INNOVATION & DEVELOPMENT IN ENGINEERING AND APPLIED SCIENCES
IDEAS is an open access journal (Open Journal System) developed at the School of Engineering in Applied Sciences, Universidad Técnica del Norte, with the purpose of disseminating the results obtained in research and technical studies. IDEAS has a permanent call for papers written by professors, professionals, university students, graduates, national and international experts, in areas related to applied sciences, science and engineering. The publication process in IDEAS does not involve any cost or fee. It is published every six months (January, July); in addition, it has the ISSN 2600-5573 that allows to identify the articles presented in the international database ISSN Portal.
Editorial de la Universidad Tecnica del Norte
Authors retain the copyright of their works and grant the journal IDEAS the right of first publication. Articles are published under the Creative Commons Attribution–NonCommercial–NoDerivatives 4.0 International License (CC BY-NC-ND 4.0), which allows reading, downloading, copying, distributing, and sharing the content for non-commercial purposes, provided that proper credit is given to the author(s) and the original publication in the journal, without making modifications or creating derivative works. The journal IDEAS does not charge fees for submission, processing, or publication of manuscripts and guarantees open access to its contents.
Environmental Monitoring with IoT and Big Data: A Systematic Review of Advances and Challenges.
The integration of the Internet of Things (IoT) and Big Data analytics has revolutionized environmental monitoring, enabling quantitative and qualitative advances in natural resource management. This systematic review, based on 55 studies published between 2019 and 2024 and following the PRISMA protocol, identifies trends, achievements and challenges in the application of these technologies. In agriculture, the adoption of IoT sensors has reduced water consumption by 35% and increased productivity by 12%. In water management, IoT nanosensors have increased the detection capacity of contaminants fivefold over conventional methods. Deep learning models, such as LSTM networks fed by data from more than 15,000 IoT nodes, have achieved greater than 92% accuracy in predicting extreme weather events. In addition, the integration of IoT and Big Data platforms in cities has helped reduce CO₂ emissions by 15% by optimizing traffic and energy consumption. Innovations such as edge computing architecture have decreased processing latency by 68%, and digital twins have improved the accuracy of predictive models by 40%. Globally, the environmental IoT market is projected to be worth $21.5 billion by 2028, with more than 152 cities implementing IoT networks for air quality and 35 million hectares under precision agriculture. However, challenges remain, such as interoperability (23% of deployments), initial deployment cost and the technology gap between regions. The IoT-Big Data convergence drives a transition towards proactive environmental management systems, although its scalability depends on overcoming these challenges.
Copyright (c) 2025 Gema Isabel Medranda Cobeña https://creativecommons.org/licenses/by-nc-nd/4.0
An Econometric Analysis of Unemployment in Ecuador: Classical Approaches and a Machine Learning-Based Proposal
This study focuses on modeling and predicting unemployment in Ecuador using neural networks, comparing their effectiveness with traditional econometric methods. The dependent variable, unemployment (), defined as the percentage of the working population without employment, is analyzed based on seven macroeconomic predictors: Real gross domestic product (GDP, x₁), inflation (x₂, percentage change in the consumer price index), exports (x₃) and imports (x₄, valued in millions of USD), real minimum wage (x₅), public spending (x₆, percentage of GDP), and interest rate (x₇). Previous research, based on Okun's Law, identified linear correlations between GDP growth and unemployment reduction using Ordinary Least Squares (OLS) and cointegration models. However, these conventional techniques, including multiple regressions, showed limitations in capturing the nonlinear dynamics inherent in unemployment. In contrast, neural networks (NN), especially sequential architectures, demonstrated superiority in modeling complex interactions between variables. The study evaluates deep learning models with one and two hidden layers, identifying an optimal configuration of one hidden layer (16 neurons), achieving a loss of 0.2846, 75% accuracy, and Mean Square Error (MSE) of 0.2064 on unseen test data. The results highlight the ability of neural networks to model unemployment more accurately than linear methods, attributing this to their adaptability to learn nonlinear patterns in multivariate data. This study demonstrates that variables such as GDP, inflation, public spending, and interest rates significantly influence unemployment. Neural networks (NN) effectively capture these complex relationships. Their usefulness in predicting socioeconomic phenomena in developing countries such as Ecuador is highlighted, overcoming the limitations of traditional models.
