The purpose of this study is to evaluate the lighting levels in the working areas of mining companies involved in the exploitation of phosphoric rocks for the production of agro-industrial goods in the department of Huila. To this end, measurements will be made with a luxometer, considering the location of the factories, and the natural and artificial lights. These measurements will be performed to evaluate the lighting conditions found in that sector, provide recommendations and thus achieve better results in the work stations according to light quantity and quality, and energy efficiency. Subsequently, these results will be analyzed based on the Colombian regulations to determine if the companies meet the rules that ensure the employees’ safety and health.

The purpose of this study is to evaluate the lighting levels in the working areas of mining companies involved in the exploitation of phosphoric rocks for the production of agro-industrial goods in the department of Huila. To this end, measurements will be made with a luxometer, considering the location of the factories, and the natural and artificial lights. These measurements will be performed to evaluate the lighting conditions found in that sector, provide recommendations and thus achieve better results in the work stations according to light quantity and quality, and energy efficiency. Subsequently, these results will be analyzed based on the Colombian regulations to determine if the companies meet the rules that ensure the employees’ safety and health.

There is a fast increase of information and data generation in virtual environments due to microblogging sites such as Twitter, a social network that produces an average of 8, 000 tweets per second, and up to 550 million tweets per day. That's why this and many other social networks are overloaded with content, making it difficult for users to identify information topics because of the large number of tweets related to different issues. Due to the uncertainty that harms users who created the content, this study proposes a method for inferring the most representative topics that occurred in a time period of 1 day through the selection of user profiles who are experts in sports and politics. It is calculated considering the number of times this topic was mentioned by experts in their timelines. This experiment included a dataset extracted from Twitter, which contains 10, 750 tweets related...