Adaptive Prediction for Ship Motion in Rotorcraft Maritime Operations

International audienc

Adaptive Prediction for Ship Motion in Rotorcraft Maritime Operations

International audienceThis paper focus on prediction of motion for a ship navigating through sea swell. Ship motion prediction may be useful for helicopter maritime operations and notably for search and rescue missions. An efficient prediction method based on ANF (Adaptive Notch Filters) is proposed for non stationary perturbations. Classical methods of prediction are reviewed for comparison. An application using real ship motion data is carried out for performance evaluation. Finally a comparative analysis based on prediction performance and real time implementation constraints is presented

Detection and Estimation of Helicopters Vibrations by Adaptive Notch Filters

International audienceThis paper addresses online vibration detection in helicopters using Adaptive Filters. Adaptive Notch Filters (ANF) are used to estimate and track the time varying frequencies of the vibrations. We estimate and track the amplitudes and phases of time varying frequencies of the vibrations. This allows the detection of abnormal oscillations in the helicopter flight to keep control of the aircraft. In the application presented, we show the detection of severe vibrations that occurred during a helicopter flight test. This proves the effectiveness of proposed ANF to track and reject narrow band perturbations

Revisiting metric sex estimation of burnt human remains via supervised learning using a reference collection of modern identified cremated individuals (Knoxville, USA)

Objectives: This study aims to increase the rate of correctly sexed calcined individuals from archaeological and forensic contexts. This is achieved by evaluating sexual dimorphism of commonly used and new skeletal elements via uni- and multi-variate metric trait analyses. Materials and methods: Twenty-two skeletal traits were evaluated in 86 individuals from the William M. Bass donated cremated collection of known sex and age-at-death. Four different predictive models, logistic regression, random forest, neural network, and calculation of population specific cut-off points, were used to determine the classification accuracy (CA) of each feature and several combinations thereof. Results: An overall CA of >= 80% was obtained for 12 out of 22 features (humerus trochlea max., and lunate length, humerus head vertical diameter, humerus head transverse diameter, radius head max., femur head vertical diameter, patella width, patella thickness, and talus trochlea length) using univariate analysis. Multivariate analysis showed an increase of CA (>= 95%) for certain combinations and models (e.g., humerus trochlea max. and patella thickness). Our study shows metric sexual dimorphism to be well preserved in calcined human remains, despite the changes that occur during burning. Conclusions: Our study demonstrated the potential of machine learning approaches, such as neural networks, for multivariate analyses. Using these statistical methods improves the rate of correct sex estimations in calcined human remains and can be applied to highly fragmented unburnt individuals from both archaeological and forensic contexts

Psychologie et performance : pratiques et représentations des entraîneurs experts

Présentation de quelques " morceaux choisis " ou témoignages d'entraîneurs des Entretiens de l'INSEP des 16 et 17 mai 2013 sur les thèmes de la préparation à la performance, de la gestion des groupes d'entraînements et des collaborations entre l'entraîneur et des tiers spécialistes en psychologie du sport