Statistical analysis and characterization of Landsat 8 satellite images of forest wildfires regions

The increase in the increase in wildfires throughout the world is largely due to increases in temperature and even to an increase in the carelessness of the population in leaving a large amount of the garbage in forests. Using Python and Matlab programs were as working medium. We performed the preprocessing on multispectral images obtained by the Landsat 8 satellite with and without wildfires, which consists of three steps: alignment, characterization and normalization, with the intention of standardization the images. From obtaining the spectral signatures of wildfires and metallic structures, boxes and whiskers diagrams, Shannon entropy and mutual information from the images, there are similar behavior in bands 6, 7, 8, 10 and 11, with more relevant information, taking into account that each image is formed by 11 bands, and in bands 1, 2, 3, 4, 5, 8 and 9 there is less information, SVD decomposition allows to have the best k-rank approximation to the original data matrix. The purpose of this analysis is to reduce the computational complexity.

Enabling experimental greenhouse for high-tech application

This work exposes the conditioning of the zenith greenhouse of the Polytechnic University of Aguascalientes for its conformation as a high-tech entity, through the adaptation of sensors, actuators and a controller, which ensure the supervision of the environmental conditions inside, mainly established by the variables of temperature and humidity. The development and application of a computer graphical interface is presented as an intuitive tool for monitoring and controlling the field devices used, and therefore, the environmental conditions provided or recorded from their activation. Likewise, the use of the open communication standard OPC is demonstrated as an alternative for effective interaction between the LabVIEW software, from which the management interface was developed, and the PLC, used as the system controller. The results achieved provide proof of the adequate operation of the devices adapted in the greenhouse installation, the compilation of the information associated with the performance of their task and the manipulation of their operation or reading, from the graphical interface developed for this purpose.

Comparison of Machine Learning algorithms for the Burnout projection

The present study aims to carry out a projection of student burnout risk detection in young university students using Machine Learning technics (Neuronal Networks, KNN, SVM, Random Forest). A descriptive method was proposed, with a cross-sectional and stratified design in which a sample of 791 students from 4 different universities. This study opens up an innovative field of research by integrating resources from psychological evaluation and virtual resources, in addition, it would allow the generation of preventive actions to treat various implications of Burnout in school dropout and low academic performance through the analysis of information and the generation of algorithms that allow the projection of burnout risk. Due to the combination of experience of professionals in psychology, education and engineering, as well as the contribution to the projection of a syndrome that affects students, makes this article an innovative proposal.

Neural network for crop rotation and soil analysis in a Greenhouse

Currently, Artificial intelligence (AI) is a very important area, the way in which it has revolutionized has allowed it to be an essential part of technological evolution in different sectors of society such as agriculture, it is a fundamental activity in the development of our country, and one of the developing areas is implementation of greenhouse crop. This article describes the use of artificial intelligence for a greenhouse through an Artificial Neural Network (ANN) of the multilayer perceptron type using the BackPropagation algorithm. The main aim is obtain the most optimal type of crop to be sown by means of the crop rotation, which, supported by a data acquisition device through sensors, obtains the values of temperature and humidity of the environment and soil pH, with those data the ANN makes the soil analysis. Through the interfaces of the data analysis module and the measurement module, the data collection process, the calculation and the results produced by the artificial neural network are shown. For this project, the Prototype model was used using the Java programming language.

Heuristic study of a full can implementation on a network of digital controllers based on experimental data

Over time, the CAN (Controller Area Network) communication bus has been implemented in different technological sectors, within which, depending on the application, the bus implementation may change. On the other hand, the design and implementation of digital controls based on experimental data is a well-known topic in the automation industry where the acquisition system is of great importance. In this document, a heuristic study of the behavior of a Full CAN network is reported to implement digital controllers in two interconnected control loops. This study takes into account the access time to the bus and the amount of data sent when observing the response to disturbances. The design of two digital controllers is presented based on the parametric identification of two plants: a DC motor with an electromagnetic brake and a pneumatic levitator. Using PSoC® microcontrollers, a Full CAN network is implemented, where the digital controllers exchange data by randomly accessing the bus. A specially designed interface allows visualizing the speed and amount of data transferred under different operating conditions of the control loops. At the document end, the experimental data obtained are discussed.

