Diseño e implementación de un sistema de Telefonía IP basado en Asterisk sobre el protocolo IPV6 para la intercomunicación en las dependencias de la empresa Sinfotecnia

Realizar el diseño e implementación un sistema de telefonía IP basado en Asterisk, mediante la utilización del protocolo IPv6, para la intercomunicación en las dependencias de la empresa Sinfotecnia.La empresa Sinfotecnia actualmente cuenta con una gran trayectoria en el sector las comunicaciones y la informática gracias a que pone al servicio su experiencia en la integración de sistemas de redes de comunicación y seguridad, cableado estructurado, redes eléctricas además ofrece estudios de ingeniería, asesoramiento técnico de hardware y software de última generación al efectuar este tipo de actividades la empresa tiene una gran demanda de clientes que esperan su atención pero en ocasiones esta se limita debido al actual sistema de comunicación que tiene y a la vez causa ciertos inconvenientes como retraso en la ejecución de actividades, perdidas económicas y molestias en los clientes. El presente trabajo de grado tiene como objetivo implementar una solución tecnológica que ofrezca el servicio de comunicación telefónica además de otras funciones como trasferencia de llamadas, captura de llamadas, IVR, etc., y de esta forma permitir que los empleados de la empresa tengan una comunicación constante en todo momento para que la atención hacia sus clientes sea la más adecuada. El sistema se desarrollara en la plataforma de telefonía Asterisk que es una herramienta basada en software libre y de código abierto que proporciona todas las funcionalidades que ofrece la telefonía IP; dicho sistema contará con una extensión telefónica por departamento en cada una de las dependencias además de la posibilidad de crecimiento futuro y toda su implementación se la realizará sobre el protocolo IPv6 debido a las mejoras que trae en comparación a su antecesor IPv4 además que es considerado actualmente como el nuevo protocolo de internet

Reconocimiento de lesiones necróticas para la detección temprana de la plaga thrips (kakothrips robustus uzel) en los cultivos del guisante o arveja mediante técnicas deep learning

Desarrollar un sistema de reconocimiento de lesiones necróticas para la detección temprana de la plaga thrips (Kakothrips Robustus Uzel) en los cultivos del guisante o arveja mediante la aplicación de técnicas de DL (Deep Learning) con la finalidad de reducir la pérdida del cultivo.En la actualidad, el seguimiento de cultivos en las parcelas agrícolas sigue siendo una de las tareas más trascendentales que tiene agricultura de precisión, ya que por medio esta se puede efectuar la estimación del rendimiento y la predicción de cosechas. Debido a las complicadas condiciones atmosféricas y factores climáticos que presenta el sector, la detección temprana de plagas y enfermedades se ha convertido en un desafío considerable que los productores deben asumir de manera constante. Esta investigación propone un sistema de reconocimiento rápido y eficaz de lesiones necróticas para la detección temprana de la plaga thrips en el guisante o arveja mediante la implementación de técnicas de Deep Learning. Para el sistema se utilizaron: un Smartphone y el drone DJI Mavic mini, para recopilar imágenes JPG (Joint Photographic Experts Group) desde las parcelas del cultivo. A continuación, se utilizó la herramienta Roboflow para la extracción, etiquetado, segmentación de las características significativas y relevantes del objeto de estudio en cada una de las imágenes. Fue propuesta la arquitectura de la red neuronal convolucional Yolov4-Tiny, para la detección de la plaga thrips en los cultivos. En el desarrollo del sistema se emplearon herramientas de software libre, como Python y librerías de aprendizaje automático como Tensorflow y de visión artificial como OpenCV. Finalmente, el sistema desarrollado fue puesto a las respectivas pruebas de funcionamiento. Donde los resultados experimentales mostraron que la IoU (Intersección sobre la Unión) es de 59,23% para una mAP (Precisión Media) de 87,8% sobre un conjunto de datos de alta densidad. Los resultados alcanzados por el sistema fueron comparados con el diagnóstico previo realizado el experto en producción del cultivo a través de observaciones directas al guisante o arveja. Donde se pudo a establecer que el sistema tiene una efectividad del 80%.Maestrí

