Guevara Maldonado, César Byron
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Guevara Maldonado, César Byron
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Quito
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cesarguevara@uti.edu.ec
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56452706300

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Editorial Design Based on User Experience Design

2020 , Borja Galeas, Carlos , Guevara Maldonado, César Byron , Castillo Salazar, David Ricardo , Arias Flores, Hugo Patricio , Fierro-Saltos, W. , Rivera, R. , Yandún-Velasteguí, M. , Varela Aldas, José , Hidalgo-Guijarro J.

This research deals with editorial design based on user experience design. The traditional editorial design has had to adapt to the new digital media composition, where multimedia audiovisual elements unthinkable a few years ago need to be integrated. The participation of the reader, as an external observer who only receives information through texts and images, now has new scenarios in which he can actively participate and decide what will come to his hands. In this study, a work methodology based on UxD User Experience Design is presented, in which will generate the editorial design of an educational book on environmental issues, which includes augmented reality for children from 6 to 8 years of age. The aim of this study is to know if an editorial product with augmented reality and developed from the user experience design can improve meaningful learning in a playful and active way. For its development, a composition model based on the Fibonacci sequence and the golden ratio will be used. Additionally, its graphic composition will be guided by the Massimo Vignelli canon and will be complemented by the reticular model of Beth Tondreau. The augmented reality markers position will also be based on the composition model previously mentioned, which will allow keeping the attention of the reader in the printed document and in the augmented reality animations. The user experience design will be applied with teachers, parents and students from 4 schools in Quito and Ambato. Once the production is completed, the impact on teaching-learning process will be evaluated with a control and a test group, and the methodology with which they will work in the classroom with the educational material developed will be defined. At the end of the study, copies of the book will be delivered to the participating schools of this research for its implementation. © Springer Nature Switzerland AG 2020.

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BackMov: Individualized Motion Capture-Based Test to Assess Low Back Pain Mobility Recovery after Treatment

2024 , Villalba-Meneses F. , Guevara Maldonado, César Byron , Velásquez-López P.A. , Arias-Serrano I. , Guerrero-Ligña S.A. , Valencia-Cevallos C.M. , Almeida-Galárraga D. , Cadena-Morejón C. , Marín J., Marín J.J.

Low back pain (LBP) is a common issue that negatively affects a person’s quality of life and imposes substantial healthcare expenses. In this study, we introduce the (Back-pain Movement) BackMov test, using inertial motion capture (MoCap) to assess lumbar movement changes in LBP patients. The test includes flexion–extension, rotation, and lateralization movements focused on the lumbar spine. To validate its reproducibility, we conducted a test-retest involving 37 healthy volunteers, yielding results to build a minimal detectable change (MDC) graph map that would allow us to see if changes in certain variables of LBP patients are significant in relation to their recovery. Subsequently, we evaluated its applicability by having 30 LBP patients perform the movement’s test before and after treatment (15 received deep oscillation therapy; 15 underwent conventional therapy) and compared the outcomes with a specialist’s evaluations. The test-retest results demonstrated high reproducibility, especially in variables such as range of motion, flexion and extension ranges, as well as velocities of lumbar movements, which stand as the more important variables that are correlated with LBP disability, thus changes in them may be important for patient recovery. Among the 30 patients, the specialist’s evaluations were confirmed using a low-back-specific Short Form (SF)-36 Physical Functioning scale, and agreement was observed, in which all patients improved their well-being after both treatments. The results from the specialist analysis coincided with changes exceeding MDC values in the expected variables. In conclusion, the BackMov test offers sensitive variables for tracking mobility recovery from LBP, enabling objective assessments of improvement. This test has the potential to enhance decision-making and personalized patient monitoring in LBP management. © 2024 by the authors.

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Multisensory learning system applying augmented reality

2020 , Guevara Maldonado, César Byron , Coronel, D.M.V.

Mathematics is essential in our daily life. However, traditional teaching methods are mainly limited to the use of textbooks, generating demotivation and low interest in learning the subject. The present study proposes the development of an augmented reality system for the multi-sensory learning of students in the field of mathematics. For the creation of this proposal, we have used a human–computer interface tool called Makey Makey. Besides, the Singapore method, which has produced excellent results in the learning of mathematics, is applied. Scratch, a programming language that allows people to develop applications without having deep knowledge of the code, was used for the development of the application. Scratch allows us to combine Singapore, Makey Makey, and Augmented Reality optimally for learning. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2020.

