Probabilistic seismic hazard analysis (PSHA) combines the probabilities of all earthquake scenarios with different magnitudes and distances with predictions of resulting ground motion intensity, in order to compute seismic hazard at a site. PSHA also incorporates uncertainties in ground motion predictions, by considering multiple Ground Motion Prediction ("attenuation") Models (GMPMs). Current ...

This paper presents results obtained by numerical study of sloshing effects in medium sized rectangular tanks subjected to a long-period seismic excitation. The Smoothed Particle Hydrodynamics (SPH) method is used, and the wave displacement and pressure are analysed. The intensity of sloshing effects depends not only on the peak ground acceleration but also on the dominant frequency of ground m...

The main objective of this study is to present new method on the basis of genetic algorithms for attenuation relationship determination of horizontal peak ground acceleration and spectral acceleration. The proposed method employs the optimization capabilities of genetic algorithm to determine the coefficients of attenuation relationships of peak ground and spectral accelerations. This method ha...

Low-level feature extraction (camera motion) Ground truth annotation Manual camera motion annotation has been performed by three groups using a tool provided by Joanneum Research. Some types of content made it difficult or impossible for human annotators to describe the camera motion. The comparison of annotations of the same content done by two groups shows significant differences for some fea...

This paper presents a robust method to solve the two coupled problems: ground layer detection and vehicle egomotion estimation, which appear in visual navigation. We virtually rotate the camera to the downward-looking pose in order to exploit the fact that the vehicle motion is roughly constrained to be planar motion on the ground. This camera geometry transformation, together with planar motio...

The widespread application of the hybrid empirical method (HEM) has made it a viable approach for developing ground motion prediction equations in regions where there are few strong motion recordings but there are ample weak motion data from small-magnitude earthquakes. The HEM uses empirical estimates of ground motion in one region (the host region) to provide estimates of ground motion in ano...

The seismic resilience of a structure has been evaluated using peak ground acceleration (PGA). Ground motion parameters such as source characteristics, local site conditions are used to forecast the PGA motion. This paper aims develop an Artificial Neural Network (ANN) based model predict PGA. Here, hypocentral distance ( R h y p o ${R}_{hypo}$ ), shear wave velocity V s 30 ${V}_{s30}$ and mome...