Paulo Freire´s contributions to the research and critical reading

Los aportes de Paulo Freire a la educación del siglo XXI han conseguido significativa aceptación por su invaluable vigencia. Sus implicaciones en la enseñanza de la investigación y la lectura crítica han sido reconsideradas por la evidente promoción de habilidades cognitivas desde las cuales posibilitarle al sujeto romper con los esquemas impositivos de una educación reproductora. Atendiendo a la relevancia de la obra de Freire, se realiza una revisión de los aspectos significativos en los que dejan entrever a la lectura crítica y a la investigación como herramientas que persiguen la transformación y el desarrollo de habilidades sociales y competencias educativas como herramientas fundamentales el ejercicio de valores democráticos, cuya contribución implícita no es otra que la educación ciudadana necesaria para la práctica de valores tales como: la autonomía, el respeto la tolerancia, la responsabilidad y el reconocimiento del otro como co-constructor y parte integral de su experiencia transformadora. Se exponen los esquemas de investigación y de lectura crítica propuestos por Freire, en un intento por destacar aspectos elementales para la formación académica del presente siglo, como lo son: el desarrollo del pensamiento crítico, la promoción de la indagación como habilidad necesaria para problematizar el mundo y el uso de la criticidad como herramienta al servicio de una recurrente objeción y reflexión sobre la realidad teniendo como elementos determinantes la autonomía y la libertad, como medios necesarios para accionar de manera trascendental y efectiva en su propio contextoPaulo Freire´s contributions to the education of XXI century have attained significant acceptance owing to its invaluable validity. Its implications in the teaching of researching and critical reading have been taking into account because of its promotion of cognitive abilities which allow the individual to achieve break the imposing schemes of a reproductive education. Attending to the relevance of Freire´s work, a revision of the significant aspects in those that hint at critical reading and research as tools that pursue the transformation and improvement of social abilities and educational competences as fundamental tools for exercising democratic values which implicit contribution is the civic education necessary in order to practice values such as: autonomy, respect, tolerance, responsibility and to recognition of the other as a constructor and integral part of her or his transformation experience is done. Freire´s proposal of research schemes and critical reading are exposed in an intent to highlight elemental aspects of academic formation in this present century, such as: the development of critical thinking, the promotion of inquiry as a necessary ability in order to question the world and the use of the critique as a tool to the service of a recurrent objection and reflection about reality keeping as determining elements the autonomy and the freedom as essential means to operate in transcendental and effective ways their own contex

A Microcontroller Based System for Controlling Patient Respiratory Guidelines

The need of making improvements in obtaining (in a non-invasive way) and monitoring the breathing rate parameters in a patient emerges due to (1) the great amount of breathing problems our society suffer, (2) the problems that can be solved, and (3) the methods used so far. Non-specific machines are usually used to carry out these measures or simply calculate the number of inhalations and exhalations within a particular timeframe. These methods lack of effectiveness and precision thus, influencing the capacity of getting a good diagnosis. This proposal focuses on drawing up a technology composed of a mechanism and a user application which allows doctors to obtain the breathing rate parameters in a comfortable and concise way. In addition, such parameters are stored in a database for potential consultation as well as for the medical history of the patients. For this, the current approach takes into account the needs, the capacities, the expectations and the user motivations which have been compiled by means of open interviews, forum discussions, surveys and application uses. In addition, an empirical evaluation has been conducted with a set of volunteers. Results indicate that the proposed technology may reduce cost and improve the reliability of the diagnosis.Ministerio de Economía y Competitividad TIN2016-76956-C3-2-RMinisterio de Economía y Competitividad TIN2015-71938-RED

Deep Neural Networks for the Recognition and Classification of Heart Murmurs Using Neuromorphic Auditory Sensors

Auscultation is one of the most used techniques for detecting cardiovascular diseases, which is one of the main causes of death in the world. Heart murmurs are the most common abnormal finding when a patient visits the physician for auscultation. These heart sounds can either be innocent, which are harmless, or abnormal, which may be a sign of a more serious heart condition. However, the accuracy rate of primary care physicians and expert cardiologists when auscultating is not good enough to avoid most of both type-I (healthy patients are sent for echocardiogram) and type-II (pathological patients are sent home without medication or treatment) errors made. In this paper, the authors present a novel convolutional neural network based tool for classifying between healthy people and pathological patients using a neuromorphic auditory sensor for FPGA that is able to decompose the audio into frequency bands in real time. For this purpose, different networks have been trained with the heart murmur information contained in heart sound recordings obtained from nine different heart sound databases sourced from multiple research groups. These samples are segmented and preprocessed using the neuromorphic auditory sensor to decompose their audio information into frequency bands and, after that, sonogram images with the same size are generated. These images have been used to train and test different convolutional neural network architectures. The best results have been obtained with a modified version of the AlexNet model, achieving 97% accuracy (specificity: 95.12%, sensitivity: 93.20%, PhysioNet/CinC Challenge 2016 score: 0.9416). This tool could aid cardiologists and primary care physicians in the auscultation process, improving the decision making task and reducing type-I and type-II errors.Ministerio de Economía y Competitividad TEC2016-77785-

