2022 IEEE Biennial Congress of Argentina (ARGENCON)最新文献

Cardiovascular Age and Central Blood Pressure assessment based on Peripheral Blood Pressure Morphology and Artificial Neural Networks 基于外周血压形态学和人工神经网络的心血管年龄和中心血压评估

2022 IEEE Biennial Congress of Argentina (ARGENCON) Pub Date : 2022-09-07 DOI: 10.1109/ARGENCON55245.2022.9939873

Eugenia Ipar, Nicolas A. Aguirre, L. Cymberknop, R. Armentano

{"title":"Cardiovascular Age and Central Blood Pressure assessment based on Peripheral Blood Pressure Morphology and Artificial Neural Networks","authors":"Eugenia Ipar, Nicolas A. Aguirre, L. Cymberknop, R. Armentano","doi":"10.1109/ARGENCON55245.2022.9939873","DOIUrl":"https://doi.org/10.1109/ARGENCON55245.2022.9939873","url":null,"abstract":"Cardiovascular health can be assessed from central blood pressure waveform and arterial stiffness, highly associated with Arterial Age (AA). However, the acquirement of these parameters is challenging. This paper proposes the estimation of Systolic Central Blood Pressure (SBPc) and classification of Chronological Age (CHA) by groups, as a substitute of AA, by means of non-invasive cuff-pressure Arterial Pulse Waveform (APW) acquisition and further pulse analysis, using regression analysis for SBPc and classification for CHA. A set of Artificial Neural Network (ANN) for each respective outcome was trained and validated with an in-silico database (n=4374) from a One-Dimensional (1-D) model. As a result, a Root Mean Squared Error (RMSE) of 0.39 mmHg and Mean Absolute Percentage Error (MAPE) of 0.61% was obtained, while an accuracy of 97.8% was achieved for classification. Following this, an in-vivo dataset (n=32) was used to evaluate the performance of both ANN obtaining an RMSE of 5.85mmHg and MAPE of 4.3%, while the accuracy decreased to 68.9%. The proposed methodology could have the potential to determine the AA of a subject using only a single peripheral APW. Furthermore, a populated in-vivo evaluation remains to be conducted.","PeriodicalId":318846,"journal":{"name":"2022 IEEE Biennial Congress of Argentina (ARGENCON)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114965558","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

Easy5G: Software for Simulation and Study of 5G NR Interface Easy5G: 5G NR接口仿真与研究软件

2022 IEEE Biennial Congress of Argentina (ARGENCON) Pub Date : 2022-09-07 DOI: 10.1109/ARGENCON55245.2022.9939905

Jean Fonseca, Amanda Fernandes, Fernanda Corrêa

引用次数: 0

Estudio de una cuenta deslizante: Modelado y análisis de estabilidad 滑动计数的研究:稳定性建模与分析

2022 IEEE Biennial Congress of Argentina (ARGENCON) Pub Date : 2022-09-07 DOI: 10.1109/ARGENCON55245.2022.9940094

Bruno A. Roccia, G. R. Bossio, C. G. Gebhardt, Fernando Mazzone

引用次数: 0

Software Engineering Education Meets DevOps: an Experience Report 软件工程教育与开发运维:一份经验报告

2022 IEEE Biennial Congress of Argentina (ARGENCON) Pub Date : 2022-09-07 DOI: 10.1109/ARGENCON55245.2022.9940102

Nicolás Paez, Hernán de la Fuente

引用次数: 1

Adaptive Extended Kalman Filter for Integrated Navigation in a Satellite Launch Vehicle 卫星运载火箭组合导航的自适应扩展卡尔曼滤波

2022 IEEE Biennial Congress of Argentina (ARGENCON) Pub Date : 2022-09-07 DOI: 10.1109/ARGENCON55245.2022.9939949

Víctor Cánepa, P. Servidia, J. Giribet

引用次数: 0

A comparative study of dynamic state estimation approaches for detecting loss of excitation failures 动态状态估计方法检测激励失效损失的比较研究

2022 IEEE Biennial Congress of Argentina (ARGENCON) Pub Date : 2022-09-07 DOI: 10.1109/ARGENCON55245.2022.9939740

Pablo Marchi, P. G. Estevez, C. Galarza

引用次数: 0

Análisis exploratorio de la morfología urbana en relación a la calidad del aire del pericentro de la ciudad de Santa Fe, Argentina 阿根廷圣达菲市中心城市形态与空气质量关系的探索性分析

2022 IEEE Biennial Congress of Argentina (ARGENCON) Pub Date : 2022-09-07 DOI: 10.1109/ARGENCON55245.2022.9939709

Guido Delaloye, V. Venturini

引用次数: 0

Software Architecture Design of Distributed Satellite Systems Test Bed 分布式卫星系统试验台软件体系结构设计