Copyright (c) 2025 Iván Andrés Narváez Pistala, Erick Patricio Herrera Granda https://creativecommons.org/licenses/by-nc-nd/4.0
Data security and privacy in the information age in Ecuador.
Digitalization in Ecuador has increased in recent years, and with it the exposure of both personal and organizational data. This exposure increases the risk of cyberattacks. It is necessary to be aware of the risks that currently exist and recommendations for avoiding them. This study presents a systematic literature review with the aim of providing recommendations and recognizing risks in an increasingly digitalized Ecuador, using the PRISMA methodology. It demonstrates that the main threats are sophisticated cyberattacks and a lack of user awareness regarding cybersecurity. Although the Organic Law on Personal Data Protection (LOPDP) exists, there are challenges to its effective implementation. In conclusion, important strategies are presented, such as regulatory frameworks, ongoing staff training on cyberattacks, and the use of new technologies to prevent such cyberattacks. These measures, aligned with international standards, are important for strengthening Ecuador's technological resilience against threats from the digital environment.
Copyright (c) 2025 Cristopher Quijije, Wilmer Moreira https://creativecommons.org/licenses/by-nc-nd/4.0
Analysis of gastric cancer using artificial intelligence: An innovative approach in oncological research.
Gastric cancer (GC) remains one of the leading causes of cancer-related mortality worldwide, primarily due to the challenges of early diagnosis, which often relies on invasive procedures and manual image analysis. This study presents the development of a web-based application powered by artificial intelligence, using convolutional Neural Network for the automatic detection of anomalies in endoscopic images. The methodology was structured into four phases: data collection, preprocessing, model implementation, and system evaluation. The algorithm achieved a classification accuracy of 97.4% and an average analysis time of 0.10 seconds per image, exceeding clinical performance benchmarks. The system proved to be effective, fast, and accessible to healthcare professionals, including those in resource-constrained environments. Its user-friendly interface and centralized database facilitated seamless integration into clinical practice. This research highlights the potential of deep neural networks in supporting early diagnosis of gastric cancer. Future work will focus on validating the tool in real-world clinical settings and exploring additional deep learning architectures to further enhance system performance.
Copyright (c) 2025 Michel Plaza Granoble, Oscar López Gorozabel https://creativecommons.org/licenses/by-nc-nd/4.0
Application of multivariate techniques to productivity indicators derived from the simulation of production processes at a dairy company
The objective of this research is to model and analyze production processes in the food industry, specifically in the manufacture of dairy products, using multivariate statistical techniques. The multivariate techniques MANOVA and PERMANOVA compare groups with multiple dependent variables. Productivity indicators evaluate efficiency and performance, facilitating improvements and strategic decisions. Simulation optimizes processes, reducing costs and improving efficiency through accurate analysis and predictions. To this end, the unit operations of the fruit yogurt production process were identified and documented, developing a structured database with the processing times for each process. The integrity of the database was validated, imputing 3.3% of the missing data using the KNN method, and the absence of outliers was verified using Mahalanobis distance. The analysis of the execution times determined the most appropriate probability distributions for each process, with validation using the Chi-square goodness-of-fit test. The simulation process was validated using a Student's t-test, comparing the actual process with the simulated one, which ensured its representativeness. Subsequently, improvement scenarios were simulated using FlexSim software and Lean Manufacturing techniques (TPM, 5S, Poka Yoke, and muda elimination), evaluating the impact on production times and the quantity of finished products. The results were analyzed using the PERMANOVA method, given that the assumptions of normality, homoscedasticity, and independence for MANOVA were not met. The analyses revealed statistically significant differences between the simulation scenarios, with the 5S scenario standing out as the most efficient in reducing production time and increasing the number of products. The model explained 44% of the variability in the results, highlighting the effectiveness of the 5S methodology in optimizing the process.
