2022 XVLIII Latin American Computer Conference (CLEI)最新文献_第4页

A synthetic Data Generator for Smart Grids based on the Variational-Autoencoder Technique and Linked Data Paradigm 基于变分自编码器技术和关联数据范式的智能电网综合数据发生器

2022 XVLIII Latin American Computer Conference (CLEI) Pub Date : 2022-10-17 DOI: 10.1109/CLEI56649.2022.9959918

R. D. Santos, J. Aguilar, M. Rodríguez-Moreno

{"title":"A synthetic Data Generator for Smart Grids based on the Variational-Autoencoder Technique and Linked Data Paradigm","authors":"R. D. Santos, J. Aguilar, M. Rodríguez-Moreno","doi":"10.1109/CLEI56649.2022.9959918","DOIUrl":"https://doi.org/10.1109/CLEI56649.2022.9959918","url":null,"abstract":"In a smart environment like the smart grids, it is necessary to have knowledge models that allow solving emerging problems. However, large datasets are required to automatically create these models, which in the vast majority of cases are not available. Therefore, in these environments is essential to have a data generator for each context. In this paper, we propose a synthetic data generation system based on the variational autoencoder (VAE) technique and linked data paradigm, to create larger datasets from small datasets acting as samples. Specifically, a Linked Data-based dataset extractor is proposed, which allows obtaining samples of data in a particular context. Then, a VAE is trained with these samples of data available in a specific context, to learn the latent distribution that characterizes the dataset, allowing the production of new records that are similar to those of the original dataset. Finally, several case studies in the field of energy management are carried out. In one of them, the process that follows our approach is described in detail; and then, another 3 more are considered to evaluate its ability to automate the data generation process for smart energy management. The results show how our synthetic data generation system can be used to obtain synthetic datasets in different energy contexts.","PeriodicalId":156073,"journal":{"name":"2022 XVLIII Latin American Computer Conference (CLEI)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132256696","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

Data Modeling with Ontological Formalism for Semantic Interoperability between Health Information Systems, applied to Primary Health Care in Paraguay 数据建模与本体形式之间的语义互操作性卫生信息系统，应用于初级卫生保健在巴拉圭

2022 XVLIII Latin American Computer Conference (CLEI) Pub Date : 2022-10-17 DOI: 10.1109/CLEI56649.2022.9959960

Viviana Osorio, Sonia Laviosa, G. Giménez-Lugo, Cynthia Villalba

{"title":"Data Modeling with Ontological Formalism for Semantic Interoperability between Health Information Systems, applied to Primary Health Care in Paraguay","authors":"Viviana Osorio, Sonia Laviosa, G. Giménez-Lugo, Cynthia Villalba","doi":"10.1109/CLEI56649.2022.9959960","DOIUrl":"https://doi.org/10.1109/CLEI56649.2022.9959960","url":null,"abstract":"In terms of public health policies, having all the information from the different Health Information Systems enriches the decision-making criteria, but the fact that each system has its own structure and protocols makes integrating all this information a challenge. Therefore, it is essential to have interoperability standards that enable such communication, but although several standards are available for this purpose, in order to make better use of such information, such as making inferences or integrated queries that depend on the semantics of a specific context, such as the public policies of a country, it is necessary to use modeling techniques according to the context. In this sense, this paper presents a solution for semantic interoperability between Health Information Systems, through the use of ontologies. For this purpose, we start from the definition of a Minimum Data Set for Primary Health Care in Paraguay, this Minimum Data Set is used as the basis for the development of an ontology, which for the scope of this work, and as a demonstration, the vaccination area was taken as a scenario. For the ontology validation process, the necessary syntactic interoperability was also implemented to integrate some testing systems and enable the execution of ontological queries.","PeriodicalId":156073,"journal":{"name":"2022 XVLIII Latin American Computer Conference (CLEI)","volume":"70 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131579702","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

Proof Assistant Based on Calculational Logic to Assist the Learning of Propositional Logic and Boolean Algebras 基于计算逻辑的证明助手辅助命题逻辑和布尔代数的学习

2022 XVLIII Latin American Computer Conference (CLEI) Pub Date : 2022-10-17 DOI: 10.1109/CLEI56649.2022.9959908

Federico Flaviani, W. Carballosa

引用次数: 1

Multiplanar Instance Segmentation Method for the Detection of Pulmonary Embolism 肺栓塞检测的多平面实例分割方法