2022 IEEE Biennial Congress of Argentina (ARGENCON) Pub Date : 2022-09-07 DOI: 10.1109/ARGENCON55245.2022.9939729

Santiago Husain Cerruti, M. España, P. Servidia

{"title":"Software Architecture Design of Distributed Satellite Systems Test Bed","authors":"Santiago Husain Cerruti, M. España, P. Servidia","doi":"10.1109/ARGENCON55245.2022.9939729","DOIUrl":"https://doi.org/10.1109/ARGENCON55245.2022.9939729","url":null,"abstract":"CONAE is currently investigating multi-static Earth Observation from Formation Flying Distributed Satellite Systems. The design, verification, testing and integration of satellite formation-flying technology pose, nonetheless, stringent challenges to achieve mission success. From a Systems Engineering standpoint, we provide a software architecture enabling a user to develop and ground validate flight software and hardware using a model-based design philosophy. This philosophy is supported by an Object-Oriented Design methodology, amply used nowadays to model and manage the software complexity of Space Systems. We first introduce the concept of Distributed Satellite Systems, their interest in Earth Observation and the main functional blocks of a test bed laboratory. After stating the fundamental principles of Object-Oriented Design, we apply them to the design of the simulation environment software architecture. A use case of an Autonomous Formation-Flying control algorithm is introduced as a guide for the usage of the proposed software Framework. We conclude with a brief description of ongoing work towards implementing a hardware in the loop test bed laboratory.","PeriodicalId":318846,"journal":{"name":"2022 IEEE Biennial Congress of Argentina (ARGENCON)","volume":"147 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116617995","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: 1

Sistema inteligente para la detección de fallas basado en redes profundas auto-ajustables 基于自调深网络的智能故障检测系统

2022 IEEE Biennial Congress of Argentina (ARGENCON) Pub Date : 2022-09-07 DOI: 10.1109/ARGENCON55245.2022.9939789

Ivo Perez Colo, Carolina Saavedra Sueldo, Mariano De Paula, Geraldina Roark, Sebastián A. Villar, Gerardo G. Acosta

{"title":"Sistema inteligente para la detección de fallas basado en redes profundas auto-ajustables","authors":"Ivo Perez Colo, Carolina Saavedra Sueldo, Mariano De Paula, Geraldina Roark, Sebastián A. Villar, Gerardo G. Acosta","doi":"10.1109/ARGENCON55245.2022.9939789","DOIUrl":"https://doi.org/10.1109/ARGENCON55245.2022.9939789","url":null,"abstract":"La creciente complejidad de los sistemas industri-ales ha fomentado el surgimiento de nuevas técnicas de análisis de datos para apoyar a los procesos de toma de decisiones. Concretamente, los modelos basados en redes neuronales pro-fundas constituyen una alternativa promisoria para diversas aplicaciones de detección, clasificación y predicción de defectos o fallas que abarca aplicaciones desde el control de calidad de los productos, identificación de defectos en los procesos en una línea de producción hasta predicción de fallas de los equipos tecnologicós. Sin embargo, el exitó de dichos modelos depende sensiblemente de la elección de sus hiper-parametrós para lo cual se requiere de un exhaustivo proceso de configuración que, hoy en día, demanda un alto grado de conocimiento experto. En este contexto, el presente trabajo propone un Sistema Inteligente basado en redes neuronales profundas, dotado con un sistema de auto-ajuste de sus hiper-parametrós, para la detección de defectos y fallas. Dicho sistema integra un algoritmo de Optimización Bayesiana para encontrar la combinación optima de los hiper- párametros que permita alcanzar el mejor desempeño posible del sistema. El sistema inteligente propuesto se prueba en dos casos de estudio de diferente naturaleza y los resultados alcanzado demuestran la efectividad de la propuesta.","PeriodicalId":318846,"journal":{"name":"2022 IEEE Biennial Congress of Argentina (ARGENCON)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129668128","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: 1

Computational modeling for decision making in the establishment and implementation of management systems in laboratories 实验室管理系统建立与实施决策的计算模型

2022 IEEE Biennial Congress of Argentina (ARGENCON) Pub Date : 2022-09-07 DOI: 10.1109/ARGENCON55245.2022.9940069

María Eugenia Durand, R. Andrés Ferreyra, M. Chesta

{"title":"Computational modeling for decision making in the establishment and implementation of management systems in laboratories","authors":"María Eugenia Durand, R. Andrés Ferreyra, M. Chesta","doi":"10.1109/ARGENCON55245.2022.9940069","DOIUrl":"https://doi.org/10.1109/ARGENCON55245.2022.9940069","url":null,"abstract":"Implementing Laboratory Management Systems (LMS) involves an accreditation process whereby the laboratory documents its processes and demonstrates the quality and reliability of those processes. The ISO/IEC 17025 standard specifies the accreditation requirements in an international context. Since accreditation processes are complex, expensive, involve multiple steps and variables and a heavy documentation burden, it would be desirable to have some form of quick a priori assessment of a laboratory before it embarks on the accreditation journey. This paper presents a computational model based on Bayesian Networks (BN) for this purpose. The formalism focused on the use of Bayesian statistics and decision graphs. Identification of the BN variables, conditional dependencies, probabilistic information and domain knowledge were obtained from field investigations. Model evaluation was performed using a set of known scenarios that represent unequivocal prescriptions. The model enables predicting the results of implementing a management system, and simulating the accreditation process results. This development also identified the variables that have a significant influence on the expected results of the LMS accreditation process.","PeriodicalId":318846,"journal":{"name":"2022 IEEE Biennial Congress of Argentina (ARGENCON)","volume":"124 3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114310370","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