Copyright (c) 2025 Cristian Andrés Flores Cadena https://creativecommons.org/licenses/by-nc-nd/4.0
Analysis of Resistance to Bactericera cockerelli in Potato Germplasm: A Sustainable Approach
Bactericera cockerelli (Sulc) is the main vector of plant phloem-associated pathogens responsible for the potato purple top complex, a disease that can cause losses of up to 100% in potato crops. Chemical control methods, mainly based on insecticides, have proven to be inefficient due to the development of insect resistance. This problem highlights the need to implement sustainable strategies to mitigate its impact. One promising strategy is the genetic resistance of plants, specifically antibiosis, this type of resistance implies that plants negatively affect the insect's biology. In this context, the present study aimed to identify potato genotypes conserved by the National Roots and Tubers Program of the National Institute of Agricultural Research with antibiosis resistance characteristics against B. cockerelli, by means of a statistical analysis based on a complete factorial design. The evaluation considered the number of eggs oviposited on different days of evaluation in 9 wild species, 18 improved varieties, 15 native varieties and 18 promising clones. Genotypes with a marked resistance due to antibiosis were identified. These materials can contribute valuable genetic resources for breeding programs and the implementation of integrated crop management strategies, thus reducing dependence on pesticides that endanger human health and biodiversity.
Copyright (c) 2025 Jessica Marlene Amagua Bautista https://creativecommons.org/licenses/by-nc-nd/4.0
Tribological Analysis of a MEP engine in the Cities of Quito and Santo Domingo with Different Oil Viscosity Grades
This project focuses on analyzing the wear of SIE engines with oils of different viscosity in the cities of Quito (2850 m.a.s.l.) and Santo Domingo (655 m.a.s.l.), to identify the wear of the internal elements of the engine through tribological tests. A 2002 Nissan Sentra B15 vehicle was used and extra 87 octane gasoline, several oil filters for each test, lubricants with viscosity grades SAE 10W30 and 20W50. Likewise, measurements were made at different engine speeds, such as 1500 and 2500 rpm. The data obtained in reference to polluting gases allowed us to observe that 10W30 oil generates higher polluting emissions and higher maintenance costs. Finally, the tribological tests and trials show that oils with the same specification and different atmospheric pressure and viscosity grade, generate different wear on the internal components of SIE engines.
Mechanical, Mechatronics, Vehicle and Materials Engineering
Copyright (c) 2025 INNOVATION & DEVELOPMENT IN ENGINEERING AND APPLIED SCIENCES
A Methodology to develop a strategic plan for Fair Trade Organizations in Ecuador. FEPP CAMARI case study
In Ecuador there are fair trade organizations that provide support to small producers who continually work empirically; FEPP CAMARI is a social organization that promotes equitable, fair and supportive marketing in society. Therefore, this study shows a methodological proposal of the strategic plan focused on small producers with fundamental and friendly strategic axes for efficient and effective execution.
Implementation of clean technologies as a strategy to improve environmental sustainability in industrial plants
This essay examines the impact of implementing clean technologies in industrial plants to enhance environmental sustainability. Case studies of companies that have adopted clean technologies, such as renewable energies, efficient waste management, and reduction of pollutant emissions, are analyzed. The results demonstrate that the implementation of clean technologies has shown to reduce greenhouse gas emissions and decrease the consumption of natural resources in the studied industrial plants. Furthermore, optimization of production processes and reduction of operational costs are observed. These findings support the importance of adopting clean technologies in the industrial sector to promote more sustainable production. The successful implementation of clean technologies not only benefits the environment but can also generate economic savings and improve the corporate image of companies.
