Martinez-Villaseñor, Lourdes
Main Affiliation
Preferred name
Martinez-Villaseñor, Lourdes
Official Name
Martínez Villaseñor, María de Lourdes
ORCID
0000-0002-9038-7821
Researcher ID
N-7607-2018
Scopus Author ID
55521085100
95 results
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Item type:Publication, Data-Driven Innovation for Intelligent Technology : Perspectives and Applications in ICT(Springer Cham, 2024); ; ; ; This book focuses on new perspectives and applications of data-driven innovation technologies, applied artificial intelligence, applied machine learning and deep learning, data science, and topics related to transforming data into value. It includes theory and use cases to help readers understand the basics of data-driven innovation and to highlight the applicability of the technologies. It emphasizes how the data lifecycle is applied in current technologies in different business domains and industries, such as advanced materials, healthcare and medicine, resource optimization, control and automation, among others. This book is useful for anyone interested in data-driven innovation for smart technologies, as well as those curious in implementing cutting-edge technologies to solve impactful artificial intelligence, data science, and related information technology and communication problems. ©Springer. ©The authors. ©The editors28 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, 17 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Towards an ontology for ubiquitous user modeling interoperability(2012); González-Mendoza, MiguelIn order to obtain a broader understanding of the user, some researchers in the community of user modeling envision the need to share information of user models between applications. But gathering distributed user information from heterogeneous sources to obtain user models interoperability implies handling syntactic and semantic heterogeneity. It is also important to provide means for a ubiquitous user model to evolve over time. We present U2MIO a dynamic ontology with flexible structure for user modeling interoperability based in SKOS ontology. The U2MIO provides mediation based user modeling for sharing and reusing information from heterogeneous user models. A two-tier matching strategy is proposed for the process of concept alignment that permits the interoperability between profile suppliers and consumers.1 47 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Special Issue on Interdisciplinary Artificial Intelligence: Methods and Applications of Nature-Inspired Computing(2022) ;González-Mendoza, Miguel ;Fonseca, Pablo A.; Inspiration in nature has been widely explored, from the macro to micro-scale. From a scientific perspective, these methods inspired by nature have proven to be efficient tools for tackling real-world problems because most of the latter are highly complex or the resources are limited to analyze them. This inspiration is justified by the fact that natural phenomena mainly emphasize adaptability, optimization, robustness, and organization, among other properties, to deal with complexity. In that sense, three methodologies are commonly considered: human-designed problem-solving techniques inspired by nature, the synthesis of natural phenomena to develop algorithms, and the use of nature-inspired materials to perform computations. Some applications of nature-inspired computing include data mining, machine learning, optimization, robotics, engineering control systems, human–machine interaction, healthcare, the Internet of Things, cloud computing, smart cities, and many others.|| This Special Issue aimed to cover original research works with emphasis on the methodologies and applications of nature-inspired computing to handle the above-mentioned complex systems. We received a total of 38 submitted papers, and 18 papers were accepted (covering 47% of acceptance rate).|| The Special Issue presents different works related to metaheuristic optimization methods and their applications of human brain inspiration and neural networks, natural language processing-based applications, and fuzzy-logic-based applications. ©2022 Applied Sciences, MDPI.1 6 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Process of Concept Alignment for Interoperability between Heterogeneous Sources(2013); González-Mendoza, MiguelSome researchers in the community of user modeling envision the need to share and reuse information scattered over different user models of heterogeneous sources. In a multi-application environment each application and service must repeat the effort of building a user model to obtain just a narrow understanding of the user. Sharing and reusing information between models can prevent the user from repeated configurations, help deal with application and services’ “cold start” problem, and provide enrichment to user models to obtain a better understanding of the user. But gathering distributed user information from heterogeneous sources to achieve user models interoperability implies handling syntactic and semantic heterogeneity. In this paper, we present a process of concept alignment to automatically determine semantic mapping relations that enable the interoperability between heterogeneous profile suppliers and consumers, given the mediation of a central ubiquitous user model. We show that the process of concept alignment for interoperability based in a two-tier matching strategy can allow the interoperability between social networking applications, FOAF, Personal Health Records (PHR) and personal devices.Scopus© Citations 2 2 40 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Orientación