Deep Learning in Aeronautics: Air Traffic Trajectory Classification Based on Weather Reports

[EN] New paradigms in aviation, as the expected shortage of qualified pilots and the increasing number of flights worldwide, present big challenges to aeronautic enterprises and regulators. In this sense, a concept known as Single Pilot Operations arises in the task of dealing with these challenges, for which, automation becomes necessary, especially in Air Traffic Management. In this regard, this paper presents a deep learning-based approach to leveraging the job of both ground controllers and pilots. Making use of Meteorological Terminal Air Reports, obtained regularly from every aerodrome worldwide, we created a model based on a multi-layer perceptron capable of determining the approach trajectory of an aircraft thirty minutes prior to the expected landing time. Experiments on aircraft trajectories from Toulouse to Seville, show an accuracy, recall and F1-score higher than 0.9 for the resultant predictive model.This work has received funding from the Clean Sky 2 Joint Undertaking (JU) under grant agreement No 831884. The Titan V used for this research was donated by the NVIDIA CorporationJiménez-Campfens, N.; Colomer, A.; Núñez, J.; Mogollón, JM.; Rodríguez, AL.; Naranjo Ornedo, V. (2020). Deep Learning in Aeronautics: Air Traffic Trajectory Classification Based on Weather Reports. Springer. 148-155. https://doi.org/10.1007/978-3-030-62365-4_14S148155Pilot and technical outlook: Seattle. Boeing Commercial Airplanes, WA (2015)Wolter, C.A., Gore, B.F.: NASA/TM-2015-218480: A validated task analysis of the Single Pilot Operations concept, no. January 2015 (2015)Harris, D.: A human-centred design agenda for the development of single crew operated commercial aircraft. Aircr. Eng. Aerosp. Technol. 79(5), 518–526 (2007)Bailey, R.E., Kramer, L.J., Kennedy, K.D., Stephens, C.L., Etherington, T.J.: An assessment of reduced crew and single pilot operations in commercial transport aircraft operations. In: AIAA/IEEE Digital Avionics System Conference - Proceedings, vol. 2017-September, no. February 2018 (2017)Lachter, J., Brandt, S.L., Battiste, V., Ligda, S.V., Matessa, M., Johnson, W.W.: Toward single pilot operations: developing a ground station. In: Proceedings of International Conference on Human-Computer Interactive Aerospace, August (2014)Comerford, D., Brandt, S.L., Mogford, R.: NASA/CP - 2013–216513 NASA’s Single -Pilot Operations Technical Interchange Meeting: Proceedings and Findings, April, p. 89 (2013)Durand, N., Alliot, J.M., Médioni, F.: Neural nets trained by genetic algorithms for collision avoidance. Appl. Intell. 13(3), 205–213 (2000)Choi, S., Kim, Y.J., Briceno, S., Mavris, D.: Prediction of weather-induced airline delays based on machine learning algorithms. In: 2016 IEEE/AIAA 35th Digital Avionics Systems Conference (DASC), pp. 1–6. IEEE, September 2016Gui, G., Liu, F., Sun, J., Yang, J., Zhou, Z., Zhao, D.: Flight delay prediction based on aviation big data and machine learning. IEEE Trans. Veh. Technol. 69, 140–150 (2019)Liu, Y., Hansen, M.: Predicting aircraft trajectories: a deep generative convolutional recurrent neural networks approach. arXiv preprint arXiv:1812.11670 (2018)Shi, Z., Xu, M., Pan, Q., Yan, B., Zhang, H.: LSTM-based flight trajectory prediction. In: 2018 IEEE International Joint Conference on Neural Networks (IJCNN), pp. 1–8, July 2018Bosson, C.D., Nikoleris, T.: Supervised learning applied to air traffic trajectory classification. In: 2018 AIAA Information Systems-AIAA Infotech@ Aerospace, p. 1637 (2018)FlightRadar24 website. https://www.flightradar24.com/Ioffe, S., Szegedy, C.: Batch normalization: Accelerating deep network training by reducing internal covariate shift. arXiv preprint arXiv:1502.03167 (2015)Srivastava, N., Hinton, G., Krizhevsky, A., Sutskever, I., Salakhutdinov, R.: Dropout: a simple way to prevent neural networks from overfitting. J. Mach. Learn. Res. 15(1), 1929–1958 (2014)Kingma, D.P., Ba, J.: Adam: a method for stochastic optimization. arXiv preprint arXiv:1412.6980 (2014)Chollet, F., et al.: Keras (2015). https://keras.i