Risk factors associated with burnout syndrome in teachers in the province of Carchi.
Summary. Burnout syndrome is widely known as a work-related problem that afflicts teachers worldwide. This problem related to risk factors that generate stress arises due to the work environment and various situations related to dealing with people who demand a high level of dedication and involvement. The present study focused on identifying risk factors associated with burnout syndrome in teachers in the province of Carchi. The main objective was to validate the adaptation of the Maslach Burnout Inventory (MBI) to the specific educational context, and to propose a model of analysis of results based on artificial intelligence. When validating the instrument, it was identified that it was not completely adapted to the local context, so the instrument was modified, having to remove 5 questions that were identified as not relevant by the Confirmatory Factor Analysis, and demographic information of the participants considered of interest to the participating institutions was incorporated. Thus, for the extraction of results from the test, a new results processing model was designed based on multivariate techniques, contemplating 37 input variables. For this, multiple alternatives were considered, including binary classifiers, shallow neural networks and five deep learning models, finding that deep learning, especially a five-layer model developed with TensorFlow and Keras, offered the most accurate predictions of emotional exhaustion, a key dimension of burnout syndrome. This model achieved an accuracy of 86% and an MSE of 0.1193604, demonstrating its reliability for automatic detection of the syndrome without the need for professional diagnosis. The research validates the adaptation of the instrument to the target context and highlights the importance of establishing new models of analysis when using instruments modified from the MBI, ensuring their relevance and applicability in specific contexts.
Detection of Chronic Malnutrition in Children Under Five Years of Age Applying Multivariate Techniques
This article shows the design of five classifiers for the detection of chronic malnutrition in children under five years of age, for which a database was processed with five quantitative and 26 qualitative variables that were subjected to a dimension decrease employing a multiple correspondence analysis, subsequently, by using neural networks the first classifier was generated. The following three designs used deep neural network techniques, starting from a principal component analysis that determined an architecture with a hidden layer that houses 96. 3% of the cumulative variance, the difference between these classifiers lies in the technique that determined the number of neurons in the hidden layer. The last designed classifier employs logistic regression as a traditional statistical technique. The study ended with tests performed with the best-performing classifier that allowed for establishing the most influential variables.
Copyright (c) 2024 INNOVATION & DEVELOPMENT IN ENGINEERING AND APPLIED SCIENCES
Study of associativity in MSMEs in the province of Imbabura-Ecuador, a case study of manufacturing industries.
The research carried out on MSMEs in the province of Imbabura through the application of a survey focused on knowing if MSMEs are aware of associativity and the benefits it generates, seeks to identify if companies are interested in managing an associative consortium model based on the economic sector in which they are classified according to the work activity carried out, for this the research was divided into phases. Phase I. identification of the population and selection of the sample using statistical formulas and a greater number of companies according to the economic sector and canton, obtaining a sample of 328 for the purposes of this investigation, phase II, information gathering was carried out through the application of a survey where information was collected about the strategic planning managed in each MSME and it was identified that a low number of companies have a strategic planning and organizational structure, phase III, with the purpose of analyzing whether companies are interested in forming associative consortia, six questions were developed, from which it was obtained that there is a lack of knowledge of the benefits that an associative consortium provides and that they are interested in managing activities to improve their positioning. both nationally and internationally
The implementation of an "Innovation in Public Services: Web Application for Citizen Revenue Collection with ISO/IEC 25010 Focus" arises as an essential measure to address the challenges inherent in the manual collection process of citizen services: drinking water, drinking water service installation, connection maintenance, reconnection of connections, garbage collection, sewerage, in society. The adoption of SCRUM, recognized for its agile and adaptable approach, is key to the execution of this project. By employing SCRUM, effective process management is facilitated, with iterative deliveries and close collaboration between developers and end users. This iterative approach allows for continuous adjustments and improvements during development, ensuring that the final platform meets the specific needs of the Santo Domingo N°1 community in the province of Pichincha, Cayambe canton. By integrating SCRUM and usability metrics in accordance with ISO/IEC 25010, the aim is not only to speed up payment processes but also to provide high-quality software that meets the expectations of partners and local authorities.
