Castillo Salazar, David Ricardo
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Castillo Salazar, David Ricardo
Main Affiliation
Ambato
Email
davidcastillo@uti.edu.ec
Scopus Author ID
57210800584

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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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Autonomous Learning Mediated by Digital Technology Processes in Higher Education: A Systematic Review

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

The concept of autonomous learning has been resignified in recent years as a result of the expansion of the different types of study. Online education in higher education institutions has become an effective option to increase and diversify opportunities for access and learning, however, high rates of dropout, reprisal and low averages still persist. academic performance. Recent research shows that the problem is accentuated because most students have difficulty self-regulating their own learning process autonomously. From this perspective, the purpose of the study was to examine and analyze, through a systematic review of the literature, on autonomous/self-regulated learning, theoretical models and determine which variables influence a learning process mediated by technology processes in the higher education. The findings indicate that: (1) autonomous learning is a synonym of self-regulation; (2) Pintrich’s self-regulatory model is the most used in digital contexts; and (3) the self-regulatory variables identified are wide and varied. © 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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Control of an Arm-Hand Prosthesis by Mental Commands and Blinking

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

Patients who lack upper and lower extremities have difficulties in carrying out their daily activities. The new technological advances have allowed the development of robotic applications to support people with disabilities, also, portable electroencephalographic (EEG) sensors are increasingly accessible and allow the development of new proposals which involve the mental control of electronic systems. This work presents the control by mental orders of an arm-hand prosthesis using low-cost devices, the objective is to command the arm using the user’s attention and blinking, where the components are a brain signal sensor, a prosthesis, an Arduino board, six servomotors, and a computer. The developed program in Matlab allows controlling the arm by means of an attention level y blinking. The results show the functioning of the system through experimental tests and a usability test is applied, finally, the conclusions establish adequate coordination in the movements of the prosthesis and the patient indicate satisfaction with the proposal. © Springer Nature Switzerland AG 2020.

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