Issue 1, 14, 2023

• Evaluación de residuos forestales de especies potenciales para la obtención del carbono como energía limpia de la Amazonia Ecuatoriana

  J. González, R. Darío Ledesma, R. Abreu Naranjo

  Enfoque UTE - Scientific Engineering Journal (2023). Vol. 14, (1), 4

  
  

  Abstract

  Timber residues due to its use for the construction industry and others provided by the secondary forest and its high content of lignocellulosic material for energy purposes, our objective was to evaluate the forest residues of six species to obtain carbon as clean energy. , which represents great interest for the energy industry. Through the methodology of the study of inventories and sampling of wood residues from sawmills that was in the four cantons of the province of Pastaza, through instrumental techniques of physical, chemical and thermal analysis, the parameters studied were the biomass potential and residue, density, humidity, ashes, volatiles, fixed carbon and higher calorific value (immediate analysis), carbon, hydrogen, oxygen, nitrogen and sulfur (CHONS), which allowed obtaining the thermochemical properties, reaching the main results of energy potential, of these three species that can be used for clean energy, due to the amount of ash found in the analyzes below 1% and volatiles (60-80%) of these residues, which clearly shows that it prevents the formation of scale in equipment and damage, in relation to its fixed carbon content on average of 14.78% and its superior calorific value 19.72 Mj/kg, assessing the fact industrial reliability for its energy use that will generate 515.62 GW of clean energy in electrical thermal power annually to meet the needs of vulnerable areas of the Amazon region.

  Abstract
  Timber residues due to its use for the construction industry and others provided by the secondary forest and its high content of lignocellulosic material for energy purposes, [...]

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• Adaptabilidad de algoritmos de regresión al comportamiento de las plantas proteicas

  H. Uvidia-Cabadiana, P. Estrada-Jiménez, R. Herrera-Herrera, L. Hernández-Montiel, D. Verdecia-Acosta, J. Ramírez-de la Ribera, P. Noguera-López, E. Chacón-Marcheco

  Enfoque UTE - Scientific Engineering Journal (2023). Vol. 14, (1), 2

  
  

  Abstract

  The behavior of components of protein plant is of vital importance for animals that consume them in their diet. The objective of this research is to evaluate regression algorithms, to determine the behavior of the expressions that best adapt to the procedures of a traditional laboratory and to estimate the chemical components of protein plants, in this sense the MULAN library of java has been used, that contain automatic learning algorithms capable of adapting to dissimilar problems. Three data set were created for each species treated in this study; each of these include the main elements to be evaluate in each experiment, these are delimits by: secondary metabolites, cell wall components and digestibility element for training files one, two and three, respectively; subsequently, they were evaluated through learning supervised and cross-validation of each to determine the best fit by aRMSE (Average Root Mean Square Error). The learning results were compare with previous experiments, where there was a learning variant that contained in a single dataset all the components to be evaluates in a single prediction. The result of the comparison shows that the lazy algorithms based on instances have a better learning behavior than the others evaluate.

  Abstract
  The behavior of components of protein plant is of vital importance for animals that consume them in their diet. The objective of this research is to evaluate regression algorithms, [...]

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