Role of the sediments of two tropical dam reservoirs in the flux of metallic elements to the water column

In tropical climates, the high rainfall and temperature, throughout the annual cycle, allow high leaching rates of metallic elements from the basin upstream, which accumulate in the reservoirs. However, the concentration of these elements in natural waters is usually lower than expected, due to the ease of adsorption and co-precipitation in solid phases. We have studied two tropical dam reservoirs in Brazil, Três Marias (Minas Gerais) and Tucuruí (Pará), with the aim of understanding the correlation between physical–chemical parameters of the water column, chemical and mineralogical characteristics of the accumulated material and the solubility, mobilization and precipitation of metals in reservoirs. Metals speciation performed in selected samples determined that metallic micronutrients are preferentially adsorbed or retained through precipitation/co-precipitation onto fine-size charged crystalline/amorphous Fe-oxides. Under the prevailing reducing and low pH conditions of the bottom reservoirs, some adsorbed metals (particularly Fe and Mn) are easily released from their metal bearing-phases and mobilized to the aqueous phase of sediments, which show high levels of soluble forms of these elements. However, the solubilization process and the release to the water column are not very extensive, as abundances of metals such as Fe, Mn, Zn and Cu in water are low, although increasing with dept

Incidencia y vigencia del taylorismo y fordismo en la producción industrial moderna

En el presente artículo se da a conocer que la producción industrial actual ha estado y esta influenciada por dos paradigmas de la producción como lo son el taylorismo y el fordismo, que dieron la pauta en todo un desarrollo consecuente en la mejora de los sistemas de producción actuales como el JAT, robótica, MTPS, producción en linea, manufactura flexble, entre otros, y que para el caso particular de la industria automovilística ha progresado exitosamente gracias a los preceptos y principios de estas teorías

Javier García Liendo. El intelectual y la cultura de masas. Argumentos latinoamericanos en torno a Ángel Rama y José María Arguedas. West Lafayette: Purdue UP, 2017.

Review of Javier García Liendo. El intelectual y la cultura de masas. Argumentos latinoamericanos en torno a Ángel Rama y José María Arguedas. West Lafayette, Indiana: Purdue University Press, 2017

Geometric SMOTE for imbalanced datasets with nominal and continuous features

Fonseca, J., & Bacao, F. (2023). Geometric SMOTE for imbalanced datasets with nominal and continuous features. Expert Systems with Applications, 234(December), 1-9. [121053]. https://doi.org/10.1016/j.eswa.2023.121053 --- This research was supported by research grants of the Portuguese Foundation for Science and Technology (“Fundação para a Ciência e a Tecnologia”), references SFRH/BD/151473/2021, DSAIPA/DS/0116/2019, and by project UIDB/04152/2020 — Centro de Investigação em Gestão de Informação (MagIC) .Imbalanced learning can be addressed in 3 different ways: Resampling, algorithmic modifications and cost-sensitive solutions. Resampling, and specifically oversampling, are more general approaches when opposed to algorithmic and cost-sensitive methods. Since the proposal of the Synthetic Minority Oversampling TEchnique (SMOTE), various SMOTE variants and neural network-based oversampling methods have been developed. However, the options to oversample datasets with nominal and continuous features are limited. We propose Geometric SMOTE for Nominal and Continuous features (G-SMOTENC), based on a combination of G-SMOTE and SMOTENC. Our method modifies SMOTENC’s encoding and generation mechanism for nominal features while using G-SMOTE’s data selection mechanism to determine the center observation and k-nearest neighbors and generation mechanism for continuous features. G-SMOTENC’s performance is compared against SMOTENC’s along with two other baseline methods, a State-of-the-art oversampling method and no oversampling. The experiment was performed over 20 datasets with varying imbalance ratios, number of metric and non-metric features and target classes. We found a significant improvement in classification performance when using G-SMOTENC as the oversampling method. An open-source implementation of G-SMOTENC is made available in the Python programming language.publishersversionpublishe

Evaluación - Prueba de habilidades prácticas CCNA Diplomado de profundización CISCO (Diseño e implementación de soluciones integradas LAN / WAN).