Cytochrome P450-mediated bioactivation of the chemotherapeutic cyclophosphamide for use in cancer gene therapy
This review examines the role of cytochrome P450 enzymes in the bioactivation of the chemotherapeutic agent cyclophosphamide (CPA) for use in cancer gene therapy. The study explores specific cytochrome P450 enzymes, such as CYP2B6, CYP2C9, and CYP3A4, responsible for metabolizing CPA into its active form, highlighting its potential in suicide gene therapy or GDEPT. The review also discusses genetic modifications made to improve the catalytic efficiency of these enzymes and addresses the challenges and future directions of integrating GDEPT with other cancer therapies to improve treatment specificity and efficacy.
Design and implementation of a portable modular platform for the teaching of microcontrollers.
The research focuses on the design and construction of a modular teaching platform for microcontroller and embedded systems laboratories at a university. The platform consists of 20 modules with silkscreen printed components, communication ports and power supply. It communicates with the PC through a USB port, processing the information of the entire modular platform. The design and components used were selected in response to the real needs of teachers and students, gathered through surveys. In addition, the platform allows the integration of these subjects in the simulation of technological processes and the intelligent control of a house. The results show that the modular platform has improved the teaching-learning process, applying theoretical concepts in real environments. It works with Arduino IDE software and free hardware. Its design is ergonomic and didactic for each prototype station of each circuit. Its dimensions are 555 mm long by 355 mm wide, which facilitates its mobilization. The power supply of the boards is included and is indicated with a voltage of 5 V and 3.3 V. It is optimal in practice development time, circuit design and reduction of unnecessary expenses for students. The effectiveness of the project was evaluated through performance evaluations, satisfaction surveys and development of laboratory guides in areas such as automation, control and power.
The strategic process and competitiveness of a consulting company in the year 2022, case: JC Ingeniería y Consultoría S.A.C.
This study aims to establish the level of relationship between the strategic process and the competitiveness of a consulting company in the year 2022. The results obtained from the research will allow us to determine how the strategic process is being developed in the consulting company J.C. Engineering and Consulting S.A.C. and how this impacts its competitiveness. The research will help build an effective framework to analyze, review, and measure the impact of the strategic process on business competitiveness. It is concluded that the variables 'strategic process' and 'competitiveness of a consulting company' are positively related with a correlation coefficient of 0.696. This leads to the decision to reject the null hypothesis; that is, a significant positive relationship exists between the strategic process and the competitiveness of a consulting company in 2022.
Review of the curricular design applied to mechatronics in relation to the labor field.
This article presents a review of the curricular design in mechatronics, aligned with the needs of the educational sector and the industrial field. Key components such as the integration of pedagogical knowledge and the development of technical competencies in fundamental areas such as educational robotics, mechanics, programming, design, electricity and electronics are examined, which facilitates the teaching of these disciplines in educational institutions. The research highlights the importance of training professionals capable of educating future generations in technical areas, as well as performing effectively in industrial sectors, strengthening the link between the university and contemporary social and technological demands. The study emphasizes the need to continually update curricular content, integrating essential pedagogical aspects such as didactic planning, formative evaluation and the use of active and collaborative methodologies, together with emerging technologies such as artificial intelligence (AI), advanced manufacturing and virtual simulation. It is emphasized that the flexibility of the curriculum, both pedagogically and technically, is crucial for students to adapt to the educational field of mechatronics and the dynamic industrial environment. This approach ensures effective interaction between the university, society and industry, promoting comprehensive education that not only responds to the needs of the productive sector, but also to the growing demand for educators specialized in technology.
