Browsing by Author "Tavera Romero, Carlos Andrés"
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Item A depth-controlled and energy-efficient routing protocol for underwater wireless sensor networks(2022-09) Lilhore, Umesh Kumar; Khalaf, Osamah Ibrahim; Simaiya, Sarita; Tavera Romero, Carlos Andrés; Abdulsahib, Ghaida Muttashar; Poongodi M.; Kumar, DineshUnderwater wireless sensor network attracted massive attention from researchers. In underwater wireless sensor network, many sensor nodes are distributed at different depths in the sea. Due to its complex nature, updating their location or adding new devices is pretty challenging. Due to the constraints on energy storage of underwater wireless sensor network end devices and the complexity of repairing or recharging the device underwater, this is highly significant to strengthen the energy performance of underwater wireless sensor network. An imbalance in power consumption can cause poor performance and a limited network lifetime. To overcome these issues, we propose a depth controlled with energy-balanced routing protocol, which will be able to adjust the depth of lower energy nodes and be able to swap the lower energy nodes with higher energy nodes to ensure consistent energy utilization. The proposed energy-efficient routing protocol is based on an enhanced genetic algorithm and data fusion technique. In the proposed energy-efficient routing protocol, an existing genetic algorithm is enhanced by adding an encoding strategy, a crossover procedure, and an improved mutation operation that helps determine the nodes. The proposed model also utilized an enhanced back propagation neural network for data fusion operation, which is based on multi-hop system and also operates a highly optimized momentum technique, which helps to choose only optimum energy nodes and avoid duplicate selections that help to improve the overall energy and further reduce the quantity of data transmission. In the proposed energy-efficient routing protocol, an enhanced cluster head node is used to select a strategy that can analyze the remaining energy and directions of each participating node. In the simulation, the proposed model achieves 86.7% packet delivery ratio, 12.6% energy consumption, and 10.5% packet drop ratio over existing depth-based routing and energy-efficient depth-based routing methods for underwater wireless sensor network.Item A hybrid metaheuristic based on neurocomputing for analysis of unipolar electrohydrodynamic pump flow(2021-11) Khan, Muhammad Fawad; Sulaiman, Muhammad; Tavera Romero, Carlos Andrés; Alkhathlan, AliA unipolar electrohydrodynamic (UP-EHD) pump flow is studied with known electric potential at the emitter and zero electric potential at the collector. The model is designed for electric potential, charge density, and electric field. The dimensionless parameters, namely the electrical source number (Es ), the electrical Reynolds number (ReE ), and electrical slip number (Esl ), are considered with wide ranges of variation to analyze the UP-EHD pump flow. To interpret the pump flow of the UP-EHD model, a hybrid metaheuristic solver is designed, consisting of the recently developed technique sine–cosine algorithm (SCA) and sequential quadratic programming (SQP) under the influence of an artificial neural network. The method is abbreviated as ANN-SCA-SQP. The superiority of the technique is shown by comparing the solution with reference solutions. For a large data set, the technique is executed for one hundred independent experiments. The performance is evaluated through performance operators and convergence plots.Item A Mobile Application Prototype Designed to Support Physical Therapy Assessment Learning Processes(International Journal of Interactive Mobile Technologies, 2023-08-21) Tavera Romero, Carlos Andrés; Jaramillo Losada, Jennifer; Díaz Velásquez, María Fernanda; Domínguez Pineda, Andrés Gerardo; Hurtado López, Victor ManuelThe present work is the result of applied research, which describes how the physical therapy program at the Universidad Santiago de Cali approached the support of the learning pro-cesses from the Guide to Physical Therapist Practice issued by the American Physical Therapy Association (APTA) from a teaching perspective using information technologies with an emphasis on mobile devices (D-Learning). The implementation process was conducted using the PSP (Personal Software Process) methodology, condensing its six characteristic moments to address the problem in four stages: planning, design, development, and validation, corre-sponding to phases 2 and 3 of the interdisciplinary project developed by and between the Schools of Engineering and Health Sciences, thereby understanding that the remaining phases exceed the scope of this paper (these phases include a systematic review, an analysis, and feedback from the academic community). A preliminary assessment describes