Search results for: Gustavo T. Ruiz
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 168

Search results for: Gustavo T. Ruiz

168 Prediction of the Crustal Deformation of Volcán - Nevado Del RUíz in the Year 2020 Using Tropomi Tropospheric Information, Dinsar Technique, and Neural Networks

Authors: Juan Sebastián Hernández

Abstract:

The Nevado del Ruíz volcano, located between the limits of the Departments of Caldas and Tolima in Colombia, presented an unstable behaviour in the course of the year 2020, this volcanic activity led to secondary effects on the crust, which is why the prediction of deformations becomes the task of geoscientists. In the course of this article, the use of tropospheric variables such as evapotranspiration, UV aerosol index, carbon monoxide, nitrogen dioxide, methane, surface temperature, among others, is used to train a set of neural networks that can predict the behaviour of the resulting phase of an unrolled interferogram with the DInSAR technique, whose main objective is to identify and characterise the behaviour of the crust based on the environmental conditions. For this purpose, variables were collected, a generalised linear model was created, and a set of neural networks was created. After the training of the network, validation was carried out with the test data, giving an MSE of 0.17598 and an associated r-squared of approximately 0.88454. The resulting model provided a dataset with good thematic accuracy, reflecting the behaviour of the volcano in 2020, given a set of environmental characteristics.

Keywords: crustal deformation, Tropomi, neural networks (ANN), volcanic activity, DInSAR

Procedia PDF Downloads 104
167 About the Effect of Temperature and Heating Rate on the Pyrolysis of Lignocellulosic Biomass Waste

Authors: María del Carmen Recio-Ruiz, Ramiro Ruiz-Rosas, Juana María Rosas, José Rodríguez-Mirasol, Tomás Cordero

Abstract:

At the present time, conventional fossil fuels show environmental and sustainability disadvantages with regard to renewables energies. Producing energy and chemicals from biomass is an interesting alternative for substitution of conventional fossil sources with a renewable feedstock while enabling zero net greenhouse gases emissions. Pyrolysis is a well-known process to produce fuels and chemicals from biomass. In this work, conventional and fast pyrolysis of different agro-industrial residues (almond shells, hemp hurds, olive stones, and Kraft lignin) was studied. Both processes were carried out in a fixed bed reactor under nitrogen flow and using different operating conditions to analyze the influence of temperature (400-800 ºC) and heating rate (10 and 20 ºC/minfor conventional pyrolysis and 50 ºC/s for fast pyrolysis)on the yields, products distribution, and composition of the different fractions. The results showed that for both conventional and fast pyrolysis, the solid fraction yield decreased with temperature, while the liquid and gas fractions increased. In the case of the fast pyrolysis, a higher content of liquid fraction than that obtained in conventional pyrolysis could be observed due to cracking reactions occur at a lesser extent. With respect to the composition of de non-condensable fraction, the main gases obtained were CO, CO₂ (mainly at low temperatures), CH₄, and H₂ (mainly at high temperatures).

Keywords: bio-oil, biomass, conventional pyrolysis, fast pyrolysis

Procedia PDF Downloads 189
166 Yields and Composition of the Gas, Liquid and Solid Fractions Obtained by Conventional Pyrolysis of Different Lignocellulosic Biomass Residues

Authors: María del Carmen Recio-Ruiz, Ramiro Ruiz-Rosas, Juana María Rosas, José Rodríguez-Mirasol, Tomás Cordero

Abstract:

Nowadays, fossil resources are main precursors for fuel production. Due to their contribution to the greenhouse effect and their future depletion, there is a constant search for environmentally friendly feedstock alternatives. Biomass residues constitute an interesting replacement for fossil resources because of their zero net CO₂ emissions. One of the main routes to convert biomass into energy and chemicals is pyrolysis. In this work, conventional pyrolysis of different biomass residues highly available such as almond shells, hemp hurds, olive stones, and Kraft lignin, was studied. In a typical experiment, the biomass was crushed and loaded into a fixed bed reactor under continuous nitrogen flow. The influence of temperature (400-800 ºC) and heating rate (10 and 20 ºC/min) on the pyrolysis yield and composition of the different fractions has been studied. In every case, the mass yields revealed that the solid fraction decreased with temperature, while liquid and gas fractions increased due to depolymerization and cracking reactions at high temperatures. The composition of every pyrolysis fraction was studied in detail. The results showed that the composition of the gas fraction was mainly CO, CO₂ when working at low temperatures, and mostly CH₄ and H₂at high temperatures. The solid fraction developed an incipient microporosity, with narrow micropore volume of 0.21 cm³/g. Regarding the liquid fraction, pyrolysis of almond shell, hemp hurds, and olive stones led mainly to a high content in aliphatic acids and furans, due to the high volatile matter content of these biomass (>74 %wt.), and phenols to a lesser degree, which were formed due to the degradation of lignin at higher temperatures. However, when Kraft lignin was used as bio-oil precursor, the presence of phenols was very prominent, and aliphatic compounds were also detected in a lesser extent.

