elbow flexor muscle contractions at 5% of maximal voluntary contraction (MVC) force in the presence and absence of a difficult mental-math task (counting backward by 13 from a four-digit number). Force steadiness was quantified as the coefficient of variation (CV) of force and executive function was estimated with the Trail-making Test part A and B. The cognitive challenge increased the CV of force (i.e., decreased force steadiness) with greater changes in older adults than young adults (5.2 vs. 1.3%, respectively, cognitive challenge × age: P \u3c 0.001). Older adults were 35% slower in both parts A and B of the Trail-making Test (P \u3c 0.001), and to eliminate the effects of age and education on this variable, all further analyses were performed with the age-corrected z-scores for each individual using established normative values. Hierarchical regression models indicated that decreased force steadiness during a cognitive challenge trial was in part, explained by the performance in the Trail-making Test part A and B in older (r = 0.53 and 0.50, respectively, P \u3c 0.05), but not in young adults (P \u3e 0.05). Thus, healthy community-dwelling older adults, who have poorer executive function skills, exhibit reduced force steadiness during tasks when also required to perform a high cognitive demand task, and are likely at risk of reduced capacity to perform daily activities that involve cognitively challenging motor tasks

A Bayesian Probabilistic Argumentation Framework for Learning from Online Reviews

In the real world it is common for agents to posit arguments concerning an issue but not directly specify the attack relations between them. Nonetheless the agent may have these attacks in mind and instead they may provide a proxy indicator through which one can infer the agent's intended argument graph (arguments and attacks). Consider online reviews, where reviews are collections of arguments for and against the product (positive and negative) under review and the rating indicates whether the positive or negative arguments succeed ultimately. In previous work [1] we have proposed a method that formalises this intuition and uses the constellations approach to probabilistic argumentation to construct a probability distribution over the set of arguments graphs the agent may have had in mind. In this paper we extend this proposal and provide a method, that uses Bayesian inference, to update the initial probability distribution using real data. We evaluate our proposal by conducting a number of simulations using synthetic data

Brain Areas Associated with Force Steadiness and Intensity During Isometric Ankle Dorsiflexion in Men and Women

Although maintenance of steady contractions is required for many daily tasks, there is little understanding of brain areas that modulate lower limb force accuracy. Functional magnetic resonance imaging was used to determine brain areas associated with steadiness and force during static (isometric) lower limb target-matching contractions at low and high intensities. Fourteen young adults (6 men and 8 women; 27.1 ± 9.1 years) performed three sets of 16-s isometric contractions with the ankle dorsiflexor muscles at 10, 30, 50, and 70 % of maximal voluntary contraction (MVC). Percent signal changes (PSCs, %) of the blood oxygenation level-dependent response were extracted for each contraction using region of interest analysis. Mean PSC increased with contraction intensity in the contralateral primary motor area (M1), supplementary motor area, putamen, pallidum cingulate cortex, and ipsilateral cerebellum (p \u3c 0.05). The amplitude of force fluctuations (standard deviation, SD) increased from 10 to 70 % MVC but relative to the mean force (coefficient of variation, CV %) was greatest at 10 % MVC. The CV of force was associated with PSC in the ipsilateral parietal lobule (r = −0.28), putamen (r = −0.29), insula (r = −0.33), and contralateral superior frontal gyrus (r = −0.33, p \u3c 0.05). There were minimal sex differences in brain activation across the isometric motor tasks indicating men and women were similarly motivated and able to activate cortical motor centers during static tasks. Control of steady lower limb contractions involves cortical and subcortical motor areas in both men and women and provides insight into key areas for potential cortical plasticity with impaired or enhanced leg function

Analysing product reviews using probabilistic argumentation

Product reviews which are increasingly commonplace on the web typically contain a textual component and a numerical rating. The textual component can be viewed as a collection of arguments for and against the product. Whilst the reviewer may not have provided the attacks between these arguments they typically provide an indication of which set of arguments they view as being more acceptable/winning via the numerical rating (i.e. a positive rating indicates that the positive arguments are accepted and vice versa). Our framework builds upon this intuition and we propose a two step process for identifying a probability distribution over the set of possible argument graphs that the reviewer may have had in mind. The first is the identification step in which for a given review, we identify a distribution by analysing the relationship between the rating and polarity of arguments in the review via the constellations approach to probabilistic argumentation. The second step is the refinement step in which we harness ratings from multiple reviews and use this to refine our probability distribution thus enabling us to learn from the data. We illustrate the applicability of our approach by testing it with real data