Sobre el análisis de información en la actual revolución tecnológica

In these times in which technology has permeated everything–or almost everything–so as not to be extreme, the availability of data from processes, systems, equipment, etc., it has not only been overwhelming but in most cases almost totally underutilized [1]. And that in addition, consequently, if it is evaluated without much effort, it is onerous considering an installed capacity that does not generate benefits.En estos tiempos en que la tecnología ha permeado todo - o casi todo - para no resultarextremista, la disponibilidad de datos provenientes de procesos, sistemas, equipos, etc., haresultado no solo desbordante, sino en la mayoría de casos casi totalmente subutilizados[1]. Y que además, en forma consecuente si se evalúa sin mucho esfuerzo, resulta onerosa atendiendo a una capacidad instalada que no genera beneficios

Diseño de un sistema microcontrolado para la dosificación e inyección de fertilizantes en campo

En este proyecto de investigación fue diseñado el sistema de inyección y dosificación de fertilizantes usando un sistema microcontrolado. El sistema microcontrolado recibe la información de la cantidad de fertilizante requerido por el suelo para su nutrición, y envía señales un dispositivo mecánico para regular el paso del fertilizante haciendo una dosificación exacta del producto. Finalmente, un sistema de inyección introduce el fertilizante en el suelo ABSTRACT In this project of investigation was designed the system of dosage and injection of fertilizers using a microcontrolled system. The microcontrolled system receives the information of the quantity of fertilizer that needs the soil for his nutrition, and it sends signals to a mechanical device to regulate the step of the fertilizer doing the exact dosage of the product. Finally, a system of injection introduces the fertilizer inside the soil.

Sistema de monitoreo de conductores de vehículos a partir de análisis de expresiones faciales

Introduction-When driving, any person is exposed to different stimuli that can lead to accidents. Although numerous technological proposals have been presented to keep the driver monitored, these have overlooked the state of mind in which they driver is, which could have negative effects on the ability to react when driving. Objective- Find different artificial intelligence alternatives for the permanent analysis of drivers' faces, in order to find a good model for classifying facial expression (happy, angry, surprise, neutral). Methodology- The methodology proposed consists in the selection of a database that is pre-processed, in orden to later train different models and make precision comparisons between them. Results- It is possible to find a precision greater than 80% in the detection of the user's mood and then the model is migrated to a portable monitoring system. Conclusions- In this particular case, traditional machine learning methods consume less processing time when classifying, however, they are exceeded in precision by deep learning.  Resumen Introducción-Al conducir, la persona se encuentra expuesta a diferentes estímulos que pueden llevar a que se ocasione accidentes. Aunque Numerosas propuestas tecnológicas se han presentado para mantener monitoreado al conductor, estas han pasado por alto el estado anímico en el que este se encuentra, el cual podría generar efectos negativos en la capacidad de reacción al conducir. Objetivo- Buscar diferentes alternativas de inteligencia artificial para el análisis permanente de rostros de conductores, con el fin de encontrar un buen modelo de clasificación de expresión facial (feliz, enojo, sorpresa, neutral). Metodología- La metodología utilizada consiste en la selección de una base de datos que es preprocesada, para posteriormente entrenar diferentes modelos y realizar comparaciones de precisión entre ellos. Resultados- Se logra encontrar una precisión mayor al 80% en la detección del estado anímico del usuario. Y se logra migrar el modelo a un sistema de monitoreo portátil. Conclusiones- En este caso particular los métodos de aprendizaje de maquina tradicionales (machine learning) consumen menos tiempo a la hora de clasificar, sin embargo, estos son superados en precisión por un aprendizaje profundo

Diseño y simulación de un control de velocidad y tensión para un generador sincrónico. Parte 1

RESUMEN: El objetivo de este trabajo es proponer un procedimiento para simular el generador sincrónico (Parte I) y diseñar controladores óptimos (Parte II), con la ayuda de herramientas de fácil trabajo y amplia divulgación como son MATLAB y su módulo de simulación SIMULINK

Análisis moderno de sistemas dinámicos en ingeniería : un ejemplo

RESUMEN: En este documento se presentan los pasos a seguir cuando se realiza un análisis en ingeniería y se resuelve un problema sobre la dinámica de un sistema electromecánico utilizando software moderno de simulación como MATLAB y SIMULINK

Diseño y simulación de un control de velocidad y tensión para un generador sincrónico - parte II

RESUMEN: El objetivo de este trabajo es proponer un procedimiento para simular el generador sincrónico (Parte I) y diseñar controladores óptimos (Parte II), con la ayuda de herramientas de fácil trabajo y amplia divulgación como son MATLAB y su módulo de simulación SIMULINK

Characteristics and outcomes of an international cohort of 600 000 hospitalized patients with COVID-19

Background: We describe demographic features, treatments and clinical outcomes in the International Severe Acute Respiratory and emerging Infection Consortium (ISARIC) COVID-19 cohort, one of the world's largest international, standardized data sets concerning hospitalized patients. Methods: The data set analysed includes COVID-19 patients hospitalized between January 2020 and January 2022 in 52 countries. We investigated how symptoms on admission, co-morbidities, risk factors and treatments varied by age, sex and other characteristics. We used Cox regression models to investigate associations between demographics, symptoms, co-morbidities and other factors with risk of death, admission to an intensive care unit (ICU) and invasive mechanical ventilation (IMV). Results: Data were available for 689 572 patients with laboratory-confirmed (91.1%) or clinically diagnosed (8.9%) SARS-CoV-2 infection from 52 countries. Age [adjusted hazard ratio per 10 years 1.49 (95% CI 1.48, 1.49)] and male sex [1.23 (1.21, 1.24)] were associated with a higher risk of death. Rates of admission to an ICU and use of IMV increased with age up to age 60 years then dropped. Symptoms, co-morbidities and treatments varied by age and had varied associations with clinical outcomes. The case-fatality ratio varied by country partly due to differences in the clinical characteristics of recruited patients and was on average 21.5%. Conclusions: Age was the strongest determinant of risk of death, with a ∼30-fold difference between the oldest and youngest groups; each of the co-morbidities included was associated with up to an almost 2-fold increase in risk. Smoking and obesity were also associated with a higher risk of death. The size of our international database and the standardized data collection method make this study a comprehensive international description of COVID-19 clinical features. Our findings may inform strategies that involve prioritization of patients hospitalized with COVID-19 who have a higher risk of death

The value of open-source clinical science in pandemic response: lessons from ISARIC

International audienc

ISARIC-COVID-19 dataset: A Prospective, Standardized, Global Dataset of Patients Hospitalized with COVID-19

The International Severe Acute Respiratory and Emerging Infection Consortium (ISARIC) COVID-19 dataset is one of the largest international databases of prospectively collected clinical data on people hospitalized with COVID-19. This dataset was compiled during the COVID-19 pandemic by a network of hospitals that collect data using the ISARIC-World Health Organization Clinical Characterization Protocol and data tools. The database includes data from more than 705,000 patients, collected in more than 60 countries and 1,500 centres worldwide. Patient data are available from acute hospital admissions with COVID-19 and outpatient follow-ups. The data include signs and symptoms, pre-existing comorbidities, vital signs, chronic and acute treatments, complications, dates of hospitalization and discharge, mortality, viral strains, vaccination status, and other data. Here, we present the dataset characteristics, explain its architecture and how to gain access, and provide tools to facilitate its use