. Colima’s volcano is one of the most active volcanoes in Mexico, therefore, constant monitoring of its explosive activity is necessary to provide a timely warning of volcanic danger for nearby populations. Each explosive event generates seismic waves. The characteristics of the seismic signals can serve to identify an explosive event as strong, or as a weak explosive event. Therefore, the rapid identi(cid:28)cation of the type of explosive event can be important for estimating the level of danger for nearby populations. Normally, the identi(cid:28)cation of the type of seismic signal produced by the explosions is carried out after the event has ended (o(cid:27)-line analysis). An improvement to the o(cid:27)-line type of analysis is to perform an analysis at the moment the continuous explosive seismic signal originates ( on-line analysis) since this will allow determining the type of seismic signal in one stage early where the event originates. An algorithm was developed that allows identifying the type of seismic signal through analysis (on-line) and issuing an alarm to the population of the occurrence of a strong explosive event with a high probability of danger. The results obtained by our on-line analysis algorithm show that the type of seismic event can be identi(cid:28)ed in the same way as using the o(cid:27)-line method.
Resumen. Atribución de Autoría es la tarea de identificar el autor de un texto anónimo. El uso de inteligencia artificial es muy común en esta tarea y uno de los principales problemas es que no se cuenta con suficientes textos de entrenamiento de uno o más candidatos autores, lo que genera un problema de desbalance, afectando en gran medida el rendimiento de los métodos propuestos en el estado del arte. La mayoría de estos métodos utilizan SVM como clasificador y una de las siguientes características como modelo de representación de texto: unigramas de palabra o trigramas de carácter. En este artículo se propone un método con un rendimiento superior a los métodos del estado del arte en muestras balanceadas y desbalanceadas, esto se logra mediante la combinación de distintos tamaños de n-gramas para formar la bolsa de n-gramas y generar un nuevo modelo de representación de texto. Los experimentos realizados muestran la importancia de entrenar al clasificador con una bolsa de n-gramas de diferentes tamaños y no solo con un tamaño fijo. Los mejores resultados se obtienen cuando se combinan unigramas y bigramas de palabra, además se muestra la importancia que tiene la estrategia de clasificación cuando se utiliza SVM. Palabras clave:
. Lane detection is an important module for active safety systems, as it increases safety and reduces traffic accidents caused by driver inattention. Illumination changes or occlusions make lane detection a challenging task, especially if the detection is performed from a single image. Consequently, this paper presents a probabilistic approach based on the Kalman filter, which using information from previous image frames manages to estimate the lane that could not be detected in the current image frame, considering uncertainty in the prediction as well as in the detection. To this end, a principal component analysis of the segmented curvature is introduced with the purposes of dimensionality reduction, moving from a large dimensional pixel representation to a considerably reduced space representation.
. The current context in which higher education institutions operating in Mexico is adverse and multifactorial. In this work, the data obtained from a survey applied to 1,582 students are analyzed to determine the main factors that influence school dropout in a pre-COVID19 stage. With this information, an analysis of the decision tree was developed, detecting the main routes that influence school dropout. This study can be useful both to the public and to the instances involved in decision-making, to try to create an environment conducive to allow students to continue with their university education.
