Carta del editor

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Automated Vigor Estimation on Vineyards

Estimating the balance or vigor in vines, as the yield to pruning weight relation, is a useful parameter that growers use to better prepare for the harvest season and to establish precision agriculture management of the vineyard, achieving specific site planification like pruning, debriefing or budding. Traditionally growers obtain this parameter by first manually weighting the pruned canes during the vineyard dormant season (no leaves); second during the harvest collect the weight of the fruit for the vines evaluated in the first step and then correlate the two measures. Since this is a very manual and time-consuming task, growers usually obtain this number by just taking a couple of samples and extrapolating this value to the entire vineyard, losing all the variability present in theirs fields, which imply loss in information that can lead to specific site management and consequently grape quality and quantity improvement. In this paper we develop a computer vision-based algorithm that is robust to differences in trellis system, varieties and light conditions; to automatically estimate the pruning weight and consequently the variability of vigor inside the lot. The results will be used to improve the way local growers plan the annual winter pruning, advancing in the transformation to precision agriculture. Our proposed solution doesn\textsc{\char13}t require to weight the shoots (also called canes), creating prescription maps (detail instructions for pruning, harvest and other management decisions specific for the location) based in the estimated vigor automatically. Our solution uses Deep Learning (DL) techniques to get the segmentation of the vine trees directly from the image captured on the field during dormant season

CyberColombia: a Regional Initiative to Teach HPC and Computational Sciences

The series Summer School HPC Colombia is an initiative to extend high-performance computing-related knowledge in Colombia, and more widely in Latin America, and integrate expertise and research from academia and industry in the same event. This year’s edition, which is the third in the series, was carried out entirely online due to the outbreak of the COVID 19 pandemic during the first half of the year 2020. In this paper, we summarise the aims, development, deployment, and results of the Summer School HPC Colombia2020event. It is an example of the potential that the use of virtual tools and environments has to grow education for HPC

COVID-19 ResNet: Residual neural network for COVID-19 classification with bayesian data augmentation

COVID-19 is an infectious disease caused by a novel coronavirus called SARS-CoV-2. The first case appeared in December 2019, and until now it still represents a significant challenge to many countries in the world. Accurately detecting positive COVID-19 patients is a crucial step to reduce the spread of the disease, which is characterize by a strong transmission capacity. In this work we implement a Residual Convolutional Neural Network (ResNet) for an automated COVID-19 diagnosis. The implemented ResNet can classify a patient´s Chest-Xray image into COVID-19 positive, pneumonia caused from another virus or bacteria, and healthy. Moreover, to increase the accuracy of the model and overcome the data scarcity of COVID-19 images, a personalized data augmentation strategy using a three-step Bayesian hyperparameter optimization approach is applied to enrich the dataset during the training process. The proposed COVID-19 ResNet achieves a 94% accuracy, 95% recall, and 95% F1-score in test set. Furthermore, we also provide an insight into which data augmentation operations are successful in increasing a CNNs performance when doing medical image classification with COVID-19 CXR.

Análisis y evaluación de la eficiencia coseno de un colector cilindro parabólico polar: Aplicación en una región subtropical de Argentina

Se reporta la influencia del ángulo de incidencia de un sistema de concentración solar que se aplicará a la generación directa de vapor. Dicho sistema consta de un colector cilindro parabólico y un receptor a través del cual fluye el agua como fluido de trabajo. El colector se encuentra inclinado según la coordenada de latitud, curvado parabólicamente y con seguimiento en un eje. El colector se analiza matemáticamente utilizando los datos de un año solar típico y se compara con un colector sin inclinación. Hay una mejora significativa en la eficiencia óptica coseno durante todo el año en el colector cilindro parabólico polar, especialmente en la temporada de invierno. Este colector también se analiza empleando herramientas informáticas basadas en la metodología Tonatiuh Ray-Tracing, y se calculan las dimensiones óptimas del receptor. El colector cilindro parabólico polar es un colector prometedor para sistemas de energía solar concentrada en latitudes subtropicales, ya que proporciona un mejor aprovechamiento del recurso solar para los procesos involucrados en la obtención de calor o generación de electricidad, especialmente en aplicaciones de mediana y baja escala.

Natural products as drugs source in the Ecuador´s essential medicines list

This paper presents the analysis of the origin of 391 active ingredients (AIs) of the 9th list of essential medicines in Ecuador, using the system proposed by Newman and Cragg with certain modifications. The AIs of natural origin represent 54.2% of the list and have greater importance in the categories H, R and B of the Anatomical, Therapeutic and Chemical classification system for pharmacological substances and medicines. In addition, the influence of natural products was analyzed in the categories with the highest amount of IAs J, L and N, as well as in category C, which is associated with the main cause of death in Ecuador.

