Design of a Neurofeedback Training System for Meditation Based on EEG Technology

Meditation is a form of mental training that has therapeutic potential and cognitive benefits that may enhance attention, mental well-being, and neuroplasticity. However, the learning process is not easy because meditators do not receive immediate feedback that lets them know if they are correctly doing the activity. EEG Neurofeedback training is one of the techniques to train brain self-regulation and it has the potential to increase the effectiveness of meditation. However, the benefits greatly differ between subjects with a high percentage of inefficacy. In this work, an EEG Neurofeedback Training System is proposed based on user-centered design methodology to provide real-time performance feedback to meditators to increase levels of attention and relaxation through a visual, sound and smell stimuli interface. Levels of attention and relaxation of nine participants were measured with a mobile Neurosky EEG headset biosensor during meditation practice to analyze the incidence of each type of stimuli during activity. Visual stimuli feedback was able to increase attention levels of 78% of the participants by 11.8% compared to a meditation session without any stimuli. The sound stimuli feedback was able to increase the relaxation levels of 44.4% of the participants by 16% compared to a session without any stimuli. These results might bring new insights for the design of a neurofeedback system interface for meditation. Further research on neurofeedback training interfaces for meditators is suggested to validate these results with more participants.

Evaluation of Load Capacity of Stratified Soils (2 Layers) by Means of Numerical Analytical Comparison

The methods for determining load capacity in stratified soils are numerous and differ in their methods and results. These differences in analysis lead to uncertainty in engineering practices or over-dimensioning of the foundation solution. This study seeks to determine three analytical methods of load capacity in stratified soils (2 layers) for shallow foundations: 1) Imaginary foundation, 2) Average parameter method (APM), and 3) Terzaghi's method to compare their results with those obtained from numerical modeling by means of the finite element method using a widely applied software (Abaqus academic version). Within the methodology developed in the finite element modeling, variables were parameterized (modulus of elasticity, depth of deflection, and displacement-load) and two behavioral laws were evaluated (Elastic and Drucker-Prager). The results that were obtained from the analysis show that when performing numerical modeling using the law of elastic behavior in soils of two layers, exaggerated results are generated with respect to analytical methods. Another important result is that when hard soils are on top of soft soils the results of numerical and analytical methods tend to be similar to each other. Most importantly, the variables that have the greatest influence on the load capacity in soils of one and two layers are the angle of friction, yield stress, and in the case of numerical analysis the constraint displacement (load). In addition, it was observed that for numerical modeling better results are obtained when considering an elastoplastic model, such as Drucker Prager.

Development of an Adaptive Trajectory Tracking Control of Wheeled Mobile Robot

Classical modeling and control methods applied to differential locomotion mobile robots generate mathematical equations that approximate the dynamics of the system and work relatively well when the system is linear in a specific range. However, they may have low accuracy when there are many variations of the dynamics over time or disturbances occur. To solve this problem, we used a recursive least squares (RLS) method that uses a discrete-time structure first-order autoregressive model with exogenous variable (ARX). We design and modify PID adaptive self-adjusting controllers in phase margin and pole allocation. The main contribution of this methodology is that it allows the permanent and online update of the robot model and the parameters of the adaptive self-adjusting PID controllers. In addition, a Lyapunov stability analysis technique was implemented for path and trajectory tracking control, this makes the errors generated in the positioning and orientation of the robot when performing a given task tend asymptotically to zero. The performance of the PID adaptive self-adjusting controllers is measured through the implementation of the criteria of the integral of the error, which allows to determine the controller of best performance, being in this case, the PID adaptive self-adjusting type in pole assignment, allowing the mobile robot greater precision in tracking the trajectories and paths assigned, as well as less mechanical and energy wear, due to its smooth and precise movements.