Copyright (c) 2025 Héctor Barros Castro https://creativecommons.org/licenses/by-nc-nd/4.0
The impact of educational robotics on the development of soft skills and abilities in students in Ecuador
The present research reviews the impact of educational robotics on the development of competencies of students in Ecuador. In a context where education seeks to adapt to the demands of the 21st century, robotics is presented as an innovative tool to improve learning. The objective of this review is to analyze how the implementation of robotics in the classroom contributes to the development of technical and soft skills. A documentary methodology was used, reviewing previous studies and educational experiences in different institutions. The analysis techniques included literature review and case study. The main results indicate that students participating in educational robotics activities improved significantly in areas such as problem solving, teamwork and creativity [2]. In addition, an increase in motivation and interest in core subjects was observed. In conclusion, educational robotics not only enhances the learning of technical skills, but also fosters interpersonal skills, preparing students to face the challenges of future employment in an increasingly technological world.
Copyright (c) 2025 Marco Chiluisa https://creativecommons.org/licenses/by-nc-nd/4.0
Methodology for the development of maintenance management systems based on the NTE- INEN-EN-15341 standard in manufacturing MSMEs in the province of Imbabura
Maintenance management in companies, whether large, small or medium-sized, is important since it allows adequate work of the machinery and operation of the processes, the research focuses on the design of a methodology for maintenance management, in manufacturing MSMEs in the province of Imbabura, which was divided into phases. Phase I. The population and sample selection were identified by applying statistical formulas and the type of economic activity they generate, obtaining a sample of 340 manufacturing MSMEs, In phase II, information was collected by applying the MES survey (Maintenance Effectiveness Survey), which consists of a set of questions related to the administration and management of maintenance that seeks to identify the level of maintenance carried out in manufacturing MSMEs in the region. province of Imbabura, as well as the processes that are carried out to fulfill the declared economic activity, where the strategic, operational and support processes were identified, it is necessary to emphasize that as they are manufacturing companies and their focus is production of clothing, food, leather goods, among others, have specialized machinery that must provide adequate operating and operational conditions. In phase II, once the information is obtained, the methodology for maintenance management in MSMEs, manufacturing companies in the province of Imbabura, is proposed, considering the situational diagnosis, design, implementation and verification.
Copyright (c) 2025 Jenyffer Yepez, Karla Paola Negrete, Marco Gabriela Alarcón https://creativecommons.org/licenses/by-nc-nd/4.0
The research to obtain non-woven sheep wool (NWW) for application in felt hats begins with the washing of sheep wool (SW), which is then centrifuged and air-dried. Next, SW is opened and blended in the opening and mixing machine (O) to achieve homogenization with an average of 40mm. It is then processed in the carding machine (C) to align the fibers in the machine direction (MD) and cross direction (CD), and then it is rolled layer by layer onto a properly sized and shaped cone. Subsequently, it is placed on a vibrating plate (VP) where steam at 120°C is introduced from a steam boiler (SB) onto the SW layer. It is kneaded and rubbed with circular reciprocating movements to compact and felt, forming the NWW. Finally, it is left in the open air to dry with various shapes and sizes. The data obtained were analyzed using Past 4 software and have a 95% reliability (P>0.05). The conclusion reached is that the elongation (E) in MD and CD has averages of 59.56% and 58.27%, respectively. The tensile strength (TS) is 335.846 N in MD and 392.218 N in CD, with greater energy at break (EB) being observed at 20,052.36 joules in MD and 21,951.38 joules in CD when force is applied.
Immersive Education in the Transfer and Innovation of Scientific Research Results
In this work, augmented reality is applied to offer enveloping and participatory learning experiences through virtual environments or elements that complement the real world with digital content. It has been a documentary, exploratory, descriptive, and, in the pilot stage, with a qualitative approach. Technical information was collected on the various digitized and accessible topics through the ITCA Academy application, where the user receives the default information through electronic devices. The participants were satisfied with what was observed and said they processed the information received through immersive education. The understanding of the participants was superior compared to traditional teaching, minimizing the inconveniences of the teaching-learning process through the use of the application. The practical implementation of immersive education, with its interactive resources, covered the failures of traditional education, causing novel results in the teaching-learning process.
