Human activity recognition from inertial sensor time-series using batch normalized deep LSTM recurrent networks

In recent years machine learning methods for human activity recognition have been found very effective. These classify discriminative features generated from raw input sequences acquired from body-worn inertial sensors. However, it involves an explicit feature extraction stage from the raw data, and although human movements are encoded in a sequence of successive samples in time most state-of-the-art machine learning methods do not exploit the temporal correlations between input data samples. In this paper we present a Long-Short Term Memory (LSTM) deep recurrent neural network for the classification of six daily life activities from accelerometer and gyroscope data. Results show that our LSTM can processes featureless raw input signals, and achieves 92 % average accuracy in a multi-class-scenario. Further, we show that this accuracy can be achieved with almost four times fewer training epochs by using a batch normalization approach

On the influence that the ground electrode diameter has in the propulsion efficiency of an asymmetric capacitor in nitrogen gas

In this work the propulsion force developed in an asymmetric capacitor will be calculated for three different diameters of the ground electrode. The used ion source is a small diameter wire, which generates a positive corona discharge in nitrogen gas directed to the ground electrode. By applying the fluid dynamic and electrostatic theories all hydrodynamic and electrostatic forces that act on the considered geometries will be computed in an attempt to provide a physical insight on the force mechanism that acts on the asymmetrical capacitors, and also to understand how to increase the efficiency of propulsion.Comment: 13 pages, 8 figures, Accepted for publication in "Physics of Plasmas

The GALFA-HI Compact Cloud Catalog

We present a catalog of 1964 isolated, compact neutral hydrogen clouds from the Galactic Arecibo L-Band Feed Array Survey Data Release One (GALFA-HI DR1). The clouds were identified by a custom machine-vision algorithm utilizing Difference of Gaussian kernels to search for clouds smaller than 20'. The clouds have velocities typically between |VLSR| = 20-400 km/s, linewidths of 2.5-35 km/s, and column densities ranging from 1 - 35 x 10^18 cm^-2. The distances to the clouds in this catalog may cover several orders of magnitude, so the masses may range from less than a Solar mass for clouds within the Galactic disc, to greater than 10^4 Solar Masses for HVCs at the tip of the Magellanic Stream. To search for trends, we separate the catalog into five populations based on position, velocity, and linewidth: high velocity clouds (HVCs); galaxy candidates; cold low velocity clouds (LVCs); warm, low positive-velocity clouds in the third Galactic Quadrant; and the remaining warm LVCs. The observed HVCs are found to be associated with previously-identified HVC complexes. We do not observe a large population of isolated clouds at high velocities as some models predict. We see evidence for distinct histories at low velocities in detecting populations of clouds corotating with the Galactic disc and a set of clouds that is not corotating.Comment: 34 Pages, 9 Figures, published in ApJ (2012, ApJ, 758, 44), this version has the corrected fluxes and corresponding flux histogram and masse

A community-based survey of posttraumatic stress disorder in the Netherlands

In this study, the lifetime prevalence of stressful events and current posttraumatic stress disorder (PTSD) in the general adult population in theNetherlands were examined, and risk groups for PTSD were determined. A representative sample of 2,238 adults (≥18 years) in the Netherlands completed digital questionnaires by computer-assisted self-interviewing. In total, 52.2% of the population reported at least one stressful event throughout their life. The estimated prevalence of current PTSD in the total population was 3.8%. Rape and physical assault were the stressful events most likely to be associated with PTSD, witness of injury the least likely. Stressful medical events were moderately associated with PTSD. Prevalence of PTSD was elevated among single women and middle-aged men

Pulsar bow-shock nebulae. II. Hydrodynamical simulation

We present hydrodynamical simulations, using a 2-D two component model (ambient medium and pul sar wind have different specific heat ratios), of bow shocks in a representative regime for pu lsar wind driven bow-shock nebulae. We also investigate the behaviour of a passive toroidal ma gnetic field wound around the pulsar velocity direction. Moreover we estimate the opacity of t he bow-shock to penetration of ISM neutral hydrogen: this quantity affects observable properti es of the nebula, like its size, shape, velocity and surface brightness distribution. Finally we compare these numerical results with those from an analytical model. The development of mor e realistic models is needed in order to tune the criteria for searches of new such objects, a s well as to interpret data on the known objects.Comment: 17 pages, Latex, 6 Encapsulated PostScript figures, accepted for publication in A&

Multiphysics simulation of corona discharge induced ionic wind

Ionic wind devices or electrostatic fluid accelerators are becoming of increasing interest as tools for thermal management, in particular for semiconductor devices. In this work, we present a numerical model for predicting the performance of such devices, whose main benefit is the ability to accurately predict the amount of charge injected at the corona electrode. Our multiphysics numerical model consists of a highly nonlinear strongly coupled set of PDEs including the Navier-Stokes equations for fluid flow, Poisson's equation for electrostatic potential, charge continuity and heat transfer equations. To solve this system we employ a staggered solution algorithm that generalizes Gummel's algorithm for charge transport in semiconductors. Predictions of our simulations are validated by comparison with experimental measurements and are shown to closely match. Finally, our simulation tool is used to estimate the effectiveness of the design of an electrohydrodynamic cooling apparatus for power electronics applications.Comment: 24 pages, 17 figure

