3,035 research outputs found
On the Alexandrov Topology of sub-Lorentzian Manifolds
It is commonly known that in Riemannian and sub-Riemannian Geometry, the
metric tensor on a manifold defines a distance function. In Lorentzian
Geometry, instead of a distance function it provides causal relations and the
Lorentzian time-separation function. Both lead to the definition of the
Alexandrov topology, which is linked to the property of strong causality of a
space-time. We studied three possible ways to define the Alexandrov topology on
sub-Lorentzian manifolds, which usually give different topologies, but agree in
the Lorentzian case. We investigated their relationships to each other and the
manifold's original topology and their link to causality.Comment: 20 page
Effects of ecstasy/polydrug use on memory for associative information
Rationale
Associative learning underpins behaviours that are fundamental to the everyday functioning of the individual. Evidence pointing to learning deficits in recreational drug users merits further examination.
Objectives
A word pair learning task was administered to examine associative learning processes in ecstasy/polydrug users.
Methods
After assignment to either single or divided attention conditions, 44 ecstasy/polydrug users and 48 non-users were presented with 80 word pairs at encoding. Following this, four types of stimuli were presented at the recognition phase: the words as originally paired (old pairs), previously presented words in different pairings (conjunction pairs), old words paired with new words, and pairs of new words (not presented previously). The task was to identify which of the stimuli were intact old pairs.
Results
Ecstasy/ploydrug users produced significantly more false-positive responses overall compared to non-users. Increased long-term frequency of ecstasy use was positively associated with the propensity to produce false-positive responses. It was also associated with a more liberal signal detection theory decision criterion value. Measures of long term and recent cannabis use were also associated with these same word pair learning outcome measures. Conjunction word pairs, irrespective of drug use, generated the highest level of false-positive responses and significantly more false-positive responses were made in the divided attention condition compared to the single attention condition.
Conclusions
Overall, the results suggest that long-term ecstasy exposure may induce a deficit in associative learning and this may be in part a consequence of users adopting a more liberal decision criterion value
Case study in six sigma methadology : manufacturing quality improvement and guidence for managers
This article discusses the successful implementation of Six Sigma methodology in a high precision and critical process in the manufacture of automotive products. The Six Sigma define–measure–analyse–improve–control approach resulted in a reduction of tolerance-related problems and improved the first pass yield from 85% to 99.4%. Data were collected on all possible causes and regression analysis, hypothesis testing, Taguchi methods, classification and regression tree, etc. were used to analyse the data and draw conclusions. Implementation of Six Sigma methodology had a significant financial impact on the profitability of the company. An approximate saving of US$70,000 per annum was reported, which is in addition to the customer-facing benefits of improved quality on returns and sales. The project also had the benefit of allowing the company to learn useful messages that will guide future Six Sigma activities
Improved model identification for non-linear systems using a random subsampling and multifold modelling (RSMM) approach
In non-linear system identification, the available observed data are conventionally partitioned into two parts: the training data that are used for model identification and the test data that are used for model performance testing. This sort of 'hold-out' or 'split-sample' data partitioning method is convenient and the associated model identification procedure is in general easy to implement. The resultant model obtained from such a once-partitioned single training dataset, however, may occasionally lack robustness and generalisation to represent future unseen data, because the performance of the identified model may be highly dependent on how the data partition is made. To overcome the drawback of the hold-out data partitioning method, this study presents a new random subsampling and multifold modelling (RSMM) approach to produce less biased or preferably unbiased models. The basic idea and the associated procedure are as follows. First, generate K training datasets (and also K validation datasets), using a K-fold random subsampling method. Secondly, detect significant model terms and identify a common model structure that fits all the K datasets using a new proposed common model selection approach, called the multiple orthogonal search algorithm. Finally, estimate and refine the model parameters for the identified common-structured model using a multifold parameter estimation method. The proposed method can produce robust models with better generalisation performance
Statistical process control of mortality series in the Australian and New Zealand Intensive Care Society (ANZICS) adult patient database: implications of the data generating process
