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.

Quaternionic periodicity transform: an algebraic solution to the tandem repeat detection problem

Abstract: Motivation: One of the main tasks of DNA sequence analysis is identification of repetitive patterns. DNA symbol repetitions play a key role in a number of applications, including prediction of gene and exon locations, identification of diseases, reconstruction of human evolutionary history and DNA forensics. Results: A new approach towards identification of tandem repeats in DNA sequences is proposed. The approach is a refinement of previously considered method, based on the complex periodicity transform. The refinement is obtained, among others, by mapping of DNA symbols to pure quaternions. This mapping results in an enhanced, symbol-balanced sensitivity of the transform to DNA patterns, and an unambiguous threshold selection criterion. Computational efficiency of the transform is further improved, and coupling of the computation with the period value is removed, thereby facilitating parallel implementation of the algorithm. Additionally, a post-processing stage is inserted into the algorithm, enabling unambiguous display of results in a convenient graphical format. Comparison of the quaternionic periodicity transform with two well-known pattern detection techniques shows that the new approach is competitive with these two techniques in detection of exact and approximate repeats. Supplementary information: Supplementary data are available at Bioinformatics online.

Collaborative Discourse Theory as a Foundation for Tutorial Dialogue

Abstract: Research on intelligent tutoring systems has not leveraged general models of collaborative discourse, even though tutoring is inherently collaborative. Similarly, research on collaborative discourse theory has rarely addressed tutorial issues, even though teaching and learning are important components of collaboration. We help bridge the gap between these two related research threads by presenting a tutorial agent, called Paco, that we built using a domain-independent collaboration manager, called Collagen. Our primary contribution is to show how a variety of tutorial behaviors can be expressed as rules for generating candidate discourse acts in the framework of collaborative discourse theory.

Scaling drug indication curation through crowdsourcing.

Abstract: Motivated by the high cost of human curation of biological databases, there is an increasing interest in using computational approaches to assist human curators and accelerate the manual curation process. Towards the goal of cataloging drug indications from FDA drug labels, we recently developed LabeledIn, a human-curated drug indication resource for 250 clinical drugs. Its development required over 40 h of human effort across 20 weeks, despite using well-defined annotation guidelines. In this study, we aim to investigate the feasibility of scaling drug indication annotation through a crowdsourcing technique where an unknown network of workers can be recruited through the technical environment of Amazon Mechanical Turk (MTurk). To translate the expert-curation task of cataloging indications into human intelligence tasks (HITs) suitable for the average workers on MTurk, we first simplify the complex task such that each HIT only involves a worker making a binary judgment of whether a highlighted disease, in context of a given drug label, is an indication. In addition, this study is novel in the crowdsourcing interface design where the annotation guidelines are encoded into user options. For evaluation, we assess the ability of our proposed method to achieve high-quality annotations in a time-efficient and cost-effective manner. We posted over 3000 HITs drawn from 706 drug labels on MTurk. Within 8 h of posting, we collected 18 775 judgments from 74 workers, and achieved an aggregated accuracy of 96% on 450 control HITs (where gold-standard answers are known), at a cost of $1.75 per drug label. On the basis of these results, we conclude that our crowdsourcing approach not only results in significant cost and time saving, but also leads to accuracy comparable to that of domain experts. Database URL: ftp://ftp.ncbi.nlm.nih.gov/pub/lu/LabeledIn/Crowdsourcing/.

A horizontal miss distance filter system for suppressing false resolution alerts

Abstract: A horizontal miss distance filter system (220) is provided for inhibiting resolution alert messages from an air traffic alert and collision avoidance system (210) to a pilot's display (230) The horizontal miss distance filter employs a parabolic range tracker (10) to derive a range acceleration estimate (11) utilized to discriminate intruder aircraft (110) having non-zero horizontal miss distances The horizontal miss distance calculated from the range data provided by the parabolic range tracker is compared with a bearing based horizontal miss distance provided by a bearing based tracker (22) The smaller of the two calculated horizontal miss distances defines a projected horizontal miss distance which is compared with a threshold value Any resolution alert for intruder aircraft whose projected horizontal miss distance is greater than the threshold will be inhibited unless it is determined that the encounter involves a maneuver of one of the aircraft As many as five maneuver detectors (50, 52, 56, 58 and 64) may be employed to assess whether the encounter involves a maneuver If any of the maneuver detectors establish the occurrence of a maneuver, then a resolution alert provided from the TCAS system (210) will not be inhibited