El presente trabajo corresponde al análisis y desarrollo de dos escenarios prácticos relacionados con diferentes temas de Networking, tales como configuración de dispositivos, validación de conectividad, construcción de la topología de la red. Los escenarios están planteados de una forma que simula una situación real, por lo que se requiere la aplicación de los conocimientos y habilidades adquiridas durante el transcurso del diplomado de profundización CCNA para su desarrollo. Como herramienta de configuración y simulación de los escenarios planteados se utiliza el software Packet Tracer, para la creación de las topologías de red y simulaciones de conectividad.The present work corresponds to the analysis and development of two practical scenarios related to different Networking topics, such as device configuration, connectivity validation, construction of the network topology. The scenarios are presented in a way that simulates a real situation, so the application of the knowledge and skills acquired during the course of the CCNA deepening diploma is required for its development. The Packet Tracer software is used as a configuration and simulation tool for the proposed scenarios, for the creation of network topologies, connectivity simulations

Improving Active Learning Performance through the Use of Data Augmentation

Fonseca, J., & Bacao, F. (2023). Improving Active Learning Performance through the Use of Data Augmentation. International Journal of Intelligent Systems, 2023, 1-17. https://doi.org/10.1155/2023/7941878 --- Funding: This research was supported by three research grants of the Portuguese Foundation for Science and Technology (“Fundação para a Ciencia e a Tecnologia”): SFRH/BD/151473/2021 - MIT Portugal PhD Grant; DSAIPA/DS/0116/2019, and PCIF/SSI/0102/2017.Active learning (AL) is a well-known technique to optimize data usage in training, through the interactive selection of unlabeled observations, out of a large pool of unlabeled data, to be labeled by a supervisor. Its focus is to find the unlabeled observations that, once labeled, will maximize the informativeness of the training dataset, therefore reducing data-related costs. The literature describes several methods to improve the effectiveness of this process. Nonetheless, there is a paucity of research developed around the application of artificial data sources in AL, especially outside image classification or NLP. This paper proposes a new AL framework, which relies on the effective use of artificial data. It may be used with any classifier, generation mechanism, and data type and can be integrated with multiple other state-of-the-art AL contributions. This combination is expected to increase the ML classifier’s performance and reduce both the supervisor’s involvement and the amount of required labeled data at the expense of a marginal increase in computational time. The proposed method introduces a hyperparameter optimization component to improve the generation of artificial instances during the AL process as well as an uncertainty-based data generation mechanism. We compare the proposed method to the standard framework and an oversampling-based active learning method for more informed data generation in an AL context. The models’ performance was tested using four different classifiers, two AL-specific performance metrics, and three classification performance metrics over 15 different datasets. We demonstrated that the proposed framework, using data augmentation, significantly improved the performance of AL, both in terms of classification performance and data selection efficiency (all the codes and preprocessed data developed for this study are available at https://github.com/joaopfonseca/publications/).publishersversionpublishe

a literature review

Fonseca, J., & Bacao, F. (2023). Tabular and latent space synthetic data generation: a literature review. Journal of Big Data, 10, 1-37. [115]. https://doi.org/10.1186/s40537-023-00792-7 --- This research was supported by two research grants of the Portuguese Foundation for Science and Technology (“Fundação para a Ciência e a Tecnologia”), references SFRH/BD/151473/2021 and DSAIPA/DS/0116/2019, and by project UIDB/04152/2020 - Centro de Investigação em Gestão de Informação (MagIC).The generation of synthetic data can be used for anonymization, regularization, oversampling, semi-supervised learning, self-supervised learning, and several other tasks. Such broad potential motivated the development of new algorithms, specialized in data generation for specific data formats and Machine Learning (ML) tasks. However, one of the most common data formats used in industrial applications, tabular data, is generally overlooked; Literature analyses are scarce, state-of-the-art methods are spread across domains or ML tasks and there is little to no distinction among the main types of mechanism underlying synthetic data generation algorithms. In this paper, we analyze tabular and latent space synthetic data generation algorithms. Specifically, we propose a unified taxonomy as an extension and generalization of previous taxonomies, review 70 generation algorithms across six ML problems, distinguish the main generation mechanisms identified into six categories, describe each type of generation mechanism, discuss metrics to evaluate the quality of synthetic data and provide recommendations for future research. We expect this study to assist researchers and practitioners identify relevant gaps in the literature and design better and more informed practices with synthetic data.publishersversionpublishe

Universidades portuguesas: una visión general de su historiografía

The purpose of this essay, rather than an exhaustive presentation of the historiographical output on Portuguese universities, is to lead the reader to the threshold of a comprehensive knowledge of the achievements and problems in this field; and try to provide a working tool for future research. Encompassing a long time span, with several changes in the higher education system in Portugal, besides mentioning general works and source publication, it approaches some topics: material conditions (buildings and funding), students and student culture, professors (with a glimpse on scientific production).La intención de este trabajo, más que hacer una presentación exhaustiva de la producción historiográfica sobre las universidades portuguesas, es conducir el lector hasta el umbral de un conocimiento informado de lo conseguido y de los problemas en esta materia; y también proporcionar un instrumento para ulterior investigación. Abarcando un largo período temporal con cambios notables en el sistema de educación superior en Portugal, aborda distintos tópicos como sean las condiciones materiales (los edificios y la financiación), los estudiantes y su cultura peculiar, los profesores (con una breve mirada a la producción científica).