Large-scale internet user behavior analysis of a nationwide K-12 education network based on DNS queries

ANII Fondo Sectorial de Investigación a partir de datos (FSDA_1_2018_1_154853)To the best of our knowledge, this paper presents the first Internet Domain Name System (DNS) queries data study from a national K-12 Education Service Provider. This provider, called Plan Ceibal, supports a one-to-one computing program in Uruguay. Additionally, it has deployed an Information and Communications Technology (ICT) infrastructure in all of Uruguay’s public schools and high-schools, in addition to many public spaces. The main development is wireless connectivity, which allows all the students (whose ages range between 6 and 18 years old) to connect to different resources, including Internet access. In this article, we use 9,125,888,714 DNS-query records, collected from March to May 2019, to study Plan Ceibal user’s Internet behavior applying unsupervised machine learning techniques. Firstly, we conducted a statistical analysis aiming at depicting the distribution of the data. Then, to understand users’ Internet behavior, we performed principal component analysis (PCA) and clustering methods. The results show that Internet use behavior is influenced by age-group and time of the day. However, it is independent of the geographical location of the users. Internet use behavior analysis is of paramount importance for evidence-based decision making by any education network provider, not only from the network-operator perspective but also for providing crucial information for learning analytics purposes

LETEO: Scalable anonymization of big data and its application to learning analytics

ANII Fondo sectorial de investigación con datos - 2018Created in 2007, Plan Ceibal is an inclusion and equal opportunities plan with the aim of supporting Uruguayan educational policies with technology. Throughout these years, and within the framework of its tasks, Ceibal has an important amount of data related to the use of technology in education, necessary to manage the plan and fulfill the assigned legal tasks. However, the data does not they can be studied without accounting for the problem of de identifying the users of the Plan. To exploit this data, Ceibal has deployed an instance of the Hortonworks Data Platform (HDP), a open source platform for the storage and parallel processing of massive data (big data). HDP offers a wide range of functional components ranging from large file storage (HDFS) to distributed programming of machine learning algorithms (Apache Spark / MLlib). However, as of today there are no solutions for the de-identification of personal code data open and integrated into the Hortonworks ecosystem. On the one hand, the deidentification tools existing data have not been designed so that they can easily scale to large volumes of data, and they also do not offer easy integration mechanisms with HDFS. This forces you to export the data outside of the platform that stores them to be able to anonymize them, with the consequent risk of exposure of confidential information. On the other hand, the few integrated solutions in the Hortonworks ecosystem are owners and the cost of their licenses is very significant. The objective of this project is to promote the use of the enormous amount of educational and technological data that Ceibal possesses, lifting one of the greatest obstacles that exist for that, namely, the preservation of privacy and the protection of the personal data of the beneficiaries of the Plan. To this end, this project seeks to generate anonymization tools that extend the HDP platform. On In particular, it seeks to develop open source modules to integrate into said platform, which implement a set of programmed anonymization techniques and algorithms in a distributed manner using Apache Spark and that can be applied to data sets stored in HDFS files

Informe final del proyecto: Evaluación temporal y espacial del impacto del cambio de cobertura del suelo sobre la calidad del agua: cuenca del río Santa Lucía como cuenca piloto

En las últimas décadas, en Uruguay, se han producido cambios significativos de uso del suelo como resultado de la intensificación y expansión de las actividades agropecuarias e industriales. Estas actividades, muchas veces realizadas sin considerar la protección del medio ambiente, han generado severos daños a la conservación de los ecosistemas acuáticos del país en general, y a la calidad del agua en particular. La cuenca del río Santa Lucía constituye uno de los sistemas hidrográficos más importantes del país porque representa la fuente de agua potable para más de la mitad de la población nacional, además de ser una fuente de agua de riego para la zona de actividad agroindustrial más intensa del país. Desde 2004, año de comienzo del registro de información sistemático de calidad de agua, el río Santa Lucía sufre una progresiva eutrofización, alcanzando niveles elevados de fósforo total. El desafío es por lo tanto desarrollar en la cuenca actividades productivas relevantes para el desarrollo económico del país preservando la calidad de los cuerpos de agua y evitando la afectación de otras actividades como la potabilización de aguas o la preservación de ecosistemas relevantes como los humedales del río Santa Lucía. Basándonos en lo anterior, este proyecto propone utilizar algoritmos de aprendizaje automático no supervisados para investigar las correlaciones entre los cambios en el uso del suelo y/o cobertura del suelo, y los parámetros físico-químicos de calidad del agua. Como resultado, se crearán conocimientos fundamentales para diseñar estrategias efectivas para disminuir la contaminación del agua debido al cambio en el uso del suelo a lo largo del tiempo. El enfoque metodológico desarrollado por este trabajo no será específico para el lugar de estudio, sino que será aplicable en otras cuencas donde se aborden problemáticas similares a las aquí planteadas.Agencia Nacional de Investigación e Innovació

Reduction of Weed Growth under the Influence of Extracts and Metabolites Isolated from <i>Miconia</i> spp.

