Rodríguez Aguilar, Román

Main Affiliation
Preferred name
Rodríguez Aguilar, Román
Official Name
Rodríguez Aguilar, Román
ORCID
0000-0002-6496-4453
Researcher ID
AAO-6158-2020
Scopus Author ID
56717663000

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2014 - 2019272020 - 202670

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Now showing 1 - 10 of 97
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    Genetic electro-search optimization for optimum energy consumption in edge computing-based internet of healthcare things
    (Springer Nature, 2024)
    Köse, Utku
    ;
    Marmolejo Saucedo, José Antonio
    ;
    Rodríguez Aguilar, Román  
    ;
    Marmolejo-Saucedo, Liliana
    ;
    Rodriguez-Aguilar, Miriam
    Energy consumption is a vital issue when optimum usage and carbon footprint are all considered in today’s Internet of Things (IoT) environments. Considering edge computing, that becomes too critical in terms of wireless devices with limited battery power. Especially in healthcare applications, the defined IoHT approach requires sustainability while future massive solutions may result negative outputs in terms of carbon footprint. So, optimum energy consumption seems positive in terms of multiple ways. In the literature, one trendy method is using clustering for lowering the energy consumption within the Internet of Healthcare Things (IoHT) environment on edge computing. In this study, optimization of energy consumption in IoHT was done via improved Genetic Electro-Search Optimization (GESO) algorithm. According to the obtained findings in the performed applications, GESO was effective enough in finding optimum conditions of energy consumption for an active IoHT setup. © 2024 Springer Nature
      1  18
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    Optimization of public resources through an ensemble-learning model to measure quality perception in the social protection system in health of Mexico
    (Springer, 2018)
    Rodríguez Aguilar, Román  
    ;
    Rivera-Peña, Gustavo
    In order to optimize the use of public resources, a model of ensemble learning was proposed to measure the perception of quality in the medical care granted to the people affiliated to the social protection in health system of Mexico. Which allows a more efficient allocation of resources based on the main areas of opportunity identified in the measurement of service quality. Identify the effect of the main factors that are directly related to the satisfaction level and perception of quality of health services. A satisfaction index was built using an ensemble model using principal component analysis, logistic model and bagging meta-estimator, to identify the effect of a group of factors in the perception of quality of health services and monitor the perceived quality of users in real time. The survey data collected for the “Social Protection System in Health-SPSS 2014” was used, considering a sample of 28,290 users. The proposed index shows, in general, the positive perception of quality of health services, the national average index was of 0.0756, 95% CI [− 9.714 to 2.027]. There are factors statistically significant (P < 0.05) that influence these results, among the most important that can be highlighted is the good perception of infrastructure OR 2.12; CI [95% 1.9–2.36]; the gratuity of the service provided OR 1.98; CI [95% 1.42–2.76]; and full medicines supply OR 1.81; CI [95% 1.91–2.36]. The key factors identified that determine the perception of quality allow to define focused strategies and lines of action to improve service quality as well as better allocation of resources. ©Springer, The Authors.
    Scopus© Citations 1  14
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    Evolutionary Optimization of Entanglement Distillation Using Chialvo Maps
    (Springer, 2023)
    Ganesan, Timothy
    ;
    Rodríguez Aguilar, Román  
    ;
    Marmolejo Saucedo, José Antonio
    ;
    Vasant, Pandian
    In quantum information theory, entanglement distillation is a key component for designing quantum computer networks and quantum repeaters. In this work, the practical entanglement distillation problem is re-designed in a bilevel optimization framework. The primary goal of this work is to propose and test an effective optimization technique that combines evolutionary algorithms (differential evolution) and the Chialvo map - for solving the bilevel practical entanglement distillation problem. The primary idea is to leverage on the complex dynamical behavior of Chialvo maps to improve the optimization capabilities of the evolutionary algorithm. Analysis on the computational results and comparisons with a standard evolutionary algorithm implementation is presented. ©2023 springer, The authors.
    Scopus© Citations 1  27
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    Designing a resilient supply chain: An approach to reduce drug shortages in epidemic outbreaks
    (European Alliance for Innovation, 2020)
    Lozano-Díez, José Antonio  
    ;
    Marmolejo Saucedo, José Antonio
    ;
    Rodríguez Aguilar, Román  
    Introduction: Supply network design is a long-studied topic that has evolved to address disruptive situations. The risk of supply chain disruption leads to the development of resilient supply chains that are capable of reacting effectively. Objectives: In the context of public health, drug supply networks face shortage challenges in many situations, such as current epidemic outbreaks such as COVID-19. Drug shortages can occur due to manufacturing problems, lack of infrastructure, and immediate reaction mechanisms. Methods: The case study is solved with anyLogistix optimization and simulation software. RESULTS: We present the results of a hypothetical study on the impact of COVID-19 on a regional supply network. The results of this research are intended to be the basis for the design of resilient supply chains in epidemic outbreaks. Conclusión: Drug providers should consider strategies to prevent or reduce the impact of shortages as well as disruption spreads. ©2020 José Antonio Lozano Díez, José Antonio Marmolejo Saucedo & Roman Rodríguez Aguilar, licensed to European Alliance for Innovation.
      2  14Scopus© Citations 50
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    Structural Dynamics and disruption events in Supply Chains using Fat Tail Distributions
    (2019)
    Rodríguez Aguilar, Román  
    ;
    Marmolejo Saucedo, José Antonio
    The analysis of structural dynamics in a supply chain requires robust methods for the modeling of disruption events that can be faced. Statistical modeling, the machine learning application and access to large amounts of data require much more realistic models to manage risk in the supply chain. This study proposes a statistical methodology for the modeling of disruption events in the supply chain with heavy tailed distributions, which will allow the construction of models more closely linked to reality for risk management in the supply chain. © 2019, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.
