Guevara Maldonado, César Byron

Preferred name

Main Affiliation

Centro de investigación en Mecatrónica y Sistemas Interactivos

Quito

cesarguevara@uti.edu.ec

ORCID

0000-0003-1571-5829

Scopus Author ID

56452706300

Now showing 1 - 10 of 47

Some of the metrics are blocked by your
consent settings
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.
Scopus© Citations 11 20
Some of the metrics are blocked by your
consent settings
Development of a Convolutional Neural Network for Detection of Ovarian Cancer Based on Computed Tomography Images
(2024)
Gabriela Narvaez-Chunillo
;
Ronny Ordoñez-Sanchez
;
Lizbeth Ortiz-Vinueza
;
Diego Almeida-Galárraga
;
Fernando Villalba-Meneses
Ovarian cancer is one of the most frequent gynecologic malignancies in women, but it is often detected in late stage, leaving patients with little time to follow a successful therapy. Specialists have opted to use computer-aided diagnosis (CAD) for the detection of ovarian cancer through the analysis of computed tomography (CT) images, in which the professional examines the size, shape and different characteristics that enable a precise diagnosis in the ovary. This present project purposes a Convolutional Neural Network (CNN) which consist on four convolutional layers; including two pooling layer and two fully-connected layer. The cancerous ovaries images is selected from the Cancer Imaging Achive dataset for training and validation of the model. Moreover, the training of the CNN contain filters to ensure that all of the images are the same dimensions and pixel size. The testing results from the training of the images showed that the proposed model obtained a range of accuracy that goes from 90.0% to the best of the cases 98.85%. The variables obtained like the data of the pressure and loss of the training were compared with those of the validation, allowing for the determination of a successful CNN training.
15
Some of the metrics are blocked by your
consent settings
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.
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.
25
Some of the metrics are blocked by your
consent settings
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.
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.
20
Some of the metrics are blocked by your
consent settings
Health Impact of Gnathostomiasis and its Integral Approach to Parasitic Infection: A Systematic Review
(2024)
Gisnella María Cedeño Cajas
;
José Andrés Zaporta Ramos
;
Andrea Stefannia Flores Villacrés
;
Guevara Maldonado, César Byron
The present study focuses on gnathostomiasis, a parasitic disease caused by the nematode gnathostoma that affects both humans and other animals, with a prevalence of 0,14 %. The aim of the study is to analyze the main research related to gnathostomiasis, its diagnosis and treatment. To achieve this objective, a systematic review of clinical cases, observational and retrospective studies of the disease was carried out, following the PRISMA methodology. The literature search, conducted between 2018 and 2022 in the Web of Science, Scopus, PubMed, Redalyc and Dialnet databases, resulted in the identification of five articles relevant and pertinent to the topic. The study findings indicate that gnathostomiasis, on the rise in Latin America and Asia, is transmitted mainly through the consumption of raw fish infected with Gnathostoma larvae. Although preventive measures and treatments, such as albendazole, are available, their efficacy is limited, and it is difficult to implement changes in dietary habits. Therefore, more research is needed to better understand the disease, develop more effective diagnostics and treatments, and raise awareness among physicians of its increasing global prevalence.
15
Some of the metrics are blocked by your
consent settings
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.
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.
38
Some of the metrics are blocked by your
consent settings
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.
22
Some of the metrics are blocked by your
consent settings
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.
30
Some of the metrics are blocked by your
consent settings
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.
19
Some of the metrics are blocked by your
consent settings
Unlocking the puzzle: non-defining mutations in SARS-CoV-2 proteome may affect vaccine effectiveness
(2024)
Eugenia Ulzurrun
;
Ana Grande-Pérez
;
Daniel del Hoyo
;
Guevara Maldonado, César Byron
;
Carmen Gil
Introduction: SARS-CoV-2 variants are defined by specific genome-wide mutations compared to the Wuhan genome. However, non-clade-defining mutations may also impact protein structure and function, potentially leading to reduced vaccine effectiveness. Our objective is to identify mutations across the entire viral genome rather than focus on individual mutations that may be associated with vaccine failure and to examine the physicochemical properties of the resulting amino acid changes. Materials and methods: Whole-genome consensus sequences of SARS-CoV-2 from COVID-19 patients were retrieved from the GISAID database. Analysis focused on Dataset_1 (7,154 genomes from Italy) and Dataset_2 (8,819 sequences from Spain). Bioinformatic tools identified amino acid changes resulting from codon mutations with frequencies of 10% or higher, and sequences were organized into sets based on identical amino acid combinations. Results: Non-defining mutations in SARS-CoV-2 genomes belonging to clades 21 L (Omicron), 22B/22E (Omicron), 22F/23A (Omicron) and 21J (Delta) were associated with vaccine failure. Four sets of sequences from Dataset_1 were significantly linked to low vaccine coverage: one from clade 21L with mutations L3201F (ORF1a), A27- (S) and G30- (N); two sets shared by clades 22B and 22E with changes A27- (S), I68- (S), R346T (S) and G30- (N); and one set shared by clades 22F and 23A containing changes A27- (S), F486P (S) and G30- (N). Booster doses showed a slight improvement in protection against Omicron clades. Regarding 21J (Delta) two sets of sequences from Dataset_2 exhibited the combination of non-clade mutations P2046L (ORF1a), P2287S (ORF1a), L829I (ORF1b), T95I (S), Y145H (S), R158- (S) and Q9L (N), that was associated with vaccine failure. Discussion: Vaccine coverage associations appear to be influenced by the mutations harbored by marketed vaccines. An analysis of the physicochemical properties of amino acid revealed that primarily hydrophobic and polar amino acid substitutions occurred. Our results suggest that non-defining mutations across the proteome of SARS-CoV-2 variants could affect the extent of protection of the COVID-19 vaccine. In addition, alteration of the physicochemical characteristics of viral amino acids could potentially disrupt protein structure or function or both.
11

Guevara Maldonado, César Byron

Filters

Settings

Sort By

Results per page