Dimension-adaptive bounds on compressive FLD Classification

Efficient dimensionality reduction by random projections (RP) gains popularity, hence the learning guarantees achievable in RP spaces are of great interest. In finite dimensional setting, it has been shown for the compressive Fisher Linear Discriminant (FLD) classifier that forgood generalisation the required target dimension grows only as the log of the number of classes and is not adversely affected by the number of projected data points. However these bounds depend on the dimensionality d of the original data space. In this paper we give further guarantees that remove d from the bounds under certain conditions of regularity on the data density structure. In particular, if the data density does not fill the ambient space then the error of compressive FLD is independent of the ambient dimension and depends only on a notion of ‘intrinsic dimension'

Clustering in surgical trials : database of intracluster correlations

PMID: 22217216 [PubMed - indexed for MEDLINE] PMCID: PMC3311136 Free PMC ArticlePeer reviewedPublisher PD

Comparison of three methods for evaluation of work postures in a truck assembly plant

This study compared the results of three risk assessment tools (self-reported questionnaire, observational tool, direct measurement method) for the upper limbs and back in a truck assembly plant at two cycle times (11 and 8 min). The weighted Kappa factor showed fair agreement between the observational and direct measurement method for the arm (0.39) and back (0.47). The weighted Kappa factor for these methods was poor for the neck (0) and wrist (0) but the observed proportional agreement (Po) was 0.78 for the neck and 0.83 for the wrist. The weighted Kappa factor between questionnaire and direct measurement showed poor or slight agreement (0) for different body segments in both cycle times. The results revealed moderate agreement between the observational tool and the direct measurement method, and poor agreement between the self-reported questionnaire and direct measurement. Practitioner Summary: This study provides risk exposure measurement by different common ergonomic methods in the field. The results help to develop valid measurements and improve exposure evaluation. Hence, the ergonomist/practitioners should apply the methods with caution, or at least knowing what the issues/errors are

Development of a Biomechanical Method for Ergonomic Evaluation: Comparison with Observational Methods

A wide variety of observational methods have been developed to evaluate the ergonomic workloads in manufacturing. However, the precision and accuracy of these methods remain a subject of debate. The aims of this study were to develop biomechanical methods to evaluate ergonomic workloads and to compare them with observational methods. Two observational methods, i.e. SCANIA Ergonomic Standard (SES) and Rapid Upper Limb Assessment (RULA), were used to assess ergonomic workloads at two simulated workstations. They included four tasks such as tightening & loosening, attachment of tubes and strapping as well as other actions. Sensors were also used to measure biomechanical data (Inclinometers, Accelerometers, and Goniometers). Our findings showed that in assessment of some risk factors both RULA & SES were in agreement with the results of biomechanical methods. However, there was disagreement on neck and wrist postures. In conclusion, the biomechanical approach was more precise than observational methods, but some risk factors evaluated with observational methods were not measurable with the biomechanical techniques developed

Bibliographie des pathologies inhérentes aux cavaliers professionnels

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Flame spread over solid fuel in low-speed concurrent flow

This research program is concerned with the effect of low speed flow on the spreading and extinction processes of flames over solid fuels. Primary attention is given to flame propagation in concurrent flow - the more hazardous situation from the point of view of fire safety

A comparison of neck bending and flexion measurement methods for assessment of ergonomic risk

Head movements of workers were measured in the sagittal plane in order to establish a precise and accurate assessment method to be used in real work situations. Measurements were performed using two inclinometers connected to an embedded recording system. Two quantitative analysis methods were tested, i.e., measurement of bending with an inclinometer attached to the head, and measurement of flexion/extension by using an additional inclinometer located at C7/T1. The results were also compared with a video observation method (qualitative). The results showed that bending measurements were significantly different from those of flexion/extension for angles between 0° and 20°, and angles >45°. There were also significant differences between workers for flexion >45°, reflecting individual variability. Additionally, several limitations of observational methods were revealed by this study

Nonlinear description of transversal motion in a laminar boundary layer with streaks

The nonlinear streamwise growth of a spanwise periodic array of steady streaks in a flat plate boundary layer is numerically computed using the well known Reduced Navier-Stokes formulation. It is found that the flow configuration changes substantially when the amplitude of the streaks grows and the nonlinear effects come into play. The transversal motion (in the wall normal-spanwise plane), which is normally not considered, becomes non-negligible in the nonlinear regime, and it strongly distorts the streamwise velocity profiles, which end up being quite different from those predicted by the linear theory. We analyze in detail the resulting flow patterns for the nonlinearly saturated streaks, and compare them with available experimental results

The Five Factor Model of personality and evaluation of drug consumption risk

The problem of evaluating an individual's risk of drug consumption and misuse is highly important. An online survey methodology was employed to collect data including Big Five personality traits (NEO-FFI-R), impulsivity (BIS-11), sensation seeking (ImpSS), and demographic information. The data set contained information on the consumption of 18 central nervous system psychoactive drugs. Correlation analysis demonstrated the existence of groups of drugs with strongly correlated consumption patterns. Three correlation pleiades were identified, named by the central drug in the pleiade: ecstasy, heroin, and benzodiazepines pleiades. An exhaustive search was performed to select the most effective subset of input features and data mining methods to classify users and non-users for each drug and pleiad. A number of classification methods were employed (decision tree, random forest, $k$-nearest neighbors, linear discriminant analysis, Gaussian mixture, probability density function estimation, logistic regression and na{\"i}ve Bayes) and the most effective classifier was selected for each drug. The quality of classification was surprisingly high with sensitivity and specificity (evaluated by leave-one-out cross-validation) being greater than 70\% for almost all classification tasks. The best results with sensitivity and specificity being greater than 75\% were achieved for cannabis, crack, ecstasy, legal highs, LSD, and volatile substance abuse (VSA).Comment: Significantly extended report with 67 pages, 27 tables, 21 figure