公开(公告)号：US20240219579A1

公开(公告)日：2024-07-04

申请号：US18072866

申请日：2022-12-01

Applicant: Intelligent Fusion Technology, Inc.

Inventor： Dan SHEN ,  Genshe CHEN ,  Tien NGUYEN ,  Khanh PHAM

IPC: G01S19/29 ,  G01S19/32

CPC classification number: G01S19/29 ,  G01S19/32

Abstract: A global navigation satellite system (GNSS) is disclosed comprising a transmitter. The transmitter is configured to: receive a plurality of frequencies; determine a minimum frequency from the plurality of frequencies; determine a maximum frequency from the plurality of frequencies; determine a carrier from the minimum frequency and the maximum frequency; determine a set of subcarriers from the carrier and the plurality of frequencies; identify optimal radius of desired phase points to select optimal subcarriers from the set of subcarriers; determine inter-modulation terms with a minimal energy based on the optimal subcarriers; and generate multi-carrier constant envelope waveforms based on the inter-modulation terms.

公开(公告)号：US20230186620A1

公开(公告)日：2023-06-15

申请号：US17551436

申请日：2021-12-15

Applicant: Intelligent Fusion Technology, Inc.

Inventor： Qi ZHAO ,  Huong Ngoc DANG ,  Yi LI ,  Xin TIAN ,  Nichole SULLIVAN ,  Genshe CHEN ,  Khanh PHAM

IPC: G06V10/94 ,  G06V10/764 ,  G06V10/82 ,  G06V10/96 ,  G06V10/77

CPC classification number: G06V10/95 ,  G06V10/764 ,  G06V10/82 ,  G06V10/96 ,  G06V10/7715

Abstract: A system includes: a named data networking (NDN) based Spark distributed computing network including a Spark distributed computing network including a master computer node and a plurality of slave computer nodes, and a named data networking (NDN) protocol installed on the Spark distributed computing network, and a coded distributed computing (CDC) target recognition model deployed on the NDN-based Spark distributed computing network. The NDN-based Spark distributed computing network is configured to: receive one or more batches of input images; generate a parity image from each batch of the input images; predict a label for each image of the batch of the input images; process the generated parity image; upon a label prediction of one image of the batch of the input images being unavailable, reconstruct the unavailable label prediction; and classify labels for the input images.

公开(公告)号：US20230186120A1

公开(公告)日：2023-06-15

申请号：US17534754

申请日：2021-11-24

Applicant: Intelligent Fusion Technology, Inc.

Inventor： Qingliang ZHAO ,  Jiaoyue LIU ,  Nichole SULLIVAN ,  Kuochu CHANG ,  Erik BLASCH ,  Genshe CHEN

IPC: G06N5/04 ,  G06N5/02 ,  G06F40/295 ,  G06F40/30 ,  G06F16/25 ,  G06F16/26

CPC classification number: G06N5/04 ,  G06F16/26 ,  G06F16/258 ,  G06F40/30 ,  G06F40/295 ,  G06N5/022

Abstract: A computing system includes: a memory, containing instructions for a method for anomaly and pattern detection of unstructured big data via semantic analysis and dynamic knowledge graph construction; a processor, coupled with the memory and, when the instructions being executed, configured to: receive unstructured big data associated with social network interactions, events, or activities; parse and structure the unstructured big data to generate structured big data; form a dynamic knowledge base based on the structured big data; and perform sematic reasoning on the dynamic knowledge base to discover patterns and anomalies among the social network interactions, events, or activities; and a display, comprising an interactive graphical user interface (GUI), configured to receive the anomalies and patterns to display real-time actionable alerts, provide recommendations, and support decisions.

公开(公告)号：US20230040237A1

公开(公告)日：2023-02-09

申请号：US17876908

申请日：2022-07-29

Applicant: Intelligent Fusion Technology, Inc.

Inventor： Hua-mei CHEN ,  Bora SUL ,  Genshe CHEN ,  Erik BLASCH ,  Khanh PHAM

IPC: G06T7/00 ,  G06V10/80 ,  G06V10/82

Abstract: A method for detecting fake images includes: obtaining an image for authentication, and hand-crafting a multi-attribute classifier to determine whether the image is authentic. Hand-crafting the multi-attribute classifier includes fusing at least an image classifier, an image spectrum classifier, a co-occurrence matrix classifier, and a one-dimensional (1D) power spectrum density (PSD) classifier. The multi-attribute classifier is trained by pre-processing training images to generate an attribute-specific training dataset to train each of the image classifier, the image spectrum classifier, the co-occurrence matrix classifier, and the 1D PSD classifier.

公开(公告)号：US20220247443A1

公开(公告)日：2022-08-04

申请号：US17167674

申请日：2021-02-04

Applicant: INTELLIGENT FUSION TECHNOLOGY, INC.

