Optimization techniques for curved path computing

Participating media with an inhomogeneous index of refraction make light follow curved paths. Simulating this in a global illumination environment has usually been neglected due to the complexity of the calculations involved, sacrificing accurate physical simulations for efficient visual results. This paper aims to simulate non-linear media in a more reasonable time than previous works without losing physical correctness. Accuracy is achieved by solving the Eikonal equation of geometrical optics, which describes the path followed by a light beam that traverses a non-linear medium. This equation is used in the context of a photon mapping extension.     

Whole-body vibration exposure in sport: four relevant cases

This study investigates the whole-body vibration exposure in kite surfing, alpine skiing, snowboarding and cycling. The vibration exposure was experimentally evaluated following the ISO 2631 guidelines. Results evidenced that the most critical axis is the vertical one. The weighted vibration levels are always larger than 2.5 m/s² and the vibration dose values are larger than 25 m/s^1.75. The exposure limit values of the EU directive are reached after 8–37 min depending on the sport. The vibration magnitude is influenced by the athletes’ speed, by their skill level and sometimes by the equipment. The large vibration values suggest that the practice of sport activities may be a confounding factor in the aetiology of vibration-related diseases.     

Learning Temperature Dynamics on Agar-Based Phantom Tissue Surface During Single Point CO $$_2$$ 2 Laser Exposure

Neural Processing Letters - This paper presents an approach to determine a model of superficial tissue temperature dynamics during continuous wave CO $$_2$$ laser irradiation. The main contribution...     

New approach for optimizing the interpretation and representation of the degree of historical-archaeological evidence in the virtual reconstructions

Virtual Reality - Virtual reconstruction is defined as the visual recovery of a building or object through the creation of a three-dimensional model of the asset to be reconstructed, in a...     

A sampling approach to Debiasing the offline evaluation of recommender systems

Journal of Intelligent Information Systems - Offline evaluation of recommender systems (RSs) mostly relies on historical data, which is often biased. The bias is a result of many confounders that...     

Structural damage identification via time domain response and Markov Chain Monte Carlo method

The present work addresses the problem of structural damage identification built on the statistical inversion approach. Here, the damage state of the structure is continuously described by a cohesion parameter, which is spatially discretized by the finite element method. The inverse problem of damage identification is then posed as the determination of the posterior probability densities of the nodal cohesion parameters. The Markov Chain Monte Carlo method, implemented with the Metropolis–Hastings algorithm, is considered in order to approximate the posterior probabilities by drawing samples from the desired joint posterior probability density function. With this approach, prior information on the sought parameters can be used and the uncertainty concerning the known values of the material properties can be quantified in the estimation of the cohesion parameters. The assessment of the proposed approach has been performed by means of numerical simulations on a simply supported Euler–Bernoulli beam. The damage identification and assessment are performed considering time domain response data. Different damage scenarios and noise levels were addressed, demonstrating the feasibility of the proposed approach.