Tecnura

15-28

Authors: Hernán Darío Vargas Cardona, Mauricio A. Álvarez, Álvaro Orozco Gutiérrez

Identification of brain signals from microelectrode recordings (MER) is a key procedure during deep brain stimulation (DBS) applied in Parkinson’s disease patients. The main purpose of this research work is to identify with high accuracy a brain structure called subthalamic nucleus (STN), since it is the target structure where the DBS achieves the best therapeutic results. To do this, we present an approach for optimal representation of MER signals through method of frames (MOF). We obtain coefficients that minimize the Euclidean norm of order two. From optimal coefficients, we extract some features from signals combining the wavelet packet and cosine dictionaries. For a comparison frame with the state of the art, we also process the signals using the discrete wavelet transform (DWT) with several mother functions. We validate the proposed methodology in a real data base. We employ simple supervised machine learning algorithms, such as the K-Nearest Neighbors classifier (K-NN), a linear Bayesian classifier (LDC) and a quadratic Bayesian classifier (QDC). Classification results obtained with the proposed method improve significantly the performance of the DWT. We achieve a positive identification of the STN superior to 97,6%. Identification outcomes achieved by the MOF are highly accurate, as we can potentially get a false positive rate of less than 2% during the DBS

41-52

Authors: Lina Marcela Hoyos Palacio, Edwin Espinel Blanco, Yeixon Quintero Martínez

Quartz is a silicate, available in a variety of geological conditions, it appears in many igneous and metamorphic rocks, and it is a major constituent of granite pegmatite. Among minerals, quartz is the closest to a pure chemical compound and has constant physical properties, and due to their applications and uses it becomes a material that contributes to improving the living conditions of man. For that reason, it is necessary to know their properties to propose optimal applications. This work presents the physicochemical characterization of quartz in the municipality of La Playa de Belen (North Santander Department, Colombia) using elementary techniques through studies to establish the physical and chemical properties of this mineral. Techniques such as scanning electron microscopy (SEM) with disperse energy analyzer (EDS), X-ray diffraction (XRD), thermogravimetric (TGA) and differential thermogravimetric analysis (DTG) were used. The compositional, chemical and morphological characteristics are obtained, and the thermal behavior is evaluated according to the composition.

65-74

Authors: Alexander Armesto Arenas, Wilson Angarita, Ramón Lobo Jácome

This work evaluated the electromagnetic effects on germination of corn Zea mays, seed usually cultivated in the municipality of Ocaña (North Santander, Colombia), whose common name is described as pullita corn. Three treatments were carried, one with 945 MHz (Megahertz frequencies), other with 440 MHz and a witness one, all of them with three repetitions. Such wave emissions were made with half wave antennas, located at a distance of 37 cm from the substrate to which the seeds were planted. The electromagnetic radiation emitted was 24 hours a day, for 8 days and the results showed statistically significant differences; observing after those eight days a germination rate of 92%, 80% and 50%, and past 15 days 98%, 95% and 84%, for treatments with wave emissions of 945 MHz, 440 MHz and the witness ones, respectively. Likewise, low percentage of ash was observed in comparison to witnesses, having results of 12,69%, 16,17% and 18,45%. In terms of height, it was observed in the early days, a gain in length for plants subjected to the highest frequencies, followed by the lowest frequency and the witness. For the last day a greater height was noted for lower frequency, followed by the highest frequency and the witness.

89-100

Authors: Claudia Jeanneth Becerra Cortés Sergio Gonzalo Jiménez Vargas, Fabio A. González, Alexander Gelbukh

Recommender systems allow users to have a personalized view of large sets of products, relieving the overload problem of choice in e-commerce sites. Usually recommendations are obtained using the technique called “collaborative filtering”. This technique filters the products the users wish, from those they don´t want, inferring affinities between products and users in a space of abstract features, also called a latent space. These techniques have proven to be of great predictive value, but these created profiles are neither understandable, nor editable for users, enclosing users in a bubble, in which they only receive collaborative recommendations conditioned by their historical behaviors. In our work we propose a method to build user profiles, defined in interpretable spaces, or defined in terms of collaborative tags or keywords (i.e. words extracted from the descriptions of the product), which can be interpreted and modified by users. The model proposed generate linear profiles, whose coefficients, positive or negative, reflect the user’s affinity towards tags or keywords, according to the space selected. To test our hypothesis, we used the dataset of research in movie recommender systems from the University of Minnesota: Movielens. The results show that the predictive ability of the model, based on interpretable user profiles, is comparable to those models based on abstract profiles with the added benefit that these profiles are interpretable

115-126

Authors: Omar Iván Trejos Buriticá

This article shows a simple, parametric and effective methodology to solve the big problem of the Engineering Program’s students when they are in the last semesters of his careers: the formulation of the preproject and, from there, the design of the activities’ schedule to finish his studies successfully. For long, the author has been teacher, adviser and accompanist for a lot of students and he has found a simple methodology to formulate a preproject in an easy way. This is the target of this article.

141-158

Authors: Carlos Alberto Vera Romero, Jhon Erickson Barbosa Jaimes, Diana Carolina Pabón González

This article presents information on the configuration of the wireless communication through the Institute of Electrical and Electronics Engineers IEEE 802.4.15 and ZigBee® protocols, using RF modules XBee-PRO® ZB S2B Digi International Inc. The design phase of the wireless link using the star topology is shown; it is also characterized the parameters for the configuration of radio frequency devices that enable the communication for the measurement of parameters of some environmental variables, by coupling various sensors using the XBee shield for Arduino Mega 2560 microcontroller board making up four nodes, allowing each one to measure four variables: environment temperature, relative humidity, precipitation and global solar radiation. In turn, the coordinator and Arduino Ethernet card allows to observing the data in real time through an application on the local area network