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

A computer vision approach to classification of birds in flight from video sequences

Bird populations are an important bio-indicator; so collecting reliable data is useful for ecologists helping conserve and manage fragile ecosystems. However, existing manual monitoring methods are labour-intensive, time-consuming, and error-prone. The aim of our work is to develop a reliable system, capable of automatically classifying individual bird species in flight from videos. This is challenging, but appropriate for use in the field, since there is often a requirement to identify in flight, rather than when stationary. We present our work in progress, which uses combined appearance and motion features to classify and present experimental results across seven species using Normal Bayes classifier with majority voting and achieving a classification rate of 86%

Lower thermosphere densities of N2, O and Ar under high latitude winter conditions

Measurements of the neutral thermosphere were conducted in northern Scandinavia during the Energy Budget Campaign. These measurements included determinations of N2, O, and Ar densities using rocket-borne experiments. The results obtained in the experiments are presented, taking into account also details regarding the employed experimental methods, and an evaluation of the significance of the data. It is found that there are striking differences in thermospheric distributions of the neutral constituents under different geomagnetic conditions. Under quiet geomagnetic conditions there was reasonable agreement with the United States Standard Atmosphere. The concentrations of N2 and Ar were about 70 percent of the predicted values, while the O concentration was about 2.5 times greater

On almost randomizing channels with a short Kraus decomposition

For large d, we study quantum channels on C^d obtained by selecting randomly N independent Kraus operators according to a probability measure mu on the unitary group U(d). When mu is the Haar measure, we show that for N>d/epsilon^2$, such a channel is epsilon-randomizing with high probability, which means that it maps every state within distance epsilon/d (in operator norm) of the maximally mixed state. This slightly improves on a result by Hayden, Leung, Shor and Winter by optimizing their discretization argument. Moreover, for general mu, we obtain a epsilon-randomizing channel provided N > d (\log d)^6/epsilon^2$. For d=2^k (k qubits), this includes Kraus operators obtained by tensoring k random Pauli matrices. The proof uses recent results on empirical processes in Banach spaces.Comment: We added some background on geometry of Banach space

Radio Astronomy

Contains reports on one research project.National Aeronautics and Space Administration (Grant NGL 22-009-016)National Aeronautics and Space Administration (Grant NGR 22-009-421)National Science Foundation Grant GP-2076

Studies in the Lake Ontario Basin using ERTS-1 and high altitude data

Studies in the Lake Ontario Basin are designed to provide input for models of river basin discharge and macro-scale features of lake circulation. Lake studies appear to require high altitude imagery to record the dynamic features of Lake Ontario so that ERTS-1 data may be interpreted. Land area studies require input of soil moisture, land use and soil-sediment-geomorphology measurements some of which appear to be available, on a regional scale from ERTS-1 products

Characterization and Evaluation of Methane Oxidation Catalysts for Dual-Fuel Diesel and Natural Gas Engines

The UK has incentivized the use of natural gas in heavy goods vehicles (HGVs) by converting to dual-fuel (DF) diesel-natural gas systems to reduce noxious and greenhouse gas emissions. Laboratory and on-road measurements of DF vehicles have demonstrated a decrease in CO$_2$ emissions relative to diesel, but there is an increase in greenhouse gas (CO$_2$e) emissions because of unburned methane. Decreasing tailpipe emissions of methane via after-treatment devices in lean-burn compression ignition engines is a challenge because of low exhaust temperatures (~400 °C) and the presence of water vapor. In this study, six commercially available methane oxidation catalysts (MOCs) were tested for their application in DF HGV vehicles. Each MOC was characterized in terms of the catalyst platinum group metal (PGM) loading (both Pd and Pt), particle size, catalytic surface area, and Pd:Pt ratio. In addition, the washcoat surface area, pore volume, and pore size were evaluated. The MOC conversion efficiency was evaluated in controlled methane-oxidation experiments with varying temperatures, flow rates, and gas compositions. Characteristic-conversion efficiency correlations demonstrate that the influential MOC characteristics were PGM loading (both Pd and Pt), Pd:Pt ratio, washcoat surface area, and washcoat pore volume. With 90 % methane oxidation at less than 400 °C in DF HGV exhaust conditions, sample 1 had the highest conversion efficiency because of a high PGM loading (330 g/ft$^3$, 12,000 g/m$^3$), a 5.9 Pd:Pt ratio, a high alumina washcoat surface area of 20 m$^2$/cm$^3$, and 74-mm$^3$/cm$^3$ pore volume. Additional studies showed increased MOC conversion efficiency with decreasing gas hourly space velocities (GHSVs) and increasing methane concentrations.We acknowledge support from the UK Engineering and Physical Sciences Research Council (EP/K00915X/1), the UK Department for Transport, the Office for Low Emission Vehicles and Innovate UK (project reference 400266), and the industrial partners of the Centre for Sustainable Road Freight. GreenUrban Technologies Ltd. (3) and Prins Autogas UK Ltd. (1) provided the samples for testing in this study

Ledipasvir-Sofosbuvir for treating Chronic Hepatitis C: A NICE Single Technology Appraisal - An Evidence Review Group Perspective

The National Institute for Health and Care Excellence (NICE) invited Gilead, the company manufacturing ledipasvir-sofosbuvir (LDV/SOF), to submit evidence for the clinical effectiveness and cost-effectiveness of LDV/SOF for treating Chronic Hepatitis C. The School of Health and Related Research (ScHARR) Technology Assessment Group was commissioned as the Evidence Review Group (ERG). This paper describes the company’s submission (CS), the ERG review and the subsequent decision of the NICE Appraisal Committee (AC). The ERG produced a critical review of the clinical effectiveness and cost-effectiveness evidence of LDV/SOF based upon the CS. The clinical effectiveness data for LDV/SOF were taken from ten trials, comprised of three Phase III trials and seven Phase II trials. Trials compared different durations of LDV/SOF, with and without ribavirin (RBV). There were no head-to-head trials comparing LDV/SOF with any comparator listed in the NICE scope. Data from the trials were mostly from populations with genotype 1 (GT1) disease, although some limited data were available for populations with genotypes 3 and 4. For GT1 treatment-naïve patients, sustained viral response for 12 weeks (SVR12) rates for LDV/SOF ranged from 93.1% to 99.4% for subgroups of patients with non-cirrhotic disease, whilst SVR rates of 94.1% to 100% were reported for subgroups of patients with compensated cirrhosis. For GT1 treatment-experienced patients, SVR12 rates ranging from 95.4% to 100% were reported for subgroups of non-cirrhotic patients and SVR rates ranging from 81.8% to 100% were reported within subgroups of patients with compensated cirrhosis. Comparator data were not searched systematically as part of the submission, but were based on the company’s previous NICE submission of sofosbuvir, with additional targeted searches. The ERG’s critical appraisal of the company’s economic evaluation highlighted a number of concerns. The ERG’s base case analyses suggested that the incremental cost effectiveness ratios (ICERs) for LDV/SOF (+RBV) are dependent on a) treatment durations, b) whether patients have been previously treated and c) whether patients have liver cirrhosis or not. The AC concluded that it was appropriate to use the approach taken in the ERG’s exploratory analyses, in line with the marketing authorisation, which considered people with and without cirrhosis separately, and estimated the cost-effectiveness for each recommended treatment duration of LDV/SOF