Prediction of rainfall for prevention using ARIMA models, Bayesian Optimization, and XGBoost Model.
This study focuses on providing a statistical model for precipitation at the Meteorological Station of the Universidad Politécnica Estatal del Carchi, Tulcán canton, with the purpose of improving the forecasting capacity and resilience of the regional agricultural sector. Consequently, this work analyzes the vulnerabilities caused by meteorological variations in different regions of Ecuador and highlights the importance of agriculture in this context. For this purpose, a statistical model combining ARIMA method, Bayesian optimization and XGBoost models is proposed to predict rainfall behavior. On the basis of the results obtained in the study, we can predict the adjacent behavior of rainfall in a temporal margin that goes up to the month of December of the year 2024. This constitutes an essential resource for the choice of more favorable decisions and thus benefit the agricultural area in the ability to adapt to unfavorable climatic events.
MATRIX METHOD FOR EVALUATION BASED ON EIGENVALUES AND EIGENVECTORS
In response to various causes leading to poor academic performance among students in Mathematics, the objective was to establish a matrix method metric for assessing Complex Mathematics learning; taking into account attitudinal, procedural, and cognitive axes, as well as conceptual, algebraic, and graphic-numerical aspects, i.e., a 3x3 matrix that allowed for the collection of specific data. Following the application of experimental trials focused on the acquisition, processing, and interpretation of numerical data, the result was two specific evaluation matrices. A "state matrix" describes the student's knowledge before the activity's execution and another at the trial's end, which allows for the comparison of knowledge before and after, expressing it as the extremes of a Markov chain; also, comparing it with other existing evaluation metrics, with the matrices serving as a grading rubric that helps identify shortcomings and propose improvements. Through a program in MATH LAB, a second outcome in the form of a "Transformation Matrix" was identified, which determines the evolution of the state matrix, i.e., quantitatively visualizes learning and thus measures the academic activity's efficiency. This involved analyzing the existence of eigenvalues and eigenvectors, which are interpreted in the discussion stage.
Systematic review of the cotton dyeing process with reactive dyes to optimize dye kinetics in the adsorption phase.
The adsorption phase and dye kinetics, as correlated elements in a reactive dyeing process on cotton fibers, are of vital importance. Not only are they crucial for the dyeing process itself, but also a proper and conscious use of the components involved in the dye recipe, a process curve adjusted to the realities of equipment, machinery, and processes, as well as a suitable selection of dyes and auxiliaries, will allow for the optimal utilization of color on the fiber. This is why, after a systematic literature review, several authors address these two topics as fundamental elements to be considered in a process, as they contribute to reducing dyeing time, achieving proper color matching on the fiber, and, above all, maximizing the use of dyes and auxiliaries, thereby minimizing waste. Subsequently, this facilitates more efficient, environmentally friendly, and natural water recovery processes.
Guardián Comunitario: Innovación en seguridad y respuesta rápida a emergencias
This work focuses on the development of a mobile panic button application to meet the security and rapid emergency response needs of the Ainche community in Chimborazo province. Field research was conducted to analyze the importance of the application and user satisfaction; additionally, a bibliographic review was carried out on agile software development methodologies. Guardian Comunitario is a mobile application developed using the SCRUM methodology, which contributes to the community's security and emergency response. To evaluate its impact, a satisfaction survey was conducted, showing that 60% of respondents consider the application easy to use; 80% perceive an improvement in communication between community members and emergency services; furthermore, the response time to emergencies was reduced from 20 to 10 minutes
Advanced Optimization and Numerical Simulation of a Pump as Turbine System
Flying Aerial Laboratory for water sampling in the Amazon Region of Ecuador
This paper presents a brief research related to the environmental problem of preventive monitoring of water sources in the Amazon region of Ecuador. As consequence, a proposal for an effective strategy is presented through the implementation of an Intelligent Aerial Laboratory LAI, consisting of an Unmanned Aerial Vehicle RPA and a water sample collection system. In order to guarantee an autonomous remote monitoring of aquatic environments, the LAI integrates a Human-Machine interface HMI that allows the operator on land station to interact through long-range communication protocols with the LAI, which fulfills its functionality through an integrated hardware and software architecture on board. This work presents the assembled LAI prototype, results of its exploitation in real conditions for physicochemical properties sensing, as well as a reflection towards future work on this topic.