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Analysis and design of an internal Top-Down network applying international standards [Análisis y diseño de una red interna Top-Down aplicando estándares internacionales]

2023 , Almeida A. , Suarez B. , Guevara Maldonado, César Byron , Coronel D. , Hidalgo J.

Telecommunications networks have become something essential within public or private companies, since they contribute to technological development. A network infrastructure with adequate cabling structured together with rules and standards enables the integration of multiple technologies and services. Currently, most institutions in Latin American countries do not apply norms, standards or good practices in their design, due to lack of knowledge or to save resources, without understanding that this generates an unreliable and unstable network infrastructure. Consequently, this study focuses on the design, architecture and administration of the network of a public institution in the city of Tulcán-Ecuador. The main objective of this proposal was the design of a network infrastructure that facilitates the administration of the network at a logical and physical level, taking into account the requirements and facilities of the institution. This network proposal applied the Top-Down Network Design By Cisco methodology to design a centralized, stable, flexible, and secure network. In addition, different international network design and management standards and regulations (ANSI/TIA/EIA/ISO) were used to generate a high-quality network. © 2023 ITMA.

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Framework based on gestalt principles to design mobile interfaces for a better user experience

2020 , Ripalda D. , Guevara Maldonado, César Byron , Garrido A.

This paper presents the results of the user experience test comparing a real functional application and a high fidelity prototype that used a Framework to design graphic user interfaces on mobile devices. This Framework links Nielsen’s heuristics with the principles of perception of Gestalt, offering to developers and usability experts, references to generate and evaluate mockups and prototypes. The constructive and evaluative model of the Framework allows to recognize usability criteria in visual components of the interfaces, during the initial phases of a project that uses agile software development methodologies, reducing the “trial - error” regressions. The experiment allowed obtaining data about satisfaction measures and specific user attitudes regarding the interfaces developed. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2020.

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The triple helix model linked to knowledge transfer and economic progress from universities [El modelo de la triple hélice vinculado a la transferencia de conocimiento y progreso económico desde las universidades]

2023 , Bonilla-Jurado, Diego , Guevara Maldonado, César Byron , Montero I.K.S. , Pazmiño S.J.I. , Zuta M.E.C.

The strategic actions that are being developed from the Ecuadorian universities, are heading towards the linking of innovative factors under an interrelated scheme known as Triple Helix, whose intention is framed in connecting entrepreneurship, using knowledge and society as a platform, generating a model sustainable development between university-state-business. The objective of this research is to show the relationship between university-company-state with entrepreneurial research through the triple helix functional model, with a view to innovative potentializing that serves as a boost to socioeconomic progress. The research approach is qualitative at a descriptive level, using a hermeneutical review focused on entrepreneurship studies, business and university alliances, government plans and the triple helix theory. The results indicate that scientific research based on the triple helix method should be strengthened, the main obstacles being lack of communication, business disinterest and distorted state policies. The Ecuadorian universities UEM, UTB and UEB must make concerted efforts so that the investigations are directed towards the true social needs of each area. The conclusions indicate that the links of the triple helix model lead to socioeconomic strengthening through the development of research and scientific projects, without neglecting technological advances. © Este es un artículo en acceso abierto.

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Development of Behavior Profile of Users with Visual Impairment

2020 , Guevara Maldonado, César Byron , Arias Flores, Hugo Patricio , Varela Aldas, José , Castillo Salazar, David Ricardo , Borja M. , Fierro-Saltos W. , Rivera R. , Hidalgo-Guijarro J. , Yandún-Velasteguí M.

