2022 IEEE Mexican International Conference on Computer Science (ENC)最新文献_第2页

Comparison of development and characteristics of several educational tools in augmented reality for visualization of 3D models difficult to understand. Chemistry application case 比较几种增强现实教育工具的发展和特点，以实现难以理解的3D模型的可视化。化学应用案例

2022 IEEE Mexican International Conference on Computer Science (ENC) Pub Date : 2022-08-24 DOI: 10.1109/ENC56672.2022.9882948

León F. Austria-Melo, Jorge Cuellar-Castillo, Abdiel Ambriz Hernández, Cristian Montiel, D. Fabila-Bustos, M. Hernández-Chávez

{"title":"Comparison of development and characteristics of several educational tools in augmented reality for visualization of 3D models difficult to understand. Chemistry application case","authors":"León F. Austria-Melo, Jorge Cuellar-Castillo, Abdiel Ambriz Hernández, Cristian Montiel, D. Fabila-Bustos, M. Hernández-Chávez","doi":"10.1109/ENC56672.2022.9882948","DOIUrl":"https://doi.org/10.1109/ENC56672.2022.9882948","url":null,"abstract":"This paper shows the development of different scenarios in augmented reality (AR) using several programming tools, these applications were focused on visualization of 3D Bohr atomic models of the chemical elements from periodic table, organic and inorganic chemical molecules. The development tools were a) Unity3D in conjunction with the EasyAR SDK, b) HTML 5, CSS and the Google ARCore software development kit, c) Spark AR Studio and d) Adobe Aero with Glitch and HTML 5. The different scenarios created and described in this work were designed and developed to improve the learning of topics in an area of chemistry that requires three-dimensional models. The developments allowed 3D visualization and the interaction with the models to achieve several views of them, since the representations of these models are traditionally projected in books in two dimensions, making their understanding and interpretation in a not easy form.","PeriodicalId":145622,"journal":{"name":"2022 IEEE Mexican International Conference on Computer Science (ENC)","volume":"61 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129033210","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Creation of a Dataset for personality and professional interest recognition 个性和职业兴趣识别数据集的创建

2022 IEEE Mexican International Conference on Computer Science (ENC) Pub Date : 2022-08-24 DOI: 10.1109/ENC56672.2022.9882942

Abel Robles Montoya, M. L. B. Estrada, Ramón Zatarain Cabada, Héctor Manuel Cárdenas López, Arcelia Judith Bustillos Martínez

引用次数: 0

User Modeling for Collaborative Adaptative Mobile Educational Applications: A Systematic Review of the Literature 协作适应性移动教育应用的用户建模:文献系统综述

2022 IEEE Mexican International Conference on Computer Science (ENC) Pub Date : 2022-08-24 DOI: 10.1109/ENC56672.2022.9882919

Héctor Miguel Figueroa Pucheta, V. Y. Rosales-Morales, Y. H. Velázquez

{"title":"User Modeling for Collaborative Adaptative Mobile Educational Applications: A Systematic Review of the Literature","authors":"Héctor Miguel Figueroa Pucheta, V. Y. Rosales-Morales, Y. H. Velázquez","doi":"10.1109/ENC56672.2022.9882919","DOIUrl":"https://doi.org/10.1109/ENC56672.2022.9882919","url":null,"abstract":"Nowadays mobile devices promote better academic training in classrooms and in the daily lives of students. The challenges in the ecosystem of mobile applications are related to features particular student learning, so there is a shortage of investigations in this regard. The objective of this study is to understand how characteristics of users can be used to adapt the content of an educational mobile application based on models. These are used to create a profile based on the behavior of the person, and the most used methods to create them are the explicit one, manually, the implicit one, automatically and the hybrid. In this systematic review of the literature, we analyze the methods, techniques and properties that exist for the construction of user models following the methodology developed by Kitchenham and Kumar, following their structured process. The qualitative results obtained of the systematic review are a total of 2279 articles, of which, we selected 6 for their complete analysis. As results of the analysis, we identified the most relevant approaches for the construction of user models, that are divided into two categories, structural modeling and modeling of behavior, its use depends on the purpose of the application. Also, the significant characteristics to define a student in a user model are exposed.","PeriodicalId":145622,"journal":{"name":"2022 IEEE Mexican International Conference on Computer Science (ENC)","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124963307","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Water quality assurance in aquaculture ponds using Machine Learning and IoT techniques 使用机器学习和物联网技术的水产养殖池塘水质保证