Variation of the phenolic composition and a-glucosidase inhibition potential of seeds, soaked seeds, and sprouts of four wild forms and four varieties of common bean (Phaseolus vulgaris)

The determination of the changes in the composition of bioactive phenolic compounds of germinating seeds which accumulate high levels of these compounds could contribute to the understanding of the germination mechanism and the development of markers for the selection of plant genotypes. In the current study, the changes in the phenolic composition and a-glucosidase inhibition activity, taking place during the germination of four wild forms and four varieties of common bean (Phaseolus vulgaris L.) from Durango Mexico, were determined. A total of 66 phenolic compounds (19 phenolic acids, 18 isoflavones, 18 flavonol glycosides, 3 flavonol aglycones, 3 flavones, 2 dihydroflavonoids, 2 chalcones and one non-identified type) were found by HPLC-DAD, which were differentially accumulated by the seeds, 24 h-soaked seeds, and 4 day-sprouts of each genotype. The accumulation of the flavonol aglycones, myricetin, quercetin and kaempferol was distinctive of the wild seeds. Soaking not only caused leaching and degradation but also triggered the synthesis of new phenolic compounds whereas germination diversified the composition of isoflavones and flavonol glycosides. The seeds of all genotypes analyzed were important inhibitors of a-glucosidase, improving their potential after soaking and germination. The results suggested that the structure rather than the concentration of the flavonoids and phenolic acids determined the inhibitory potential of a-glucosidase of samples. The principal component analysis and cluster analysis revealed HPLC-DAD phenolic profiles as genotype-specific chemomarkers at any of the states (seeds, soaked seeds, and sprouts). The results have wide implications on agronomy and food quality

α-Glucosidase and α- amylase inhibition potentials of ten wild Mexican species of Verbenaceae

Purpose: To evaluate the inhibitory activity of 10 wild Verbenaceae species from Mexico against α- glucosidase and α-amylase.Methods: Ethanol leaf extracts of 10 Verbenaceae species from Mexico were prepared. The inhibitory activity of the extracts against α-glucosidase and α-amylase was evaluated using enzymatic protocols. At least four serial diluted concentrations of each extract was used to calculate the half-maximal inhibitory concentration (IC50).Results: The 10 evaluated Verbenaceae species showed high α-glucosidase inhibition activity, but a low inhibitory effect on α-amylase. Aloysia gratissima (IC50 = 0.122 mg/mL), Verbena carolina (IC50 = 0.112 mg/mL), Bouchea prismatica (IC50 = 0.122 mg/mL), Verbena menthiflora (IC50 = 0.071mg/mL) and Priva mexicana (IC50 = 0.032 mg/mL) exhibited the strongest inhibitory activities against α- glucosidase.Conclusion: All the Verbenaceae species studied possess α-glucosidase inhibitory effect, with P. mexicana being the one with the strongest activity. These findings demonstrate the highs potential of these species as a source of natural antihyperglycemic agents for type 2 diabetes therapy.Keywords: Hyperglycemic, Diabetes, α-Glucosidase, α-Amylase Verbenaceae, Aloysia gratissima, Bouchea prismatica, Priva mexican

4to. Congreso Internacional de Ciencia, Tecnología e Innovación para la Sociedad. Memoria académica

