Trident Systems (United States)

Resumo: A noção de paisagem sonora (Soundscapes) que tem vindo a ganhar cada vez mais expressão nos círculos musicológicos internacionais permite entender a música realizada numa determinada área a partir de uma perspectiva contextual abrangente, contrariamente à leitura centrada num compositor ou grupo restrito de compositores. Permite reconstruir contextos, circuitos, trânsitos e cartografar a presença da música e dos músicos, entendendo a música como uma actividade social, política e económica e não meramente artística.

Flight quality solid-state lasers require a unique and extensive set of testing and qualification processes, both at the system and component levels to insure the laser's promised performance. As important as the overall laser transmitter design is, the quality and performance of individual subassemblies, optics, and electro-optics dictate the final laser unit's quality. The Global Ecosystem Dynamics Investigation (GEDI) laser transmitters employ all the usual components typical for a diode-pumped, solid-state laser, yet must each go through their own individual process of specification, modeling, performance demonstration, inspection, and destructive testing. These qualification processes and results for the laser crystals, laser diode arrays, electro-optics, and optics, will be reviewed as well as the relevant critical issues encountered, prior to their installation in the GEDI flight laser units.

We applied Compressive Sensing to design an affordable, convenient Brain Machine Interface (BMI) measuring the high spatial density, and real-time process of Electroencephalogram (EEG) brainwaves by a Smartphone. It is useful for therapeutic and mental health monitoring, learning disability biofeedback, handicap interfaces, and war gaming. Its spec is adequate for a biomedical laboratory, without the cables hanging over the head and tethered to a fixed computer terminal. Our improved the intrinsic signal to noise ratio (SNR) by using the non-uniform placement of the measuring electrodes to create the proximity of measurement to the source effect. We computing a spatiotemporal average the larger magnitude of EEG data centers in 0.3 second taking on tethered laboratory data, using fuzzy logic, and computing the inside brainwave sources, by Independent Component Analysis (ICA). Consequently, we can overlay them together by non-uniform electrode distribution enhancing the signal noise ratio and therefore the degree of sparseness by threshold. We overcame the conflicting requirements between a high spatial electrode density and precise temporal resolution (beyond Event Related Potential (ERP) P300 brainwave at 0.3 sec), and Smartphone wireless bottleneck of spatiotemporal throughput rate. Our main contribution in this paper is the quality and the speed of iterative compressed image recovery algorithm based on a Block Sparse Code (Baranuick et al, IEEE/IT 2008). As a result, we achieved real-time wireless dynamic measurement of EEG brainwaves, matching well with traditionally tethered high density EEG.

Abstract The Montney gas reservoir presents exciting potential and is likely to become a critically important component of future gas supply. However, the Montney often presents variable and unique stimulation challenges. Unlike reservoirs like the US Barnett shale but possibly like the Muskwa in the northeast B.C. Horn River basin, recovery of water-based fluids can be a key issue to achieving economic production rates in the Montney. Choice of fracturing fluid must be carefully determined for each area of the Montney, balancing economics with production response. One must always keep in mind that key reservoir properties can vary dramatically in the Montney, both as a function of geographic location and depth. A presentation entitled "Montney Fracturing Fluid Considerations" was given at the 2009 CSUG conference, which summarized results of regained methane permeability vs. drawdown pressure and contact time with Montney core under representative reservoir conditions. Water-, foamed water-, and hydrocarbon-based fracturing-fluid systems were studied. Implications of the results as to choice of optimum fluid were discussed. This paper presents field-production results of the trials conducted with fluid systems resulting in conjunction with the above study. The concepts and reasoning used to arrive at final fluid choices for field trials are discussed, as well as a theoretical interpretation of the field-production results.

