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Quach, Tu-Thach

Publications and source records attributed to Quach, Tu-Thach.

At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Task-specific sensor optical designs

A method and system architecture for designing a compressive sensing matrix for machine learning includes receiving an image associated with a classification task and; generating a sensing matrix. The sensing matrix includes an array of nonzero elements of the image. A prism array of prism elements is in communication with the sensing matrix. A row of values corresponding with an input angle of the prism array is mapped to a respective column corresponding with a detector. Then the detector detects light refracted at an output angle dictated by the physical shape of the prism element. A physical model of the detector is fabricated and generates a compressed representation of the image. A machine learning classification algorithm is applied to the compressed representation of the image and generates an optimized non-invertible final determination of the image.

Birch, Gabriel Carlisle↗
DOE OSTI2024

Secure authentication using recurrent neural networks

A computer-implemented method of user authentication is provided. The method comprises combining, by a computer system, a user recurrent neural network with a system recurrent neural network to form a unique combined recurrent neural network. The user recurrent neural network is configured to generate a unique user key, and the system recurrent neural network is configured to generate a system key. The computer system inputs a predetermined input into the combined recurrent neural network, and the combined recurrent neural network generates a unique combined key from the input, wherein the combined key differs from both the user key and system key. The computer system then associates the combined key with a unique access authorization to authenticate a user.

Aimone, James Bradley↗
DOE OSTI2023

Efficient generalized boundary detection

Fast, efficient, and robust compression-based methods for detecting boundaries in arbitrary datasets, including sequences (1D datasets), are desired. The methods, each employing three simple algorithms, approximate the information distance between two adjacent sliding windows within a dataset. One of the algorithms calculates an initial ordered list of subsequences; while a second algorithm updates the ordered list of subsequences by dropping a first entry and appending a last entry rather than calculating completely new ordered lists with each iteration. Large values in the distance metric are indicative of boundary locations. A smoothed z-score or a wavelet-based algorithm may then be used to locate peaks in the distance metric, thereby identifying boundary locations. An adaptive version of the method employs a collection of window sizes and corresponding weighting functions, making it more amenable to real datasets with unknown, complex, and changing structures.

Ting, Christina↗
DOE OSTI2021

Malicious activity detection in a memory

A method and apparatus for monitoring a volatile memory in a computer system. Samples of compressed data from locations in the volatile memory in the computer system are read. Data in the volatile memory is reconstructed using the samples of compressed data. The data is an image of the volatile memory. The image enables determining whether an undesired process is present in the volatile memory.

Wheeler, Jason W.↗
DOE OSTI2020

Efficient Generalized Boundary Detection Using a Sliding Information Distance

In this work, we present a general machine learning algorithm for boundary detection within general signals based on an efficient, accurate, and robust approximation of the universal normalized information distance. Our approach uses an adaptive sliding information distance (SLID) combined with a wavelet-based approach for peak identification to locate the boundaries. Special emphasis is placed on developing an adaptive formulation of SLID to handle general signals with multiple unknown and/or drifting section lengths. Although specialized algorithms may outperform SLID when domain knowledge is available, these algorithms are limited to specific applications and do not generalize. SLID excels in these cases. We demonstrate the versatility and efficacy of SLID on a variety of signal types, including synthetically generated sequences of tokens, binary executables for reverse engineering applications, and time series of seismic events.

42 ENGINEERING↗
DOE OSTI2020

Memory access system

A method and system for accessing a memory for a data processing system. The method comprises sending a read request for a plurality of locations in the memory to read the plurality of locations in parallel based on an upper bound for reading the memory. The upper bound for a number of locations is based on a group of constraints for the memory. The method receives a summed value of a plurality of memory values in the plurality of locations in the memory.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Vehicle track detection in synthetic aperture radar imagery

The various technologies presented herein relate to detecting one or more vehicle tracks in radar imagery. A CCD image can be generated from a first SAR image and a second SAR image captured for a common scene, wherein the second SAR image may include a vehicle track that is not present in the first SAR image. A Radon transform (RT) process can be applied to each pixel in the CCD image, and further, a radial derivative (RDRT) can be determined for each pixel from RT values derived for each pixel. Each pixel can be labelled as being related to a track, or not, based upon a unary cost obtained from the RDRT value of that pixel, combined with a probability of the pixel label based upon labels applied to neighboring pixels. A labelled representation of the CCD image can be generated based upon the determination of “track” or “not track”.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