Keywords: Bio-oil, biomass, conventional pyrolysis, lignocellulosic

Procedia PDF Downloads 134
165 Learning the Dynamics of Articulated Tracked Vehicles

Authors: Mario Gianni, Manuel A. Ruiz Garcia, Fiora Pirri

Abstract:

In this work, we present a Bayesian non-parametric approach to model the motion control of ATVs. The motion control model is based on a Dirichlet Process-Gaussian Process (DP-GP) mixture model. The DP-GP mixture model provides a flexible representation of patterns of control manoeuvres along trajectories of different lengths and discretizations. The model also estimates the number of patterns, sufficient for modeling the dynamics of the ATV.

Keywords: Dirichlet processes, gaussian mixture models, learning motion patterns, tracked robots for urban search and rescue

Procedia PDF Downloads 450
164 Particle Size Distribution Estimation of a Mixture of Regular and Irregular Sized Particles Using Acoustic Emissions

Authors: Ejay Nsugbe, Andrew Starr, Ian Jennions, Cristobal Ruiz-Carcel

Abstract:

This works investigates the possibility of using Acoustic Emissions (AE) to estimate the Particle Size Distribution (PSD) of a mixture of particles that comprise of particles of different densities and geometry. The experiments carried out involved the mixture of a set of glass and polyethylene particles that ranged from 150-212 microns and 150-250 microns respectively and an experimental rig that allowed the free fall of a continuous stream of particles on a target plate which the AE sensor was placed. By using a time domain based multiple threshold method, it was observed that the PSD of the particles in the mixture could be estimated.

Keywords: acoustic emissions, particle sizing, process monitoring, signal processing

Procedia PDF Downloads 353
163 Health Status Monitoring of COVID-19 Patient's through Blood Tests and Naïve-Bayes

Authors: Carlos Arias-Alcaide, Cristina Soguero-Ruiz, Paloma Santos-Álvarez, Adrián García-Romero, Inmaculada Mora-Jiménez

Abstract:

Analysing clinical data with computers in such a way that have an impact on the practitioners’ workflow is a challenge nowadays. This paper provides a first approach for monitoring the health status of COVID-19 patients through the use of some biomarkers (blood tests) and the simplest Naïve Bayes classifier. Data of two Spanish hospitals were considered, showing the potential of our approach to estimate reasonable posterior probabilities even some days before the event.

Keywords: Bayesian model, blood biomarkers, classification, health tracing, machine learning, posterior probability

Procedia PDF Downloads 233
162 Instructional Design Strategy Based on Stories with Interactive Resources for Learning English in Preschool

Authors: Vicario Marina, Ruiz Elena, Peredo Ruben, Bustos Eduardo

Abstract:

the development group of Educational Computing of the National Polytechnic (IPN) in Mexico has been developing interactive resources at preschool level in an effort to improve learning in the Child Development Centers (CENDI). This work describes both a didactic architecture and a strategy for teaching English with digital stories using interactive resources available through a Web repository designed to be used in mobile platforms. It will be accessible initially to 500 children and worldwide by the end of 2015.

Keywords: instructional design, interactive resources, digital educational resources, story based English teaching, preschool education

Procedia PDF Downloads 475
161 Evaluation of Corrosion by Impedance Spectroscopy of Embedded Steel in an Alternative Concrete Exposed a Chloride Ion

Authors: E. Ruíz, W. Aperador

Abstract:

In this article evaluates the protective effect of the concrete alternative obtained from the fly ash and iron and steel slag mixed in binary form and were placed on structural steel ASTM A 706. The study was conducted comparatively with specimens exposed to natural conditions free of chloride ion. The effect of chloride ion on the specimens was generated of form accelerated under controlled conditions (3.5% NaCl and 25 ° C temperature). The Impedance data were acquired over a range of 1 mHz to 100 kHz. At frequencies high is found the response of the interface means of the exposure-concrete and to frequency low the response of the interface corresponding to concrete-steel.

Keywords: alternative concrete, corrosion, alkaline activation, impedance spectroscopy

Procedia PDF Downloads 359
160 Effect of Inclusions in the Ultrasonic Fatigue Endurance of Maraging 300 Steel

Authors: G. M. Dominguez Almaraz, J. A. Ruiz Vilchez, M. A. Sanchez Miranda

Abstract:

Ultrasonic fatigue tests have been carried out in the maraging 300 steel. Experimental results show that fatigue endurance under this modality of testing is closely related to the nature and geometrical properties of inclusions present in this alloy. A model was proposed to correlate the ultrasonic fatigue endurance with the nature and geometrical properties of the crack initiation inclusion. Scanning Electron Microscopy analyses were obtained on the fracture surfaces, in order to assess the crack initiation inclusion and to introduce these parameters in the proposed model, with good agreement for the fatigue life prediction.

