Tecnura

15-28

Authors: Miller Gómez-Mora, Leonardo Flórez-Valencia

Abstract Modeling objects, their properties and relations is an important topic in computer science. In this sense, this research contributes to the framework of heterogeneous solid modeling, as well as the popular and intricate study of implicit solid representation. The approach presented here is broad and generic, but this article will focus on bio-CAD models, alluding to the existing extension and implementation in other fields. The overall aim of this work is to demonstrate that solid models of heterogeneous object can be built implicitly. This is shown to have promise in practical applications from biomedical computing to computer animation and engineering. The approach adopted here is based on the observation that current solid models cannot intrinsically represent multiphase geometric information along with the attribute information. This makes necessary to explore new modeling techniques in order to represent real-world objects. The availability of such modeling techniques remains central to the design, analysis, and fabrication of heterogeneous objects

39-48

Authors: Luis Carlos Ruiz Cárdenas, Darío Amaya Hurtado, Robinson Jiménez Moreno

The continued development of computational tools offers the possibility to execute processes with the ability to carry out activities more efficiently, exactness and precision. Between these tools there is the neural architecture, Deep Belief Network (DBN), designed to collaborate in the development of prediction technics to find information that allows to study the behavior of the natural phenomena, such as the solar insolation. This paper presents the obtained results when using the DBN architecture for solar insolation prediction, simulated through the programming tool Visual Studio C#, showing the deep level that this architecture has, how it affects the number of layers and neurons per layer in the training and the results to predict the desired values in 2014, with errors close to 2% and faster to training, respect to errors obtained through conventional methods for neural training, which are about 5% and take long periods of training

57-70

Authors: Francisco Javier Moreno Arboleda, John Freddy Duitama Muñoz, Luis Fernando Montoya Gómez

Current volumes of data require automated methods for knowledge extraction. In particular, text mining deals with extracting knowledge from texts. In this paper we propose two algorithms to determine, from the lyrics of its songs, the emotional tendency of an album. We follow a hierarchical approach: the emotional categories to classify the albums group the emotional subcategories of the songs. This is reasonable because a song tends to be oriented to a specific emotional (sub) category. In this way, the emotional category of an album is a weighting of the emotional subcategories of its songs. This weighting can be customized by the musical analyst, which allows incorporating a subjective element in our proposal. Through a series of experiments we evaluated our algorithms. Although it is necessary to experiment with more data, our results show the expediency, consistency, and usefulness of our proposed algorithms.

85-96

Authors: Julio Eduardo Beltrán Vargas

A dynamic simulation model is presented to explain the general behavior of the primary production of phytoplankton in the wetland Jaboque–Bogota, Colombia, in three sections with differential physical and chemical characteristics. The model takes into account the physicochemical variables, the basin area, depth, annual rainfall, water temperature, pH and concentration of chlorophyll _a. The dynamic modeling is based on differential equations and the Euler integration method is used, the modeling was developed using Stella 9.1® computer program. The model allows quantifying the primary production of phytoplankton in wetland Jaboque from chlorophyll _a monthly average concentration for each section. The results of the Ppf modeling show that Ppf concentration variations in each section of the wetland follow a reverse pattern to the bimodal behavior of precipitation. A high degree of correspondence between the values of chlorophyll_a Ppf field and modeled in the following manner r 2 = 0.86 for the first section and r2 = 0.86 and r2 = 0.79 for the remaining sections was found. Error determination was 0,57 relative to the first section and 0,35; 0,46, indicating that the results are not overstated. The model shows in general terms the functional aspects of behavior Ppf and its relation to the process of eutrophication, and it allows recommendations for the management and restoration of wetlands

107-118

Authors: María Camila García Vaca, César Augusto García Ubaque, Juan Sebastián de Plaza Solórzano

Dye wastewater is considered pollutant because it may contain polyaromatic substances known as carcinogenic, mutagenic and teratogenic to a variety of living species. Within the many treatment methods, the electrocoagulation/electroflotation method has been widely studied and it is known to be very effective. However, there is currently no industrial use of it in Colombia, and it is not a priority in academic investigation either. Because of this, this work is an exploratory study of the treatment of printing dye wastewater through the electrocoagulation/electroflotation method. A 22 with a central point experimental design was applied. Removal percentage of OCD (Oxygen Chemical Demand) of the wastewater was obtain between 10,43% and 50,93%. Nevertheless, results show that decontamination through this treatment method may be reversible, and the expected incidence of factors is not observed.