High-throughput plot-level quantitative phenotyping using convolutional neural networks on very high-resolution satellite images

Francisco Pinto Matthew Paul Reynolds Robert Furbank (2024, [Artículo])

Deep Learning Object-Based Image Analysis Optical Imagery CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA AGRICULTURE IMAGE ANALYSIS PLANT BREEDING REMOTE SENSING MACHINE LEARNING

Classification of Cucumber Leaves Based on Nitrogen Content Using the Hyperspectral Imaging Technique and Majority Voting.

Sajad Sabzi Razieh Pourdarbani Mohammad Hossein Rohban Alejandro Fuentes_Penna José Luis Hernández-Hernández Mario Hernández Hernández (2021, [Artículo])

Improper usage of nitrogen in cucumber cultivation causes nitrate accumulation in the fruit and results in food poisoning in humans; therefore, mandatory evaluation of food products becomes inevitable. Hyperspectral imaging has a very good ability to evaluate the quality of fruits and vegetables in a non-destructive manner. The goal of the present paper was to identify excess nitrogen in cucumber plants. To obtain a reliable result, the majority voting method was used, which takes into account the unanimity of five classifiers, namely, the hybrid artificial neural network¿imperialism competitive algorithm (ANN-ICA), the hybrid artificial neural network¿harmonic search (ANN-HS) algorithm, linear discrimination analysis (LDA), the radial basis function network (RBF), and the Knearest- neighborhood (KNN). The wavelengths of 723, 781, and 901 nm were determined as optimal wavelengths using the hybrid artificial neural network¿biogeography-based optimization (ANNBBO) algorithm, and the performance of classifiers was investigated using the optimal spectrum. The results of a t-test showed that there was no significant difference in the precision of the algorithm when using the optimal wavelengths and wavelengths of the whole range. The correct classification rate of the classifiers ANN-ICA, ANN-HS, LDA, RBF, and KNN were 96.14%, 96.11%, 95.73%, 64.03%, and 95.24%, respectively. The correct classification rate of majority voting (MV) was 95.55% for test data in 200 iterations, which indicates the system was successful in distinguishing nitrogen-rich leaves from leaves with a standard content of nitrogen.

artificial neural network cucumber hyperspectral imaging majority voting nitrogen INGENIERÍA Y TECNOLOGÍA CIENCIAS TECNOLÓGICAS TECNOLOGÍA DE LOS ALIMENTOS

Multispectral-derived genotypic similarities from budget cameras allow grain yield prediction and genomic selection augmentation in single and multi-environment scenarios in spring wheat

Jose Crossa Osval Antonio Montesinos-Lopez Morten Lillemo (2024, [Artículo])

Multispectral Imaging Grain Yield Genomic Prediction CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA GRAIN YIELDS HIGH-THROUGHPUT PHENOTYPING SPRING WHEAT

Risk, Covid-19 and hospital care in Mexico City: Are we moving toward a new medical practice?

Rubén Muñoz (2023, [Artículo, Artículo])

Covid-19 pandemic has entailed new challenges for health care in the Mexican public health sector, producing changes in clinical practices that are now handling patients infected with covid-19 and also outpatient consultations at tertiary-level care hospitals. Some of these challenges are related to the perception of risk held by physicians regarding the possibility of contracting or transmitting covid-19 during their work,and to the management of risk from the standpoint of biomedical organizational culture linked to the material and symbolic conditions of public health services predating the pandemic. We analyze these issues from a anthropological research based on in-depth interviews to physicians that work with covid-19 patients at “Covid-19 hospitals” or “hybrid hospitals” in Mexico City. Covid-19 has arrived in social relations and perceptions of risk in the arena of health care and involves knowing and transforming some structural and symbolic conditions, resignified with the pandemic, for proper medical care.

Covid-19 percepción de riesgo personal de salud atención médica hospitalaria cultura organizacional biomédica CIENCIAS SOCIALES CIENCIAS SOCIALES risk perception health care workers hospital care biomedical organizational culture

Study of modal coupling in tapered optical fibers

LUIS ALEJANDRO HERRERA PIAD (2019, [Tesis de doctorado])

La comunicación por fibra óptica es una forma de transmitir información mediante el envío de pulsos de luz a través de una fibra óptica. Desarrollados por primera vez en la década de los 70s, los sistemas de comunicación de fibra óptica han revolucionado la industria debido a sus ventajas sobre la transmisión eléctrica. Las tecnologías de telecomunicaciones y láseres se han relacionado recientemente con fibras de pocos modos, de área modal grande y multimodo. Más específicamente, se han propuesto linternas fotónicas, combinadores de fuentes y fibras multimodo para láseres de alta potencia y comunicaciones. Otro dispositivo que se usa frecuentemente en los láseres, sensores y otras sistemas de comunicaciones es la fibra óptica cónica o estrechada. Fue necesario maximizar la potencia óptica recolectada en una guía de onda desde el campo de difracción de un láser semiconductor; por lo tanto, la técnica de mapeo permitió la remodelación del campo capturado en el modo fundamental de la guía de onda de salida. Además, los sensores de fibra estrechada son capaces de medir diversas variables como índice de refracción, tensión, campo magnético, temperatura y señales acústicas. En comparación con las estructuras de fibra convencionales, las fibras ópticas estrechadas pueden proporcionar una serie de características útiles como un gran campo evanescente, capacidad de confinamiento, diámetro a pequeña escala y generación de supercontinuo, entre muchas otras. En este trabajo se propone una investigación sobre la interacción modal en fibras ópticas estrechadas para observar este dispositivo bajo diversos cambios físicos con el objetivo de proponer la geometría óptima que se implementará en las aplicaciones de detección y láseres de nuestro laboratorio.

CIS- Doctorado en Ingeniería Eléctrica INGENIERÍA Y TECNOLOGÍA Fibra óptica Óptica Física Tapered optical fibers Modal coupling

Variability of Microcirculation Detected by Blood Pulsation Imaging

Alexei Kamshilin (2013, [Artículo])

The non-invasive assessment of blood flow is invaluable for the diagnostic and monitoring treatment of numerous vascular and neurological diseases. We developed a non-invasive and non-contact method of blood pulsation imaging capable of visualizing and monitoring of the two-dimensional distribution of two key parameters of peripheral blood flow: the blood pulsation amplitude and blood pulsation phase. The method is based on the photoplethysmographic imaging in the reflection mode. In contrast with previous imaging systems we use new algorithm for data processing which allows two dimensional mapping of blood pulsations in large object's areas after every cardiac cycle. In our study we carried out the occlusion test of the arm and found (i) the extensive variability of 2D-distribution of blood pulsation amplitude from one cardiac cycle to another, and (ii) existence of the adjacent spots to which the blood is asynchronously supplied. These observations show that the method can be used for studying of the multicomponent regulation of peripheral blood circulation. The proposed technique is technologically simple and cost-effective, which makes it applicable for monitoring the peripheral microcirculation in clinical settings for example, in diagnostics or testing the efficiency of new medicines. © 2013 Kamshilin et al.

algorithm, article, blood analysis, heart cycle, human, human experiment, image analysis, imaging system, male, microcirculation, peripheral circulation, photoelectric plethysmography, process development, Algorithms, Diagnostic Imaging, Diagnostic T CIENCIAS FÍSICO MATEMÁTICAS Y CIENCIAS DE LA TIERRA MATEMÁTICAS ANÁLISIS NUMÉRICO ANÁLISIS NUMÉRICO