Keywords: inclusions, ultrasonic fatigue, maraging 300 steel, crack initiation

Procedia PDF Downloads 215
159 Association between G2677T/A MDR1 Polymorphism with the Clinical Response to Disease Modifying Anti-Rheumatic Drugs in Rheumatoid Arthritis

Authors: Alan Ruiz-Padilla, Brando Villalobos-Villalobos, Yeniley Ruiz-Noa, Claudia Mendoza-Macías, Claudia Palafox-Sánchez, Miguel Marín-Rosales, Álvaro Cruz, Rubén Rangel-Salazar

Abstract:

Introduction: In patients with rheumatoid arthritis, resistance or poor response to disease modifying antirheumatic drugs (DMARD) may be a reflection of the increase in g-P. The expression of g-P may be important in mediating the effluence of DMARD from the cell. In addition, P-glycoprotein is involved in the transport of cytokines, IL-1, IL-2 and IL-4, from normal lymphocytes activated to the surrounding extracellular matrix, thus influencing the activity of RA. The involvement of P-glycoprotein in the transmembrane transport of cytokines can serve as a modulator of the efficacy of DMARD. It was shown that a number of lymphocytes with glycoprotein P activity is increased in patients with RA; therefore, P-glycoprotein expression could be related to the activity of RA and could be a predictor of poor response to therapy. Objective: To evaluate in RA patients, if the G2677T/A MDR1 polymorphisms is associated with differences in the rate of therapeutic response to disease-modifying antirheumatic agents in patients with rheumatoid arthritis. Material and Methods: A prospective cohort study was conducted. Fifty seven patients with RA were included. They had an active disease according to DAS-28 (score >3.2). We excluded patients receiving biological agents. All the patients were followed during 6 months in order to identify the rate of therapeutic response according to the American College of Rheumatology (ACR) criteria. At the baseline peripheral blood samples were taken in order to identify the G2677T/A MDR1 polymorphisms using PCR- Specific allele. The fragment was identified by electrophoresis in polyacrylamide gels stained with ethidium bromide. For statistical analysis, the genotypic and allelic frequencies of MDR1 gene polymorphism between responders and non-responders were determined. Chi-square tests as well as, relative risks with 95% confidence intervals (95%CI) were computed to identify differences in the risk for achieving therapeutic response. Results: RA patients had a mean age of 47.33 ± 12.52 years, 87.7% were women with a mean for DAS-28 score of 6.45 ± 1.12. At the 6 months, the rate of therapeutic response was 68.7 %. The observed genotype frequencies were: for G/G 40%, T/T 32%, A/A 19%, G/T 7% and for A/A genotype 2%. Patients with G allele developed at 6 months of treatment, higher rate for therapeutic response assessed by ACR20 compared to patients with others alleles (p=0.039). Conclusions: Patients with G allele of the - G2677T/A MDR1 polymorphisms had a higher rate of therapeutic response at 6 months with DMARD. These preliminary data support the requirement for a deep evaluation of these and other genotypes as factors that may influence the therapeutic response in RA.

Keywords: pharmacogenetics, MDR1, P-glycoprotein, therapeutic response, rheumatoid arthritis

Procedia PDF Downloads 209
158 Accuracy of a 3D-Printed Polymer Model for Producing Casting Mold

Authors: Ariangelo Hauer Dias Filho, Gustavo Antoniácomi de Carvalho, Benjamim de Melo Carvalho

Abstract:

The work´s purpose was to evaluate the possibility of manufacturing casting tools utilizing Fused Filament Fabrication, a 3D printing technique, without any post-processing on the printed part. Taguchi Orthogonal array was used to evaluate the influence of extrusion temperature, bed temperature, layer height, and infill on the dimensional accuracy of a 3D-Printed Polymer Model. A Zeiss T-SCAN CS 3D Scanner was used for dimensional evaluation of the printed parts within the limit of ±0,2 mm. The mold capabilities were tested with the printed model to check how it would interact with the green sand. With little adjustments in the 3D model, it was possible to produce rapid tools without the need for post-processing for iron casting. The results are important for reducing time and cost in the development of such tools.