the knowledge gathering and idea conception processes, as well as the solution design process in Enterprise Architect. Subsequently, the prototype was implemented, the corresponding documentation was prepared, and its usability was validated by the academic community at the university. Therefore, a supporting tool was generated, focusing specifically on learning about the Guide to Physical Therapist Practice.Item Acerca de autores y pares evaluadores - Estudio comparativo entre lenguajes textuales y lenguajes visuales: caso PiCO y GraPICO(Editorial Universidad Santiago de Cali, 2018) Espinosa Galliady, Luis Eduardo; Cano Castillo, Christian Felipe; Tavera Romero, Carlos Andrés; Cruz Pérez, Yenny Viviana; Penagos Muñoz, Juan David; Ramírez Arcila, Paola Andrea; Triana Lozano, Marco AntonioItem Analysis of Nanofluid Particles in a Duct with Thermal Radiation by Using an Efficient Metaheuristic-Driven Approach(MDPI, 2022) Khan, Naveed Ahmad; Sulaiman, Muhammad; Tavera Romero, Carlos Andrés; Alshammari, Fahad SameerThis study investigated the steady two-phase flow of a nanofluid in a permeable duct with thermal radiation, a magnetic field, and external forces. The basic continuity and momentum equations were considered along with the Buongiorno model to formulate the governing mathematical model of the problem. Furthermore, the intelligent computational strength of artificial neural networks (ANNs) was utilized to construct the approximate solution for the problem. The unsupervised objective functions of the governing equations in terms of mean square error were optimized by hybridizing the global search ability of an arithmetic optimization algorithm (AOA) with the local search capability of an interior point algorithm (IPA). The proposed ANN-AOA-IPA technique was implemented to study the effect of variations in the thermophoretic parameter (Nt), Hartmann number (Ha), Brownian (Nb) and radiation (Rd) motion parameters, Eckert number (Ec), Reynolds number (Re) and Schmidt number (Sc) on the velocity profile, thermal profile, Nusselt number and skin friction coefficient of the nanofluid. The results obtained by the designed metaheuristic algorithm were compared with the numerical solutions obtained by the Runge–Kutta method of order 4 (RK-4) and machine learning algorithms based on a nonlinear autoregressive network with exogenous inputs (NARX) and backpropagated Levenberg–Marquardt algorithm. The mean percentage errors in approximate solutions obtained by ANN-AOA-IPA are around 10−6 to 10−7 . The graphical analysis illustrates that the velocity, temperature, and concentration profiles of the nanofluid increase with an increase in the suction parameter, Eckert number and Schmidt number, respectively. Solutions and the results of performance indicators such as mean absolute deviation, Theil’s inequality coefficient and error in Nash–Sutcliffe efficiency further validate the proposed algorithm’s utility and efficiency.Item Aplicación de algoritmos de clasificación como soporte al diagnóstico del cáncer de mama en unidades oncológicas(Universidad Santiago de Cali, 2020) García Restrepo, Diego Fernando; Rondón Otero, Leidy Viviana; Tavera Romero, Carlos AndrésBreast cancer is one of the diseases that cause a lot of deaths every year, it is the most common type of all cancers and one of the leading causes of death of women in the world and Colombia. In this article, we present the use of WEKA as a machine learning and data mining tool, applying different classifiers to a set of breast cancer data provided by the cancer unit with the objective of supporting the diagnosis and supporting the taking of decisions in the diagnosis of breast cancer. The results obtained show how researchers in the area of health can use both statistical analysis and data mining techniques to discover knowledge and make a better diagnosis of breast cancer and other diseases. In the document a comparison of the effectiveness of the classifiers and an analysis of correct classification, incorrect classification and precision are made, aspects that are of importance for researchers who want to use algorithms in other types of studies or with other attributes to diagnose if the values of these lead or not to conclude that a person has breast cancerItem Aplicativo web orientado a mejorar los procesos de especies menores: Caso de estudio CUY (Guinea Pig)(Universidad Santiago de Cali, 2019) Portillo Cuaran, Luis Makensey; Tavera Romero, Carlos AndrésTaking into account the importance that the raising of the guinea pig has acquired in recent years, the present research sought to study and analyze in an exhaustive manner the state of the art of the processes of breeding of minor species: case of a guinea pig and how it can be improved its production implementing an application in terms of food and vaccination, as a second objective, analyzed the characteristics, tools, technologies, which