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

Potential groundwater pollution from improper oil and metal waste disposal in Suame, Ghana

Suame is an industrialized hub in Kumasi, Ghana, that is noted for vehicle repairs and servicing, sale of automobile spare parts, and metal fabrication. Some of these activities generate huge volumes of waste oil and metals that are often disposed off indiscriminately into the environment. These could pose a threat to the quality of groundwater in the area, especially if they continuously accumulate in the environment. This study, therefore, investigated the potential impact of the waste disposal on groundwater quality in the area. The methods employed involved mapping all the potential waste oil spillage sources and sampling the soils in such areas (at 0 – 30 and 30 – 60 cm depths) and groundwater supply points for laboratory analyses to determine the presence of the waste. In all, 36 samples (comprising 12 soil and 24 groundwater) were analysedfor the presence of heavy metals including Cd, Ni, Cu, Pb, Zn and Cr, which were used as traceelements for the presence of the waste in the samples. Computedgeo-accumulation indices from the results show the soils are moderately to heavily polluted with Cd and Pb whilst the groundwater, when compared to the WHO drinking water guidelines, is polluted with Pb and Ni. Althoughthe source of the high Pb content observed could be attributed to its transport directly from the activities in the area, the presence of high Ni makes it inconclusive since the Ni in the soil was within the concentration expected of the parent rock geochemistry. This notwithstanding, the study has indicated that groundwater in the area is not safe for human consumption unless the lead and nickel concentrations are reduced to acceptable standard for drinking.Keywords: Groundwater quality, pollution, waste disposal, Suame, Ghan

Si elegans: a computational model of C. elegans muscle response to light

It has long been the goal of computational neuroscientists to understand animal nervous systems, but their vast complexity has made it very difficult to fully understand even basic functions such as movement. The C. elegans nematode offers the opportunity to study a fully described connectome and link neural network to behaviour. In this paper a model of the responses of the body wall muscle in C. elegans to a random light stimulus is presented. An algorithm has been developed that tracks synapses in the nematode nervous system from the stimulus in the phototaxis sensory neurons to the muscles cells. A linear second order model was used to calculate the isometric force in each of the C. elegans body wall muscle cells. The isometric force calculated resembles that of previous investigations in muscle modelling

Service quality practices and students satisfaction towards the Department of Communication Design

The increase in the number of tertiary institutions in Ghana offering Communication Design calls for a review of activities in the premium Department of Communication Design in Kwame Nkrumah University of Science and Technology. Grounded in service qualitytheory, the study examined students' perceptions and satisfaction relationships among five key variables related to satisfaction with service quality: assurance, tangibles, reliability, empathy and responsibility. The design employed for the study was survey. A total of 400 questionnaire were randomly distributed, out of which 260 were returned during the end of the second semester of the 2014/2015 academic year. The instrument used for the study was adapted from Cronin and Taylor's Service Quality Questionnaire.The instrument consisted of two parts; Part A consisted of items o respondent's biodata while Part B comprised of 22 items which elicited responses from student's perceived satisfaction. The results of the study using the factorial analysis technique indicated that students had negative perceptions and satisfaction about service delivery in the department. The findings suggest that there is a missing link between the deapartment and students. Baesd on these findings, the researchers recommend that there should be an avenue where students can address their concerns without malice, and also ensure that these concerns are given the maximum consideration

Growth and Yield Response of Carrot (Daucus Carota L) to Different Green Manures and Plant Spacing