Keywords: additive manufacturing, Taguchi method, rapid tooling, fused filament fabrication, casting mold

Procedia PDF Downloads 145
157 Optimization of Maritime Platform Transport Problem of Solid, Special and Dangerous Waste

Authors: Ocotlán Díaz-Parra, Jorge A. Ruiz-Vanoye, Alejandro Fuentes-Penna, Beatriz Bernabe-Loranca, Patricia Ambrocio-Cruz, José J. Hernández-Flores

Abstract:

The Maritime Platform Transport Problem of Solid, Special and Dangerous Waste consist of to minimize the monetary value of carry different types of waste from one location to another location using ships. We offer a novel mathematical, the characterization of the problem and the use CPLEX to find the optimal values to solve the Solid, Special and Hazardous Waste Transportation Problem of offshore platforms instances of Mexican state-owned petroleum company (PEMEX). The set of instances used are WTPLib real instances and the tool CPLEX solver to solve the MPTPSSDW problem.

Keywords: oil platform, transport problem, waste, solid waste

Procedia PDF Downloads 472
156 Exploring Photoreactive Coordination Compounds: The Role of Re Complexes in Ibuprofen Photosensitized Decomposition

Authors: Emilia R. Serrano, Pedro M. David Gara, Gustavo T. Ruiz

Abstract:

Water pollution is an urgent global issue, impacting not only the availability and quality of water for consumption but also the health and lifestyle of populations worldwide. One growing concern is the presence of pharmaceuticals in natural waters, which pose significant risks to both the environment and public health. These substances, even in trace amounts, can cause physiological effects that are often undetected due to insufficient monitoring. Among the many compounds of concern are caffeine, paracetamol, ibuprofen, and enrofloxacin, all of which have been detected in rivers across Argentina. These substances are part of a broader class of emerging pollutants (EPs), which also include chemicals from household and personal care products. The environmental dangers posed by EPs are substantial, particularly their effects on the biotic components of aquatic ecosystems. Bioaccumulation of these pollutants has been observed in various aquatic organisms, raising concerns about long-term ecological impacts. Additionally, continuous exposure to EPs has been linked to a range of harmful effects, including cytotoxicity, genotoxicity, apoptosis, and functional impairments in living organisms. More alarmingly, the prevalence of antibiotics in the environment contributes to the growing issue of antibiotic resistance, creating a significant global health crisis. Unfortunately, these pollutants often go unnoticed during routine water quality assessments, which underscores the need for innovative approaches to mitigate their impact. One promising solution lies in the use of transition metal coordination compounds as photosensitizers, which can help degrade EPs through photocatalytic processes. Transition metals like rhenium (Re) form stable complexes with organic ligands, and these Re(I) complexes (ReC) exhibit tunable photophysical and photochemical properties based on metal-ligand combinations. By focusing on bi-azinic ligands, we aim to optimize the behavior of Re(I) complexes, enhancing their efficiency as photosensitizers in the degradation of harmful pollutants. ReC molecules are of particular interest due to their excellent thermal and photochemical stability, as well as their ability to facilitate electron transfer and redox reactions. When activated by light, these complexes generate reactive species capable of breaking down toxic pollutants into less harmful byproducts. This photo-driven degradation process offers a sustainable and environmentally friendly approach to removing EPs from natural waters, reducing their impact on aquatic life and human health. The unique properties of ReC, such as their excited-state behavior and efficient energy transfer, make them highly suitable for photocatalytic applications aimed at mitigating water pollution. The methodology employed in this research integrates several techniques to explore the effectiveness of ReC in pollutant degradation. These include optoacoustic measurements, absorption and fluorescence spectroscopy, laser flash photolysis, and the use of a phoreactor to simulate real-world conditions. Our recent results showed that a ferrocene-rhenium complex with phenanthroline enhanced the photodegradation of ibuprofen under oxidizing conditions. While promising, further studies, such as HPLC, are needed to determine the exact nature of the degradation products and assess the efficiency of the process. Through this approach, this research aims to contribute to the development of efficient, green technologies for degrading emerging pollutants in natural waters.

Keywords: Rhenium complexes, photosensitizers, emerging pollutants, Ibuprofen

Procedia PDF Downloads 0
155 Material Failure Process Simulation by Improved Finite Elements with Embedded Discontinuities

Authors: Gelacio Juárez-Luna, Gustavo Ayala, Jaime Retama-Velasco

Abstract:

This paper shows the advantages of the material failure process simulation by improve finite elements with embedded discontinuities, using a new definition of traction vector, dependent on the discontinuity length and the angle. Particularly, two families of this kind of elements are compared: kinematically optimal symmetric and statically and kinematically optimal non-symmetric. The constitutive model to describe the behavior of the material in the symmetric formulation is a traction-displacement jump relationship equipped with softening after reaching the failure surface. To show the validity of this symmetric formulation, representative numerical examples illustrating the performance of the proposed formulation are presented. It is shown that the non-symmetric family may over or underestimate the energy required to create a discontinuity, as this effect is related with the total length of the discontinuity, fact that is not noticed when the discontinuity path is a straight line.

