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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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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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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Preprocessing Information from a Data Network for the Detection of User Behavior Patterns

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

This study focuses on the preprocessing of information for the selection of the most significant characteristics of a network traffic database, recovered from an Ecuadorian institution, using a method of classifying optimal entities and attributes, with the In order to achieve a complete understanding of its real composition to be able to generate patterns and identification of trends of behavior in the network, both of patterns that deviate from normal traffic behavior (intrusive), as well as normal, to detect with high precision possible attacks. Network management tools were used as a multifunctional security server software, as well as pre-processing of data tools for the selection of attributes, as well as the elimination of noise from the instances of the database, It allowed to identify which ins- tances and attributes are correct and contribute with effective information in the study. Among them we have: Greedy Stepwise Algorithm (Algoritmo Voráz), K-Means Algorithm, Discrete Chi-square Attributes and the use of computational models as Evolutionary Neural Networks and Gene Algorithms. © Springer Nature Switzerland AG 2020.

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Mathematical model of intrusion detection based on sequential execution of commands applying pagerank

2020 , Guevara Maldonado, César Byron , Hidalgo, J. , Yandún, M. , Arias Flores, Hugo Patricio , Zapata-Saavedra, L. , Ramirez-Morales, I. , Aguilar-Galvez, F. , Chalco-Torres, L. , Ortiz, D.P.

Cybersecurity in networks and computer systems is a very important research area for companies and institutions around the world. Therefore, safeguarding information is a fundamental objective, because data is the most valuable asset of a person or company. Users interacting with multiple systems generate a unique behavioral pattern for each person (called digital fingerprint). This behavior is compiled with the interactions between the user and the applications, websites, communication equipment (PCs, mobile phones, tablets, etc.). In this paper the analysis of eight users with computers with a UNIX operating system, who have performed their tasks in a period of 2 years, is detailed. This data is the history of use in Shell sessions, which are sorted by date and token. With this information a mathematical model of intrusion detection based on time series behaviors is generated. To generate this model a data pre-processing is necessary, which it generates user sessions (Equation presented), where u identifies the user and m the number of sessions the user u has made. Each session (Equation presented) contains a sequence of execution of commands (Equation presented), that is (Equation presented), where n is the position in wich the C command was executed. Only 17 commands have been selected, which are the most used by each user u. In the creation of the mathematical model we apply the page Rank algorithm [1], the same that within a command execution session (Equation presented), determines which command (Equation presented) calls another command (Equation presented), and determines which command is the most executed. For this study we will perform a model with sb subsequences of two commands, (Equation presented), where the algorithm is applied and we obtain a probability of execution per command defined by (Equation presented). Finally, a profile is generated for each of the users as a signal in time series, where maximum and minimum normal behavior is obtained. If any behavior is outside those ranges, it is determined as intrusive behavior, with a detection probability value. Otherwise, it is determined that the behavior is normal and can continue executing commands in a normal way. The results obtained in this model have shown that the proposal is quite effective in the testing phase, with an accuracy rate greater than 90% and a false positive rate of less than 4%. This shows that our model is effective and adaptable to the dynamic behavior of the user. On the other hand, a variability in the execution of user commands has been found to be quite high in periods of short time, but the proposed algorithm tends to adapt quite optimally. © Springer Nature Switzerland AG 2020.

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Editorial design of interactive picture book with mobile application based on uxd user experience design

2020 , Borja Galeas, Carlos , Guevara Maldonado, César Byron , Amagua M.

This research presents an interactive human-computer learning system model applying adaptive editorial design. The proposal aims to generate an interactive picture book and a mobile application based on user experience design (UxD). The results will be obtained using UX metrics and will have the particularity of working with the technique of participatory design and reticular deconstruction. This book includes its presentation as an audiobook and an editorial composition with pop-ups and pages to paint. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2020.

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Building hybrid interfaces to increase interaction with young children and children with special needs

2020 , Jadán Guerrero, Janio , Guevara Maldonado, César Byron , Lara Álvarez, Patricio , Sanchez-Gordon, S. , Calle-Jimenez, T. , Salvador-Ullauri, L. , Acosta-Vargas, P. , Bonilla-Jurado, Diego

Young children as well as children with special educational needs learn from their environment with social, emotional and physical stimuli. In this context, educational resources and teaching strategies play a main role for them in order to understand the new information. This paper describes the experience of building hybrid interfaces that combine technology with traditional educational resources. A total of 60 teachers divided in two groups completed some tasks which consisted of generating new educative resources with tecnology. Through Design Thinking methodology, teachers designed three hybrid interfaces: 1. Interactive books, combining traditional fairy tales books with mobile devices, where QR codes and NFC tags give life to the stories; 2. Educational Board Games, where augmented reality markers give an extra information to the players; 3. Tangible educational resources, which integrate Makey-Makey device and Scratch with fruit, clay, aluminum foil or water to build laboratory. © 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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Surveillance Routing of COVID-19 Infection Spread Using an Intelligent Infectious Diseases Algorithm

2020 , Guevara Maldonado, César Byron , Penas M.S.

In this study, the Intelligent Infectious Diseases Algorithm (IIDA) has been developed to locate the sources of infection and survival rate of coronavirus disease 2019 (COVID-19), in order to propose health care routes for population affected by COVID-19. The main goal of this computational algorithm is to reduce the spread of the virus and decrease the number of infected people. To do so, health care routes are generated according to the priority of certain population groups. The algorithm was applied to New York state data. Based on infection rates and reported deaths, hot spots were determined by applying the kernel density estimation (KDE) to the groups that have been previously obtained using a clustering algorithm together with the elbow method. For each cluster, the survival rate - the key information to prioritize medical care - was determined using the proportional hazards model. Finally, ant colony optimization (ACO) and the traveling salesman problem (TSP) optimization algorithms were applied to identify the optimal route to the closest hospital. The results obtained efficiently covered the points with the highest concentration of COVID-19 cases. In this way, its spread can be prevented and health resources optimized. © 2013 IEEE.

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Biomechanical Study of the Eye with Keratoconus-Type Corneal Ectasia Using a 3D Geometric Model

2023 , Sánchez-Real E. , Otuna-Hernández D., , Fajardo-Cabrera A. , Davies-Alcívar R. , Madrid-Pérez M. , Cadena-Morejón C. , Almeida-Galárraga D. , Guevara Maldonado, César Byron , Tirado-Espín A. , Villalba-Meneses F.

Keratoconus is an eye disease that distorts the shape of the cornea. This study aimed to analyze the effect of an increase in intraocular pressure applied to eyes with different severity of keratoconus disease using patient-specific models. Finite element models of the normal eye, eye with keratoconus, and eye with keratoglobus were constructed. The loading conditions considered the intraocular pressure increment as well as their physiological intraocular pressure. The analysis was performed with distinct materials for normal and keratoconic eyes. The finite element analysis revealed differences in the three models in terms of their deformation and maximum principal stress, and differences were observed in corneal curvature and thickness. These findings could enhance research in the biomechanical area, leading to more successful treatment options and a more individualized approach in the field of practical ophthalmology. Further investigation with larger sample sizes and more precise data on eye material would allow us to evaluate whether these disparities could inform the diagnosis of keratoconus. © 2023 by the authors.

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