Primeras experiencias para construir la Red Colombiana de Computación Avanzada: LaRedCCA

La Red Colombiana de Computación Avanzada (LaRedCCA) fue establecida para fortalecer la comunidad de supercómputo y unir conocimientos, recursos e infraestructura distribuida geográficamente en Colombia mediante la red académica. Igualmente busca integrar los centros de recursos de computación de alto rendimiento para soportar iniciativas científicas y académicas de interés nacional y sin ánimo de lucro. Ha sido conformada inicialmente por el SC3UIS (Supercomputación y Cálculo Científico) de la Universidad Industrial de Santander, la Universidad de los Andes y la Red Nacional Académica de Tecnología Avanzada (RENATA). LaRedCCA ha establecido un banco de prueba inicial para compartir recursos informáticos a través de un enlace de alta velocidad proporcionado por RENATA y busca apoyar la investigación en todas las áreas del ecosistema científico y tecnológico del país, impulsando áreas como la computación paralela y distribuida, la inteligencia artificial y el Big Data. Este enlace ha mostrado resultados interesantes al proporcionar un canal HPC dedicado que proporciona un alto ancho de banda para la transferencia de datos para análisis posteriores o simulaciones realizadas por los centros de investigación de la Universidad de los Andes en y en los recursos de computación de alto rendimiento de SC3UIS, principalmente en la plataforma GUANE-1.

Modeling and analysis of a prestressed girder bridge prior to diagnostic load testing

Progressive deterioration is a problem that affects road infrastructure, especially bridges. This requires the development of methods for its adequate detection and revision, one of them being load testing. Within load testing, finite element analysis (FEA) models provide initial information to understand the behavior of a structure and plan accordingly, which represents a fundamental step towards a precise structural evaluation of a bridge. This study focused on the modeling and analysis of the static response of the bridge over the river Lili in Cali, Colombia, a prestressed girder bridge programmed to undergo a diagnostic load test. A linear FEA model was created with information from a manual survey and from other bridges’ plans designed and built under the regulations in force at the time. Due to the absence of plans and design specifications for the bridge, variations were applied to certain model parameters (stiffness of diaphragms and elastomeric bearings), to quantify their effect on the overall behavior of the bridge. The analysis included obtaining the critical position for the design vehicles, the transversal distribution of stresses and determining the influence of the variation parameters in the response of the structure. Results showed that the critical combinations for bending moment and shear were when the loads were the closest to the exterior girders, being these elements the most affected. The variation on the modulus of elasticity for the diaphragms and the stiffness of the elastomeric bearings did not significantly influence the results for bending moment and shear, nor the critical position. Girder distribution factors (GDF) from the model were compared to previous research, finding similarities in shape and value with other FEA models and experimental results. Finally, an instrumentation plan focused on the girders of the bridge was proposed based on the zones where the maximum effects are expected. The findings in this study show how linear FEA models provide initial but relevant information regarding the critical position of design vehicles, the distribution of stresses and the expected values for bending moment and shear under design loads.

Estudio de pre-factibilidad técnica y económica de la implementación de una biorrefinería para la conversión de residuos de cáscara de naranja

La cáscara de naranja es un residuo orgánico abundante en el Ecuador que puede ser aprovechado y transformado en productos de alto valor agregado. Por ello, el presente artículo analiza la pre-factibilidad técnico-económica de una biorrefinería a partir de cáscara de naranja para la obtención de aceite esencial, pectina y/o bioetanol. Primero, se compararon varios escenarios alrededor de la combinación de productos a ser obtenidos, y se estableció que el más conveniente sería la obtención de aceite esencial y pectina, con una producción anual de 8,7 y 44,4 toneladas, respectivamente. A continuación, se diseñó un proceso para esta biorrefinería que consiste en 3 secciones: el pretratamiento de la materia prima, la extracción del aceite, y la extracción de la pectina. Se realizaron los balances de materia y energía del proceso, y posteriormente, se seleccionaron y dimensionaron los equipos de acuerdo a metodologías específicas. El proceso consideró la recuperación y recirculación de etanol empleado en la sección de extracción de pectina para reducir los costos de producción. Finalmente, se realizó un análisis económico a partir de las estimaciones de costos teóricos y un análisis de costos de catálogo. Se encontró que el proyecto es rentable y que el tiempo de recuperación de la inversión estaría entre 5 y 6 años. Por lo tanto, la implementación de la biorrefinería generaría un impacto positivo a nivel económico, ambiental y social en el país.

A High Granularity Approach to NetworkPacket Processing for Latency-TolerantApplications with CUDA (Corvyd)

Currently, practical network packet processing used for In-trusion Detection Systems/Intrusion Prevention Systems (IDS/IPS) tendto belong to one of two disjoint categories: software-only implementa-tions running on general-purpose CPUs, or highly specialized networkhardware implementations using ASICs or FPGAs for the most commonfunctions, general-purpose CPUs for the rest. These approaches cover tryto maximize the performance and minimize the cost, but neither system,when implemented effectively, is affordable to any clients except for thoseat the well-funded enterprise level. In this paper, we aim to improve theperformance of affordable network packet processing in heterogeneoussystems with consumer Graphics Processing Units (GPUs) hardware byoptimizing latency-tolerant packet processing operations, notably IDS,to obtain maximum throughput required by such systems in networkssophisticated enough to demand a dedicated IDS/IPS system, but notenough to justify the high cost of cutting-edge specialized hardware. Inparticular, this project investigated increasing the granularity of OSIlayer-based packet batching over that of previous batching approaches.We demonstrate that highly granular GPU-enabled packet processing isgenerally impractical, compared with existing methods, by implementingour own solution that we call Corvyd, a heterogeneous real-time packetprocessing engine.