The interaction of the user with visual impairment with assistive technologies, and in particular with screen readers, generates a group of actions and events during their navigation. These interactions are defined as behavioral patterns, which have a sequence that occurs at specific time slot. Understanding user behavior by analyzing their interaction with applications, in addition, details the characteristics, relationships, structures and functions of the sequence of actions in a specific application domain. The objective of this document is to find activity patterns from a set of commands used by the user, combining data mining and a Bayesian model. This model calculates the probability of the functions used with the screen reader and generates a behavior profile to improve the user experience. For this study, the screen reader JAWS version 2018, the Open Journal Systems platform version 3.0.1 and a computer with Windows 10 operating system were used. During the first phase, command history used by the user by interacting with the Open Journal Systems platform were collected. The result is that the accessibility of users with visual impairment to interact with the computer and its applications has been improved by applying this model. © Springer Nature Switzerland AG 2020.

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Twitter Mining for Multiclass Classification Events of Traffic and Pollution

2020 , Chamorro V. , Rivera R. , Varela Aldas, José , Castillo Salazar, David Ricardo , Borja Galeas, Carlos , Guevara Maldonado, César Byron , Arias Flores, Hugo Patricio , Fierro-Saltos W. , Hidalgo-Guijarro J. , Yandún-Velasteguí M.

During the last decade social media have generated tons of data, that is the primal information resource for multiple applications. Analyzing this information let us to discover almost immediately unusual situations, such as traffic jumps, traffic accidents, state of the roads, etc. This research proposes an approach for classifying pollution and traffic tweets automatically. Taking advantage of the information in tweets, it evaluates several machine learning supervised algorithms for text classification, where it determines that the support vector machine (SVM) algorithm achieves the highest accuracy value of 85,8% classifying events of traffic and not traffic. Furthermore, to determine the events that correspond to traffic or pollution we perform a multiclass classification. Where we obtain an accuracy of 78.9%. © Springer Nature Switzerland AG 2020.

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Emotion classification using EEG headset signals and Random Forests [Clasificación de emociones utilizando señales de auriculares EEG y Random Forests]

2023 , Vasquez R. , Carrion-Jumbo J. , Riofrio-Luzcando D. , Guevara Maldonado, César Byron

Emotions are one of the important components of the human being, thus they are a valuable part of daily activities such as interaction with people, decision making and learning. For this reason, it is important to detect, recognize and understand emotions using computational systems to improve communication between people and machines, which would facilitate the ability of computers to understand the communication between humans. This study proposes the creation of a model that allows the classification of people's emotions based on their EEG signals, for which the brain-computer interface EMOTIV EPOC was used. This allowed the collection of electroencephalographic information from 50 people, all of whom were shown audiovisual resources that helped to provoke the desired mood. The information obtained was stored in a database for the generation of the model and the corresponding classification analysis. Random Forest model was created for emotion prediction (happiness, sadness and relaxation), based on the signals of any person. The results obtained were 97.21% accurate for happiness, 76% for relaxation and 76% for sadness. Finally, the model was used to generate a real-time emotion prediction algorithm; it captures the person's EEG signals, executes the generated algorithm and displays the result on the screen with the help of images representative of each emotion. © 2023 ITMA.

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Classification of the Pathological Range of Motion in Low Back Pain Using Wearable Sensors and Machine Learning

2024 , Villalba-Meneses F. , Guevara Maldonado, César Byron , Lojan A.B. , Gualsaqui M.G. , Arias-Serrano I. , Velásquez-López P.A. , Almeida-Galárraga D. , Tirado-Espín A. , Marín J., Marín J.J.

Low back pain (LBP) is a highly common musculoskeletal condition and the leading cause of work absenteeism. This project aims to develop a medical test to help healthcare professionals decide on and assign physical treatment for patients with nonspecific LBP. The design uses machine learning (ML) models based on the classification of motion capture (MoCap) data obtained from the range of motion (ROM) exercises among healthy and clinically diagnosed patients with LBP from Imbabura–Ecuador. The following seven ML algorithms were tested for evaluation and comparison: logistic regression, decision tree, random forest, support vector machine (SVM), k-nearest neighbor (KNN), multilayer perceptron (MLP), and gradient boosting algorithms. All ML techniques obtained an accuracy above 80%, and three models (SVM, random forest, and MLP) obtained an accuracy of >90%. SVM was found to be the best-performing algorithm. This article aims to improve the applicability of inertial MoCap in healthcare by making use of precise spatiotemporal measurements with a data-driven treatment approach to improve the quality of life of people with chronic LBP. © 2024 by the authors.

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