Browsing by Author "Moya-Almeida, Vinicio"

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    Assessing Service Imbalances as Contributing Factors to Mobility Issues in the Metropolitan District of Quito, Ecuador
    (Urban Science, 2024-12-10) Astudillo-Ortega, Tatiana; Moya-Almeida, Vinicio; Cabrera-Torres, Francisco; Ávila-Castro, Emilia; Heredia-R, Marco; Vázquez Hoehne, Antonio
    This article analyzes the service distribution imbalance within the Metropolitan District of Quito (DMQ) and its impact on urban mobility, aiming to propose strategies for more equitable territorial planning. The data were gathered from sources such as the National Institute of Statistics and Census (INEC), the Ministry of Health, the Ministry of Education, and OpenStreetMap. These data were integrated with GIS tools to model patterns of accessibility and mobility. Through a comprehensive approach, the study assessed education, banking services, employment, and healthcare, identifying how inequitable access to these services drives increased travel demand, especially in rural and peri-urban areas. In the education field, over 500 neighborhoods faced a shortage of institutions, compelling students to commute to other neighborhoods. For financial services, only 67% of neighborhoods had adequate access, with disparities across different socioeconomic zones. Additionally, employment-related mobility posed another challenge, with 88% of workers commuting outside their residential parish. Finally, access to healthcare was also unequal across the DMQ, particularly in peripheral areas where residents must travel long distances. In this context, it can be concluded that more efficient urban planning in the Metropolitan District of Quito (DMQ) is crucial to address imbalances in the distribution of services and enhance quality of life. Proposed strategies include establishing a land reserve, decentralizing services to underserved areas, integrating smart technologies, and promoting incentives for remote work, sustainable mobility, and public transport. These actions aim to foster greater territorial equity and accessibility.
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    Quantitative assessment of urban sustainability perceptions in Lurin, Peru
    (One Ecosystem, 2024-08-06) Ojeda-Zaga, Ruth; Moya-Almeida, Vinicio; Alvarado-Arias, Natalia; Zuleta-Mediavilla, Diana
    In the current context, urban centres in Latin America are facing fundamental challenges in their endeavour for Sustainable Development. The focus of this study is the meticulous assessment of the perception of urban sustainability within the Lurín District of Peru. It introduces a system based on urban sustainability indicators, derived from social surveys and implements this system through linear regression models to discern their interrelations. The objective of the research is to quantify and evaluate essential elements linked to the management of natural resources, air and water quality, the advancement of sustainable mobility, education and the well-being of urban residents. By delineating these mathematical and statistical correlations amongst variables pertinent to urban sustainability, this study provides a robust framework for quantitative decision-making in the urban sphere. A methodology for the development of univariable and multivariable models has been demonstrated. Amongst the most important findings, it has been discovered that the variable Environmental Education System (SEA) is perceived as the least important and even negligible within the multivariable models. However, we believe this effect occurs because the impacts of education are perceived in the long term. This article contributes significantly to the academic discourse by providing a more nuanced understanding of the social perception of urban sustainability and its influence on policy formulation and decision-making processes in Latin America.
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    Setpoint temperature estimation to achieve target solvent concentrations in S. cerevisiae fermentations using inverse neural networks and fuzzy logic
    (Engineering Applications of Artificial Intelligence, 2024-01-31) Moya-Almeida, Vinicio; Diezma-Iglesias, Belén; Correa-Hernando, Eva; Vaquero-Miguel, Cristian; Alvarado-Arias, Natalia
    Over the years, many technical advances have been made to improve the final quality of beers by controlling the concentrations of compounds obtained at the end of alcoholic fermentation. However, these efforts have mainly focused on increasing ethanol and reducing other compounds considered defects. This study addresses the challenge of obtaining specific concentrations of four solvent compounds (isobutanol, ethyl acetate, amyl alcohols, and n-propanol) produced by the yeast S. cerevisiae Safale S04, determined by an expert. A model based on four inverse neural networks (INNs) has been developed to predict the target temperature required to achieve the desired concentrations. These INNs have been trained using virtual data generated by four artificial neural networks (ANNs), as described in detail in previous work. For implementation, a fuzzy control system based on the Mamdani inference method was utilized. To experimentally validate the results, four complete fermentations were conducted. The INNs were found to be accurate tools for predicting the target temperatures based on predetermined compound concentrations, with R2 values ranging from 0.982 to 0.986. When comparing the experimental concentration data, the most accurate prediction was achieved for n-propanol, with an average error of 0.18 mg L−1, while ethyl acetate had an error of 0.25 mg L−1, isobutanol had an error of 0.48 mg L−1, and amyl alcohols, being the least precise prediction, had an error of 0.83 mg L−1.