Efficient Computation of Multiple Density-Based Clustering Hierarchies

HDBSCAN*, a state-of-the-art density-based hierarchical clustering method, produces a hierarchical organization of clusters in a dataset w.r.t. a parameter mpts. While the performance of HDBSCAN* is robust w.r.t. mpts in the sense that a small change in mpts typically leads to only a small or no change in the clustering structure, choosing a "good" mpts value can be challenging: depending on the data distribution, a high or low value for mpts may be more appropriate, and certain data clusters may reveal themselves at different values of mpts. To explore results for a range of mpts values, however, one has to run HDBSCAN* for each value in the range independently, which is computationally inefficient. In this paper, we propose an efficient approach to compute all HDBSCAN* hierarchies for a range of mpts values by replacing the graph used by HDBSCAN* with a much smaller graph that is guaranteed to contain the required information. An extensive experimental evaluation shows that with our approach one can obtain over one hundred hierarchies for the computational cost equivalent to running HDBSCAN* about 2 times.Comment: A short version of this paper appears at IEEE ICDM 2017. Corrected typos. Revised abstrac

Bifurcations and Averages in the Homoclinic Chaos of a Laser with a Saturable Absorber

The dynamical bifurcations of a laser with a saturable absorber were calculated, with the 3-2 level model, as function of the gain parameter. The average power of the laser is shown to have specific behavior at bifurcations. The succession of periodic-chaotic windows, known to occur in the homoclinic chaos, was studied numerically. A critical exponent of 1/2 is found on the tangent bifurcations from chaotic into periodic pulsations.Comment: 6 or 7 pages, 3 figures, publishe

A study on the impact of data balance on rainfall prediction through artificial neural networks using surface microwave radiometers

The National Institute for Space Research (INPE) has been a partner in significant projects that conduct atmospheric investigations impacting various sectors, such as the Amazon Tall Tower Observatory (ATTO) project. Since 2009, the project has conducted studies on the interactions between climate and the Amazon forest. ATTO has played an essential role in providing large volumes of data obtained by meteorological sensors, contributing to a deeper understanding of the atmospheric dynamics of the region. In a landscape where Artificial Intelligence-based rainfall forecast models gain prominence, this study explores the imbalance of data from the ATTO Campina field experiment and its influence on short-term rainfall forecasts using Artificial Neural Networks (ANNs). Metrics such as MAE, RMSE, and POD, as well as FAR indices, were applied in the assessment and revealed the connection between data balance and forecast results. More balanced data or data with greater weights for different rainfall ranges yield better results. The study emphasizes the importance of reliable data for training rain forecast models, aiming to improve the dexterity of these models. This approach is fundamental to increase the reliability of these models in real environments.The National Institute for Space Research (INPE) has been a partner in significant projects that conduct atmospheric investigations impacting various sectors, such as the Amazon Tall Tower Observatory (ATTO) project. Since 2009, the project has conducted studies on the interactions between climate and the Amazon forest. ATTO has played an essential role in providing large volumes of data obtained by meteorological sensors, contributing to a deeper understanding of the atmospheric dynamics of the region. In a landscape where Artificial Intelligence-based rainfall forecast models gain prominence, this study explores the imbalance of data from the ATTO Campina field experiment and its influence on short-term rainfall forecasts using Artificial Neural Networks (ANNs). Metrics such as MAE, RMSE, and POD, as well as FAR indices, were applied in the assessment and revealed the connection between data balance and forecast results. More balanced data or data with greater weights for different rainfall ranges yield better results. The study emphasizes the importance of reliable data for training rain forecast models, aiming to improve the dexterity of these models. This approach is fundamental to increase the reliability of these models in real environments

A súmula vinculante e o sistema recursal

Disponível também na Revista Juris Plenum, Caxias do Sul, RS, v. 3, n. 14, p. 57-62, mar. 2007.Sustenta que a reclamação constitucional contra decisão judicial ou ato administrativo não obsta outros recursos ou meios admissíveis de impugnação, como ação rescisória ou mandando de segurança e, na verdade, caracteriza uma exceção ao princípio da singularidade (unirrecorribilidade, absorção ou unicidade recursal)

Effect of temperature and flow rate on parallel flow co2 absorption by distilled water in co-current microchannel device / Efeito da temperatura e taxa de fluxo na absorção paralela de co2 por água destilada em dispositivo de microcanal co-atual

Mass transfer is a transport phenomenon that has great importance in chemical processes, especially in the processes of separation and absorption. The study of this phenomenon between phases carried out in channels has been developed in smaller scales, seeking to intensify the processes, increasing the mass transfer coefficients. To prove that these studies could be performed at low costs, a pure carbon dioxide absorption by distilled water was performed in a PMMA microchannel designed with 0.008 m of hydraulic diameter.  A parallel and stratified flow was achieved in the channel and all experiments had this flow characteristics throughout the changes in operating conditions. In the study, the Reynolds numbers were quantified, corresponding to the interval 212-563. These parameters were acquired by varying the gas surface velocity in the range of 0.46-1.84 m/s and the liquid surface velocity in the range of 0.034-0.071 m/s. The mass transfer quantification was also performed by calculating the volumetric mass transfer coefficient for different operating conditions, which included the surface velocities of the phases and the operating temperature of the system. The results of this work allow the analysis of the effects of temperature and flow characteristics between the liquid and gaseous phases on the mass transfer efficiency in channels. This paper shows that a higher mass transfer coefficient can be achieved in microchannels and that the results show the superiority of these systems compared to conventional mass transfer equipment such as bubble tower, spray tower and static mixers.

Aproveitamento de espaços ociosos com jardinagem e ornamentação

Orientador : Ionete Hasse.Monografia (especialização) - Universidade Federal do Paraná, Setor Litoral, Curso de Especialização em Educação Ambiental com ênfase em Espaços Educadores Sustentáveis.Inclui referências[não há resumo