Taking into account that in Peru, there is an increase in people with difficulties in speaking or communicating. According to the National Institute of Statistics and Informatics of Peru (INEI for its acronym in Spanish), around 80000 people use the gesturing language. For this reason, this research proposes to use the electromyography (EMG) signals to detect the hand movement and identify the alphabet of the sign language to provide essential communication to people who need it. The idea is to classify the signals and recognize the letters of the Spanish alphabet, interpreted in the Peruvian sign language. The results show the classification of the 27 letters of the alphabet with a general success rate of 93.9%.

Currently in Peru, there is a per capita milk consumption of 87 kg per year; however, the Food and Agriculture Organization of the United Nations (FAO) recommends a consumption of 120 kg per person; the industry, when the milk is acquired from small livestock suppliers, does not analyze the milk before buying it, which there is a high risk that the milk is adulterated with water, in this sense, it proposes an alternative way of preliminary detection of the presence of water in milk, only through a laser a photograph, which greatly reduces the costs of milk analysis. Milk contains different nutrients, vitamins and minerals, which are beneficial for people, so it is very known if it is adulterated or not, that way to prevent diseases. In this document, the reader will read an alternative to the existing methods for the analysis of milk, for the presented method the application of Matlab Classification Learner and the fine K-Nearest Neighbors (KNN) algorithm were used, in which a success rate of 95.4% was obtained.

The people who require greater protection and safety are children, mainly when they are in an educational center, where teachers are responsible for their care, therefore, it is important to have prepared teachers to face emergency situations, since, the sense of insecurity is greater in national schools due to the shortage of prepared teachers to handle emergencies situations in Peru; there are studies which mention that 98.2% of accidents in educational centers are trauma and falls, also 1 of every 4 students suffers a fracture, therefore, in this study, spatial data of kindergarten and primary education is presented from Peru, relating the number of students per teacher for the year 2019. The regions whose student-teacher relationship is risky for the welfare of the students are presented and analyzed by georeference, this data is public and is provided by the Ministerio de Educación de Perú (MINEDU), and using tools from the Geographic Information System (GIS), and it was possible to generate maps at the district level. Observing at the maps, it was possible to identify that the areas with the greatest risk are in the natural region of the jungle. Base on the spatial distribution of vulnerable points and outliers of the studentteacher relationship at the levels of kindergarten and primary education, it is recommended that governmental and nongovernmental institutions in Peru allocate resources urgently to reduce student vulnerability, reducing the relationship between the number of students and teachers, in order to get better the response to any accident or natural disaster.

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