Weeds pose a problem, infesting areas and imposing competition and harvesting difficulties in agricultural systems. Studies that provide the use of alternative methods for weed control, in order to minimize negative impacts on the environment, have intensified. Native flora represents a source of unexplored metabolites with multiple applications, such as bioherbicides. Therefore, we aimed to carry out a preliminary phytochemical analysis of crude extracts and fractions of Miconia auricoma and M. ligustroides and to evaluate these and the isolated metabolites phytotoxicity on the growth of the target species. The growth bioassays were conducted with Petri dishes with lettuce, morning glory, and sourgrass seeds incubated in germination chambers. Phytochemical analysis revealed the presence of flavonoids, isolated myricetin, and a mixture of quercetin and myricetin. The results showed that seedling growth was affected in a dose-dependent manner, with the root most affected and the seedlings of the lettuce, morning glory, and sourgrass as the most sensitive species, respectively. Chloroform fractions and myricetin were the most inhibitory bioassays evaluated. The seedlings showed structural changes, such as yellowing, nonexpanded cotyledons, and less branched roots. These results indicate the phytotoxic potential of Miconia allelochemicals, since there was the appearance of abnormal seedlings and growth reduction

Qualidade para processamento de clones de batata cultivados durante a primavera e outono no Rio Grande do Sul Processing quality of potato clones during spring and autumn grown conditions of Rio Grande do Sul

A industrialização da batata (Solanum tuberosum L.) tem sido limitada no Brasil, quase que exclusivamente, pela falta de matéria-prima adequada. Alta qualidade do produto processado é dependente de altos teores de matéria seca, que reduz a absorção de óleo durante a fritura e confere crocância, e baixos teores de açúcares redutores, que mantêm a coloração clara das fritas. O objetivo deste trabalho foi identificar clones de batata de alta qualidade para processamento a partir da avaliação de tubérculos produzidos durante os cultivos de primavera de 2003 e outono de 2004 em Santa Maria, RS. O experimento foi conduzido em um fatorial (15 clones e duas épocas de cultivo) no delineamento de blocos ao acaso, com quatro repetições. Foram avaliados os clones Dakota Rose, SMINIAIporã, SMIJ461-1, SMIJ319-1, SMIJ456-4Y, SMID040-4RY, SMIE040-6RY, SMIC148-A, SMIF165-6RY, SMIH095-1, SMINIA90244-1, SMINIA793101-3, SMINIA95043-11, Macaca e Asterix nos cultivos de primavera de 2003 e outono de 2004 em Santa Maria, RS. As condições ambientais, durante o período de produção, influenciaram a qualidade pós-colheita dos tubérculos. Os clones SMIJ461-1, SMIJ319-1, SMIJ456-4Y, SMIC148-A, SMIDO40-4RY e SMIH095-1 foram os que apresentaram o melhor desempenho nas características desejáveis para processamento, sendo superiores a Asterix, cultivada para consumo de mesa ou para processamento na forma de chips nas diferentes regiões produtoras de batata. Dentre esses clones, SMIDO40-4RY e SMIH095-1 foram os menos influenciados pelas diferenças de temperatura e insolação típicas das épocas de cultivo de outono e primavera no RS. Os clones SMIJ461-1 e SMIJ456-4Y apresentaram maior teor de matéria seca e coloração mais clara do chips no cultivo da primavera.<br>The development of the potato (Solanum tuberosum L.) processing industry has been limited in Brazil, because of the low availability of tubers with adequate quality. High dry matter, responsible for chips with low oil content and crispy consistency, and low reduced sugars, keep chips with light color, are necessary for high quality processing products. The objective was to identify potato clones with high processing quality based upon the evaluation of tubers produced under spring 2003 and autumn 2004 grown seasons at Santa Maria, RS, Brazil. The experiment was conducted in a factorial (15 clones and two grown seasons) in a complete random design with four replications. The clones Dakota Rose, SMINIAIporã, SMIJ461-1, SMIJ319-1, SMIJ456-4Y, SMID040-4RY, SMIE040-6RY, SMIC148-A, SMIF165-6RY, SMIH095-1, SMINIA90244-1, SMINIA793101-3, SMINIA95043-11, Macaca and Asterix were evaluated in Santa Maria, Rio Grande do Sul (RS) State, during spring 2003 and autumn 2004 grown seasons. The environmental conditions during grown season affected the postharvest quality of tubers. The clones SMIJ461-1, SMIJ319-1, SMIJ456-4Y, SMIC148-A, SMIDO40-4RY and SMIH095-1 had the highest processing quality, even better than Asterix cultivated for tablestock or chip processing in different potato production regions. Different environmental conditions of temperature and sunshine, common between spring and autumn grown seasons of RS, had little effect in the processing quality performance of SMIDO40-4RY and SMIH095-1 clones. The clones SMIJ461-1 and SMIJ456-4Y had the highest dry matter content and the lightest chip color during the spring grown conditions