Using evolutionary algorithms to resolve 3-dimensional geometries encoded in indeterminate data-sets

This thesis concerns the development of optimisation algorithms to determine the relative co-location, (localisation), of a number of freely-flying 'Smart Dust mote' sensor platform elements using a non-deterministic data-set derived from the duplex wireless transmissions between elements. Smart dust motes are miniaturised, microprocessor based, electronic sensor platforms, frequently used for a wide range of remote environmental monitoring applications; including specific climate synoptic observation research and more general meteorology. For the application proposed in this thesis a cluster of the notional smart dust motes are configured to imitate discrete 'Radio Drop Sonde' elements of the wireless enabled monitoring system in use by meteorological research organisations worldwide. This cluster is modelled in software in order to establish the relative positions during the 'flight' ; the normal mode of deployment for the Drop Sonde is by ejection from an aeroplane into an upper-air zone of interest, such as a storm cloud. Therefore the underlying research question is, how to track a number of these independent, duplex wireless linked, free-flying monitoring devices in 3-dimensions and time (to give the monitored data complete spatio-temporal validity). This represents a significant practical challenge, the solution applied in this thesis was to generate 3-dimensional geometries using the only 'real-time' data available; the Radio Signal Strength Indicator (RSSI) data is generated through the 'normal' duplex wireless communications between motes. Individual RSSI values can be considered as a 'representation of the distance magnitude' between wireless devices; when collated into a spatio-temporal data-set it 'encodes' the relative, co-locational, 3-dimensional geometry of all devices in the cluster. The reconstruction, (or decoding), of the 3-dimensional geometries encoded in the spatio-temporal data-set is a complex problem that is addressed through the application of various algorithms. These include, Random Search, and optimisation algorithms, such as the Stochastic Hill-climber, and various forms of Evolutionary Algorithm. It was found that the performance of the geometric reconstruction could be improved through identification of salient aspects of the modelled environment, the result was heuristic operators. In general these led to a decrease in the time taken to reach a convergent solution or a reduction in the number of candidate search space solutions that must be considered. The software model written for this thesis has been implemented to generalise the fundamental characteristics of an optimisation algorithm and to incorporate them into a generic software framework; this then provides the common code to all model algorithms used.EPSRC sourced bursary via The University of Exete

A Qualitative Study Exploring Facilitators for Improved Health Behaviors and Health Behavior Programs: Mental Health Service Users’ Perspectives

Objective. Mental health service users experience high rates of cardiometabolic disorders and have a 20–25% shorter life expectancy than the general population from such disorders. Clinician-led health behavior programs have shown moderate improvements, for mental health service users, in managing aspects of cardiometabolic disorders. This study sought to potentially enhance health initiatives by exploring (1) facilitators that help mental health service users engage in better health behaviors and (2) the types of health programs mental health service users want to develop. Methods. A qualitative study utilizing focus groups was conducted with 37 mental health service users attending a psychosocial rehabilitation center, in Northern British Columbia, Canada. Results. Four major facilitator themes were identified: (1) factors of empowerment, self-value, and personal growth; (2) the need for social support; (3) pragmatic aspects of motivation and planning; and (4) access. Participants believed that engaging with programs of physical activity, nutrition, creativity, and illness support would motivate them to live more healthily. Conclusions and Implications for Practice. Being able to contribute to health behavior programs, feeling valued and able to experience personal growth are vital factors to engage mental health service users in health programs. Clinicians and health care policy makers need to account for these considerations to improve success of health improvement initiatives for this population

Using evolutionary algorithms to resolve 3-dimensional geometries encoded in indeterminate data-sets