Influence of Frequency and Injection Time on the Performance of CRDi Injectors
The article analyzes the influence of injection frequency and timing on the performance of electronic injectors. In the experimental process, two independent variables and three dependent variables were controlled, obtaining the amount of delivery, fuel return, and rail pressure using injection pulse simulation equipment. Tests were carried out with different combinations of time and frequency. The results showed that frequency has a significant influence on the amount of injection and fuel return, being the most relevant variable. It was found that fuel delivery increases as a function of time and frequency, with 1.5 ms being the point where the highest delivery was obtained when varying from 5 to 20 Hz. In addition, the rail pressure showed an inverse relationship with injection time and frequency, decreasing by 17.5%, 11.1%, 11.4%, and 11.7% at values of 5, 10, 15, and 20 Hz, respectively. Statistical analysis revealed that the adjusted models effectively explain the variability in fuel delivery and rail pressure.
Copyright (c) 2025 Carlos Mafla, Cesar Morales, Jorge Melo, Paul Hernández, Jesús Mafla https://creativecommons.org/licenses/by-nc-nd/4.0
Expanding technological horizons from the implementation of an ecosystem of virtual learning resources for university students
During the pandemic, universities had to change their teaching modality from face-to-face to virtual. This limited the opportunity to learn about digital manufacturing technologies in an experiential way. In response to this, the "Ruta Maker" program was adapted by incorporating ecosystems of learning resources for digital manufacturing. The objective was to know, in the students of the "Ruta Maker" program, the scope of a comprehensive ecosystem of virtual learning resources in strengthening technological skills, in adopting a maker in-house and DIY culture, and in the construction of open source digital manufacturing machines. It is a cross-sectional study, with intentional sampling, where four instruments were applied to 48 university students of the "Ruta Maker" program. Adequate level of learning was achieved in the program. On axis 1 "4.0 technological skills" the dimension "2D and 3D design" stood out (83%). On axis 2 "Experimentation spaces", the dimension "CNC MASLOW layout" had a better result than the other dimensions (83%). On axis 3 "DIY Culture Digital Manufacturing Machines", the two dimensions had similar achievements (73% and 71%). Student satisfaction values the Fabber Tech team and the accompaniment/prototyping more. In conclusion, digital manufacturing learning ecosystems in virtual modality, is a pedagogical option that allows digital design and manufacturing at home, promoting the Maker-DIY culture.
Economic Impact of Ecuador's Largest Christmas Tree on Entrepreneurship - Cuenca 2022
Seasonal tourist attractions became a source of work and economic development, which is why entertainment spaces are created during the Christmas season. The objective of the study is to analyze the economic impact of the Largest Christmas Tree in Ecuador on the enterprises located in the Miraflores park in the city of Cuenca 2022. The methodology was quantitative and qualitative with descriptive and phenomenological scope, with a non-experimental research design. cross-sectional, to collect information a questionnaire was used applied to a population of 43 entrepreneurs and a simple random sample of 28 involved. The results reveal that the average daily income of the entrepreneurs is less than $300, while they have the same monthly income, but they earn payment amounts for basic services and taxes. In conclusion, the activities generated in the temporary attractions enhance domestic tourism and entrepreneurs benefit because their economic income is strengthened in the event of the largest Christmas tree in Ecuador.