Publications

Klein, Brandon T.; Giese, Gerald G.; Lane, Jayson L.; Miner, John G.; Jones, John J.; Venezuela, Otoniel V.

This report presents work performed in 2017 and is a reissue of the end-of-year report SAND2018-0240, A Proof-of-Concept Approach to DevOps and Microservices, January 2018, modified for unlimited release. This report describes the approach, investigation, and prototyping efforts to create an API management solution and automated deployment pipeline for REST-based microservices. Additionally, it reviews: the microservices created for testing purposes; our experiences and results in using an open-source API management tool; and future plans.

Rodriguez, Mark A.; Madison, Jonathan D.; Amon, Tod T.; Comen, Aaron C.; Dropps, Timothy D.; Ivanoff, Thomas I.; Jones, John J.

Abstract not provided.

Strosnick, Matthew S.; Arpin, Bettina K.; Jones, John J.; McGlinchey, John M.

Abstract not provided.

Reeves, Paul C.; Farkas, Benjamin D.; Jones, John J.

This document describes ROCIT, a neural-inspired object recognition algorithm based on a rank-order coding scheme that uses a light-weight neuron model. ROCIT coarsely simulates a subset of the human ventral visual stream from the retina through the inferior temporal cortex. It was designed to provide an extensible baseline from which to improve the fidelity of the ventral stream model and explore the engineering potential of rank order coding with respect to object recognition. This report describes the baseline algorithm, the model's neural network architecture, the theoretical basis for the approach, and reviews the history of similar implementations. Illustrative results are used to clarify algorithm details. A formal benchmark to the 1998 FERET fafc test shows above average performance, which is encouraging. The report concludes with a brief review of potential algorithmic extensions for obtaining scale and rotational invariance.