Mitre Corporation

About: Mitre Corporation is a company organization based out in Bedford, Massachusetts, United States. It is known for research contribution in the topics: Air traffic control & National Airspace System. The organization has 4884 authors who have published 6053 publications receiving 124808 citations. The organization is also known as: Mitre & MITRE.

Array self calibration with large sensor position errors

Abstract: Self-calibration algorithms estimate both source directions-of-arrival (DOAs) and perturbed array response vector parameters, such as sensor locations. Calibration errors are usually assumed to be small and a first order approximation to the perturbed array response vector is often used to simplify the estimation procedure. In this paper, we develop a new procedure that does not rely on the small error assumption. It has better performance for large estimation errors, and when used to initialize the Weiss and Friedlander (1991) MUSIC-based iterative technique, we see significant improvement over existing techniques for both small and large errors.

Scalability simulations for nanomemory systems integrated on the molecular scale.

Abstract: A BSTRACT : Simulations were performed to assess the prospective performance of a 16 Kbit nanowire-based electronic nanomemory system. Commercial off-the-shelf microcomputer system modeling software was applied to evaluate the operation of an ultra-dense storage array. This array consists of demonstrated experimental non-volatile nanowire diode switches, plus encoder‐decoder structures consisting of demonstrated experimental nanowirebased nanotransistors, with nanowire interconnects among all the switching devices. The results of these simulations suggest that a nanomemory of this type can be operated successfully at a density of 10 11 bits/cm 2 . Furthermore, modest device alterations and system design alternatives are suggested that might improve the performance and the scalability of the nanomemory array. These simulations represent early steps toward the development of a simulation-based methodology to guide nanoelectronic system design in a manner analogous to the way such methodologies are used to guide microelectronic system design in the silicon industry.

Bagging and Boosting a Treebank Parser

Abstract: Bagging and boosting, two effective machine learning techniques, are applied to natural language parsing. Experiments using these techniques with a trainable statistical parser are described. The best resulting system provides roughly as large of a gain in F-measure as doubling the corpus size. Error analysis of the result of the boosting technique reveals some inconsistent annotations in the Penn Treebank, suggesting a semi-automatic method for finding inconsistent treebank annotations.

Application of Acoustic Sensors to Robotic Seam Tracking

Abstract: Robotic seam tracking systems require three-dimensional information about the seam geometry. The applicability of a nontactile acoustic sensing system, which provides range information about the distance between a sensor and the workpiece, is evaluated for the three-dimensional surface characterization task. An algorithm for executing a two-dimensional surface height sampling of an unknown workpiece is developed and evaluated through digital simulation and hardware experimentation. The algorithm incorporates the limitations of the sensor's aperture size and uses only the range information provided by the sensing system. A recovery strategy is included if the sensor's aperture has been exceeded and range information is not available. The sampling procedure is found to be applicable for piecewise constant surfaces and surfaces with slight curvature. The effectiveness of the acoustic sensing system's surface characterization can be enhanced by using a priori knowledge of the workpiece. The sensing system appears to be promising for such industrial operations as part location and inspection.