      1Scopus© Citations 4  32
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    The mahalanobis distance between the hurst coefficient and the Alpha-Stable parameter: An early warning indicator of crises
    (Academic Publications, 2016)
    Rodríguez Aguilar, Román  
    ;
    Cruz-Aké, Salvador
    ;
    Venegas-Martínez, Francisco
    The Hurst coefficient and the alpha-stable parameter are useful indicators in the analysis of time series to detect normality and absence of self-similarity. In particular, when these two features met simultaneously the series is driven by white noise. This paper is aimed at developing an index to measure the degree to which a time series departs from white noise. The proposed index is built by using the principal component analysis of the Mahalanobis distances between the Hurst coefficient and the alpha-stable parameter from theoretical values of normality and absence of self-similarity. The proposed index is applied to examine the Mexican Peso exchange rate against the US Dollar. The distinctive characteristic of the index is that it can be used as an early warning indicator of crises, as it is shown for the Mexican case. © 2010, Academic Publications, Ltd.; https://ijpam.eu ©The authors.
      15
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    Foreword : Digital Transformation and XAI in Healthcare
    (CRC Press, 2025)
    Rodríguez Aguilar, Román  
    ;
    Uysal, Ilhan
    ;
    Jafar Ahmad, Abed Alzubi
    ;
    Milen, Mehmet
    This book explores the pivotal role of explainable artificial intelligence (XAI) in driving digital transformation within the healthcare sector, providing comprehensive insights into its applications, ethical and legal considerations, technological requirements, and future trends. ©The authors ©CRC Press.
      30  33
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    Guide for Sustainable Project Analysis to Improve Energy Efficiency of Mexican SME
    (2021)
    Reyes Ortega, Luz María Adriana
    ;
    Rodríguez Aguilar, Román  
    Faced with the need of overall cleaner production processes, the Government of Mexico, in coalition with international cooperation agencies, has made efforts to spark to a cleaner transition by the conferment of financing under preferential conditions for small and medium-sized enterprises (SMEs), which are the backbone of the Mexican economy. This will help the implementation of sustainable projects that promote the reduction of energy consumption and Greenhouse Gas (GHG) emissions. However, these efforts have not yielded the expected results since the viability of the loans is determined by the Financial Institutions (FIs) based solely on profitability analysis of the SMEs. If this analysis is complemented with consideration of environmental and social aspects, a greater number of projects would be subject to financing. Real Options method allows the calculation of future cash flows incorporating the uncertainty from the volatility associated with the projects, allowing future adjustments to be made to them based on their performance. In addition, under the economic cost-effectiveness analysis, costs incurred in the implemented projects are compared against the results, assigning a monetary value to them to determine their overall impact. Derived from the limitations in the valuation of sustainable projects in SMEs, this article aims to establish a guide for comprehensive evaluation, using a cost-effectiveness approach and addressing the uncertainty of the project through Real Options. Considering the diversity of the SME during this study, the target companies and the type of projects that have the best opportunities for successful application of the proposed guide were segmented. © 2021, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.
    Scopus© Citations 1  2  5
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    Catastrophic Health Spending by COVID-19 in the Mexican Insurance Sector
    (Springer, 2024-01-01)
    Domínguez-Gutiérrez, Ulises
    ;
    Rodríguez Aguilar, Román  
    The COVID-19 pandemic that the world has been suffering for 3 years has generated major impacts worldwide, both in public health systems and in the private insurance industry. The high costs of care derived from cases with complications have likewise generated a great impact on the private insurance industry. In the case of Mexico, the mortality rates observed are among the first places, in addition to generating a great impact on private insurance. This work deals with the measurement of the impact of catastrophic expenses derived from COVID-19 in an insurance company; using a set of machine learning models, the key variables in the estimation of patients with potential catastrophic expenses were determined. The results show that the estimated classification model has a positive performance in addition to allowing the identification of the main risk factors of the insured as well as their potentially catastrophic impact on insurance companies.© 2024 Springer Nature
      1  20
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    Catastrophic health spending in Mexico and its determinants, 2002-2014
    (Academia Nacional de Medicina de México, 2017)
    Rodríguez Aguilar, Román  
    ;
    Rivera-Peña, Gustavo
    Objective: To assess the financial protection of public health insurance by analyzing the percentage of households with catastrophic health expenditure (HCHE) in Mexico and its relationship with poverty status, size of locality, federal entity, insurance status and items of health spending. Method: Mexican National Survey of Income and Expenditures 2002-2014 was used to estimate the percentage of HCHE. Through a probit model, factors associated with the occurrence of catastrophic spending are identified. Analysis was performed using Stata-SE 12. Results: In 2014 there were 2.08% of HCHE (1.82-2.34%; N = 657,474). The estimated probit model correctly classified 98.2% of HCHE (Pr (D) ≥ 0.5). Factors affecting the catastrophic expenditures were affiliation, presence of chronic disease, hospitalization expenditure, rural condition and that the household is below the food poverty line. Conclusions: The percentage of HCHE decreased in recent years, improving financial protection in health. This decline seems to have stalled, keeping inequities in access to health services, especially in rural population without affiliation to any health institution, below the food poverty line and suffering from chronic diseases. ©2017 Gaceta Médica de México, Los autores.
    Scopus© Citations 2  6