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.

Learning to Resolve Bridging References

Abstract: We use machine learning techniques to find the best combination of local focus and lexical distance features for identifying the anchor of mereological bridging references. We find that using first mention, utterance distance, and lexical distance computed using either Google or WordNet results in an accuracy significantly higher than obtained in previous experiments.

Inquiry into murine and human lupus

Abstract: Systemic lupus is a multi-system, inflammatory disorder characterized by the production of autoantibodies of multiple specificities, especially antibodies reactive with nuclear ligands, including native DNA (Steinberg 1992, Steinberg et al. 1991, 1984. 1990, Andrews et al. 1978, Tan 1985, Harada et al. 1994, Smith & Steinberg 1983). One ofthe impediments to understanding human systemic lupus has been its marked heterogeneity (Steinberg et al. 1992, 1991). Indeed, a comparable heterogeneity is observed among the several strains of mice which spontaneously develop SLE-like syndromes. Taken together, they demonstrate the genetic and pathogenetic heterogeneity oflupus (Andrews et al. 1978, Steinberg et al. 1984, Theofilopoulos & Dixon 1980, Ebling & Hahn 1980). Autoantibody production in murine and human lupus has historically been attributed to (i) the selective stimulation of autoreactive B cells by self antigens (or antigens cross-reactive with self) (Hardin 1986) or (ii) a more generalized process of immune dysregulation leading to multi-clonal B-cell activation (Klinman & Steinberg 1987a, 1987b, Budman et al. 1977, Becker et al. 1981). Several years ago, we proposed a synthesis of these ideas; that polyclonal activation initiated autoantibody production but that this process was perpetuated by autoantigen-driven immune stimulation (Klinman et al. 1990). Herein we expand upon that concept. Indeed, our emphasis on B-cell hyperactivity early in disease (e.g. Klinman & Steinberg 1987a, 1987b) has been inappropriately viewed as demonstrating a lack of recognition of the contribution of T cells to specific autoantibody production late in disease as well as to non-specific activation of B cells through their production of cytokines (Steinberg et al. 1980, Cohen et al. 1982, Datta et al. 1987. Rajagopalan et al. 1992. Inghirami 1988, Laskin et al. 1986, Harada et al. 1994). We have clearly stated that this is not the case (Steinberg 1989, Klinman et al. 1990). Rather, we have attempted to divide early events

The SHARE 2012 data campaign

Abstract: A multi-modal (hyperspectral, multispectral, and LIDAR) imaging data collection campaign was conducted just south of Rochester New York in Avon, NY on September 20, 2012 by the Rochester Institute of Technology (RIT) in conjunction with SpecTIR, LLC, the Air Force Research Lab (AFRL), the Naval Research Lab (NRL), United Technologies Aerospace Systems (UTAS) and MITRE. The campaign was a follow on from the SpecTIR Hyperspectral Airborne Rochester Experiment (SHARE) from 2010. Data was collected in support of the eleven simultaneous experiments described here. The airborne imagery was collected over four different sites with hyperspectral, multispectral, and LIDAR sensors. The sites for data collection included Avon, NY, Conesus Lake, Hemlock Lake and forest, and a nearby quarry. Experiments included topics such as target unmixing, subpixel detection, material identification, impacts of illumination on materials, forest health, and in-water target detection. An extensive ground truthing effort was conducted in addition to collection of the airborne imagery. The ultimate goal of the data collection campaign is to provide the remote sensing community with a shareable resource to support future research. This paper details the experiments conducted and the data that was collected during this campaign.

Frequency Limitations and Optimal Step Size for the Two-Point Central Difference Derivative Algorithm with Applications to Human Eye Movement Data

Abstract: There are many algorithms for calculating derivatives. The two-point central difference algorithm is the simplest. Besides simplicity, the two most important characteristics of this algorithm are accuracy and frequency response. The frequency content of the data prescribes a lower limit on the sampling rate. The smoothness and accuracy of the data determine the optimal step size. We discuss the low-pass filter characteristics of this algorithm and derive the optimal step size for two types of human eye movement data. To calculate the velocity of fast (saccadic) eye movements, the algorithm should have a cutoff frequency of 74 Hz. For typical slow (smooth pursuit) eye movements, a step size of 25 or 50 ms is optimal.

Application of guidelines for designing user interface software

Abstract: A survey was conducted of people who had received a report on guidelines for designing user interface software. Analysis of questionnaire responses indicates that respondents considered guidelines useful, that they have used guidelines in various stages of design, and that they plan to use guidelines again. However, respondents also reported significant problems in the practical application of guidelines. Respondents had difficulty locating relevant guidelines within the report, choosing which guidelines would actually be used, establishing priorities among the selected guidelines, and translating generally worded guidelines into specific design rules.