2022 XVLIII Latin American Computer Conference (CLEI) Pub Date : 2022-10-17 DOI: 10.1109/CLEI56649.2022.9959947

D. Lozano, M. H. Hoyos, Haydemar Núñez, Luis Felipe Uriza Carrasco

{"title":"Multiplanar Instance Segmentation Method for the Detection of Pulmonary Embolism","authors":"D. Lozano, M. H. Hoyos, Haydemar Núñez, Luis Felipe Uriza Carrasco","doi":"10.1109/CLEI56649.2022.9959947","DOIUrl":"https://doi.org/10.1109/CLEI56649.2022.9959947","url":null,"abstract":"Pulmonary embolism (PE) is a clinical condition with high mortality and morbidity rates without prompt detection. Computer Aided Detection (CAD) systems support the radiologist in detecting and diagnosing PE using Computed Tomography Pulmonary Angiography (CTPA) images. During the last few years, there have been several contributions to this field by applying Deep Learning models, methods, and algorithms. Still, some challenges need to be addressed to obtain better results. This work is based on the Probability-based Mask R-CNN (P-Mask RCNN) model as our starting point due to the promising results when adapting the Mask R-CNN instance segmentation algorithm for PE detection. With the P-Mask R-CNN model as the backbone, we proposed and implemented a methodology that considers the axial slices of a CTPA image and the sagittal and coronal slices by providing additional information to the whole process. As a result of this exercise, we developed a multiplanar instance segmentation method merging the outputs of three segmentation models trained for each of the three CTPA image planes. The results of feeding a CTPA image into each model were combined into a single volume using three different operations: union, intersection, and majority. An additional contribution surpassing the detection of each model was perceived when compared with the radiologists’ annotations. Testing with the CTPA images of three patients and merging with the union operation resulted in a mean positive percentage detection of 48%, compared to 43% of the axial model, 6.3% of the sagittal model, and 4.8% of the coronal model. Intersection and majority operations also managed to obtain contributions from the three models, which could allow the radiologists to focus on specific parts of the volume where there are the most coincidences. The result of this approach is promising and can help achieve a better performance in detecting PE by focusing on improving specific steps of the methodology in future works.","PeriodicalId":156073,"journal":{"name":"2022 XVLIII Latin American Computer Conference (CLEI)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115047295","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

CLEI 2022 Cover Page CLEI 2022封面页

2022 XVLIII Latin American Computer Conference (CLEI) Pub Date : 2022-10-17 DOI: 10.1109/clei56649.2022.9959923

引用次数: 0

Analysis of Semantic Shift Before and After COVID-19 in Spanish Diachronic Word Embeddings 新冠肺炎前后西班牙语历时词嵌入的语义转移分析

2022 XVLIII Latin American Computer Conference (CLEI) Pub Date : 2022-10-17 DOI: 10.1109/CLEI56649.2022.9959896

Esteban Rodríguez Betancourt, Edgar Casasola Murillo

引用次数: 1

Face recognition using deep learning feature injection: An accurate hybrid network combining neural networks based on feature extraction with convolutional neural network 基于深度学习特征注入的人脸识别:基于特征提取的神经网络与卷积神经网络相结合的精确混合网络

2022 XVLIII Latin American Computer Conference (CLEI) Pub Date : 2022-10-17 DOI: 10.1109/CLEI56649.2022.9959927

Yilber J. Sisco, R. Carmona

引用次数: 1

How Has Requirements Engineering Supported Data Protection? 需求工程如何支持数据保护?

2022 XVLIII Latin American Computer Conference (CLEI) Pub Date : 2022-10-17 DOI: 10.1109/CLEI56649.2022.9959962

Paulo Henrique Da Silva, F. Benitti, Michelle S. Wangham

引用次数: 0

Automatic Chord Recognition Based on Bass Estimation and Pitch Classes Classification by Volume 基于低音估计和音高分类的自动和弦识别

2022 XVLIII Latin American Computer Conference (CLEI) Pub Date : 2022-10-17 DOI: 10.1109/CLEI56649.2022.9959903

Arturo Camacho

引用次数: 0

Evaluating the performance of web rendering technologies based on JavaScript: Angular, React, and Vue 评估基于JavaScript的web渲染技术的性能:Angular、React和Vue

2022 XVLIII Latin American Computer Conference (CLEI) Pub Date : 2022-10-17 DOI: 10.1109/CLEI56649.2022.9959901

Diniz-Junior Raimundo N. V., Caio César L. Figueiredoy, Gilson De S.Russo, Marcos Roberto G. Bahiense-Junior, Arbex Mateus V. L., Lanier M. Dos Santos, Raimundo F. Da Rocha, Renan R. Bezerra, F. Giuntini

引用次数: 2