Keywords: variational formulation, strong discontinuity, embedded discontinuities, strain localization

Procedia PDF Downloads 783
154 A Neuro-Automata Decision Support System for the Control of Late Blight in Tomato Crops

Authors: Gizelle K. Vianna, Gustavo S. Oliveira, Gabriel V. Cunha

Abstract:

The use of decision support systems in agriculture may help monitoring large fields of crops by automatically detecting the symptoms of foliage diseases. In our work, we designed and implemented a decision support system for small tomatoes producers. This work investigates ways to recognize the late blight disease from the analysis of digital images of tomatoes, using a pair of multilayer perceptron neural networks. The networks outputs are used to generate repainted tomato images in which the injuries on the plant are highlighted, and to calculate the damage level of each plant. Those levels are then used to construct a situation map of a farm where a cellular automata simulates the outbreak evolution over the fields. The simulator can test different pesticides actions, helping in the decision on when to start the spraying and in the analysis of losses and gains of each choice of action.

Keywords: artificial neural networks, cellular automata, decision support system, pattern recognition

Procedia PDF Downloads 456
153 Lean Healthcare: Barriers and Enablers in the Colombian Context

Authors: Erika Ruiz, Nestor Ortiz

Abstract:

Lean philosophy has evolved over time and has been implemented both in manufacturing and services, more recently lean has been integrated in the companies of the health sector. Currently it is important to understand the successful way to implement this philosophy and try to identify barriers and enablers to the sustainability of lean healthcare. The main purpose of this research is to identify the barriers and enablers in the implementation of Lean Healthcare based on case studies of Colombian healthcare centers. In order to do so, we conducted semi-structured interviews based on a maturity model. The main results indicate that the success of Lean implementation depends on its adaptation to contextual factors. In addition, in the Colombian context were identified new factors such as organizational culture, management models, integration of the care and administrative departments and triple helix relationship.

Keywords: barriers, enablers, implementation, lean healthcare, sustainability

Procedia PDF Downloads 366
152 Stability of a Biofilm Reactor Able to Degrade a Mixture of the Organochlorine Herbicides Atrazine, Simazine, Diuron and 2,4-Dichlorophenoxyacetic Acid to Changes in the Composition of the Supply Medium

Authors: I. Nava-Arenas, N. Ruiz-Ordaz, C. J. Galindez-Mayer, M. L. Luna-Guido, S. L. Ruiz-López, A. Cabrera-Orozco, D. Nava-Arenas

Abstract:

Among the most important herbicides, the organochlorine compounds are of considerable interest due to their recalcitrance to the chemical, biological, and photolytic degradation, their persistence in the environment, their mobility, and their bioacummulation. The most widely used herbicides in North America are primarily 2,4-dichlorophenoxyacetic acid (2,4-D), the triazines (atrazine and simazine), and to a lesser extent diuron. The contamination of soils and water bodies frequently occurs by mixtures of these xenobiotics. For this reason, in this work, the operational stability to changes in the composition of the medium supplied to an aerobic biofilm reactor was studied. The reactor was packed with fragments of volcanic rock that retained a complex microbial film, able to degrade a mixture of organochlorine herbicides atrazine, simazine, diuron and 2,4-D, and whose members have microbial genes encoding the main catabolic enzymes atzABCD, tfdACD and puhB. To acclimate the attached microbial community, the biofilm reactor was fed continuously with a mineral minimal medium containing the herbicides (in mg•L-1): diuron, 20.4; atrazine, 14.2, simazine, 11.4, and 2,4-D, 59.7, as carbon and nitrogen sources. Throughout the bioprocess, removal efficiencies of 92-100% for herbicides, 78-90% for COD, 92-96% for TOC and 61-83% for dehalogenation were reached. In the microbial community, the genes encoding catabolic enzymes of different herbicides tfdACD, puhB and, occasionally, the genes atzA and atzC were detected. After the acclimatization, the triazine herbicides were eliminated from the mixture formulation. Volumetric loading rates of the mixture 2,4-D and diuron were continuously supplied to the reactor (1.9-21.5 mg herbicides •L-1 •h-1). Along the bioprocess, the removal efficiencies obtained were 86-100% for the mixture of herbicides, 63-94% for for COD, 90-100% for COT, and dehalogenation values of 63-100%. It was also observed that the genes encoding the enzymes in the catabolism of both herbicides, tfdACD and puhB, were consistently detected; and, occasionally, the atzA and atzC. Subsequently, the triazine herbicide atrazine and simazine were restored to the medium supply. Different volumetric charges of this mixture were continuously fed to the reactor (2.9 to 12.6 mg herbicides •L-1 •h-1). During this new treatment process, removal efficiencies of 65-95% for the mixture of herbicides, 63-92% for COD, 66-89% for TOC and 73-94% of dehalogenation were observed. In this last case, the genes tfdACD, puhB and atzABC encoding for the enzymes involved in the catabolism of the distinct herbicides were consistently detected. The atzD gene, encoding the cyanuric hydrolase enzyme, could not be detected, though it was determined that there was partial degradation of cyanuric acid. In general, the community in the biofilm reactor showed some catabolic stability, adapting to changes in loading rates and composition of the mixture of herbicides, and preserving their ability to degrade the four herbicides tested; although, there was a significant delay in the response time to recover to degradation of the herbicides.

