Dome growth, collapse, and valley fill at Soufrière Hills Volcano, Montserrat, from 1995 to 2013: Contributions from satellite radar measurements of topographic change

Frequent high-resolution measurements of topography at active volcanoes can provide important information for assessing the distribution and rate of emplacement of volcanic deposits and their influence on hazard. At dome-building volcanoes, monitoring techniques such as LiDAR and photogrammetry often provide a limited view of the area affected by the eruption. Here, we show the ability of satellite radar observations to image the lava dome and pyroclastic density current deposits that resulted from 15 years of eruptive activity at Soufrière Hills Volcano, Montserrat, from 1995 to 2010. We present the first geodetic measurements of the complete subaerial deposition field on Montserrat, including the lava dome. Synthetic aperture radar observations from the Advanced Land Observation Satellite (ALOS) and TanDEM-X mission are used to map the distribution and magnitude of elevation changes. We estimate a net dense-rock equivalent volume increase of 108 ± 15M m3 of the lava dome and 300 ± 220M m3 of talus and subaerial pyroclastic density current deposits. We also show variations in deposit distribution during different phases of the eruption, with greatest on-land deposition to the south and west, from 1995 to 2005, and the thickest deposits to the west and north after 2005. We conclude by assessing the potential of using radar-derived topographic measurements as a tool for monitoring and hazard assessment during eruptions at dome-building volcanoes

Risk profiles and one-year outcomes of patients with newly diagnosed atrial fibrillation in India: Insights from the GARFIELD-AF Registry.

BACKGROUND: The Global Anticoagulant Registry in the FIELD-Atrial Fibrillation (GARFIELD-AF) is an ongoing prospective noninterventional registry, which is providing important information on the baseline characteristics, treatment patterns, and 1-year outcomes in patients with newly diagnosed non-valvular atrial fibrillation (NVAF). This report describes data from Indian patients recruited in this registry. METHODS AND RESULTS: A total of 52,014 patients with newly diagnosed AF were enrolled globally; of these, 1388 patients were recruited from 26 sites within India (2012-2016). In India, the mean age was 65.8 years at diagnosis of NVAF. Hypertension was the most prevalent risk factor for AF, present in 68.5% of patients from India and in 76.3% of patients globally (P < 0.001). Diabetes and coronary artery disease (CAD) were prevalent in 36.2% and 28.1% of patients as compared with global prevalence of 22.2% and 21.6%, respectively (P < 0.001 for both). Antiplatelet therapy was the most common antithrombotic treatment in India. With increasing stroke risk, however, patients were more likely to receive oral anticoagulant therapy [mainly vitamin K antagonist (VKA)], but average international normalized ratio (INR) was lower among Indian patients [median INR value 1.6 (interquartile range {IQR}: 1.3-2.3) versus 2.3 (IQR 1.8-2.8) (P < 0.001)]. Compared with other countries, patients from India had markedly higher rates of all-cause mortality [7.68 per 100 person-years (95% confidence interval 6.32-9.35) vs 4.34 (4.16-4.53), P < 0.0001], while rates of stroke/systemic embolism and major bleeding were lower after 1 year of follow-up. CONCLUSION: Compared to previously published registries from India, the GARFIELD-AF registry describes clinical profiles and outcomes in Indian patients with AF of a different etiology. The registry data show that compared to the rest of the world, Indian AF patients are younger in age and have more diabetes and CAD. Patients with a higher stroke risk are more likely to receive anticoagulation therapy with VKA but are underdosed compared with the global average in the GARFIELD-AF. CLINICAL TRIAL REGISTRATION-URL: http://www.clinicaltrials.gov. Unique identifier: NCT01090362

Spatial-Frequency Data Acquisition using Rotational Invariant Pattern Matching in Smart Environments

This article details the development and testing of an empirical data capture system with the ability to collect spatial-frequency statistics relating to the movement behaviour of a smart home inhabitant. This is achieved using a greyscale normalised cross-correlation pattern matching algorithm. Environmental obstructions on the floor space can also be inferred from a visual representation of the accumulated data. Whilst this methodology itself is not novel, its application to person tracking specifically within a smart home environment does not appear in the literature and is considered a novel approach. The results of tests performed on the pattern matching technique show a tracking competency rate of 94.45% with a standard deviation of 0.009027, indicating high fidelity across a wide variety of environmental factors

Stopping Criterion impact on Pure Random Search Optimisation for Intelligent Device Distribution

The number of intelligent environment implementations such as smart homes is set to increase dramatically within the next 40 years. This is predicted using forecasts of demographic data which indicates an expansion of the aged population. It has also been predicted that governments will struggle to meet the demand for resources such as sensor technology due to costs. Optimisation of limited resources involves physically positioning devices to maximise pertinent data gathering potential. Currently the most utilised methodology of distributing limited spatial detection sensors such as pressure mats within smart homes is via ad-hoc deployments performed by a human being. In this study idiosyncratic inhabitant spatial-frequency data was processed using a Pure Random Search (PRS) algorithm to uncover probabilistic future regions of interest, alluding to optimal sensor distributions under resource constraint. With PRS a null hypothesis was stated: ‘using lower iteration stopping criteria produce less optimal sensor distributions than when using higher iteration stopping criteria’. A student t-test between 1000 and 5000 iterations was statistically significant at 5% (p = 0.016852) whereby the null hypothesis was rejected. Similar results were obtained between other iteration criteria. These data demonstrate that the iteration stopping criterion is not as critical as sensor size or number of sensors; and that comparable results could be obtained when lower stopping parameters are specified when using PRS

Smart Home Research: Projects and Issues

Smart Homes are environments facilitated with technology that act in a protective and proactive function to assist an inhabitant in managing their daily lives specific to their individual needs. A typical Smart Home implementation would include sensors and actuators to detect changes in status and to initiate beneficial interventions. This paper aims to introduce the diversity of recent Smart Home research and to present the challenges that are faced not only by engineers and potential inhabitants; but also by policy makers and healthcare professionals

Human Positioning and Tracking using Colour Pattern Matching

The gold standard for detection and tracking of a human target in an indoor setting is Background Subtraction (BS). However BS has numerous problems when utilised indoors. Colour pattern matching may offer a viable and superior alternative to BS whilst enhancing privacy and person-device independence. Results obtained from this study demonstrate that, when using colour pattern matching to target a person's clothing, detection rates of 97.28% can be maintained across the electromagnetic spectrum of visible light, and during instances of acute differentiation in ambient illumination whilst allowing for a privacy-enabling blurring technique to be applied to all frames

Human Positioning and Tracking using Colour Pattern Matching

The gold standard for detection and tracking of a human target in an indoor setting is Background Subtraction (BS). However BS has numerous problems when utilised indoors. Colour pattern matching may offer a viable and superior alternative to BS whilst enhancing privacy and person-device independence. Results obtained from this study demonstrate that, when using colour pattern matching to target a person's clothing, detection rates of 97.28% can be maintained across the electromagnetic spectrum of visible light, and during instances of acute differentiation in ambient illumination whilst allowing for a privacy-enabling blurring technique to be applied to all frames

Chapter 24: Smart Home Research: Projects and Issues

Smart Homes are environments facilitated with technology that act in a protective and proactive function to assist an inhabitant in managing their daily lives specific to their individual needs. A typical Smart Home implementation would include sensors and actuators to detect changes in status and to initiate beneficial interventions. This paper aims to introduce the diversity of recent Smart Home research and to present the challenges that are faced not only by engineers and potential inhabitants, but also by policy makers and healthcare professional