can be implemented for the development of this application which will allow a large amount of data to be stored allowing a more suitable inventory through a good modeling of Entity Relationship; and finally, he sought to identify a reliable method so that the application is easy to understand, so that everything related to the central theme of the investigation can be known. The selected development methodology was PSP, the goals set are: construction of the requirements formats, elaboration of the UML diagrams, codification of the application and application tests. This document is organized as follows: introduction, state of the art of minor species processes, technologies for application development, results and conclusions. The main contribution of the research presented here is to allow systematization of breeding in small species, presenting the guinea pig as a case study. Also, strengthening the market for Nariñenses is expected to reduce costs by approximately 40 percent. All of the above based on the need to manage the time to feed, when and how to provide the respective vaccines and keep an adequate control of the species, in order to place a new vision of the producer in the breeding process, since it will be shown that they can obtain significant savings at the time of producing it, thus motivating it to strengthen this ancestral activity carried out by the producers.Item Application of Intelligent Paradigm through Neural Networks for Numerical Solution of Multiorder Fractional Differential Equations(Hindawi Limited, 2022) Khan, Naveed Ahmad; Ibrahim Khalaf, Osamah; Tavera Romero, Carlos Andrés; Sulaiman, Muhammad; Bakar, Maharani A.In this study, the intelligent computational strength of neural networks (NNs) based on the backpropagated Levenberg-Marquardt (BLM) algorithm is utilized to investigate the numerical solution of nonlinear multiorder fractional differential equations (FDEs). The reference data set for the design of the BLM-NN algorithm for different examples of FDEs are generated by using the exact solutions. To obtain the numerical solutions, multiple operations based on training, validation, and testing on the reference data set are carried out by the design scheme for various orders of FDEs. The approximate solutions by the BLM-NN algorithm are compared with analytical solutions and performance based on mean square error (MSE), error histogram (EH), regression, and curve fitting. This further validates the accuracy, robustness, and efficiency of the proposed algorithm.Item Aprendizaje basado en problemas (abp) aplicado a los lenguajes de programación - Estudio comparativo entre lenguajes textuales y lenguajes visuales: caso PiCO y GraPICO(Editorial Universidad Santiago de Cali, 2018) Cano Castillo, Christian Felipe; Espinosa Galliady, Luis Eduardo; Tavera Romero, Carlos AndrésEn esta etapa del estudio se mostrará el punto de vista aportado por el Aprendizaje Basado en Problemas en el estudio comparativo, presentando diversas teorías existentes usadas en el taller de modelación realizado con cada uo de estos lenguajes de programación.Item Breast Calcifications and Histopathological Analysis on Tumour Detection by CNN(Tech Science Press, 2022) Banumathy D.; Khalaf, Osamah Ibrahim; Tavera Romero, Carlos Andrés; Raja, P. Vishnu; Sharma, Dilip KumarThe most salient argument that needs to be addressed universally is Early Breast Cancer Detection (EBCD), which helps people live longer lives. The Computer-Aided Detection (CADs)/Computer-Aided Diagnosis (CADx) system is indeed a software automation tool developed to assist the health professions in Breast Cancer Detection and Diagnosis (BCDD) and minimise mortality by the use of medical histopathological image classification in much less time. This paper purposes of examining the accuracy of the Convolutional Neural Network (CNN), which can be used to perceive breast malignancies for initial breast cancer detection to determine which strategy is efficient for the early identification of breast cell malignancies formation of masses and Breast microcalcifications on the mammogram. When we have insufficient data for a new domain that is desired to be handled by a pre-trained Convolutional Neural Network of Residual Network (ResNet50) for Breast Cancer Detection and Diagnosis, to obtain the Discriminative Localization, Convolutional Neural Network with Class Activation Map (CAM) has also been used to perform breast microcalcifications detection to find a specific class in the Histopathological image. The test results indicate that this method performed almost 225.15% better at determining the exact location of disease (Discriminative Localization) through breast microcalcifications images. ResNet50 seems to have the highest level of accuracy for images of Benign Tumour (BT)/Malignant Tumour (MT) cases at 97.11%. ResNet50’s average accuracy for pre-trained Convolutional Neural