Olga Lucía Ramos Sandoval

Prediction of endocrine system affectation in fisher 344 rats by food intake exposed with malathion, applying naïve bayes classifier and genetic algorithms

Background: Reported cases of uncontrolled use of pesticides and its produced effects by direct or indirect exposition, represent a high risk for human health. Therefore, in this paper, it is shown the results of the development and execution of an algorithm that predicts the possible effects in endocrine system in Fisher 344 (F344) rats, occasioned by ingestion of malathion. Methods: It was referred to ToxRefDB database in which different case studies in F344 rats exposed to malathion were collected. The experimental data were processed using Naïve Bayes (NB) machine learning classifier, which was subsequently optimized using genetic algorithms (GAs). The model was executed in an application with a graphical user interface programmed in C#. Results: There was a tendency to suffer bigger alterations, increasing levels in the parathyroid gland in dosages between 4 and 5 mg/kg/day, in contrast to the thyroid gland for doses between 739 and 868 mg/kg/day. It was showed a greater resistance for females to contract effects on the endocrine system by the ingestion of malathion. Females were more susceptible to suffer alterations in the pituitary gland with exposure times between 3 and 6 months. Conclusions: The prediction model based on NB classifiers allowed to analyze all the possible combinations of the studied variables and improving its accuracy using GAs. Excepting the pituitary gland, females demonstrated better resistance to contract effects by increasing levels on the rest of endocrine system glands.

Monitoreo preliminar de incidencia de fisiopatías en cultivos de fresa usando procesamiento digital de imágenes

Processes executed for Identifying anomalies in agricultural crops using image processing have been effective, however these methods involve tear off plant’s leaflets and fruits under study. For this paper it is shown the results of the development and validation of an algorithm that allows the execution of incidence monitoring in strawberry crops (Fragaria x ananassa), able to make a first approximation to distinguish senescence and mechanical damage in their leaflets, implementing an indirect (non-destructive) methodology. Image processing techniques used for this research include smoothing, erosion, dilation, edge detection, pattern matching, thresholding, among others. The results were visualized in an application developed in C # using the Emgu CV library. It is concluded that is possible to offer a preliminary monitoring of incidence using this algorithm, saving time for producers and researchers who require a first approximation of the state of the crop, with the ability to run on desktops, notebooks and aerial robots (drones) that allow to automate this task^les^aLa identificacion de diferentes anomalias en cultivos agricolas usando procesamiento de imagenes, ha demostrado cada vez mas su efectividad, contrario con los metodos de ejecucion tradicionales, los cuales arrancan los foliolos y frutos de la planta, para realizar el estudio. En este trabajo se presentan los resultados del desarrollo e validacion de un algoritmo, que permita realizar monitoreo de incidencia en cultivos de fresa (Fragaria x ananassa), capaz de dar una primera aproximacion para distinguir senescencia y danos mecanicos en sus foliolos, implementando una metodologia indirecta (no destructiva). Las tecnicas de procesamiento de imagenes implementadas incluyen Suavizado, Erosion, Dilatacion, Deteccion de Contornos, Correspondencia de Patrones, Umbralizacion, entre otros. Los resultados obtenidos se visualizaron en una aplicacion desarrollada en C# usando la libreria Emgu CV, mostrando al usuario un diagnostico de la planta de estudio. Se concluye que es posible ofrecer un servicio de monitoreo preliminar de incidencia usando este algoritmo, ahorrando tiempo para productores e investigadores que requieran una primera aproximacion del estado del cultivo, con la posibilidad de ejecutarse tanto en computadores e robots aereos (drones) para hacer mas eficiente esta tarea.^len^aProcesses executed for identifying anomalies in agricultural crops using image processing have been effective, however these methods involve tear off plant’s leaflets and fruits under study. For this paper it is shown the results of the development and validation of an algorithm that allows the execution of incidence monitoring in strawberry crops (Fragaria x ananassa), able to make a first approximation to distinguish senescence and mechanical damage in their leaflets, implementing an indirect (non-destructive) methodology. Image processing techniques used for this research include smoothing, erosion, dilation, edge detection, pattern matching, thresholding, among others. The results were visualized in an application developed in C# using the Emgu CV library. It is concluded that is possible to offer a preliminary monitoring of incidence using this algorithm, saving time for producers and researchers who require a first approximation of the state of the crop, with the ability to run on desktops, notebooks and aerial robots (drons) that allow to automate this task.^lpt^aA identificacao das diferentes anomalias em cultivos agricolas utilizando processamento de imagens ha demonstrado cada vez mais sua efetividade. Contrario com os metodos tradicionais, que tiram as folhas e frutos da arvore para realizar o estudo. Neste trabalho se apresentam os resultados do desenvolvimento e validacao do algoritmo, que permite realizar monitoramentos da incidencia em cultivos de morango (Fragaria x ananassa), capaz de realizar uma primeira aproximacao para identificar senescencia e danos mecânicos em suas folias, desenvolvendo uma metodologia nao destrutiva. As tecnicas de processamento de imagens desenvolvidas, incluem suavizacao, erosao, dilatacao, deteccao de bordas, correspondencia de padroes, umbral (Thresholding), entre outros. Os resultados obtidos se visualizaram em uma aplicacao em C# utilizando a biblioteca Emgu CV, mostraram ao usuario um diagnostico da planta em estudo. Se conclui que e possivel oferecer um servico de monitoramento preliminar de incidencia, utilizando este algoritmo, poupando tempo para produtores e pesquisadores que precisem uma primeira aproximacao do estado de um cultivo, com a possibilidade de utilizar computadores e Drones para fazer mais eficiente esta tarefa.

Technologies and Applications Review of Subvocal Speech

This paper presents a review of the main applicative and methodological approaches that have been developed in recent years for sub-vocal speech or silent language. The sub-vocal speech can be defined as the identification and characterization of bioelectric signals that control the vocal tract, when is not produced sound production by the caller. The first section makes a deep review of methods for detecting silent language. In the second part are evaluated the technologies implemented in recent years, followed by a review of the main applications of this type of speech and finally present a broad comparison between jobs that have been developed in industry and academic applications.