Reconocimiento de lesiones necróticas para la detección de la plaga thrips en el guisante mediante el uso del modelo deep learning yolov4 tiny

At present, the monitoring of crops in agricultural plots remains one of the most important tasks that precision agriculture has since through it is possible to perform the estimation of the yield and the prediction of crops. Due to the complicated atmospheric conditions and climatic factors that the sector presents, the early detection of pests and diseases has become a considerable challenge that producers must constantly assume. This research proposes a rapid and effective necrotic lesion recognition system for the early detection of the thrips infestation in peas by implementing the yolov4-tiny deep learning method. The results obtained by the developed system showed that the IoU (Intersection at the Union) is 59.23% for an mAP (Medium Precision) of 87.8% in a high-density data set. In addition, each of the values ​​delivered by the system was compared with a prescribed diagnosis that was made by an expert in crop production through direct observations of the pea. In this way, it was established that the system is 80% effective.En la actualidad, el seguimiento de cultivos en las parcelas agrícolas sigue siendo una de las tareas más trascendentales que tiene la agricultura de precisión, ya que por medio de esta se puede efectuar la estimación del rendimiento y la predicción de cosechas. Debido a las complicadas condiciones atmosféricas y factores climáticos que presenta el sector, la detección temprana de plagas y enfermedades se ha convertido en un desafío considerable que los productores deben asumir de manera constante. Esta investigación propone un sistema de reconocimiento rápido y eficaz de lesiones necróticas para la detección temprana de la plaga thrips en el guisante mediante la implementación del método de deep learning yolov4-tiny. Los resultados alcanzados por el sistema desarrollado mostraron que la IoU (Intersección sobre la Unión) es de 59,23% para una mAP (Precisión Media) de 87,8% sobre un conjunto de datos de alta densidad. Además, cada uno de los valores entregados por el sistema fueron comparados con un diagnóstico prescrito que fue realizado por un experto en la producción del cultivo a través de observaciones directas al guisante. De esta manera, se llegó a establecer que el sistema tiene una efectividad del 80%. &nbsp

Transesterification Reaction of Waste Cooking Oil and Chicken Fat by Homogeneous Catalysis

In the last years, biodiesel production has been on a steady increase due to it is renewable and biodegradable fuel. The process to obtain biodiesel can be carried out using different raw materials. It is commonly performed by transesterification reaction of vegetable oils with methanol and using a homogeneous or heterogeneous catalyst. This work seeks to compare the results produced in transesterification of wasted cooking oil and chicken fat by homogeneous catalysis with NaOH. Due to in each case triglyceride comes from different raw materials, operation conditions differ slightly, which is more evident in the values used for the temperature. For chicken fat was used temperature variations between 35 oC and 55 oC, varying catalyst in percentages between 0.3% and 0.7% with a molar ratio 6:1 in all cases and a reaction time of 1 h. Likewise, the conditions used in the transesterification process of waste cooking oil were temperature between 50 oC and 60 oC with a molar ratio 6/1 and 9/1 for alcohol and oil, and catalyst percentage between 0.5% and 0.7% by weight. The yields obtained were between 78% and 94%, or 83% and 95%, for chicken fat and wasted cooking oil, respectively

Biodiesel Production by Enzymatic Catalysis Process Using Two Analytical Ways: Gas Chromatography and Total Glycerol Determination

