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431 results on '"Sanchez, Julio"'

1. Simultaneous navigation and mascon gravity estimation around small bodies

Author

Sanchez, Julio C. and Schaub, Hanspeter

Subjects
Astrophysics - Earth and Planetary Astrophysics, Astrophysics - Instrumentation and Methods for Astrophysics, Physics - Space Physics
Abstract

This manuscript develops a simultaneous navigation and gravity estimation strategy around a small body. The scheme combines dynamical model compensation with a mascon gravity fit. Dynamical compensation adds the unmodeled acceleration to the filter state. Consequently, the navigation filter is able to generate an on-orbit position-unmodeled acceleration dataset. The available measurements correspond to the landmarks-based navigation technique. Accordingly, an on-board camera is able to provide landmark pixels. The aforementioned position-unmodeled acceleration dataset serves to train a mascon gravity model on-board while in flight. The training algorithm finds the optimal mass values and locations using Adam gradient descent. By a careful choice of the mascon variables and constraints projection, the masses are ensured to be positive and within the small body shape. The numerical results provide a comprehensive analysis on the global gravity accuracy for different estimation scenarios.

Published
2023

11. Manoeuvre detection in Low Earth Orbit with Radar Data

Author

Montilla, Jose M., Sanchez, Julio C., Vazquez, Rafael, Galan-Vioque, Jorge, Benayas, Javier Rey, and Siminski, Jan

Subjects
Mathematics - Optimization and Control, Electrical Engineering and Systems Science - Systems and Control, Mathematics - Probability, Statistics - Applications, 70M20
Abstract

This work outlines and assesses several methods for the detection of manoeuvres in Low Earth Orbit (LEO) from surveillance radar data. To be able to detect manoeuvres, the main starting assumption is that the object under analysis has an orbit known with a sufficient degree of precision. Based on the precise (a posteriori) orbit and radar data, several manoeuvre detection methods are presented; one is based on unscented Kalman filtering, whereas two others algorithms are based on reachability analysis of the state, which correlates its prediction set with the next track from the radar. The filtering algorithm can be extended for several radar tracks, whereas the reachability-based methods are more precise in detecting manoeuvres. Then, to inherit the best properties of both classes of algorithms, a manoeuvre detection filter that combines both concepts is finally presented. Manoeuvre detection results are presented first for simulated scenarios -- for validation and calibration purposes -- and later for real data. Radar information comes from the Spanish Space Surveillance Radar (S3TSR), with real manoeuvre information and high-quality ephemerides. The results show promise, taking into account that a single surveillance radar is the only source of data, obtaining manoeuvre detection rates of more than 50% and false positive rates of less than 10%., Comment: Preprint submitted to Advances in Space Research

Published
2022

20. Adventures in Multi-Omics I: Combining heterogeneous data sets via relationships matrices

Author

Akdemir, Deniz and Sanchez, Julio Isidro

Subjects
Statistics - Applications, Mathematics - Statistics Theory, Quantitative Biology - Genomics, Statistics - Methodology
Abstract

In this article, we propose a covariance based method for combining partial data sets in the genotype to phenotype spectrum. In particular, an expectation-maximization algorithm that can be used to combine partially overlapping relationship/covariance matrices is introduced. Combining data this way, based on relationship matrices, can be contrasted with a feature imputation based approach. We used several public genomic data sets to explore the accuracy of combining genomic relationship matrices. We have also used the heterogeneous genotype/phenotype data sets in the https://triticeaetoolbox.org/ to illustrate how this new method can be used in genomic prediction, phenomics, and graphical modeling., Comment: This project was supported by WheatSustain

Published
2019

33. EVASIÓN TRIBUTARIA: TENDENCIAS, RETOS Y OPORTUNIDADES. UNA REVISIÓN SISTEMÁTICA.

Author

Campos Velásquez, William Jesús, Contreras Rivera, Robert Julio, and Ramirez Sanchez, Julio Americo

Subjects
TAX administration & procedure, PUBLIC services, PUBLIC finance, TAX evasion, TECHNOLOGICAL innovations
Abstract