A brief description of the GPS architecture

The GPS is a radio-satellite system that allows to the GPS receiver to figure out its tridimensional position on the globe (latitude, longitude, and elevation), as well as allows it to determine its velocity and to make precise timing measurements. This article describes the architecture of the GPS system for the non- specialized reader. The objective is that the lector has an idea of all that happens when using some equipment or application based on this technology.

Hydrodynamic analysis of different impellers used in the stir casting process

In this work, the hydrodynamic behavior of four types of impellers used in the manufacture of metal matrix composites (MMC) through the stir casting process is analyzed, in order to determine which of them is adequate to generate a uniform flow in the metal. Liquid and thereby achieve a uniform distribution of reinforcing particles. The impellers analyzed are the belt type, the vane type, the propeller type and the turbine type. As a first part, the parameters of each one of them were determined to later carry out the modeling in SolidWorks. Some properties of liquid aluminum were also determined, such as density and viscosity for a melting temperature. These characteristics were assigned in the software used. As results, the flow velocities and turbulences that occur with each impeller were obtained, being the propeller-type impeller the one that shows a more uniform distribution in terms of velocities.

Methodology to calculate the density of the magnetic field generated in overhead transmission lines in HVDC applying a two-dimensional analysis of parallel poles above ground level

The growth in the demand for electricity has led to the development and application of technologies that make its means of transport more efficient. Thus, one of these options is the implementation of transmission lines in HVDC. One of important design parameters of these lines is to know their magnetic field distribution, when it is required to calculate it, there is no methodology that can be applied to HVDC transmission lines. The following article presents a methodology that allows obtaining the density of the magnetic field on the corridor of an overhead transmission line. A case study of a 500 kV bipolar line in HVDC is presented, the results obtained are compared using the commercial software Field and corona Effects (FACE), the results obtained are consistent with those obtained from the presented methodology. An analysis of the impact of the transmission line configuration on the magnetic field density is developed, defining the most efficient configuration.

Application of Artificial Intelligence in the prediction of breast cancer survival in Mexican women

In Mexico, the leading cause of death caused by malignant tumors in women is breast cancer and the general survival of five years treated in facilities of the Public Health System is between 75 and 80%. There are applications that determine the survival of patients with breast cancer, based on the use of drugs that are not prescribed in Mexico, so cancer specialists cannot consider the information offered by these programs for decision-making with patients Mexican. This article describes the development of an expert system that, by applying artificial intelligence techniques, allows the evaluation and prediction of patient survival, based on a model generated with data mining techniques. Rules were obtained from the patterns obtained with data collected from patients with breast cancer since 2006. The development of the system is governed by the Knowledge Discovery from Databases (KDD) methodology, supported by the WEKA tool for modeling data mining techniques. There is a data warehouse of 4,773 women with breast cancer provided by two tertiary hospitals in Mexico City: an INCan cohort of 4,300 patients diagnosed from 2006 to 2013 with a median follow-up of 40.5 months of survival and an INCMSZprovided cohort of 473 patients from 2011 to 2018 with a median of 39 months.

Structural and thermoelectric properties of the Pr2Zr2O7 compound

In this research, it is presented a detailed study of the structural and thermoelectric properties of the pyrochlore zirconium Pr2Zr2O7 compound prepared by solid-state reaction (SSR) in air at ambient pressure. The synthesized sample was characterized using powder X-ray diffraction. The thermal stability of the thermoelectric compound (TE) Pr2Zr2O7 was tested by thermogravimetric analysis (TGA) and differential thermal analysis (DTA). Scanning electron microscopy shows that the crystal size varies between 0.69 and 2.81μm. Electrical conductivity (\sigma) of the sample calcined at 1400 °C presented values increase irregularly with the increasing temperature from 0.001 to 0.018 S cm-1 as expected in a semiconductor material. The thermal conductivity is lower than 0.44 - 775 W m-1 K-1 which is quite anomalous in comparison with the thermal conductivity of other oxides.