Currently, biodiesel is presented as one of the best alternatives for gradually replacing the use of fossil fuels, but it has some factors that make it economically impractical if it does not have a government support. For this reason, research efforts focused on this area have been responsible for optimizing the process of biodiesel production by different catalytic routes to achieve greater efficiency at a lower cost. In this case, the biggest problem has been the high cost generated by an investigation, which in many occasions is the main factor to decide if an investigation could be carried out. Trying to reduce these costs, in the current study, we are using a technique of glycerol quantification by volumetric methods and comparing obtained results with the chromatographic method, which is conventionally used and comparatively much more expensive. Biodiesel employee was obtained by an enzymatic catalysis process varying one of three process variables :oil: alcohol molar ratio, temperature and proportion of catalyst. The numerical differences obtained between the two quantification methods generated relative errors lower than 10%, resulting in some occasions lower than 1%. By gas chromatography analysis the best yield was obtained at the same conditions of the volumetric method, a temperature of 45 oC, an oil:alcohol ratio 1:4 and 8 wt.% of catalyst, but a yield of 95.5% and 97.1%, respectively. Due to the high precision of gas chromatography, this method is used to carry out a surface response analysis obtaining as ideal operating conditions a temperature of 43.5 °C, 8.9 wt.%. of catalyst and an oil:alcohol ratio 1:4

Global variation in diabetes diagnosis and prevalence based on fasting glucose and hemoglobin A1c

Fasting plasma glucose (FPG) and hemoglobin A1c (HbA1c) are both used to diagnose diabetes, but these measurements can identify different people as having diabetes. We used data from 117 population-based studies and quantified, in different world regions, the prevalence of diagnosed diabetes, and whether those who were previously undiagnosed and detected as having diabetes in survey screening, had elevated FPG, HbA1c or both. We developed prediction equations for estimating the probability that a person without previously diagnosed diabetes, and at a specific level of FPG, had elevated HbA1c, and vice versa. The age-standardized proportion of diabetes that was previously undiagnosed and detected in survey screening ranged from 30% in the high-income western region to 66% in south Asia. Among those with screen-detected diabetes with either test, the age-standardized proportion who had elevated levels of both FPG and HbA1c was 29-39% across regions; the remainder had discordant elevation of FPG or HbA1c. In most low- and middle-income regions, isolated elevated HbA1c was more common than isolated elevated FPG. In these regions, the use of FPG alone may delay diabetes diagnosis and underestimate diabetes prevalence. Our prediction equations help allocate finite resources for measuring HbA1c to reduce the global shortfall in diabetes diagnosis and surveillance

Global variations in diabetes mellitus based on fasting glucose and haemogloblin A1c

Fasting plasma glucose (FPG) and haemoglobin A1c (HbA1c) are both used to diagnose diabetes, but may identify different people as having diabetes. We used data from 117 population-based studies and quantified, in different world regions, the prevalence of diagnosed diabetes, and whether those who were previously undiagnosed and detected as having diabetes in survey screening had elevated FPG, HbA1c, or both. We developed prediction equations for estimating the probability that a person without previously diagnosed diabetes, and at a specific level of FPG, had elevated HbA1c, and vice versa. The age-standardised proportion of diabetes that was previously undiagnosed, and detected in survey screening, ranged from 30% in the high-income western region to 66% in south Asia. Among those with screen-detected diabetes with either test, the agestandardised proportion who had elevated levels of both FPG and HbA1c was 29-39% across regions; the remainder had discordant elevation of FPG or HbA1c. In most low- and middle-income regions, isolated elevated HbA1c more common than isolated elevated FPG. In these regions, the use of FPG alone may delay diabetes diagnosis and underestimate diabetes prevalence. Our prediction equations help allocate finite resources for measuring HbA1c to reduce the global gap in diabetes diagnosis and surveillance.peer-reviewe

Purification of glycerol from biodiesel production by sequential extraction monitored by 1H NMR

The purification of raw glycerin in biodiesel production can provide economic benefits and help to avoid residue accumulation, thus reducing environmental impacts. In this work, the glycerin obtained from biodiesel production by catalytic transesterification of waste cooking oi lwas purified by sequential extraction with organic solvents, followed by discoloration with activated coal and monitoring by 1H NMR spectroscopy. Through sequential extraction with petroleum ether and toluene, in that order, followed by discoloration with activated carbon, 99.2% pure glycerin was obtained. This technique is shown to allow for glycerin purification using less drastic or hazardous conditions than those commonly applied in vacuum distillation

ATLANTIC ANTS: a data set of ants in Atlantic Forests of South America

International audienc