Copyright of International Journal of Professional Business Review (JPBReview) is the property of Open Access Publications LLC and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Published
2024
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36. External Logistic Biplots for Mixed Types of Data

Author

Vicente-Villardón, José L., Hernández-Sánchez, Julio C., Gaul, Wolfgang, Managing Editor, Vichi, Maurizio, Managing Editor, Weihs, Claus, Managing Editor, Baier, Daniel, Editorial Board Member, Critchley, Frank, Editorial Board Member, Decker, Reinhold, Editorial Board Member, Diday, Edwin, Editorial Board Member, Greenacre, Michael, Editorial Board Member, Lauro, Carlo Natale, Editorial Board Member, Meulman, Jacqueline, Editorial Board Member, Monari, Paola, Editorial Board Member, Nishisato, Shizuhiko, Editorial Board Member, Ohsumi, Noboru, Editorial Board Member, Opitz, Otto, Editorial Board Member, Ritter, Gunter, Editorial Board Member, Schader, Martin, Editorial Board Member, Imaizumi, Tadashi, editor, Okada, Akinori, editor, Miyamoto, Sadaaki, editor, Sakaori, Fumitake, editor, and Yamamoto, Yoshiro, editor

Published
2020
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40. Efficient Breeding by Genomic Mating

Author

Akdemir, Deniz and Sanchez, Julio Isidro

Subjects
Quantitative Biology - Populations and Evolution
Abstract

In this article, we propose an approach to breeding which focuses on mating instead of truncation selection, our method uses genome-wide marker information in a similar fashion to genomic selection so we refer it to as genomic mating. Using concepts of estimated breeding values, risk (usefulness) and inbreeding, an efficient mating approach is formulated for improvement of breeding values in the long run. We have used a genetic algorithm to find solutions to this optimization problem. Results from our simulations point to the efficiency of genomic mating for breeding complex traits compared to truncation selection.

Published
2016

44. Sparse testing designs for optimizing predictive ability in sugarcane populations.

Author

Garcia-Abadillo, Julian, Adunola, Paul, Silva Aguilar, Fernando, Trujillo-Montenegro, Jhon Henry, Jaime Riascos, John, Persa, Reyna, Isidro y Sanchez, Julio, and Jarquín, Diego

Subjects
SUGAR crops, SUCROSE, PREDICTION models, GENOTYPES, PHENOTYPES
Abstract

Sugarcane is a crucial crop for sugar and bioenergy production. Saccharose content and total weight are the two main key commercial traits that compose sugarcane's yield. These traits are under complex genetic control and their response patterns are influenced by the genotype-by-environment (G×E) interaction. An efficient breeding of sugarcane demands an accurate assessment of the genotype stability through multi-environment trials (METs), where genotypes are tested/evaluated across different environments. However, phenotyping all genotype-in-environment combinations is often impractical due to cost and limited availability of propagation-materials. This study introduces the sparse testing designs as a viable alternative, leveraging genomic information to predict unobserved combinations through genomic prediction models. This approach was applied to a dataset comprising 186 genotypes across six environments (6×186=1,116 phenotypes). Our study employed three predictive models, including environment, genotype, and genomic markers as main effects, as well as the G×E to predict saccharose accumulation (SA) and tons of cane per hectare (TCH). Calibration sets sizes varying between 72 (6.5%) to 186 (16.7%) of the total number of phenotypes were composed to predict the remaining 930 (83.3%). Additionally, we explored the optimal number of common genotypes across environments for G×E pattern prediction. Results demonstrate that maximum accuracy for SA (ρ=0:611) and for TCH (ρ=0:341) was achieved using in training sets few (3) to no common (0) genotype across environments maximizing the number of different genotypes that were tested only once. Significantly, we show that reducing phenotypic records for model calibration has minimal impact on predictive ability, with sets of 12 non-overlapped genotypes per environment (72=12×6) being the most convenient costbenefit combination. [ABSTRACT FROM AUTHOR]

Published
2024
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