Network is 94.17%.Item CAD of BCD from Thermal Mammogram Images Using Machine Learning(Tech Science Press, 2022) Banumathy D.; Khalaf, Osamah Ibrahim; Tavera Romero, Carlos Andrés; Indra J.; Sharma, Dilip KumarLump in the breast, discharge of blood from the nipple, and deformation of the nipple/breast and its texture are the symptoms of breast cancer. Though breast cancer is very common in women, men can also get breast cancer. In the early stages, BCD makes use of Thermal Mammograms Breast Images (TMBI). The cost of treatment can be severely reduced in the early stages of detection. Based on the techniques of segmentation, the Breast Cancer Detection (BCD) works. Moreover, by providing a balanced, reliable and appropriate second opinion, a tremendous role has been played by ML in medical practices due to enhanced Information and Communication Technology (ICT). For the purpose of making the whole detection process of Malignant Tumor (MT)/Benign Tumor (BT) very resourceful and time-efficient, there is now a possibility to form an automated and precise ComputerAided Diagnosis System (CADs). Several Image Pattern Recognition Techniques were used to classify breast cancer using Thermal Mammograms Image Processing Techniques (TMIPT) in the present investigation. Presenting a new model to classify the BCD with the help of TMIPT, thermal imaging, and smart devices is the aim of this research article. Using well-designed experiments like Intensive Preoperative Radio Therapy (IPRT) and BCD, the implementation and valuation of a concrete application are carried out. This proposed method is for the automatic classification of TMBI of a similar standard so that the thermal camera of FLIR One Gen 3 One 3rd Generation (FLIR One Gen 3) that can be attached to the smart devices are capable of capturing BCD using Machine Learning (ML) algorithms. To imitate the behaviour of human Artificial Intelligence (AI), designing drug formulations, helping in clinical diagnosis and robotic surgery systems, finding medical statistical datasets, and decoding human diseases’ wireless network model as well as cancer are the reasons for the ML to empower the computer and robots. The outperformance of the ML models against all other classifiers and scoring impressively across heterogeneous performance metrics like 98.44% of Precision, 98.83% of Accuracy, and 100% of Recall are observed from the comparative analysis.Item Classification of Liver Tumors from Computed Tomography Using NRSVM(Tech Science Press, 2022) Priyadarsini S.; Tavera Romero, Carlos Andrés; Mrunalini M.; Koteswara Rao, Ganga Rama; Sengan, SudhakarA classification system is used for Benign Tumors (BT) and Malignant Tumors (MT) in the abdominal liver. Computed Tomography (CT) images based on enhanced RGS is proposed. Diagnosis of liver diseases based on observation using liver CT images is essential for surgery and treatment planning. Identifying the progression of cancerous regions and Classification into Benign Tumors and Malignant Tumors are essential for treating liver diseases. The manual process is time-consuming and leads to intra and inter-observer variability. Hence, an automatic method based on enhanced region growing is proposed for the Classification of Liver Tumors (LT). To enhance the Liver Region (LR) from the surrounding tissues, Non-Linear Mapping (NLP) is used. Region Growing Segmentation (RGS) is employed to segment the LR, and Expectation-Maximization (EM) algorithm is used to segment the region of interest. Grey Level Co-occurrence Matrix (GLCM) features are extracted from the tumor region, and Nonlinear Random Support Vector Machine (NRSVM) classification is performed to classify the Benign Tumors and Malignant Tumors. The proposed method is tested on a database of medical images collected from Med all Diagnostic Research Centre and attained an accuracy of 96%. The proposed method is beneficial for better liver tumor diagnosis in an optimized method by the medical expert.Item La comunicación en el estudio comparativo entre lenguajes textuales y lenguajes visuales caso: pico y grapico - Estudio comparativo entre lenguajes textuales y lenguajes visuales: caso PiCO y GraPICO(Editorial Universidad Santiago de Cali, 2018) Cruz Pérez, Yenny Viviana; Tavera Romero, Carlos AndrésEste es un proyecto interdisciplinario entre la Ingeniería de Software y la Comunicación Social. Es un trabajo interinstitucional entre la Universidad de San Buenaventura Cali –USBC– y la Universidad Autónoma de Occidente– UAO–, que se gestó para dar apoyo al Laboratorio de Investigación para el Desarrollo de la Ingeniería de Software (LIDIS), de la USBC, en el trabajo posdoctoral de su entonces director, el ingeniero de sistemas Carlos Andrés Tavera Romero, consistente en el estudio comparativo entre el Cálculo textual: PiCO y el Cálculo visual: GraPiCO[1][2], los cuales hacen parte del programa E_GraPiCO, para conocer bajo qué