De los Aspectos Sociales del Desarrollo Económico a la Teoría de la Dependencia: Sobre la gestación de un pensamiento social propio en Latinoamérica

In the epistemological context of theory transfer and scientific exchanges, the aim of this paper is to indicate the presence of Weberian categories and ideas on dependency theory formulated by Fernando Cardoso and Enzo Faletto. Here we see how the construction of this paradigm was based on some issues, concepts, approaches and orientations of the Weberian research program formulated by José Medina Echavarría to explain Latin American development. We will also consider the contexts of enunciation and reception theories, allowing us to talk about the “sociological school” that was formed in the Social Planning Division of ILPES in mid-sixties, crucial for understanding the history of sociology in Latin America.En el contexto de la discusión epistemológica sobre el examen de las transferencias y los intercambios científicos de las teorías, el objetivo de este artículo es señalar la presencia de categorías e ideas weberianas en la teoría de la dependencia formulada por Fernando Cardoso y Enzo Faletto. Aquí veremos cómo la construcción de este paradigma se sustentó en algunos temas, conceptos, enfoques y orientaciones del programa de investigación weberiano formulado por José Medina Echavarría para explicar el desarrollo latinoamericano. También tendremos en cuenta los contextos de enunciación y de recepción de las teorías, lo que nos permitirá hablar de la “escuela sociológica” que se formó en la División de Planificación Social del ILPES a mitad de los años 60, decisiva para comprender la historia de la sociología en América Latina

NAVIS: Neuromorphic Auditory VISualizer Tool

This software presents diverse utilities to perform the first post-processing layer taking the neuromorphic auditory sensors (NAS) information. The used NAS implements in FPGA a cascade filters architecture, imitating the behavior of the basilar membrane and inner hair cells and working with the sound information decomposed into its frequency components as spike streams. The well-known neuromorphic hardware interface Address-Event-Representation (AER) is used to propagate auditory information out of the NAS, emulating the auditory vestibular nerve. Using the information packetized into aedat files, which are generated through the jAER software plus an AER to USB computer interface, NAVIS implements a set of graphs that allows to represent the auditory information as cochleograms, histograms, sonograms, etc. It can also split the auditory information into different sets depending on the activity level of the spike streams. The main contribution of this software tool is that it allows complex audio post-processing treatments and representations, which is a novelty for spike-based systems in the neuromorphic community and it will help neuromorphic engineers to build sets for training spiking neural networks (SNN).Ministerio de Economía y Competitividad TEC2012-37868-C04-0

Wearable Fall Detector Using Recurrent Neural Networks

Falls have become a relevant public health issue due to their high prevalence and negative effects in elderly people. Wearable fall detector devices allow the implementation of continuous and ubiquitous monitoring systems. The effectiveness for analyzing temporal signals with low energy consumption is one of the most relevant characteristics of these devices. Recurrent neural networks (RNNs) have demonstrated a great accuracy in some problems that require analyzing sequential inputs. However, getting appropriate response times in low power microcontrollers remains a difficult task due to their limited hardware resources. This work shows a feasibility study about using RNN-based deep learning models to detect both falls and falls’ risks in real time using accelerometer signals. The effectiveness of four different architectures was analyzed using the SisFall dataset at different frequencies. The resulting models were integrated into two different embedded systems to analyze the execution times and changes in the model effectiveness. Finally, a study of power consumption was carried out. A sensitivity of 88.2% and a specificity of 96.4% was obtained. The simplest models reached inference times lower than 34 ms, which implies the capability to detect fall events in real-time with high energy efficiency. This suggests that RNN models provide an effective method that can be implemented in low power microcontrollers for the creation of autonomous wearable fall detection systems in real-time

A Sensor Fusion Horse Gait Classification by a Spiking Neural Network on SpiNNaker

The study and monitoring of the behavior of wildlife has always been a subject of great interest. Although many systems can track animal positions using GPS systems, the behavior classification is not a common task. For this work, a multi-sensory wearable device has been designed and implemented to be used in the Doñana National Park in order to control and monitor wild and semiwild life animals. The data obtained with these sensors is processed using a Spiking Neural Network (SNN), with Address-Event-Representation (AER) coding, and it is classified between some fixed activity behaviors. This works presents the full infrastructure deployed in Doñana to collect the data, the wearable device, the SNN implementation in SpiNNaker and the classification results.Ministerio de Economía y Competitividad TEC2012-37868-C04-02Junta de Andalucía P12-TIC-130