Spray flows containing droplets and particles are used in various industrial fields. In this study, we investigate an efficient reliable way to predict the spray flow of by combining discrete droplet model (DDM) with ensemble data assimilation for application such problems. The aim is augment cross-sectional measurements as particle image velocimetry (PIV) fast DDM simulations droplets. paper, ...

The mirror effect - a phenomenon whereby a manipulation produces opposite effects on hit and false alarm rates - is benchmark regularity of recognition memory. A likelihood ratio decision process, basing recognition on the relative likelihood that a stimulus is a target or a lure, naturally predicts the mirror effect, and so has been widely adopted in quantitative models of recognition memory. ...

The Data Diffusion Machine (DDM) is a virtual shared memory architecture in which the data has no home location. In this paper we present a preliminary evaluation of a link-based DDM, show the influence of the major design parameters, and show the performance of a set of eight benchmark programs. Most programs are sensitive to item size but to varying degrees. The associativity is unimportant f...

Dynamic decision making (DDM) is usually operationalized in a way that subjects explore and control computersimulated dynamic systems consisting of interconnected variables. Most authors in the field agree on a “standard model of DDM” that assumes that decision makers have to learn the causal structure of the system through appropriate explorative behavior before they can bring the system to gi...

An important open problem is how values are compared to make simple choices. A natural hypothesis is that the brain carries out the computations associated with the value comparisons in a manner consistent with the Drift Diffusion Model (DDM), since this model has been able to account for a large amount of data in other domains. We investigated the ability of four different versions of the DDM ...

Centralized data mining techniques are widely used today for the analysis of large corporate and scientific data stored in databases. However, industry, science, and commerce fields often need to analyze very large datasets maintained over geographically distributed sites by using the computational power of distributed systems. The Grid can play a significant role in providing an effective comp...

BACKGROUND This study examined the osteoinductive activity of demineralized dentin matrix (DDM) from human and polydeoxyribonucleotide (PDRN) for nude mice. METHODS Twenty healthy nude mice, weighing about 15~20 g, were used for the study. DDM from human and PDRN were prepared and implanted subcutaneously into the dorsal portion of the nude mice. The nude mice were sacrificed at 1, 2, and 4 w...

Particle-tracking microrheology (PT-μr) exploits the thermal motion of embedded particles to probe the local mechanical properties of soft materials. Despite its appealing conceptual simplicity, PT-μr requires calibration procedures and operating assumptions that constitute a practical barrier to its wider application. Here we demonstrate differential dynamic microscopy microrheology (DDM-μr), ...

Bounded by limited cognitive capabilities, decision-makers resort to using mental models (reduced versions of real world dynamics) for decision-making and interventions in complex tasks. Such mental models are constantly updated with new experience and knowledge acquired, facilitating a learning process. Through this learning process, mental models can be refined to better represent real world ...

We present a domain decomposition method (DDM) devoted to the iterative solution of time-harmonic electromagnetic scattering problems, involving large and resonant cavities. This DDM uses the electric field integral equation (EFIE) for the solution of Maxwell problems in both interior and exterior subdomains, and we propose a simple preconditioner for the global method, based on the single laye...