condiciones es más adecuado un lenguaje que otro y qué mejoras requieren.Item Development and Impact of a Mobile Application that Allows Users to Track Their Location on an Educational Institution Campus, a Simulation Study(International Association of Online Engineering, 2024) Tavera Romero, Carlos Andrés; Segovia de Maya, Patricia Del Rosario; Díaz Velásquez, María Fernanda; Pérez Carvajal, Diego FernandoThis research study aims to solve user location issues within the campus at an educational institution. As this campus comprises a large number of places and departments, users often get confused about how to reach a specific location. To address this problem, the “Ubícate” (“locate by yourself” in Spanish) application was developed following the CDIO methodology, which encompasses four creative process steps: conceive, design, implement, and operate. The “Ubícate” app provides users with information on places of interest such as schools, departments, halls, auditoriums, and sports venues, offering a visual reference of available locations through 360-degree images. The application also uses Google Maps to track user location within the campus, thus marking a reference route between university gates and the different locations available, in addition to providing information on university-sponsored events. In this paper, Section 2 describes the methodology and each of the stages that were addressed in the following sections. Section 3 presents the development itself and the data used for the purposes thereof. Next, Section 4 reveals the results from this study. Later, Section 5 assesses these results and the findings from the study. In Section 6, our conclusions are discussed. Finally, Section 7 lists topics for future research. The application did indeed contribute to improving the attendance of the academic community at events. Where the application was used, the first-hand perception of visitors and their own was very positive and enhanced the institutional image and sense of belonging. The contribution of this study consists of presenting a mobile application as a solution from three approaches: the technical aspects for application development, the business vision to satisfy the user’s needs, and the end user’s perception. All three approaches provide a technical reader, an entrepreneur, or an end user an overview of a scalable solution to different types of implementations in different types of businesses that require indoor location through the use of technologies in mobile applications. The mobile application performs the location indoors using the Google Maps platform, allowing a more agile development in implementing the APP.Item Digitalización de instrumentos aeronáuticos para el simulador de vuelo X – Plane 11 y Air Manager(Universidad Santiago de Cali, 2019) Luna Espinosa, Jeffrey; Villada Luna, David; Tavera Romero, Carlos AndrésThe use of flight simulators is of great importance in an aviation course, they are a way to effectively and efficiently face, among others, aspects such as security, economy and coverage. But sometimes students are required to practice in an aircraft that is not on the simulator's predetermined list, it is then: 1) Acquire the manufacturer the aircraft that is needed, if it is already designed or failing to assume the costs of a development 2) use the most similar aircraft (moving the student away from an experience with the real airplane) or 3) select the aircraft that requires the least changes and adapt it to the pedagogical needs. This last possibility was the one that the Colombian Air Force and the Santiago de Cali University chose when it was needed that the Cadets of the Military Aviation School "Marco Fidel Suárez" were trained in a plane that is not one of the default options in the flight simulator program they use.Item Diseño de un prototipo para el Control de Acceso y Seguridad usando IoT(Universidad Santiago de Cali, 2019) Gallego Angulo, Larry Jhoan; Tavera Romero, Carlos AndrésThis article presents the prototype design of a system for access control and security using IoT (Internet of Things), taking into account the case study of the Santiago de Cali University laboratory of block 4 floor 3. This design is It consists of a web portal hosted on a web server for administration, two readers, the central and an input module and a web server. The objective was to design a system that allows us to control the entrance and exit of the laboratories through the UUID (universal unique identifier) of the Tag or RFID Card (radio frequency identification), this is consulted from the reader or by the EEPROM memory or in MySQL database. EEPROM memory guarantees the operation of the system, if the reader is not connected to the network to authenticate in the database hosted on the server, the input readers are made with an Arduino card and the central reader with a board Nodemcu; The central reader has