Architecture Technology Corporation

Andrew Murphy

Eric R Chartier

William Colligan

Evan Eaves

Paul C Davis

Douglas Sweet

An automatic, autonomous, and aircraft-centric interference advisory method is executed entirely on a fist aircraft operating on a movement area of a runway, the movement are including ramps, taxiways, and runways. The method includes a processor onboard the first aircraft computing a first movement projection for the first aircraft using first aircraft data received at the first aircraft; the processor computing additional second movement projections for multiple second aircraft operating on the movement area of the airport using second data regarding each of the multiple second aircraft; the processor detecting a threat to the first aircraft on approach to a defined intersection of the movement area from any of the multiple second aircraft based on a corresponding second movement projection within a configurable time limit of entry into the defined intersection by the first aircraft; and providing on the first aircraft, a threat advisory for a detected threat.

Advisor system and method

A method, executed by a processor, includes the processor receiving signals information from a device located on a departing airplane; verifying an identification of the airplane and identifying an expected departure sequence of aircraft surface states; monitoring and identifying additional signals information received from the mobile device, including comparing the additional signals information to known data; logging the additional signals information, and processing the additional signals information, and determining the logged data corresponds to events indicative of an aircraft surface state; sending an aircraft surface state reached message to Local and Center flight management; and executing a statistical routine and providing statistical data from the execution relating to an occurrence of upcoming aircraft surface state event and sending the statistical data with the aircraft surface state message.

Aircraft surface state event track system and method

A system and a corresponding computer-implemented method identifies and classifies community-sourced documents as true documents. The community-sourced documents include one or more data objects such as data items, including text, strings, phrases, and words; image items, including still image items, video image items, and icons; and drawing items. The system and corresponding method then report the analysis results.

Systems and methods for identifying and classifying community-sourced documents as true documents

An automatic, autonomous, and aircraft-centric interference advisory method is executed entirely on a first aircraft operating on a movement area of a runway, the movement are including ramps, taxiways, and runways. The method includes a processor onboard the first aircraft computing a first movement projection for the first aircraft using first aircraft data received at the first aircraft; the processor computing additional second movement projections for multiple second aircraft operating on the movement area of the airport using second data regarding each of the multiple second aircraft; the processor detecting a threat to the first aircraft on approach to a defined intersection of the movement area from any of the multiple second aircraft based on a corresponding second movement projection within a configurable time limit of entry into the defined intersection by the first aircraft; and providing on the first aircraft, a threat advisory for a detected threat.

A computer-implemented method for training a neural network system to classify data items as true mentions of relevant data objects includes, based on a domain of interest, a processor controlling an input component and a data store to receive and store a document related to the domain of interest, control a natural language processor to extract data items related to the domain of interest from the document, create a first training data set of selected ones of the data items, using the first training data set, train the neural network to identify true mentions of data objects relevant to the domain of interest, apply tweaks to one or more of the data items to create a list of tweaked data items, creating a second training data set including the tweaked data items, and using the first and second training data sets, further train the neural network to identify true mentions of relevant data objects.

Community-based reporting and analysis system and method

An advisor system includes a computer-readable storage medium having encoded thereon a program of instructions. Execution of the instructions causes a processor to determine a current state of a first aircraft operating on a movement area of an airport including determining a path vector for the first aircraft. The path vector includes a speed and direction of travel of the first aircraft and identification of a runway intersection the first aircraft is projected to enter. The processor processes a surveillance signal transmitted from a second aircraft operating on the movement area, including determining a quality of the surveillance signal. The processor further determines a movement vector of the second aircraft, and compares the path vector and the movement vector to identify possible interference. Finally, the processor provides an advisory at the first aircraft based on the compared path vector and the movement vector.

A computer-implemented method for analyzing documents includes a processor receiving one or more documents, from a community-based document delivery system, related to a domain of interest; the processor identifying and extracting one or more data items from the one or more documents; determining if an identified and extracted data item comprises a true mention of a named entity; analyzing a context of the true mention of the named entity in the document; and determining, based on the analyzed context, if the document is a true document.

A mobile emergency perimeter system includes one or more fixed radio frequency (RF) sensors, and one or more moving RF sensors; a wireless mesh network coupling together each of the sensors; and a central processor system coupled to the wireless mesh network. The central processor system executes machine instructions stored on a computer-readable storage medium to control each of the RF sensors to receive time of arrival data for a RF signal transmitted by an emitter and received at each of the RF sensors, receive location information for each of the RF sensors and determine a three-dimensional (3-D) estimate of the geographical location of the emitter.

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Washington, DC, United States of America

Andrew Murphy