Characterizing the Circumgalactic Medium of the Lowest-mass Galaxies: A Case Study of IC 1613

Using 10 sight lines observed with the Hubble Space Telescope/Cosmic Origins Spectrograph, we study the circumgalactic medium (CGM) and outflows of IC 1613, which is a low-mass (M_* ~ 10⁸ M_⊙), dwarf irregular galaxy on the outskirts of the Local Group. Among the sight lines, four are pointed toward UV-bright stars in IC 1613, and the other six sight lines are background QSOs at impact parameters from 6 kpc (<0.1R_(200)) to 61 kpc (0.6R_(200)). We detect a number of Si ii, Si iii, Si iv, C ii, and C iv absorbers, most of which have velocities less than the escape velocity of IC 1613 and thus are gravitationally bound. The line strengths of these ion absorbers are consistent with the CGM absorbers detected in dwarf galaxies at low redshifts. Assuming that Si ii, Si iii, and Si iv comprise nearly 100% of the total silicon, we find 3% (~8 × 10³ M_⊙), 2% (~7 × 10³ M_⊙), and 32%–42% [~(1.0–1.3) × 10⁵ M_⊙] of the silicon mass in the stars, interstellar medium, and within 0.6R_(200) of the CGM of IC 1613. We also estimate the metal outflow rate to be Ṁ_(out,Z) ⩾ 1.1 x 10⁻⁵ M_⊙ yr⁻¹ and the instantaneous metal mass loading factor to be η_Z ≥ 0.004, which are in broad agreement with available observation and simulation values. This work is the first time a dwarf galaxy of such low mass is probed by a number of both QSO and stellar sight lines, and it shows that the CGM of low-mass, gas-rich galaxies can be a large reservoir enriched with metals from past and ongoing outflows

Clinical Performance Feedback Intervention Theory (CP-FIT): a new theory for designing, implementing, and evaluating feedback in health care based on a systematic review and meta-synthesis of qualitative research

Background: Providing health professionals with quantitative summaries of their clinical performance when treating specific groups of patients (“feedback”) is a widely used quality improvement strategy, yet systematic reviews show it has varying success. Theory could help explain what factors influence feedback success, and guide approaches to enhance effectiveness. However, existing theories lack comprehensiveness and specificity to health care. To address this problem, we conducted the first systematic review and synthesis of qualitative evaluations of feedback interventions, using findings to develop a comprehensive new health care-specific feedback theory. Methods: We searched MEDLINE, EMBASE, CINAHL, Web of Science, and Google Scholar from inception until 2016 inclusive. Data were synthesised by coding individual papers, building on pre-existing theories to formulate hypotheses, iteratively testing and improving hypotheses, assessing confidence in hypotheses using the GRADE-CERQual method, and summarising high-confidence hypotheses into a set of propositions. Results: We synthesised 65 papers evaluating 73 feedback interventions from countries spanning five continents. From our synthesis we developed Clinical Performance Feedback Intervention Theory (CP-FIT), which builds on 30 pre-existing theories and has 42 high-confidence hypotheses. CP-FIT states that effective feedback works in a cycle of sequential processes; it becomes less effective if any individual process fails, thus halting progress round the cycle. Feedback’s success is influenced by several factors operating via a set of common explanatory mechanisms: the feedback method used, health professional receiving feedback, and context in which feedback takes place. CP-FIT summarises these effects in three propositions: (1) health care professionals and organisations have a finite capacity to engage with feedback, (2) these parties have strong beliefs regarding how patient care should be provided that influence their interactions with feedback, and (3) feedback that directly supports clinical behaviours is most effective. Conclusions: This is the first qualitative meta-synthesis of feedback interventions, and the first comprehensive theory of feedback designed specifically for health care. Our findings contribute new knowledge about how feedback works and factors that influence its effectiveness. Internationally, practitioners, researchers, and policy-makers can use CP-FIT to design, implement, and evaluate feedback. Doing so could improve care for large numbers of patients, reduce opportunity costs, and improve returns on financial investments

Process Mining in Primary Care: A Literature Review

Process mining is the discipline of discovering processes from event logs, checking the conformance of real world events to idealized processes, and ultimately finding ways to improve those processes. It was originally applied to business processes and has recently been applied to healthcare. It can reveal insights into clinical care pathways and inform the redesign of healthcare services. We reviewed the literature on process mining, to investigate the extent to which process mining has been applied to primary care, and to identify specific challenges that may arise in this setting. We identified 143 relevant papers, of which only a small minority (n=7) focused on primary care settings. Reported challenges included data quality (consistency and completeness of routinely collected data); selection of appropriate algorithms and tools; presentation of results; and utilization of results in real-world applications