129 research outputs found
Multiobjective gas turbine engine controller design using genetic algorithms
This paper describes the use of multiobjective genetic algorithms (MOGAs) in the design of a multivariable control system for a gas turbine engine. The mechanisms employed to facilitate multiobjective search with the genetic algorithm are described with the aid of an example. It is shown that the MOGA confers a number of advantages over conventional multiobjective optimization methods by evolving a family of Pareto-optimal solutions rather than a single solution estimate. This allows the engineer to examine the trade-offs between the different design objectives and configurations during the course of an optimization. In addition, the paper demonstrates how the genetic algorithm can be used to search in both controller structure and parameter space thereby offering a potentially more general approach to optimization in controller design than traditional numerical methods. While the example in the paper deals with control system design, the approach described can be expected to be applicable to more general problems in the fields of computer aided design (CAD) and computer aided engineering (CAE
Data - Time-dependent Behavior of Microvascular Blood Flow and Oxygenation: a Predictor of Functional Outcomes
This data is supplied in support of the the article "Time-dependent Behavior of Microvascular Blood Flow and Oxygenation: a Predictor of Functional Outcomes" by Katarzyna Z. Kuliga, Rodney Gush, Geraldine F. Clough and Andrew J. Chipperfield published in IEEE Transactions on Biomedical Engineering, 2017.
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Dataset: Analysis of microvascular blood flow and oxygenation: discrimination between two haemodynamic steady states using nonlinear measures and multiscale analysis
Dataset supports: Thanaj, M., Chipperfield, A. J., & Clough, G. F. (2018). Analysis of microvascular blood flow and oxygenation: Discrimination between two haemodynamic steady states using nonlinear measures and multiscale analysis. Computers in Biology and Medicine, 102, 157-167.</span
Data-Raspberry data for 'Wearable multimodal skin sensing for the diabetic foot'
This data is supplied in support of the the article "Wearable multimodal skin sensing for the diabetic foot" by Coates, Chipperfield and Clough in the open access journal 'electronics - Raspberry Pi Special edition'.
A data set is provided for each volunteer referenced as 001, 009 and 1001 are enclosed. Biomentric data is supplied for each volunteer along with the data set used in the article. The title of each graph presented in the article identifies the data set used together with the chosen data filter type (low pass) and filter cut off frequency. TA 6 pole Butterwoth filter was used. Data was analysed in Python Spyder 2.3.5.2.
Data is taken in time series with a descriptor of the data stream collected in row 5 of the respective column. The unis for each data stream is in row 6. All data ws taken at 20Hz.</span
Artificial intelligence and mathematical models for intelligent management of aircraft data
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Attractor reconstruction analysis for blood flow signals
Attractor reconstruction analysis has been previously used to determine changes in the shape and variability of fairly periodic signals such as arterial blood pressure signals and electroencephalogram signals, providing a two-dimensional attractor with features like density and symmetry. Since BF signals are fairly periodic and quasi-stationary, we set out to investigate whether attractor reconstruction method could be applied in signals derived from the microvascular perfusion. We describe the basis and the implementation of attractor reconstruction analysis of the microvascular blood flux (BF) signals recorded from the skin of 15 healthy male volunteers, age 29.2 ± 8.1y (mean ± SD). The efficacy of attractor reconstruction analysis (ARA) as a potential method of identifying changes in the microvascular function is evaluated in two haemodynamic steady states, at 33°C, and during warming at 43°C to generate a local thermal hyperaemia (LTH). Our findings show a significant drop of the maximal density derived from the ARA, during increased flow and that there was good discrimination of the blood flow signals between the two haemodynamic steady states, having good classification accuracy (80%). This study shows that ARA of BF signals can identify different microvascular functional states and thus has a potential for the clinical assessment and diagnosis of pathophysiological condition
Flow motion dynamics of microvascular blood flow and oxygenation - evidence of adaptive changes in obesity and type 2 diabetes mellitus/insulin resistance
An altered spatial heterogeneity and temporal stability of network perfusion can give rise to a limited adaptive ability to meet metabolic demands. Derangement of local flow motion activity is associated with reduced microvascular blood flow and tissue oxygenation and it has been suggested that changes in flow motion activity may provide an early indicator of declining, endothelial, neurogenic and myogenic regulatory mechanisms and signal the onset and progression of microvascular pathophysiology. This short conference review article explores some of the evidence for altered flow motion dynamics of blood flux signals acquired using laser Doppler fluximetry in the skin in individuals at risk of developing or with cardio-metabolic disease
Wearable multimodal skin sensing for the diabetic foot
Ulceration of the diabetic foot is currently difficult to detect reliably in a timely manner causing undue suffering and cost. Current best practice is for daily monitoring by those living with diabetes coupled to scheduled monitoring by the incumbent care provider. Although some metrics have proven useful in the detection or prediction of ulceration, no single metric can currently be relied upon for diagnosis. We have developed a prototype multivariate extensible sensor platform with which we demonstrate the ability to gather acceleration, rotation, galvanic skin response, environmental temperature, humidity, force, skin temperature and bioimpedance signals in real time, for later analysis, utilising low cost Raspberry Pi and Arduino devices. We demonstrate the utility of the Raspberry Pi computer in research which is of particular interest to this issue of electronics - Raspberry Pi edition. We conclude that the hardware presented shows potential as an adaptable research tool capable of gathering synchronous data over multiple sensor modalities. This research tool will be utilised to optimise sensor selection, placement and algorithm development prior to translation into a sock, insole or platform diagnostic device at a later date. The combination of a number of clinically relevant parameters is expected to provide greater understanding of tissue state in the foot but requires further volunteer testing and analysis beyond the scope of this paper which will be reported in due course
Optimal coordination of vehicle-to-grid batteries and renewable generators in a distribution system
The increasing penetration of electric vehicles (EVs) and renewable generators (RGs) in the power grid is an inevitable trend to combat air pollution and reduce the usage of fossil fuels. This will challenge distribution networks, which have constrained capacity. However, appropriate dispatch of electric vehicles via vehicle-to-grid (V2G) operation in coordination with the distributed renewable generators can provide support for the grid, reduce the reliance on traditional fossil-fuel generators and benefit EV users. This paper develops a novel agent-based coordinated dispatch strategy for EVs and distributed renewable generators, taking into account both grid's and EV users' concerns and priorities. This optimal dispatch problem is formulated as a distributed multi-objective constraint optimisation problem utilizing the Analytic Hierarchy Process and is solved using a dynamic-programming-based algorithm. The proposed strategy is tested on a modified UK Generic Distribution System (UKGDS). The electricity network model is simplified using a virtual sub-node concept to alleviate the computation burden of a node's agent. Simulation results demonstrate the feasibility and stability of this dispatch strategy
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