nodemcu board and RFID reader, the door reader has an Arduino card, RFID reader, RGB LED, Reset button. The communication of this system is via Wi-Fi, achieving productivity in the execution of the processes. This article will show the operation of the modules connected to the server via Wi-Fi and the input module in the EEPROM, to design the web portal it was necessary to create an Apache server on a Raspberry PI board and, the web portal was programmed with PHP and HTML5, CSS in a Bootstrap 4 Framework to have a Dashboard.Item Early-Stage Alzheimer's Disease Prediction Using Machine Learning Models(Frontiers Media S.A., 2022) Kavitha C.; Mani, Vinodhini; Srividhya S.R.; Khalaf, Osamah Ibrahim; Tavera Romero, Carlos AndrésAlzheimer's disease (AD) is the leading cause of dementia in older adults. There is currently a lot of interest in applying machine learning to find out metabolic diseases like Alzheimer's and Diabetes that affect a large population of people around the world. Their incidence rates are increasing at an alarming rate every year. In Alzheimer's disease, the brain is affected by neurodegenerative changes. As our aging population increases, more and more individuals, their families, and healthcare will experience diseases that affect memory and functioning. These effects will be profound on the social, financial, and economic fronts. In its early stages, Alzheimer's disease is hard to predict. A treatment given at an early stage of AD is more effective, and it causes fewer minor damage than a treatment done at a later stage. Several techniques such as Decision Tree, Random Forest, Support Vector Machine, Gradient Boosting, and Voting classifiers have been employed to identify the best parameters for Alzheimer's disease prediction. Predictions of Alzheimer's disease are based on Open Access Series of Imaging Studies (OASIS) data, and performance is measured with parameters like Precision, Recall, Accuracy, and F1-score for ML models. The proposed classification scheme can be used by clinicians to make diagnoses of these diseases. It is highly beneficial to lower annual mortality rates of Alzheimer's disease in early diagnosis with these ML algorithms. The proposed work shows better results with the best validation average accuracy of 83% on the test data of AD. This test accuracy score is significantly higher in comparison with existing works.Item Elaboración de hipótesis en experimentos de lenguajes de programación - Estudio comparativo entre lenguajes textuales y lenguajes visuales: caso PiCO y GraPICO(Editorial Universidad Santiago de Cali, 2018) Cano Castillo, Christian Felipe; Espinosa Galliady, Luis Eduardo; Tavera Romero, Carlos AndrésLuego de haber determinado el tipo de investigación que se iba a desarrollar, es necesario construir las bases teóricas desde el punto de vista de la estadística, para poder contar con la validez que ofrecen los métodos científicos. En esta etapa se presentarán algunas teorías acerca de la prueba de hipótesis que se utilizará durante el trascurso del estudio.Item Estudio comparativo entre lenguajes textuales y lenguajes visuales: caso PiCO y GraPICO(Editorial Universidad Santiago de Cali, 2018) Espinosa Galliady, Luis Eduardo; Cano Castillo, Christian Felipe; Tavera Romero, Carlos Andrés; Cruz Pérez, Yenny Viviana; Penagos Muñoz, Juan David; Ramírez Arcila, Paola Andrea; Triana Lozano, Marco AntonioEl proyecto es multidisciplinario, pues convergen las temáticas de Ingeniería de Sistemas, la Comunicación Social y la Estadística. Y también es interinstitucional, dado que unieron fuerzas el programa de Comunicación Social-Periodismo y el área de Estadística de la Facultad de Ciencias Básicas de la Universidad Autónoma de Occidente, así como los grupos de investigación LIDIS de la Universidad de San Buenaventura-Cali y COMBA I+D de la Universidad Santiago de Cali.Item Estudio de resultados de pico y grapico parte 2 - Estudio comparativo entre lenguajes textuales y lenguajes visuales: caso PiCO y GraPICO(Editorial Universidad Santiago de Cali, 2018) Triana Lozano, Marco Antonio; Tavera Romero, Carlos AndrésMediante el presente documento, se logró realizar un estudio comparativo entre lenguajes textuales y lenguajes visuales, específicamente entre lenguajes de programación textual PiCO y visual GraPiCO. Por medio de un análisis estadístico, se obtuvieron algunos resultados para establecer el nivel de aceptación de estos dos tipos de lenguajes y conocer bajo qué condiciones es más adecuado un lenguaje de programación que otro; con el fin de hacer mejoras a dicho software. Inicialmente, se escogió una población (objetiva) específica definida con anterioridad por el grupo de investigadores participantes en este proyecto institucional para realizar el estudio; en el cual se realizaron mediciones acerca del nivel de conocimiento, asimilación, comprensión y aceptación de estos dos lenguajes de programación.