This paper examines direct data domain (DDD) moving target detection for multi-channel space-based radar (SBR)1,2. DDD techniques differ from data-adaptive processing methods in that they do not rely on statistically stationary and homogeneous training data in order to estimate and null out clutter or interference and thereby reveal potential targets; instead, they operate on each range-Doppler cell independently, after any necessary preprocessing to compensate for platform motion and/or array calibration. Prior work examined a maximum-likelihood angle-of-arrival (AOA) technique and the associated target power estimator to detect slow moving targets. In this paper, we extend that methodology and propose novel detection manifolds for optimally partitioning the two-dimensional statistical space. The two dimensions are formed by the passive AOA likelihood function and the estimated target power. A computer simulation of a space radar system and associated geometry is used to assess the characteristics and performance of the new concept. We show that the two-dimensional probability densities corresponding to the target absent and target present hypotheses (H0 and H1, respectively) occupy regions in this space that are not optimally separated by independent thresholds. This immediately leads to the novel detection manifolds (or curved boundaries between detections and non-detections) that improve the detection probability while also reducing the false alarm rate.

Modularity Biometric System (MBS) is an approach to support AiTR of the cooperated and/or non-cooperated standoff biometric in an area persistent surveillance. Advanced active and passive EOIR and RF sensor suite is not considered here. Neither will we consider the ROC, PD vs. FAR, versus the standoff POT in this paper. Our goal is to catch the "most wanted (MW)" two dozens, separately furthermore ad hoc woman MW class from man MW class, given their archrivals sparse front face data basis, by means of various new instantaneous input called probing faces. We present an advanced algorithm: mini-Max classifier, a sparse sample realization of Cramer-Rao Fisher bound of the Maximum Likelihood classifier that minimize the dispersions among the same woman classes and maximize the separation among different man-woman classes, based on the simple feature space of MIT Petland eigen-faces. The original aspect consists of a modular structured design approach at the system-level with multi-level architectures, multiple computing paradigms, and adaptable/evolvable techniques to allow for achieving a scalable structure in terms of biometric algorithms, identification quality, sensors, database complexity, database integration, and component heterogenity. MBS consist of a number of biometric technologies including fingerprints, vein maps, voice and face recognitions with innovative DSP algorithm, and their hardware implementations such as using Field Programmable Gate arrays (FPGAs). Biometric technologies and the composed modularity biometric system are significant for governmental agencies, enterprises, banks and all other organizations to protect people or control access to critical resources.

X-ray photoelectron spectroscopy (XPS) was performed on AISI 52100 steel surfaces subjected to sliding in the boundary lubrication regime at 32 and 100°C. The specimens were lubricated with base oil blended with individual additives containing sulfur (S), phosphorus (P), or metal deactivator, as well as base oil with all the previous additives in the same amounts as in the single blends. XPS spectra were analyzed to confirm the formation and determine the chemical composition of the antiwear tribofilms produced on the steel surfaces during sliding. The use of S- and P-containing additives on the tested disk surfaces revealed that tribochemical reactions resulted in the formation of antiwear tribofilms containing S- and P-rich components. Results for the multi-additive blend provided evidence for two components in the produced tribofilm, appearing to consist primarily of sulfide and phosphate. This investigation provides new insight into the competing roles of these compounds on the tribological properties of the antiwear tribofilms. The significance of the sulfide components is demonstrated by the more pronounced antiwear effect of the S-containing additive in the multi-additive formulation.

This paper deals with the assessment of accuracy of simulation models from the perspective of dynamic object flows. Dynamic objects (also called temporary entities or transactions) move physically or logically from one model component to another and represent entities such as aircraft, data packets, passengers, and vehicles. Accurate flow (movement) of thousands or millions of dynamic objects within a complex simulation model significantly affects the overall model validity. We present a new automated testing technique for assessing the accuracy of dynamic object flows. The permissible sequence and precedence of dynamic object flows are specified using the context-free grammar formalism. The specification accuracy is assessed using a variety of verification and validation techniques. The executable model is instrumented and dynamic object flow trace data is generated. The trace data is automatically compared with respect to the specification and each dynamic object movement traced during model execution is automatically verified.