Intelligent Fusion Technology, Inc.

Bin Jia

Genshe Chen

Erik Philip Blasch

Khanh D Pham

Sixiao Wei

Zhijiang Chen

Dan Shen

Zhonghai Wang

Xingping Lin

Kui Liu

Carolyn Sheaff

Kuo-Chu Chang

Tao Wang

Gang Wang

Nichole Sullivan

Haibin Ling

Xingyu Xiang

Jiaoyue Liu

Huamei Chen

Thomas M Clemons, Iii

Cailing Dong

A decision support method for machinery control includes extracting entities and relations from information sources, and creating subject-predicate-object (SPO) triples. Each SPO triple includes a subject entity and an object entity, and a relation between the subject entity and the object entity. The method further includes constructing a knowledge graph (KG) based on the SPO triples. The KG includes a plurality of nodes corresponding to the entities, and a plurality of links corresponding to the relations between the entities. The method also includes predicting missing links between the nodes and adding the predicted links to the KG, and performing diagnostic and prognostic analysis using the KG, including analyzing plain text description of MCS situations to obtain relevant information concerning key components from the KG, recognizing sensor observations and component conditions to diagnose situations of other related components, and providing prognostics by analyzing the present trending/symptom in the MCS operating process.

Decision support method and apparatus for machinery control

A method for testing satellite signal receiver antenna is provided. The method includes: determining a satellite constellation state indicating status of a plurality of satellites in a satellite constellation; calculating, based on the determined satellite constellation state, initial positions of a plurality of satellite antennas that are used for emulating the satellite constellation; moving the plurality of satellite antennas to the initial positions of the plurality of satellite antennas; calibrating a phase delay of each of the plurality of satellite antennas; broadcasting, by the plurality of satellite antennas, satellite signals to test a satellite signal receiver antenna; determining a movement plan for the plurality of satellite antennas based on the satellite constellation state; and moving the plurality of satellite antennas based on the movement plan to emulate a propagation of the satellite constellation.

Methods and systems for testing satellite signal receiver antenna

A method for pattern discovery and real-time anomaly detection based on knowledge graph, comprising: based on a dataset including messages collected within a certain period, constructing a local knowledge graph (KG); applying a statistical relational learning (SRL) model to predict hidden relations between entities to obtain an updated local KG; from all SPO triples of the updated local KG, discovering a normalcy pattern that includes frequent entities, frequent relations, and frequent SPO triples; and in response to receiving streaming data from a message bus, extracting a plurality of entities, a plurality of relations, and a plurality of SPO triples, from the streaming data for comparison with the normalcy pattern using semantic distance, thereby determining whether there is an abnormal entity, relation, or SPO triple in the streaming data.

Method and system for pattern discovery and real-time anomaly detection based on knowledge graph

Methods and systems for space situational awareness (SSA) demonstration are provided. The system includes a space data collector component, for collecting space initialization data of space objects from initialized space sources and pre-processing the space initialization data; a data relocation component, for distributing the space initialization data pushed from the space data collector component into multiple streaming channels for streaming; a streaming platform, for streaming, mapping, and reducing the space initialization data from the data relocation component to provide streamed data; a real-time analysis component, for calculating the streamed data to conduct a real-time detecting and tracking analysis of the space objects by implementing algorithms for one or more of space uncertainty propagation, space object tracking, sensor management, and collision avoidance; and a space visualization component, for displaying a visualization of space situational awareness (SSA) based on analyzed results from the real-time analysis component.

System and method for space situational awareness demonstration

The present disclosure provides a gated range scanning linear frequency modulated continuous wave (LFMCW) radar structure, including: a frequency synthesizer, a first mixer, a second mixer, a first filter, and a third mixer. The frequency synthesizer is configured for generating a first local oscillating signal and a second local oscillating signal, a frequency of the first local oscillating signal varying in a frequency range, each frequency corresponding to a sub-range of a coverage range scanned by the LFMCW radar structure. The first mixer is configured for mixing a copy of a transmitted signal and the first local oscillating signal to generate a first output signal (the receiver's first local oscillator). The second mixer is configured for mixing the first output signal and a received signal from a receiving antenna to generate a second output signal that includes an intermediate frequency (IF) signal being received by the first filter.

Gated range scanning LFMCW radar structure

Method and system for detecting and tracking multiple moving targets based on wide-area motion imagery are provided. The method includes receiving a task request from a client; sending the task request to a local agent; acquiring to-be-processed images from the client, in response to the task request; calling an Hadoop API and checking a running status of a Hadoop system for an available resource in the Hadoop system; when a resource in the Hadoop system is available, pushing the to-be processed images to a back-end Hadoop distributed file system (HDFS); running tracking algorithms of multiple moving objects associated with the to-be-processed images to provide tracking results of the multiple moving objects; when the Hadoop system is completed in running the tracking algorithms, generating and sending a message to the local agent; and sending the tracking results of the multiple moving objects from the HDFS to the front-end database.

System and method for detecting and tracking multiple moving targets based on wide-area motion imagery

Method and system for predicting collision probability of space objects are provided. Space objects are allocated according to a total number thereof for parallel computation in a GPU device. Initial orbit states of the space objects are generated by an initial-orbit-state generation kernel of the GPU device. Orbit propagation for each space object is performed based on the initial orbit state to predict a state of each space object by an orbit propagation kernel of the GPU device. The predicted states of the space objects are collected by a predicted-orbit-state collection kernel of the GPU device. A real-time visualization and rendering of the predicted space objects are performed in a form of point cloud during interactions between CPU threads and GPU kernels. A CPU host predicts a collision probability of any two space objects among the multitude of space objects, according to the interactions between the CPU threads and the GPU kernels.

Method and system for predicting collision probability of space objects via graphics processing unit

In accordance with various embodiments of the disclosed subject matter, a method and a system for detecting multiple objects from real-time images are provided. The method comprises: performing, using a CPU host, an image segmentation process to divide real-time input images into a plurality of image partitions; performing, by multiple GPUs, a fast block-wise registration process, a mark setting process, a background generation process, a foreground generation process based on a Hyper-Q computation infrastructure, and a support vector machine classification process; and generating, by the CPU host, visualization classification images.

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Germantown, MD, United States of America

Bin Jia