2022 IEEE Mexican International Conference on Computer Science (ENC) Pub Date : 2022-08-24 DOI: 10.1109/ENC56672.2022.9882920

R. Quintero, Jaqueline Parra, Francisco Félix

引用次数: 0

Improving Geomorphological Classification via Binary Image Processing 利用二值图像处理改进地貌分类

2022 IEEE Mexican International Conference on Computer Science (ENC) Pub Date : 2022-08-24 DOI: 10.1109/ENC56672.2022.9882949

A. C. Salgado-Albiter, S. I. Valdez, Jorge Paredes-Tavares

{"title":"Improving Geomorphological Classification via Binary Image Processing","authors":"A. C. Salgado-Albiter, S. I. Valdez, Jorge Paredes-Tavares","doi":"10.1109/ENC56672.2022.9882949","DOIUrl":"https://doi.org/10.1109/ENC56672.2022.9882949","url":null,"abstract":"Landform classification is the basis for understanding and describing the processes and evolution of landscape. This process usually requires elevation information from different sources, expertise and time. Automatic geomorphological classification, via the geomorphons algorithm, supports expert classification by using local ternary patterns for labeling landform elements, significantly reducing the computation time. Nevertheless, it presents issues such as a noisy output, valleys that are not classified as continuous forms, valleys that are classified as peaks at low altitude, flat zones inside the valley that are not classified as a part of it, and other similar issues. In this proposal, we tackle the mentioned issues for valley classification by binarizing the geomorphons output and applying it binary-image operators. The proposal's performance is measured by using binary classification metrics and expert-made groundtruth images. The results show that the accuracy, balanced accuracy, and F1 metrics are greater than those delivered by the geomorphons classifier for all the instances in the testing data.","PeriodicalId":145622,"journal":{"name":"2022 IEEE Mexican International Conference on Computer Science (ENC)","volume":"74 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128814377","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

ENC 2022 Publications Committee ENC 2022出版委员会

2022 IEEE Mexican International Conference on Computer Science (ENC) Pub Date : 2022-08-24 DOI: 10.1109/enc56672.2022.9882913

引用次数: 0

Analysis of Audio Signals Using Deep Learning Algorithms Applied to COVID Diagnostic Systems 基于深度学习算法的音频信号分析应用于COVID诊断系统

2022 IEEE Mexican International Conference on Computer Science (ENC) Pub Date : 2022-08-24 DOI: 10.1109/ENC56672.2022.9882932

M. Rivera, P. M. Quintero-Flores, Rodolfo Eleazar Pérez Loaiza, Leticia Gómez Rivera

{"title":"Analysis of Audio Signals Using Deep Learning Algorithms Applied to COVID Diagnostic Systems","authors":"M. Rivera, P. M. Quintero-Flores, Rodolfo Eleazar Pérez Loaiza, Leticia Gómez Rivera","doi":"10.1109/ENC56672.2022.9882932","DOIUrl":"https://doi.org/10.1109/ENC56672.2022.9882932","url":null,"abstract":"In recent years the application of deep learning algorithms in the subdomain of audio analysis has grown rapidly, however it is a topic that can be complex for students and researchers who have a first approach and want to develop an application in this field. The use of deep learning techniques applied to audio signals has allowed the development of a wide variety of useful tools in our daily lives, from virtual assistants to medical applications. This article presents a literature review of the main techniques that have been used in recent years for analysis, feature extraction and classification from audio spectra or spectrograms, as well as examples of application in the context of the COVID-19 pandemic in which multiple related projects have emerged, such as diagnostic systems. The techniques addressed are recurrent neural networks (RNN), convolutional neural networks (CNN) and generative adversarial networks (GAN). It is intended that the reader will be able to acquire this knowledge from a simple perspective and that this information will be useful in their research or development.","PeriodicalId":145622,"journal":{"name":"2022 IEEE Mexican International Conference on Computer Science (ENC)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123909993","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A model supported in the clinical covid patient record using DL for pandemic preparedness 在使用DL进行大流行准备的临床covid患者记录中支持的模型

