Relationships Between Satellite Observed Lit Area and Water Footprints

Global water resources are vulnerable to depletion due to the increasing demand of an ever-increasing human population. A country’s water footprint is a measure of the total volume of water needed to produce the goods and services consumed by the country, including water originating beyond its own borders. The water footprint can be a critical indicator of global water resource use, but its practical application is hindered by a lack of comparable data across national boundaries. The purpose of this article is to test the applicability of the nighttime imagery products produced by the Defense Meteorological Satellite Program’s Operational Linescan System (DMSP-OLS) for the assessment of the global water footprint. To accomplish this purpose, the average areal extent of nighttime lighting (lit area) is calculated from 1997 to 2001. Next, lit area is regressed on the total water footprint for each country, as indicated by the Water Footprint Network (WFN), to estimate that country’s total water footprint using nighttime imagery. Model residuals are analyzed at the national scale to understand the appropriateness of nighttime imagery for assessing water consumption. Results indicate strong positive correlations between lit area and total water footprint (TWF), domestic water withdrawal (DWW), and industrial water consumption (IWC) at the national scale. Overall, the analyses reveal that the rate of agricultural water consumption to total water footprint (AWCR) and population density can affect the precision of estimates when lit area is selected as a proxy to estimate water footprints.     

Air damping of high performance resonating micro-mirrors with angular vertical comb-drive actuators

Microsystem Technologies - The maximum scan angle amplitude of resonating micro-mirrors, intended for micro-projection display applications is limited by air damping. Three-dimensional transient...     

Metamaterial-based graphene thermal emitter

A thermal emitter composed of a frequency-selective surface metamaterial layer and a hexagonal boron nitride-encapsulated graphene filament is demonstrated. The broadband thermal emission of the metamaterial (consisting of ring resonators) was tailored into two discrete bands, and the measured reflection and emission spectra agreed well with the simulation results. The high modulation frequencies that can be obtained in these devices, coupled with their operation in air, confirm their feasibility for use in applications such as gas sensing.

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Distinguishing attacks on stream ciphers based on arrays of pseudo-random words

In numerous modern stream ciphers, the internal state consists of a large array of pseudo-random words, while the output key-stream is a relatively simple function of the state. It has been heuristically shown in several situations [3], [8], [9], [10], [11] and [14] that this structure may lead to distinguishing attacks on the cipher. In this note we present a more rigorous treatment of this structural attack. First, we present a rigorous proof of the main probabilistic claim behind it in the basic cases. We then apply it concretely to the cipher sn3 [12], and demonstrate that the heuristic assumptions of the attack are remarkably precise in more complicated cases.     

Expert-driven genetic algorithms for simulating evaluation functions

In this paper we demonstrate how genetic algorithms can be used to reverse engineer an evaluation function’s parameters for computer chess. Our results show that using an appropriate expert (or mentor), we can evolve a program that is on par with top tournament-playing chess programs, outperforming a two-time World Computer Chess Champion. This performance gain is achieved by evolving a program that mimics the behavior of a superior expert. The resulting evaluation function of the evolved program consists of a much smaller number of parameters than the expert’s. The extended experimental results provided in this paper include a report on our successful participation in the 2008 World Computer Chess Championship. In principle, our expert-driven approach could be used in a wide range of problems for which appropriate experts are available.     

Complexity results on labeled shortest path problems from wireless routing metrics

Metrics to assess the cost of paths through networks are critical to ensuring the efficiency of network routing. This is particularly true in multi-radio multi-hop wireless networks. Effective metrics for these networks must measure the cost of a wireless path based not only on traditional measures such as throughput, but also on the distribution of wireless channels used. In this paper, we argue that routing metrics over such networks may be viewed as a class of existing shortest path problems, the formal language constrained path problems.On this basis, we describe labeled path problems corresponding to two multi-radio wireless routing metrics: Weighted Cumulative Expected Transmission Time (WCETT), developed by Draves et al., and Metric for Interference and Channel-switch (MIC), developed by Yang et al. For the first, we give a concise proof that calculating shortest WCETT paths is strongly NP-Complete for a variety of graph classes. We also show that the existing heuristic given by Draves et al. is an approximator. For the second, we show that calculating loop-free (simple) shortest MIC paths is NP-Complete, and additionally show that the optimization version of the problem is NPO PB-Complete. This result implies that shortest simple MIC paths are only poorly approximable in the worst case.Furthermore, we demonstrate how the polynomial-time algorithm for shortest MIC paths is derivable from an existing language constrained shortest path algorithm. We use this as a basis to exhibit the general utility of viewing multi-channel wireless routing metrics as labeled graph problems, and discuss how a class of related polynomial-time computable metrics are derivable from this algorithm.     

Mobility profiler: A framework for discovering mobility profiles of cell phone users

Mobility path information of cell phone users play a crucial role in a wide range of cell phone applications, including context based search and advertising, early warning systems, city-wide sensing applications such as air pollution exposure estimation and traffic planning. However, there is a disconnect between the low level location data logs available from the cell phones and the high level mobility path information required to support these cell phone applications. In this paper, we present formal definitions to capture the cell phone users’ mobility patterns and profiles, and provide a complete framework, Mobility Profiler, for discovering mobile cell phone user profiles starting from cell based location data. We use real-world cell phone log data (of over 350 K h of coverage) to demonstrate our framework and perform experiments for discovering frequent mobility patterns and profiles. Our analysis of mobility profiles of cell phone users expose a significant long tail in a user’s location-time distribution: A total of 15% of a cell phone user’s time is spent on average in locations that each appears with less than 1% of total time.