Pronósticos de variables climatológicas mediante los modelos de punto de cambio y Holt-Winters.

This study analyzes a time series with daily historical data from January 1, 1989 to December 31, 2021 of the precipitation variable with a total of 12053 observations, these data are obtained from the Tunjuelito climatological station. For the research the records of the variable “precipitation” were taken into account, the objective was to analyze the trends, use the data up to December 31, 2020 to estimate a forecast for the year 2021 Holt-Winters method and the change point model, the observed data are compared with the predicted data. Finally, statistical tests are performed to contrast the degree of similarity of the data obtained from the forecasts with the observed data provided by the station. The results show that the data obtained from the change point model show higher accuracy and fit relatively well with the observed data. However, this study is considered preliminary and for the results to be considered conclusive they must be applied to a significant number of time series of meteorological variables.En este estudio se analiza una serie de tiempo con datos históricos diarios desde enero 1 de 1989 hasta el 31 de diciembre del año 2021 de la variable precipitación con un total de 12053 observaciones, estos datos son obtenidos a partir de la estación climatológica Tunjuelito. Para la investigación se tuvieron en cuenta los registros de la variable “precipitación”, el objetivo fue analizar las tendencias, utilizar los datos hasta el 31 de diciembre de 2020 para estimar un pronóstico para el año 2021 método de Holt-Winters y el modelo de punto de cambio, se comparan los datos observados con los pronosticados. Por último, se realizan pruebas estadísticas para contrastar el grado de similitud de los datos obtenidos a partir de los pronósticos con los datos observados arrojados por la estación. Los resultados demuestran que los pronósticos obtenidos con el modelo de punto de cambio evidencian una mayor precisión y se ajusta relativamente bien a los datos observados. Sin embargo este estudio se considera preliminar y para que los resultados puedan ser considerados como concluyentes de deben aplicar a una cantidad significativa de series de tiempo de variables meteorológicas

Development of Markerless Systems for Automatic Analysis of Movements and Facial Expressions: Applications in Neurophysiology

This project is focused on the development of markerless methods for studying facial expressions and movements in neurology, focusing on Parkinson’s disease (PD) and disorders of consciousness (DOC). PD is a neurodegenerative illness that affects around 2% of the population over 65 years old. Impairments of voice/speech are among the main signs of PD. This set of impairments is called hypokinetic dysarthria, because of the reduced range of movements involved in speech. This reduction can be visible also in other facial muscles, leading to a hypomimia. Despite the high percentage of patients that suffer from dysarthria and hypomimia, only a few of them undergo speech therapy with the aim to improve the dynamic of articulatory/facial movements. The main reason is the lack of low cost methodologies that could be implemented at home. DOC after coma are Vegetative State (VS), characterized by the absence of self-awareness and awareness of the environment, and Minimally Conscious State (MCS), in which certain behaviors are sufficiently reproducible to be distinguished from reflex responses. The differential diagnosis between VS and MCS can be hard and prone to a high rate of misdiagnosis (~40%). This differential diagnosis is mainly based on neuro-behavioral scales. A key role to plan the rehabilitation in DOC patients is played by the first diagnosis after coma. In fact, MCS patients are more prone to a consciousness recovery than VS patients. Concerning PD the aim is the development of contactless systems that could be used to study symptoms related to speech and facial movements/expressions. The methods proposed here, based on acoustical analysis and video processing techniques could support patients during speech therapy also at home. Concerning DOC patients the project is focused on the assessment of reflex and cognitive responses to standardized stimuli. This would allow objectifying the perceptual analysis performed by clinicians