Keywords: biodegradation, biofilm reactor, microbial community, organochlorine herbicides

Procedia PDF Downloads 435
151 A Location Routing Model for the Logistic System in the Mining Collection Centers of the Northern Region of Boyacá-Colombia

Authors: Erika Ruíz, Luis Amaya, Diego Carreño

Abstract:

The main objective of this study is to design a mathematical model for the logistics of mining collection centers in the northern region of the department of Boyacá (Colombia), determining the structure that facilitates the flow of products along the supply chain. In order to achieve this, it is necessary to define a suitable design of the distribution network, taking into account the products, customer’s characteristics and the availability of information. Likewise, some other aspects must be defined, such as number and capacity of collection centers to establish, routes that must be taken to deliver products to the customers, among others. This research will use one of the operation research problems, which is used in the design of distribution networks known as Location Routing Problem (LRP).

Keywords: location routing problem, logistic, mining collection, model

Procedia PDF Downloads 218
150 Inclusion and Changes of a Research Criterion in the Institute for Quality and Accreditation of Computing, Engineering and Technology Accreditation Model

Authors: J. Daniel Sanchez Ruiz

Abstract:

The paper explains why and how a research criterion was included within an accreditation system for undergraduate engineering programs, in spite of not being a common practice of accreditation agencies at a global level. This paper is divided into three parts. The first presents the context and the motivations that led the Institute for Quality and Accreditation of Computing, Engineering and Technology Programs (ICACIT) to add a research criterion. The second describes the criterion adopted and the feedback received during 2017 accreditation cycle. The third, the author proposes changes to the accreditation criteria that respond in a pertinent way to the results-based accreditation model and the national context. The author seeks to reconcile an outcome based accreditation model, aligned with the established by the International Engineering Alliance, with the particular context of higher education in Peru.

Keywords: accreditation, engineering education, quality assurance, research

Procedia PDF Downloads 281
149 Using Artificial Vision Techniques for Dust Detection on Photovoltaic Panels

Authors: Gustavo Funes, Eduardo Peters, Jose Delpiano

Abstract:

It is widely known that photovoltaic technology has been massively distributed over the last decade despite its low-efficiency ratio. Dust deposition reduces this efficiency even more, lowering the energy production and module lifespan. In this work, we developed an artificial vision algorithm based on CIELAB color space to identify dust over panels in an autonomous way. We performed several experiments photographing three different types of panels, 30W, 340W and 410W. Those panels were soiled artificially with uniform and non-uniform distributed dust. The algorithm proposed uses statistical tools to provide a simulation with a 100% soiled panel and then performs a comparison to get the percentage of dirt in the experimental data set. The simulation uses a seed that is obtained by taking a dust sample from the maximum amount of dust from the dataset. The final result is the dirt percentage and the possible distribution of dust over the panel. Dust deposition is a key factor for plant owners to determine cleaning cycles or identify nonuniform depositions that could lead to module failure and hot spots.

Keywords: dust detection, photovoltaic, artificial vision, soiling

Procedia PDF Downloads 50
148 MIOM: A Mixed-Initiative Operational Model for Robots in Urban Search and Rescue

Authors: Mario Gianni, Federico Nardi, Federico Ferri, Filippo Cantucci, Manuel A. Ruiz Garcia, Karthik Pushparaj, Fiora Pirri

Abstract:

In this paper, we describe a Mixed-Initiative Operational Model (MIOM) which directly intervenes on the state of the functionalities embedded into a robot for Urban Search&Rescue (USAR) domain applications. MIOM extends the reasoning capabilities of the vehicle, i.e. mapping, path planning, visual perception and trajectory tracking, with operator knowledge. Especially in USAR scenarios, this coupled initiative has the main advantage of enhancing the overall performance of a rescue mission. In-field experiments with rescue responders have been carried out to evaluate the effectiveness of this operational model.