for the ANZICS Centre for Outcome and Resource Evaluation (CORE) of the Australian and New Zealand Intensive Care Society (ANZICS)BACKGROUND Statistical process control (SPC), an industrial sphere initiative, has recently been applied in health care and public health surveillance. SPC methods assume independent observations and process autocorrelation has been associated with increase in false alarm frequency. METHODS Monthly mean raw mortality (at hospital discharge) time series, 1995–2009, at the individual Intensive Care unit (ICU) level, were generated from the Australia and New Zealand Intensive Care Society adult patient database. Evidence for series (i) autocorrelation and seasonality was demonstrated using (partial)-autocorrelation ((P)ACF) function displays and classical series decomposition and (ii) “in-control” status was sought using risk-adjusted (RA) exponentially weighted moving average (EWMA) control limits (3 sigma). Risk adjustment was achieved using a random coefficient (intercept as ICU site and slope as APACHE III score) logistic regression model, generating an expected mortality series. Application of time-series to an exemplar complete ICU series (1995-(end)2009) was via Box-Jenkins methodology: autoregressive moving average (ARMA) and (G)ARCH ((Generalised) Autoregressive Conditional Heteroscedasticity) models, the latter addressing volatility of the series variance. RESULTS The overall data set, 1995-2009, consisted of 491324 records from 137 ICU sites; average raw mortality was 14.07%; average(SD) raw and expected mortalities ranged from 0.012(0.113) and 0.013(0.045) to 0.296(0.457) and 0.278(0.247) respectively. For the raw mortality series: 71 sites had continuous data for assessment up to or beyond lag ₄₀ and 35% had autocorrelation through to lag ₄₀; and of 36 sites with continuous data for ≥ 72 months, all demonstrated marked seasonality. Similar numbers and percentages were seen with the expected series. Out-of-control signalling was evident for the raw mortality series with respect to RA-EWMA control limits; a seasonal ARMA model, with GARCH effects, displayed white-noise residuals which were in-control with respect to EWMA control limits and one-step prediction error limits (3SE). The expected series was modelled with a multiplicative seasonal autoregressive model. CONCLUSIONS The data generating process of monthly raw mortality series at the ICU level displayed autocorrelation, seasonality and volatility. False-positive signalling of the raw mortality series was evident with respect to RA-EWMA control limits. A time series approach using residual control charts resolved these issues.John L Moran, Patricia J Solomo
Digital image correlation vibrometry with low speed equipment
A low-cost method is presented which enables digital image correlation (DIC) with conventional cameras (i.e. not high-speed) to be used for determination of vibration deflected shapes via the use of a stroboscopic lamp and some simple ancillary circuits. For each natural frequency of the structure under consideration, a sequence of images is captured asynchronously with the vibrations using the DIC system and the resulting displacement fields are correlated with the excitation signal driving the vibration using a least-squares approach. Three approaches for performing this correlation are outlined, one of which is developed into the algorithm used for processing the present results to obtain the amplitude and phase of the vibration at each point on the specimen, allowing the deflected shape to be reconstructed. This process is illustrated using the example of a vibrating aluminium plate. The resulting shapes and frequencies agree well with finite element modal analyses of the plate
Effect of temperature anisotropy on various modes and instabilities for a magnetized non-relativistic bi-Maxwellian plasma
Using kinetic theory for homogeneous collisionless magnetized plasmas, we
present an extended review of the plasma waves and instabilities and discuss
the anisotropic response of generalized relativistic dielectric tensor and
Onsager symmetry properties for arbitrary distribution functions. In general,
we observe that for such plasmas only those electromagnetic modes whose
magnetic field perturbations are perpendicular to the ambient magneticeld,
i.e.,B1 \perp B0, are effected by the anisotropy. However, in oblique
propagation all modes do show such anisotropic effects. Considering the
non-relativistic bi-Maxwellian distribution and studying the relevant
components of the general dielectric tensor under appropriate conditions, we
derive the dispersion relations for various modes and instabilities. We show
that only the electromagnetic R- and L- waves, those derived from them and the
O-mode are affected by thermal anisotropies, since they satisfy the required
condition B1\perpB0. By contrast, the perpendicularly propagating X-mode and
the modes derived from it (the pure transverse X-mode and Bernstein mode) show
no such effect. In general, we note that the thermal anisotropy modifies the
parallel propagating modes via the parallel acoustic effect, while it modifies
the perpendicular propagating modes via the Larmor-radius effect. In oblique
propagation for kinetic Alfven waves, the thermal anisotropy affects the
kinetic regime more than it affects the inertial regime. The generalized fast
mode exhibits two distinct acoustic effects, one in the direction parallel to
the ambient magnetic field and the other in the direction perpendicular to it.
In the fast-mode instability, the magneto-sonic wave causes suppression of the
firehose instability. We discuss all these propagation characteristics and
present graphic illustrations
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