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The burden of hypertension-related illness is greatest in lowresource settings. Barriers to its treatment include limited access to accurate Blood Pressure (BP) monitors, data on variation of BP readings over time, and training on how and when to take reliable BP readings. We developed an affordable smartphone-based BP monitor that records the pressure signal from a standard manually-inflated armband...
Groundwater accessed by handpumps is the primary water supply for many people in Africa. This “Smart Water” project considers the study of a region of Kenya where there is significant demand for groundwater, especially among the poor. Some of the engineering aims of this project are to determine if data acquired from accelerometers mounted in hand-pumps can be used to perform three tasks: (i) estimate...
Extreme Value Theory (EVT) describes the distribution of data considered extreme with respect to some generative distribution, effectively modelling the tails of that distribution. In novelty detection, we wish to determine if data are ldquonormalrdquo with respect to some model of normality. If that model consists of generative distributions, then EVT is appropriate for describing the behaviour of...
Extreme Value Theory (EVT) describes the distribution of data considered extreme with respect to some generative distribution, effectively modelling the tails of that distribution. In novelty detection, or one-class classification, we wish to determine if data are ldquonormalrdquo with respect to some model of normality. If that model consists of generative distributions, then EVT is appropriate for...
Novelty detection, one-class classification, or outlier detection, is typically employed for analysing signals when few examples of ldquoabnormalrdquo data are available, such that a multiclass approach cannot be taken. Multivariate, multimodal density estimation can be used to construct a model of the distribution of normal data. However, setting a decision boundary such that test data can be classified...
We present a novel method for the identification of abnormal episodes in gas-turbine vibration data, in which we show 1) how a model of normal engine behaviour is constructed using signatures of "normal" engine vibration response; 2) how extreme value theory (EVT), a branch of statistics used to determine the expected value of extreme values drawn from a distribution, can be used to set...
Multi-channel combustion data, consisting of gas pressure and two combustion chamber luminosity measurements, are investigated in the prediction of combustion instability. Wavelet analysis is used for feature extraction. A SVM approach is applied for novelty detection and the construction of a model of normal system operation. Novelty scores generated by classifiers from different channels are combined...
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