We have developed a new technique for generating homogeneously distributed irregular dot patterns useful for optical devices and digital halftoning technologies. To introduce irregularity, we use elaborately designed sequences called low-discrepancy sequences instead of pseudorandom numbers. We also use a molecular-dynamics redistribution method to improve the distribution of dots. Our method can produce arbitrary density distributions in accordance with a given design. The generated patterns are free from visible roughness as well as any moiré patterns when superimposed on other regular patterns. We demonstrate that our method effectively improves luminance uniformity and eliminates moiré patterns when used for a backlight unit of a liquid-crystal display.

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Using simulation and analysis we show that agent-based auction-cleared automated markets can be stabilized using only completely myopic agents (without value traders), if these naïve agents are provided with a price signal that reflects order book information. This demonstrates that information in the order book is extremely valuable, that prediction can be replaced by better instantaneous information about others' bids, and suggests new, more stable algorithms for market-based control.

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Resilient transportation systems enable quick evacuation, rescue, distribution of relief supplies, and other activities for reducing the impact of natural disasters and for accelerating the recovery from them. The resilience of a transportation system largely relies on the decisions made during a natural disaster. We developed an agent-based traffic simulator for predicting the results of potential actions taken with respect to the transportation system to quickly make appropriate decisions. For realistic simulation, we govern the behavior of individual drivers of vehicles with foundational principles learned from probe-car data. For example, we used the probe-car data to estimate the personality of individual drivers of vehicles in selecting their routes, taking into account various metrics of routes such as travel time, travel distance, and the number of turns. This behavioral model, which was constructed from actual data, constitutes a special feature of our simulator. We built this simulator using the X10 language, which enables massively parallel execution for simulating traffic in a large metropolitan area. We report the use cases of the simulator in three major cities in the context of disaster recovery and resilient transportation.