This thesis concerns the development of optimisation algorithms to determine the relative co-location, (localisation), of a number of freely-flying 'Smart Dust mote' sensor platform elements using a non-deterministic data-set derived from the duplex wireless transmissions between elements. Smart dust motes are miniaturised, microprocessor based, electronic sensor platforms, frequently used for a wide range of remote environmental monitoring applications; including specific climate synoptic observation research and more general meteorology. For the application proposed in this thesis a cluster of the notional smart dust motes are configured to imitate discrete 'Radio Drop Sonde' elements of the wireless enabled monitoring system in use by meteorological research organisations worldwide. This cluster is modelled in software in order to establish the relative positions during the 'flight' ; the normal mode of deployment for the Drop Sonde is by ejection from an aeroplane into an upper-air zone of interest, such as a storm cloud. Therefore the underlying research question is, how to track a number of these independent, duplex wireless linked, free-flying monitoring devices in 3-dimensions and time (to give the monitored data complete spatio-temporal validity). This represents a significant practical challenge, the solution applied in this thesis was to generate 3-dimensional geometries using the only 'real-time' data available; the Radio Signal Strength Indicator (RSSI) data is generated through the 'normal' duplex wireless communications between motes. Individual RSSI values can be considered as a 'representation of the distance magnitude' between wireless devices; when collated into a spatio-temporal data-set it 'encodes' the relative, co-locational, 3-dimensional geometry of all devices in the cluster. The reconstruction, (or decoding), of the 3-dimensional geometries encoded in the spatio-temporal data-set is a complex problem that is addressed through the application of various algorithms. These include, Random Search, and optimisation algorithms, such as the Stochastic Hill-climber, and various forms of Evolutionary Algorithm. It was found that the performance of the geometric reconstruction could be improved through identification of salient aspects of the modelled environment, the result was heuristic operators. In general these led to a decrease in the time taken to reach a convergent solution or a reduction in the number of candidate search space solutions that must be considered. The software model written for this thesis has been implemented to generalise the fundamental characteristics of an optimisation algorithm and to incorporate them into a generic software framework; this then provides the common code to all model algorithms used.EThOS - Electronic Theses Online ServiceEPSRCGBUnited Kingdo

Planning for whole-farm systems research at a credible scale: subdividing land into farmlets with equivalent initial conditions

Most research comparing different farming systems has been conducted on relatively uniform plots at small scales made necessary by the desire for sufficient replication of the systems and cost limitations. This paper describes an alternative approach to plan the allocation of land to three unreplicated whole-farm management systems such that each farmlet had equivalent starting conditions and yet was at a scale credible to both livestock producers and researchers. The paddocks of each farmlet were distributed across the landscape in a 'patchwork quilt' pattern after six iterations of a mapping exercise using a Geographic Information System. Allocation of paddocks took into account those variables of the landscape and natural resource capacity that were not able to be altered. An important benefit of the procedure was that it ensured that the farmlets were co-located with contiguous paddock boundaries so that all farmlets experienced the same climatic as well as biophysical conditions. An electromagnetic survey was conducted of the entire property and used in conjunction with a detailed soils map in order to classify areas into soil conductivity groupings. Equivalent areas of each soil type were allocated across the three farmlets. Similarly, land was distributed according to its topography so that no farmlet would be compromised by being allocated more low lying, flood-prone land than any other farmlet. The third factor used to allocate land to each farmlet was the prior fertiliser history of the original paddocks. This process ensured that each farmlet was objectively allocated equivalent areas of soil type, topography and fertiliser history thus avoiding initial bias among the farmlets. After the plan for all paddocks of each farmlet was finalised, new paddock boundaries were drawn and where necessary, fencing was removed, modified and added, along with re-arranged watering points. The farmlet treatments commenced in July 2000 when the first pasture establishment and differential fertiliser applications were carried out. Evidence from the electromagnetic survey and the Landsat imagery confirmed that the distribution of hydrologic soil conductivity and vegetation greenness were similar between all farmlets just before the commencement of the experiment

The LHCb upgrade I

International audienceThe LHCb upgrade represents a major change of the experiment. The detectors have been almost completely renewed to allow running at an instantaneous luminosity five times larger than that of the previous running periods. Readout of all detectors into an all-software trigger is central to the new design, facilitating the reconstruction of events at the maximum LHC interaction rate, and their selection in real time. The experiment's tracking system has been completely upgraded with a new pixel vertex detector, a silicon tracker upstream of the dipole magnet and three scintillating fibre tracking stations downstream of the magnet. The whole photon detection system of the RICH detectors has been renewed and the readout electronics of the calorimeter and muon systems have been fully overhauled. The first stage of the all-software trigger is implemented on a GPU farm. The output of the trigger provides a combination of totally reconstructed physics objects, such as tracks and vertices, ready for final analysis, and of entire events which need further offline reprocessing. This scheme required a complete revision of the computing model and rewriting of the experiment's software