2022 IEEE Mexican International Conference on Computer Science (ENC) Pub Date : 2022-08-24 DOI: 10.1109/ENC56672.2022.9882915

J. A. Guzmán-Torres, F. Domínguez-Mota, G. Tinoco-Guerrero

{"title":"A model supported in the clinical covid patient record using DL for pandemic preparedness","authors":"J. A. Guzmán-Torres, F. Domínguez-Mota, G. Tinoco-Guerrero","doi":"10.1109/ENC56672.2022.9882915","DOIUrl":"https://doi.org/10.1109/ENC56672.2022.9882915","url":null,"abstract":"This paper presents a model based on a Deep Learning approach to aid in improving our assessment of the risk of death in COVID-19 patients only based on their clinical record when admitted. It is aimed to provide an alternative fast tool for doctors and researchers to focus on a rapid selection of patients with a high likelihood of death, which is a critical aspect having in mind the growing infection dynamics of the current and perhaps future pandemics. The dataset used in this research is open-access, available for algorithm benchmarking, and represents the knowledge of the cases examined in Mexico before the immunization campaigns. The massive amount of information used to feed the algorithm provides robustness and aids in detecting the principal patterns involved in the data. The model is based on a Deep Neuronal Network, which uses different activation functions and several neurons in each hidden layer for getting a stable performance, and was tested in both a validation set and test set, obtaining a satisfactory and reliable accuracy of about 93 % for the survival prediction.","PeriodicalId":145622,"journal":{"name":"2022 IEEE Mexican International Conference on Computer Science (ENC)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128162146","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Assessing the knowledge and use of agile methods: A case study in 15 SMEs of Mexico 评估敏捷方法的知识和使用:墨西哥15家中小企业的案例研究

2022 IEEE Mexican International Conference on Computer Science (ENC) Pub Date : 2022-08-24 DOI: 10.1109/ENC56672.2022.9882945

Brisia Corona, M. Muñoz

引用次数: 0

Tamper detection and localization in color images using secure block-based watermarking 基于安全分块水印的彩色图像篡改检测与定位

2022 IEEE Mexican International Conference on Computer Science (ENC) Pub Date : 2022-08-24 DOI: 10.1109/ENC56672.2022.9882954

Elizabeth Campos-Ponce, M. Cedillo-Hernández

{"title":"Tamper detection and localization in color images using secure block-based watermarking","authors":"Elizabeth Campos-Ponce, M. Cedillo-Hernández","doi":"10.1109/ENC56672.2022.9882954","DOIUrl":"https://doi.org/10.1109/ENC56672.2022.9882954","url":null,"abstract":"Nowadays, the facilities that offers Internet in conjunction with the capabilities of the infrastructure of communication and information technologies, allowing that the multimedia data can be shared and transmitted in easy and efficient way. As consequence, the multimedia data can be copied or edited in an easy form, and this can be affecting its original content. In a context of digital images, this paper presents a tamper detection and localization algorithm in color images using secure block-based watermarking. This proposal is based on the frequency domain using the lifting wavelet transform, together with checksum criteria that make up the hash key codes, which they are hidden in the least significant bits of each low frequency component. The proposed method is evaluated in terms of imperceptibility and false positive, false negative and tamper detection rates, respectively. Watermark imperceptibility is measured using the peak signal to noise ratio and structural similarity index, respectively. The tamper detection ability has been tested on color and grayscale images using a wide variety of manipulations such as copy-paste, copymove, constant averaging, impulsive noise, and random manipulations. Comparative with the current state-of-the-art is provided.","PeriodicalId":145622,"journal":{"name":"2022 IEEE Mexican International Conference on Computer Science (ENC)","volume":"80 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122735648","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0