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The ability to quantify understory vegetation structure in forested environments on a broad scale has the potential to greatly improve our understanding of wildlife habitats, nutrient cycling, wildland fire behavior, and wildland firefighter safety. Lidar data can be used to model understory vegetation density, but the accuracy of these models is impacted by factors such as the specific lidar metrics used as independent variables, overstory conditions such as density and height, and lidar pulse density. Few previous studies have examined how these factors affect estimation of understory density. In this study we compare two widely-used lidar-derived metrics, overall relative point density (ORD) and normalized relative point density (NRD) in an understory vertical stratum, for their respective abilities to accurately model understory vegetation density. We also use a bootstrapping analysis to examine how lidar pulse density, overstory vegetation density, and canopy height can affect the ability to characterize understory conditions. In doing so, we present a novel application of an automated field photo-based understory cover estimation technique as reference data for comparison to lidar. Our results highlight that NRD is a far superior metric for characterizing understory density than ORD (R 2 NRD  = 0.44 vs. R 2 ORD  = 0.14). In addition, we found that pulse density had the strongest positive effect on predictive power, suggesting that as pulse density increases, the ability to accurately characterize understory density using lidar increases. Overstory density and canopy height had nearly identical negative effects on predictive power, suggesting that shorter, sparser canopies improve lidar's ability to analyze the understory. Our study highlights important considerations and limitations for future studies attempting to use lidar to quantify understory vegetation structure. [ABSTRACT FROM AUTHOR]

In this paper, a novel synthesizable temperature sensor for FPGA devices, which uses DSP-slices instead of LUTs, is presented. The correlation between the delay of the critical path and the temperature of a DSP-slice is exploited to implement a ring oscillator, whose oscillation frequency is used to estimate the local die temperature. In contrast to previously proposed synthesizable temperature sensors based on ring oscillators implemented with LUTs, the proposed DSP-based temperature sensor has a smaller footprint. The complete synthesizable temperature sensor, including the ring oscillator and the required time-to-digital converter, only requires three DSP-slices. An evaluation using a programmable climate chamber and a Virtex-6 FPGA evaluation board is presented. The DSP-based temperature sensor provides similar accuracies (i.e., ±0.5 °C) than LUT-based temperature sensors, while greatly improving the resolution and temperature sampling rates depending on the selected configuration. Finally, by using the proposed temperature sensors together with several internal hardware heat generators, a maximal temperature gradient of 9 °C was measured on the FPGA die. [ABSTRACT FROM AUTHOR]

Wafer-level vacuum packaging is vital in the fabrication of many microelectromechanical systems (MEMS) devices and enables significant cost reduction in high-volume MEMS production. In this paper, we propose a low-temperature wafer-level vacuum packaging method based on plastic deformation and low-temperature welding of copper sealing rings with a small footprint. A device wafer with copper ring structures and a cap wafer with corresponding metalized grooves are placed inside a vacuum chamber and pressed together at a temperature of 250 °C, resulting in low-temperature welding of the copper, and thus, hermetic sealing of the cavities enclosed by the sealing rings. The vacuum pressure inside the fabricated cavities 146 days after bonding was measured using residual gas analysis to be as low as 2.6\times 10^-2 mbar. Based on this value, the leak rate is calculated to be smaller than 3.6\times 10^-16 mbarL/s using the most conservative assumptions, demonstrating the excellent hermeticity of the seals. Shear testing was used to demonstrate that the seals are mechanically stable with over 90 MPa in shear strength for 5.2~\mu \textm -high Cu sealing rings with widths down to 8~\mu \textm . The reported method is potentially compatible with complementary metal-oxide-semiconductor (CMOS) substrates and may be applied to vacuum packaging of 3-D heterogeneously integrated MEMS on state-of-the-art CMOS substrates. [2016-0252] [ABSTRACT FROM AUTHOR]