A field experiment was carried out to study the growth and yield response of carrot to different green manures and plant spacing at the College of Agriculture Education, University of Education, Winneba-Mampong Campus in 2015 and 2016. Four different soil amendments (10 t/ha Mucuna pruriens, Chromolaena odorata, Gliricidia sepium, 300Kg/ha NPK (15, 15, 15) and control) along with three spacing regimes (25 x 10cm, 25 x 15cm and 25 x 20cm) were employed in the investigation in Randomized Complete Block Design. The result revealed that the application of 10 t/ha Mucuna pruriens, Chromolaena odorata, Gliricidia sepium and 300Kg/ha NPK (15, 15, 15) improved the vegetative growth of carrot and translocated the assimilates into the final gross and marketable yield of the root compared to the control. Among the spacing regimes, 25 x 20cm produced the best vegetative growth. Application of 300kg/ha NPK was found suitable for maximum gross and marketable yields (28.73 t/ha and 27.23 t/ha, respectively) in 2015. In 2016, Mucuna pruriens, Chromolaena odorata, and Gliricidia sepium treatments produced gross and marketable yields similar to 300kg/ha NPK. With the spacing regime, 25 x 10cm produced maximum gross and marketable yield in both years. The combined treatment effect of 300kg /ha NPK and 10 t /ha of Mucuna pruriens at 25 x 10cm spacing resulted in the best performance in terms of gross and marketable yields. From the production as well as economic points of view a combination 10t/ha Mucuna pruriens at 25 x 10cm spacing may be suggested for maximizing carrot production in the study area. Keywords: Mucuna pruriens, Chromolaena odorata, Gliricidia sepium, green manure, plant spacing, vegetative growth, gross and marketable yields

A multi-level refinement approach towards the classification of quotidian activities using accelerometer data

Wearable inertial measurement units incorporating accelerometers and gyroscopes are increasingly used for activity analysis and recognition. In this paper an activity classification algorithm is presented which includes a novel multi-step refinement with the aim of improving the classification accuracy of traditional approaches. To do so, after the classification takes place, information is extracted from the confusion matrix to focus the computational efforts on those activities with worse classification performance. It is argued that activities differ diversely from each other, therefore a specific set of features may be informative to classify a specific set of activities, but such informativeness should not necessarily be extended to a different activity set. This approach has shown promising results, achieving important classification accuracy improvements of up to 4% with the use of low-dimensional feature vectors

Supporting independent living for older adults; employing a visual based fall detection through analysing the motion and shape of the human body

Falls are one of the greatest risks for older adults living alone at home. This paper presents a novel visual-based fall detection approach to support independent living for older adults through analysing the motion and shape of the human body. The proposed approach employs a new set of features to detect a fall. Motion information of a segmented silhouette when extracted can provide a useful cue for classifying different behaviours, while variation in shape and the projection histogram can be used to describe human body postures and subsequent fall events. The proposed approach presented here extracts motion information using best-fit approximated ellipse and bounding box around the human body, produces projection histograms and determines the head position over time, to generate 10 features to identify falls. These features are fed into a multilayer perceptron neural network for fall classification. Experimental results show the reliability of the proposed approach with a high fall detection rate of 99.60% and a low false alarm rate of 2.62% when tested with the UR Fall Detection dataset. Comparisons with state of the art fall detection techniques show the robustness of the proposed approach

A Quality Control Scheme for a Commercial Pozzolana Plant: A Case Study of Pozzolana Ghana Ltd

A Quality control scheme was developed for a 200 ton per day commercial pozzolana plant. The scheme was evaluated for the first 34 days of production. Statistical Process Control tech­niques were specifically applied to the mechanical properties of setting times and compressive strength. Results obtained showed that pozzolana samples tested were chemically suitable with total SiO2, Al2O3 and Fe2O3 content ≥ 70%. Mechanical tests performed were mostly under control and when out-of-control, they gave valuable indication to plant malfunction or operator errors which were promptly corrected. The results of mechanical properties tested against the three major brands of cement on the Ghanaian market showed that pozzolana gave highest compressive strengths with Dangote CEM I 42.5R ranging between 21.3 MPa - 36.3 MPa at 7 days and 33.8 MPa - 45.1 MPa at 28 days whilst lowest compressive strengths were obtained with Ghacem CEM II B-L 32.5R cement ranging between 16.3 MPa – 23.6 MPa at 7 days and 23.3 MPa – 30.7 MPa at 28 days. Compressive strengths obtained with Diamond CEM II B-L 42.5N cement were average. A mean compressive strength for all brands of ce­ment of 25.2 MPa and 33.6 MPa at 7 days and 28 days respectively were obtained. Keywords: Pozzolana cement, statistical process control, Shewhart chart, compressive strength, setting tim