Use of Convolutional Neural Networks in Smartphones for the Identification of Oral Diseases Using a Small Dataset

Image recognition and processing is a suitable tool in systems using machine learning methods. The addition of smartphones as complementary tools in the health area for diagnosis is a fact nowadays due to the advantages they present. Following the trend of providing tools for diagnosis, this research aimed to develop a prototype mobile application for the identification of oral lesions, including potentially malignant lesions, based on convolutional neural networks, as early detection of indications of possible types of cancer in the oral cavity. A mobile application was developed for the Android operating system that implemented the TensorFlow library and the Mobilenet V2 convolutional neural network model. The training of the model was performed by transfer learning with a database of 500 images distributed in five classes for recognition (Leukoplakia, Herpes Simplex Virus Type 1, Aphthous stomatitis, Nicotinic stomatitis, and No lesion). The 80% of the images were used for training and 20% for validation. It was obtained that the application presented at least 80% precision in the recognition of four class. The f1-score and area under curve metrics were used to evaluate performance. The developed mobile application presented an acceptable performance with metrics higher than 75% for the recognition of three lesions, on the other hand, it yielded an unfavorable performance lower than 70% for identifying nicotinic stomatitis cases with the chosen dataset.

Dynamic Lighting System to Increase the Attention of Design Students in the Classroom

Dynamic lighting is playing a key role in education, by considering the main photometric variables such as the correlated color temperature and the illuminance to increase student’s attention levels inside the classroom. In the case of design students, the project component is fundamental for teaching, where students mainly need to develop activities such as presentation to listen to the teacher instructions, ideation and sketching to propose a solution according to the problem being addressed, and exhibition to present the work that has been done. These activities require specific and adequate lighting conditions to generate a positive impact on the performance of students. This article presents the design of a dynamic lighting system capable of adjusting the correlated color temperature in a range from 2500 K to 6500 K and the illuminance levels in a range from 0 lx to 800 lx to enhance the sustained and fixed attention of design students inside the classroom according to the type of activity that is being developed. The performance of the system was evaluated experimentally by measuring student’s attention inside the ergonomics and usability laboratory by using the Gesell chamber, the Emotiv Epoc EEG Headset with 14 electrodes to measure the brain activity and obtain engagement and focus levels, the eye tracking Tobii glasses, and a protocol to evaluate performance including several surveys and camera observation. In conclusion, the dynamic lighting system can improve the attention of design students by configuring the photometric variables according to the type of activity that is being done.

Constructive Technology Assessment: Systematic Review and Future Study Needs

Engineering, understood as the gathering of scientific and technological knowledge for innovation, creation, advancement and optimization of techniques, as well as a set of useful tools to meet social needs and solve technical problems of both individuals and the community, makes its main actors, engineers, key players in sustainable development and in the creation of alternatives that minimize the negative effects of technology on society. It is in this sense that technology assessment approaches should take importance among those who manage technology development and implementation policies. Generally, the undesirable effects of the intrusion of a new technology are acted upon when they already occur, and technology assessment is intended to anticipate the risk. This paper presents a bibliographic review of technology assessment, its approaches and future study needs. Based on an articulating axis that positions technological change and innovation as an imperative need for social development, an exhaustive review of related articles in specialized databases was carried out. The most important results of this work reveal that the field of technological assessment has been strongly inclined towards the health or sanitary sector; however, research is being developed in central engineering topics such as the development of nanotechnology, robotics, and the handling of big data, where the European model stands out as a reference for technological assessment processes due to its inclusive and democratic nature.

Internet of Things at the Service of Bioconstruction

The Internet of Things (Internet of Things - IoT) approach promotes the interconnection of objects that humans use on a daily basis so that they are administered, controlled and/or monitored through telematic technologies. This paradigm has a wide field of application to support several development schemes in a variety of areas. In the case of construction, there are home automation schemes, but regarding bio-constructions, the myth of incompatibility between digitized systems and “bio” schemes exists. However, bio-constructions require aesthetic, structural, environmental and technological considerations to integrate efficient and friendly systems, contributing to a sustainable environment, generating and regulating the resources of the environment in which they are implemented. In this way, a documentary research process has been developed to determine the degree of applicability of IoT for green buildings. As a result, a set of IoT technologies was identified, which can promote the administration and control of the normatively established agents involved in a bio-construction for living spaces.