A small active in-vacuum beamstop has been developed to monitor the flux of intense third-generation synchrotron X-ray beams protecting the downstream detector from the direct beam. Standard active beamstops, where a built-in diode directly absorbs the beam, have limitations in size and lifetime. In the present design, a silicon PIN diode detects the photons back-scattered from a cavity in the beamstop. This approach drastically reduces the radiation dose on the diode and thus increases its lifetime. The beamstop with a diameter of 2 mm has been fabricated to meet the requirements for the P12 bioSAXS beamline of EMBL Hamburg at PETRA III (DESY). The beamstop is in regular user operation at the beamline and displays a good response over the range of energies tested (6-20 keV). Further miniaturization of the diode is easily possible as its size is not limited by the PIN diode used. [ABSTRACT FROM AUTHOR]

The work in this paper concerns the determination of a recognition unit in a small footprint Chinese large vocabulary word recognition system for embedded devices. This paper proposes a method of extending the conventional initial/final phonetic units in Chinese language to be used as a recognition unit. The word recognition performance of the proposed extended initial/final is compared with that of other recognition units, such as syllable, phoneme, triphone and the original initial/final. Under a similar memory usage limitation, the word recognition rates of different recognition units are evaluated. The proposed extended initial/final shows the best performance in a fixed memory usage condition: 93.74%, 94.76%, and 95.42% accuracy for 50K-word recognizer under memory restriction around 500KB, 1MB, and 5MB, respectively. [ABSTRACT FROM AUTHOR]

Abstract: Accurate estimation of live and dead biomass in forested ecosystems is important for studies of carbon dynamics, biodiversity, wildfire behavior, and for forest management. Lidar remote sensing has been used successfully to estimate live biomass, but studies focusing on dead biomass are rare. We used lidar data, in conjunction with field measurements from 58 plots to distinguish between and map standing live and dead tree biomass in the mixed coniferous forest of the North Rim of Grand Canyon National Park, USA. Lidar intensity and canopy volume were key variables for estimating live biomass, whereas for dead biomass, lidar intensity alone was critical for accurate estimation. Regression estimates of both live and dead biomass ranged between 0 and 600 Mg ha−1, with means of 195.08 Mg ha−1 and 65.73 Mg ha−1, respectively. Cross validation with field data resulted in correlation coefficients for predicted vs. observed of 0.85 for live biomass (RMSE=50 Mg ha−1 and %RMSE (RMSE as a percent of the mean)=26). For dead biomass, correlation was 0.79, RMSE was 42 Mg ha−1, and %RMSE was 63. Biomass maps revealed interesting patterns of live and dead standing tree biomass. Live biomass was highest in the ponderosa pine zone, and decreased from south to north through the mixed conifer and spruce–fir forest zones. Dead biomass exhibited a background range of values in these mature forests from zero to 100 Mg ha−1, with lower values in locations having higher live biomass. In areas with high dead biomass values, live biomass was near zero. These areas were associated with recent wildfires, as indicated by fire maps derived from the Monitoring Trends in Burn Severity Project (MTBS). Combining our dead biomass maps with the MTBS maps, we demonstrated the complementary power of these two datasets, revealing that MTBS burn intensity class can be described quantitatively in terms of dead biomass. Assuming a background range of dead biomass up to 100 Mg ha−1, it is possible to estimate and map the contribution to the standing dead tree biomass pool associated with recent wildfire. [Copyright &y& Elsevier]

Water retention times less than 3 Ii from inlet to outlet were necessary to meet new effluent requirements without extending the footprint of the existing plant. Nitrogen removal was required at the existing, high loaded, direct precipitation plant and space was not readily available. The staff at the VEAS WWTP took on the task to design a new process at their own risk. Selected solutions and ups and downs in the water treatment during the past 10 years of operations and further developments are presented in this paper. Always asking for well-proven solutions might make life easy. The intent of this paper is to encourage some of our colleagues to be more daring in their approach to new challenges. However, expect sleepless nights in order to solve the unexpected problems along the way. [ABSTRACT FROM AUTHOR]