Keywords: mixed-initiative planning and control, operator control interfaces for rescue robotics, situation awareness, urban search, rescue robotics

Procedia PDF Downloads 376
147 Viscoelastic Characterization of Bovine Trabecular Bone Samples

Authors: I. Ramirez D. Edgar, J. Angeles H. José, Ruiz C. Osvaldo, H. Jacobo A. Victor, Ortiz P. Armando

Abstract:

Knowledge of bone mechanical properties is important for bone substitutes design and fabrication, and more efficient prostheses development. The aim of this study is to characterize the viscoelastic behavior of bone specimens, through stress relaxation and fatigue tests performed to trabecular bone samples from bovine femoral heads. Relaxation tests consisted on preloading the samples at five different magnitudes and evaluate them for 1020 seconds, adjusting the results to a KWW mathematical model. Fatigue tests consisted of 700 load cycles and analyze their status at the end of the tests. As a conclusion we have that between relaxation stress and each preload there is linear relation and for samples with initial Young´s modulus greater than 1.5 GPa showed no effects due fatigue test loading cycles.

Keywords: bone viscoelasticity, fatigue test, stress relaxation test, trabecular bone properties

Procedia PDF Downloads 491
146 A Low-Cost Experimental Approach for Teaching Energy Quantization: Determining the Planck Constant with Arduino and Led

Authors: Gastão Soares Ximenes de Oliveira, Richar Nicolás Durán, Romeo Micah Szmoski, Eloiza Aparecida Avila de Matos, Elano Gustavo Rein

Abstract:

This article aims to present an experimental method to determine Planck's constant by calculating the cutting potential V₀ from LEDs with different wavelengths. The experiment is designed using Arduino as a central tool in order to make the experimental activity more engaging and attractive for students with the use of digital technologies. From the characteristic curves of each LED, graphical analysis was used to obtain the cutting potential, and knowing the corresponding wavelength, it was possible to calculate Planck's constant. This constant was also obtained from the linear adjustment of the cutting potential graph by the frequency of each LED. Given the relevance of Planck's constant in physics, it is believed that this experiment can offer teachers the opportunity to approach concepts from modern physics, such as the quantization of energy, in a more accessible and applied way in the classroom. This will not only enrich students' understanding of the fundamental nature of matter but also encourage deeper engagement with the principles of quantum physics.

Keywords: physics teaching, educational technology, modern physics, Planck constant, Arduino

Procedia PDF Downloads 76
145 An Agent-Based Modelling Simulation Approach to Calculate Processing Delay of GEO Satellite Payload

Authors: V. Vicente E. Mujica, Gustavo Gonzalez

Abstract:

The global coverage of broadband multimedia and internet-based services in terrestrial-satellite networks demand particular interests for satellite providers in order to enhance services with low latencies and high signal quality to diverse users. In particular, the delay of on-board processing is an inherent source of latency in a satellite communication that sometimes is discarded for the end-to-end delay of the satellite link. The frame work for this paper includes modelling of an on-orbit satellite payload using an agent model that can reproduce the properties of processing delays. In essence, a comparison of different spatial interpolation methods is carried out to evaluate physical data obtained by an GEO satellite in order to define a discretization function for determining that delay. Furthermore, the performance of the proposed agent and the development of a delay discretization function are together validated by simulating an hybrid satellite and terrestrial network. Simulation results show high accuracy according to the characteristics of initial data points of processing delay for Ku bands.

Keywords: terrestrial-satellite networks, latency, on-orbit satellite payload, simulation

Procedia PDF Downloads 274
144 A Data Science Pipeline for Algorithmic Trading: A Comparative Study in Applications to Finance and Cryptoeconomics

Authors: Luyao Zhang, Tianyu Wu, Jiayi Li, Carlos-Gustavo Salas-Flores, Saad Lahrichi

Abstract:

Recent advances in AI have made algorithmic trading a central role in finance. However, current research and applications are disconnected information islands. We propose a generally applicable pipeline for designing, programming, and evaluating algorithmic trading of stock and crypto tokens. Moreover, we provide comparative case studies for four conventional algorithms, including moving average crossover, volume-weighted average price, sentiment analysis, and statistical arbitrage. Our study offers a systematic way to program and compare different trading strategies. Moreover, we implement our algorithms by object-oriented programming in Python3, which serves as open-source software for future academic research and applications.

Keywords: algorithmic trading, AI for finance, fintech, machine learning, moving average crossover, volume weighted average price, sentiment analysis, statistical arbitrage, pair trading, object-oriented programming, python3

Procedia PDF Downloads 149
143 Elastic and Plastic Collision Comparison Using Finite Element Method

Authors: Gustavo Rodrigues, Hans Weber, Larissa Driemeier

Abstract:

The prevision of post-impact conditions and the behavior of the bodies during the impact have been object of several collision models. The formulation from Hertz’s theory is generally used dated from the 19th century. These models consider the repulsive force as proportional to the deformation of the bodies under contact and may consider it proportional to the rate of deformation. The objective of the present work is to analyze the behavior of the bodies during impact using the Finite Element Method (FEM) with elastic and plastic material models. The main parameters to evaluate are, the contact force, the time of contact and the deformation of the bodies. An advantage of using the FEM approach is the possibility to apply a plastic deformation to the model according to the material definition: there will be used Johnson–Cook plasticity model whose parameters are obtained through empirical tests of real materials. This model allows analyzing the permanent deformation caused by impact, phenomenon observed in real world depending on the forces applied to the body. These results are compared between them and with the model-based Hertz theory.