Este volumen acoge la memoria académica de la Cuarta edición del Congreso Internacional de Ciencia, Tecnología e Innovación para la Sociedad, CITIS 2017, desarrollado entre el 29 de noviembre y el 1 de diciembre de 2017 y organizado por la Universidad Politécnica Salesiana (UPS) en su sede de Guayaquil. El Congreso ofreció un espacio para la presentación, difusión e intercambio de importantes investigaciones nacionales e internacionales ante la comunidad universitaria que se dio cita en el encuentro. El uso de herramientas tecnológicas para la gestión de los trabajos de investigación como la plataforma Open Conference Systems y la web de presentación del Congreso http://citis.blog.ups.edu.ec/, hicieron de CITIS 2017 un verdadero referente entre los congresos que se desarrollaron en el país. La preocupación de nuestra Universidad, de presentar espacios que ayuden a generar nuevos y mejores cambios en la dimensión humana y social de nuestro entorno, hace que se persiga en cada edición del evento la presentación de trabajos con calidad creciente en cuanto a su producción científica. Quienes estuvimos al frente de la organización, dejamos plasmado en estas memorias académicas el intenso y prolífico trabajo de los días de realización del Congreso Internacional de Ciencia, Tecnología e Innovación para la Sociedad al alcance de todos y todas

EL CULTIVO DE HONGOS COMESTIBLES PARA EL DESARROLLO COMUNITARIO

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MICORREMOCION DE ZINC EN SUELOS CONTAMINADOS CON ACEITE USADO AUTOMOTRIZ, EN LA CIUDAD DE DURANGO, MEXICO.

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MICORREMOCION DE ZINC EN SUELOS CONTAMINADOS CON ACEITE USADO AUTOMOTRIZ, EN LA CIUDAD DE DURANGO, MEXICO.

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Perfiles electroforéticos de las proteínas de semilla de pinos como caracteres taxonómicos

Seed proteins play a very important role in germination. Seeds from a single taxon have a highly stable composition of storage protein. This stability is useful in agronomic, ecological, physiological, taxonomic, molecular and phyto-pathological studies. This paper describes the electrophoretic characterisation in acrylamide gels of seed protein from five pine species (Pinus cembroides, P ayacahuite, P durangensis, P engelmanii, P cooperi and P maximartinezii) from México to determine the importance of their protein profile as biochemical markers in taxonomy. The results suggest that pine reserve protein electrophoretic profiles have chemical attributes having taxonomic importance at subgenus and species level. Las proteínas de semilla o de reserva son sustancias que juegan un papel importante durante la germinación. Su composición es muy conservada dentro de un grupo taxonómico de plantas, por lo que la determinación de los patrones electroforéticos de estas proteínas son útiles en estudios agronómicos, fisiológicos, taxonómicos, moleculares y en estudios de fitopatología. En este trabajo se realizó la caracterización electroforética, en geles de acrilamida, de las proteínas de semilla de cinco especies de pinos del Estado de Durango (Pinus cembroides, P. ayacahuite, E durangensis, P engelmanii y P. cooperi) y uno de Zacatecas (P. maximartinezii), México, para determinar su utilidad como caracteres bioquímicos en taxonomía. Los resultados obtenidos permiten sugerir la validez de los perfiles electroforéticos de proteínas de reserva como marcadores taxonómicos a nivel subgenérico y específico, ya que los perfiles de las tres especies del subgénero Strobus (P. maximartinezii, P cembroides y P ayacahuite) presentan perfiles semejantes entre sí pero claramente diferentes a los perfiles de las tres especies del subgénero Pinus (P durangensis, P engelmanii y P. cooperi). A su vez, los perfiles de cada una de las seis especies son especie-específicos sin presentar variabilidad intrapoblacional.

EL METABOLISMO SECUNDARIO DE LAS PLANTAS, UN NUEVO CONCEPTO

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LOS JARDINES BOTÁNICOS Y LA CONSERVACIÓN DE CACTÁCEAS

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