Properly accounting for the uncertainties in predicting ground motion parameters is critical for Probabilistic Seismic Hazard Analyses (PSHA). This is particularly important for critical facilities that are designed for long return period motions. Non-ergodic PSHA is a framework that allows for this proper accounting of uncertainties. This, in turn, allows for more informed decisions by designers, owners and regulating agencies. The ergodic assumption implies that the standard deviation applicable to a specific source-path-site combination is equal to the standard deviation estimated using a database with multiple source-path-site combinations. The removal of the ergodic assumption requires dense instrumental networks operating in seismically active zones so that a sufficient number of recordings are made. Only recently, with the advent of networks such as the Japanese KiK-net network has this become possible. This study contributes to the state of the art in earthquake engineering and engineering seismology in general and in non-ergodic seismic hazard analysis in particular. The study is divided in for parts. First, an automated protocol was developed and implemented to process a large database of strong ground motions for GMPE development. A comparison was conducted between the common records in the database processed within this study and other studies. The comparison showed the viability of using the automated algorithm to process strong ground motions. On the other hand, the automated algorithm resulted in narrower usable frequency bandwidths because of the strict criteria adopted for processing the data. Second, an approach to include path-specific attenuation rates in GMPEs was proposed. This approach was applied to a subset of the KiK-net database. The attenuation rates across regions that contains volcanoes was found to be higher than other regions which is in line with the observations of other researchers. Moreover, accounting for the path-specific attenuation rates reduced the aleatoric variability associated with predicting pseudo-spectral accelerations. Third, two GMPEs were developed for active crustal earthquakes in Japan. The two GMPEs followed the ergodic and site-specific formulations, respectively. Finally, a comprehensive residual analysis was conducted to find potential biases in the residuals and propose models to predict some components of variability as a function of some input parameters. / Ph. D.

Yes / Where do the bottlenecks for information and attention lie when our visual system processes incoming stimuli? The human visual system encodes the incoming stimulus and transfers its contents into three major memory systems with increasing time scales, viz., sensory (or iconic) memory, visual short-term memory (VSTM), and long-term memory (LTM). It is commonly believed that the major bottleneck of information processing resides in VSTM. In contrast to this view, we show major bottlenecks for motion processing prior to VSTM. In the first experiment, we examined bottlenecks at the stimulus encoding stage through a partial-report technique by delivering the cue immediately at the end of the stimulus presentation. In the second experiment, we varied the cue delay to investigate sensory memory and VSTM. Performance decayed exponentially as a function of cue delay and we used the time-constant of the exponential-decay to demarcate sensory memory from VSTM. We then decomposed performance in terms of quality and quantity measures to analyze bottlenecks along these dimensions. In terms of the quality of information, two thirds to three quarters of the motion-processing bottleneck occurs in stimulus encoding rather than memory stages. In terms of the quantity of information, the motion-processing bottleneck is distributed, with the stimulus-encoding stage accounting for one third of the bottleneck. The bottleneck for the stimulus-encoding stage is dominated by the selection compared to the filtering function of attention. We also found that the filtering function of attention is operating mainly at the sensory memory stage in a specific manner, i.e., influencing only quantity and sparing quality. These results provide a novel and more complete understanding of information processing and storage bottlenecks for motion processing. / Supported by R01 EY018165 and P30 EY007551 from the National Institutes of Health (NIH).

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