Inventor： Dan SHEN ,  Khanh PHAM ,  Tien M. NGUYEN ,  Genshe CHEN

IPC: H04B1/30 ,  H04B1/04 ,  H03D1/24 ,  H03D1/22

Abstract: A system for hybrid modulation and demodulation includes a transmitter and a receiver. The transmitter is configured to receive a hybrid signal of a space-ground link system (SGLS), including a first component and a second component; perform a double sideband (DSB) modulation on the first component using a carrier frequency to obtain a first waveform; perform a single sideband (SSB) modulation on the second component using the carrier frequency to obtain a second waveform; mix the first waveform and the second waveform to generate a hybrid waveform; and transmit the hybrid waveform. The receiver is configured to receive the hybrid waveform; determine the carrier frequency; separate the first waveform and the second waveform; perform a DSB demodulation on the first waveform to obtain a first demodulated signal; and perform an SSB demodulation on the second waveform to obtain a second demodulated signal.

公开(公告)号：US20210103841A1

公开(公告)日：2021-04-08

申请号：US16595107

申请日：2019-10-07

Applicant: INTELLIGENT FUSION TECHNOLOGY, INC.

Inventor： Dan SHEN ,  Carolyn SHEAFF ,  Jingyang LU ,  Genshe CHEN ,  Erik BLASCH ,  Khanh PHAM

IPC: G06N7/00 ,  G06N20/00 ,  B64G3/00

Abstract: A method for rapid discovery of satellite behavior, applied to a pursuit-evasion system including at least one satellite and a plurality of space sensing assets. The method includes performing transfer learning and zero-shot learning to obtain a semantic layer using space data information. The space data information includes simulated space data based on a physical model. The method further includes obtaining measured space-activity data of the satellite from the space sensing assets; performing manifold learning on the measured space-activity data to obtain measured state-related parameters of the satellite; modeling the state uncertainty and the uncertainty propagation of the satellite based on the measured state-related parameters; and performing game reasoning based on a Markov game model to predict satellite behavior and management of the plurality of space sensing assets according to the semantic layer and the modeled state uncertainty and uncertainty propagation.

公开(公告)号：US20210103256A1

公开(公告)日：2021-04-08

申请号：US16562657

申请日：2019-09-06

Applicant: INTELLIGENT FUSION TECHNOLOGY, INC.

Inventor： Bin JIA ,  Jiaoyue LIU ,  Huamei CHEN ,  Genshe CHEN ,  Kuo-Chu CHANG ,  Thomas M. CLEMONS, III

IPC: G05B13/02 ,  G06N5/02 ,  G06N7/00 ,  G06K9/62 ,  G06F40/10

Abstract: 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.

公开(公告)号：US20200373972A1

公开(公告)日：2020-11-26

申请号：US16991583

申请日：2020-08-12

Applicant: INTELLIGENT FUSION TECHNOLOGY, INC.

Inventor： Zhonghai WANG ,  Lun LI ,  Jingyang LU ,  Genshe CHEN ,  Weifeng SU ,  Xingping LIN ,  Xingyu XIANG ,  Wenhao XIONG

IPC: H04B7/0413 ,  H04B17/336 ,  H04B17/391

Abstract: A multiple-input and multiple-output (MIMO) bolt-on device for a single-input and single-output (SISO) radio, a MIMO channel emulator for testing the MIMO bolt-on device, and a MIMO channel emulation method are provided. The MIMO bolt-on device includes: a plurality of antennas, a multi-channel receiver, a plurality of couplers, a micro-controller, and a switch device. The multi-channel receiver includes a plurality of channels for signal transmission. Each coupler is configured to couple the multi-channel receiver with one of the plurality of antennas. The micro-controller is coupled to the multi-channel receiver to compare signals from the plurality of channels, thereby identifying a channel with a highest signal-to-noise (SNR) among the plurality of channels. The switch device is coupled to the micro-controller and configured to select an antenna corresponding to the channel with the highest SNR among the plurality of antennas for a connection between a selected antenna and the SISO radio.

公开(公告)号：US20190228272A1

公开(公告)日：2019-07-25

申请号：US15878188

申请日：2018-01-23

Applicant: Intelligent Fusion Technology, Inc

Inventor： Dan SHEN ,  Peter ZULCH ,  Marcello DISASIO ,  Erik BLASCH ,  Genshe CHEN ,  Zhonghai WANG ,  Jingyang LU

IPC: G06K9/62 ,  G06N7/08 ,  G06K9/68 ,  G06T7/80 ,  G01S13/58 ,  H04N5/33

Abstract: The present disclosure provides a method for joint manifold learning based heterogenous sensor data fusion, comprising: obtaining learning heterogeneous sensor data from a plurality sensors to form a joint manifold, wherein the plurality sensors include different types of sensors that detect different characteristics of targeting objects; performing, using a hardware processor, a plurality of manifold learning algorithms to process the joint manifold to obtain raw manifold learning results, wherein a dimension of the manifold learning results is less than a dimension of the joint manifold; processing the raw manifold learning results to obtain intrinsic parameters of the targeting objects; evaluating the multiple manifold learning algorithms based on the raw manifold learning results and the intrinsic parameters to determine one or more optimum manifold learning algorithms; and applying the one or more optimum manifold learning algorithms to fuse heterogeneous sensor data generated by the plurality sensors.