Evaluation of Parameters in the Removal of Linear Alkylbenzene Sulfonate Anionic Surfactant Using Electrocoagulation

The objective of the present investigation was to construct an electrocoagulation cell in a batch system and to evaluate its capacity to remove the anionic surfactant of the linear alkylbenzene sulfonate (LAS), which is present in gray water determining the effect of the type of electrodes (Al or Fe), distance between electrodes (1, 1.5 and 2 cm) and voltages (10, 15 and 20 V). The experimental tests were carried out for 20 min. The dimensions of the short wave electrolysis cell built in glass were 26 cm long, 7 cm wide and 12 cm high, with 10 electrodes of 12x6 cm supported by a PVC structure. The concentration of LAS in the solution was determined by employing UV-Vis spectrometry applying the Methylene Blue Active Substances (MBAS) method. A higher removal of 65.55% was obtained when aluminum electrodes were used, and 69.11% with iron electrodes a separation of 1.5 cm and a voltage of 20 V, presenting less change in pH, conductivity, and energy consumption when using the Al3 electrode. When evaluating the effect of time at the best experimental configuration (Al, 1.5 cm, 20 V) it was established that the removal efficiency increased to 75.13% in 60 min. Electrocoagulation with aluminum electrodes is presented as an efficient alternative for the removal of LAS in solution.

Application of Micro-Raman Spectroscopy for the Quantitative Analysis of Vitrinite Reflectance in Medium and High Rank Colombian Coals

The structural changes and the degree of maturity of three Colombian coals from the Santander and Antioquia provinces were studied using a simple and fast curve fitting method of the RBS parameters (the distance between band G and band D), FWHM - G (total width at half the maximum of the G band) and AR (area of the Raman spectrum), obtained by deconvolution and band resolution of the Micro-Raman spectra. The results were compared by morphological and chemical analysis using a SEM scanning electron microscope coupled with a solid state X - ray EDS detector. A percentage of vitrinite reflectance (% Ro) of 4.3 %, 3.8 % and 0.07 % was obtained, a percentage of carbon by EDS analysis of 91.47 %, 87.78 %, 73.4 %, a morphological description by SEM analysis presenting smooth, rough surfaces and rough-lumpy and pore size between 0.7 µm - 0.8 µm, 1.3 µm - 1.5 µm and 0.2 µm - 0.7 µm for the anthracite, semi-anthracite and bituminous samples, respectively. The results showed that based on this method, it was possible to obtain a model that allows to rapidly analyze and characterize the coal. The results compare very well to those of Colombian coals normalized by other methods to improve the precision of the measurement. The modified method, however, did not offer an appropriate fit for the lower range coal and produced extremely low reflectance values. This effect is possibly related with the molecular structure of organic matter in coal or the presence of fluorescence interference.

Numerical Study of a Helical Heat Exchanger for Wort Cooling in the Artisanal Beer Production Process

The objective of the present work is to study the behavior of a helical tube and shell heat exchanger, for the cooling of the wort in the process of making craft beer with cold water, through the methodology of computational fluid dynamics (CFD) by finite volume models for heat exchanger modeling. This by using the ANSYS Fluent software, which allows to understand the behavior of the fluid through equations that describe their movement and behavior, using numerical methods and computational techniques. In the mesh convergence, two methods were used, orthogonality and obliquity, with which it was confirmed that the meshing is ideal in the simulations that were carried out. For the simulation, the k-epsilon turbulence model and the energy model were used. Through various simulations, it was obtained that by varying the mass flow, better results are reducing the outlet temperature, with a variation of 15.16 °C, while varying the inlet temperature of the water, there is just a variation from 2.71 °C to 0.01 °C. Therefore, a significant improvement in the performance of the heat exchanger was found. In the same way, it was confirmed that the number of spikes in the heat exchanger is adequate, since the outlet temperature would not be reached with less spikes.