a padres para aprender a utilizar Internet como medio educativo(2006); Villalobos Torres, Elvia MarveyaSi se pretende hacer un buen uso de la Internet logrando que este medio sirva realmente al perfeccionamiento de las personas y por ende al mejoramiento de las familias y de la sociedad, es preciso reflexionar en torno a los nuevos retos educativos que este medio conlleva. Con respecto a las bondades de Internet se debe aprender cómo identificar información valiosa en un espacio en donde el exceso de fuentes, no todas confiables, puede llevar a la desinformación o pérdida de tiempo y esfuerzo en búsquedas inútiles. Por otro lado, es imperioso diseñar estrategias personalizadas para combatir las influencias negativas de la red y minimizar los riesgos sobre todo en los cibernautas más jóvenes permitiéndoles usar Internet asegurando su integridad física, mental y moral. Algunos padres y educadores tienen una sensación de aislamiento con respecto a las actividades que realizan los niños, adolescentes y jóvenes en la red dada la brecha digital que va creciendo entre los "enchufados" y los "desenchufados". Esta ignorancia del mundo digital en el que sus hijos y alumnos viven, virtualmente hablando, y la comunidad global con la que conviven, acarrea problemas para la familia que si no se atienden pueden terminar deteriorando las relaciones familiares, acabando con la comunicación en la familia y tirando literalmente por la "borda digital" toda la labor educativa de años. Con la finalidad de enfrentar los retos de la era de la digitalización se debe estudiar primeramente Internet para identificar las oportunidades y amenazas de este medio revolucionario con respecto a la familia9 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Ethical Challenges in Demand Prediction: A Case Study in the Wholesale Grocery Sector(Instituto Politécnico Nacional. Centro de Investigación en Computación, 2025) ;Duarte, JorgeArtificial Intelligence (AI) has emergedas a transformative tool in inventory management and demand prediction within the wholes ale grocerysector. By leveraging machine learning algorithms, businesses can analyze historical sales data, market trends, and seasonal variations to optimize inventory levels, reducing overstock and stockouts. AI-drivendemand prediction models provide accurate forecasts, enabling whole salers to anticipate customer needs and streamline supply chain operations. Thisarticle examines the ethical challenges associated with developing and implementing AI-driven demand prediction models in the wholesale grocery sector. As businesses seek to optimize their operations through artificial intelligence, significant ethical concerns arise that must be addressed to ensure responsible and fair implementation. This case study highlights the main ethical challenges identified in a grocery wholesaler, focusing on issues such as transparency, accountability, fairness, and human control. Through the analysis of aspecific demand prediction model, we discuss how these ethical concerns not only influence user acceptance of the model but also impact operational efficiency and customer satisfaction. The article aims to contribute to the ongoing dialogue on ethics in data science, providing insights and recommendations for companies looking to adopt predictive technologies ethically. ©The authors ©Computación y Sistemas © Instituto Politécnico Nacional. Centro de Investigación en Computación.17 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, An Intelligent Human Fall Detection System Using a Vision-Based StrategyElderly people is increasing dramatically during the current years, and it is expected that this population reaches 2.1 billion of individuals by 2050. In this regard, new care strategies are required. Assisted living technologies have proposed alternatives to support professional caregivers and families to take care of elderly people, such as in risk of falls. Currently, fall detection systems are able to alleviate the latter problem and reduce the time a person who suffered a fall receives assistance. Thus, this paper proposes a fall detection system based on image processing strategy to extract motion features through an optical flow method. For classification, we use these features as inputs to a convolutional neural network. We applied our approach in a dataset comprises video recordings of one subject performing different types of falls. In experimental results, our approach showed 92% accuracy on the dataset used. © 2019 IEEE.1 29Scopus© Citations 9 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Open Source Implementation for Fall Classification and Fall Detection Systems(2020); ; ;Nuñez Martínez, José Pablo; Distributed social coding has created many benefits for software developers. Open source code and publicly available datasets can leverage the development of fall detection and fall classification systems. These systems can help to improve the time in which a person receives help after a fall occurs. Many of the simulated falls datasets consider different types of fall however, very few fall detection systems actually identify and discriminate between each category of falls. In this chapter, we present an open source implementation for fall classification and detection systems using the public UP-Fall Detection dataset. This implementation comprises a set of open codes stored in a GitHub repository for full access and provides a tutorial for using the codes and a concise example for their application. © 2020, Springer Nature Switzerland AG.Scopus© Citations 2 2 19