Keywords: collision, impact models, finite element method, Hertz Theory

Procedia PDF Downloads 175
142 Latinx Adults’ Emergent Bilinguals’ Perceptions of Culturally Diverse Teaching Strategies

Authors: Sharon Diaz Ruiz

Abstract:

The population of Latinx adult English language learners (ELLs) in the United States will increase in the next few years and become even more racially and linguistically diverse. Our classrooms reflect these demographic changes; therefore, there will always be the need to identify language teaching practices that would allow educators to meet this linguistic diversity. This qualitative study explores Latinx adult English language learners' perceptions of culturally responsive teaching strategies. Participants in this study will be enrolled in an English developmental course for the Fall of 2022. The data collection process will consist of overt observation during five presentations/activities, including culturally inclusive readings and student reflections. The teaching materials selected will align with the course module's goals and objectives. The result of this investigation will shed light on the gap in the literature documenting the application of culturally responsive pedagogy to Latino adult language learners.

Keywords: emergent bilinguals, adult learners, Latinx learners, ELL

Procedia PDF Downloads 102
141 Brain Computer Interface Implementation for Affective Computing Sensing: Classifiers Comparison

Authors: Ramón Aparicio-García, Gustavo Juárez Gracia, Jesús Álvarez Cedillo

Abstract:

A research line of the computer science that involve the study of the Human-Computer Interaction (HCI), which search to recognize and interpret the user intent by the storage and the subsequent analysis of the electrical signals of the brain, for using them in the control of electronic devices. On the other hand, the affective computing research applies the human emotions in the HCI process helping to reduce the user frustration. This paper shows the results obtained during the hardware and software development of a Brain Computer Interface (BCI) capable of recognizing the human emotions through the association of the brain electrical activity patterns. The hardware involves the sensing stage and analogical-digital conversion. The interface software involves algorithms for pre-processing of the signal in time and frequency analysis and the classification of patterns associated with the electrical brain activity. The methods used for the analysis and classification of the signal have been tested separately, by using a database that is accessible to the public, besides to a comparison among classifiers in order to know the best performing.

Keywords: affective computing, interface, brain, intelligent interaction

Procedia PDF Downloads 390
140 Discriminant Analysis as a Function of Predictive Learning to Select Evolutionary Algorithms in Intelligent Transportation System

Authors: Jorge A. Ruiz-Vanoye, Ocotlán Díaz-Parra, Alejandro Fuentes-Penna, Daniel Vélez-Díaz, Edith Olaco García

Abstract:

In this paper, we present the use of the discriminant analysis to select evolutionary algorithms that better solve instances of the vehicle routing problem with time windows. We use indicators as independent variables to obtain the classification criteria, and the best algorithm from the generic genetic algorithm (GA), random search (RS), steady-state genetic algorithm (SSGA), and sexual genetic algorithm (SXGA) as the dependent variable for the classification. The discriminant classification was trained with classic instances of the vehicle routing problem with time windows obtained from the Solomon benchmark. We obtained a classification of the discriminant analysis of 66.7%.

Keywords: Intelligent Transportation Systems, data-mining techniques, evolutionary algorithms, discriminant analysis, machine learning

Procedia PDF Downloads 472
139 Water Detection in Aerial Images Using Fuzzy Sets

Authors: Caio Marcelo Nunes, Anderson da Silva Soares, Gustavo Teodoro Laureano, Clarimar Jose Coelho

Abstract:

This paper presents a methodology to pixel recognition in aerial images using fuzzy $c$-means algorithm. This algorithm is a alternative to recognize areas considering uncertainties and inaccuracies. Traditional clustering technics are used in recognizing of multispectral images of earth's surface. This technics recognize well-defined borders that can be easily discretized. However, in the real world there are many areas with uncertainties and inaccuracies which can be mapped by clustering algorithms that use fuzzy sets. The methodology presents in this work is applied to multispectral images obtained from Landsat-5/TM satellite. The pixels are joined using the $c$-means algorithm. After, a classification process identify the types of surface according the patterns obtained from spectral response of image surface. The classes considered are, exposed soil, moist soil, vegetation, turbid water and clean water. The results obtained shows that the fuzzy clustering identify the real type of the earth's surface.

Keywords: aerial images, fuzzy clustering, image processing, pattern recognition

Procedia PDF Downloads 484