332 research outputs found
Curso de Flautas Dolce
VII Seminário de Extensão Universitária da UNILA (SEUNI); VIII Encontro de Iniciação Científica e IV Encontro de Iniciação em Desenvolvimento Tecnológico e Inovação (EICTI 2019) e Seminário de Atividades Formativas da UNILA (SAFOR)El curso de flauta dulce ofrece un acercamiento inicial al instrumento como
herramienta de musicalización. A través de clases prácticas se abordan cuestiones
técnicas (respiración, digitación, escalas, entrenamiento rítmico) y el aprendizaje del
repertorio popular. Se ofrece en dos espacios: Alliance Fraternity Association
(proyecto social) y Campus AlmadaAgradezco a la Universidad de Integración Latino-Americana (UNILA) por el
financiamiento para este proyecto, los equipos y recursos necesarios para desarrollar
el proyecto del curso de flautas dulce.
Al orientador Me. Danilo Bogo, al colaborador Prof. Dr. Marcelo R. Villena y a
los voluntarios del proyect
Integral Human Pose Regression
State-of-the-art human pose estimation methods are based on heat map
representation. In spite of the good performance, the representation has a few
issues in nature, such as not differentiable and quantization error. This work
shows that a simple integral operation relates and unifies the heat map
representation and joint regression, thus avoiding the above issues. It is
differentiable, efficient, and compatible with any heat map based methods. Its
effectiveness is convincingly validated via comprehensive ablation experiments
under various settings, specifically on 3D pose estimation, for the first time
Características e controle da podridão "olho de boi" nas maçãs do sul do Brasil.
bitstream/item/55164/1/cir066.pd
Exploiting temporal information for 3D pose estimation
In this work, we address the problem of 3D human pose estimation from a
sequence of 2D human poses. Although the recent success of deep networks has
led many state-of-the-art methods for 3D pose estimation to train deep networks
end-to-end to predict from images directly, the top-performing approaches have
shown the effectiveness of dividing the task of 3D pose estimation into two
steps: using a state-of-the-art 2D pose estimator to estimate the 2D pose from
images and then mapping them into 3D space. They also showed that a
low-dimensional representation like 2D locations of a set of joints can be
discriminative enough to estimate 3D pose with high accuracy. However,
estimation of 3D pose for individual frames leads to temporally incoherent
estimates due to independent error in each frame causing jitter. Therefore, in
this work we utilize the temporal information across a sequence of 2D joint
locations to estimate a sequence of 3D poses. We designed a
sequence-to-sequence network composed of layer-normalized LSTM units with
shortcut connections connecting the input to the output on the decoder side and
imposed temporal smoothness constraint during training. We found that the
knowledge of temporal consistency improves the best reported result on
Human3.6M dataset by approximately and helps our network to recover
temporally consistent 3D poses over a sequence of images even when the 2D pose
detector fails
Learning 3D Human Pose from Structure and Motion
3D human pose estimation from a single image is a challenging problem,
especially for in-the-wild settings due to the lack of 3D annotated data. We
propose two anatomically inspired loss functions and use them with a
weakly-supervised learning framework to jointly learn from large-scale
in-the-wild 2D and indoor/synthetic 3D data. We also present a simple temporal
network that exploits temporal and structural cues present in predicted pose
sequences to temporally harmonize the pose estimations. We carefully analyze
the proposed contributions through loss surface visualizations and sensitivity
analysis to facilitate deeper understanding of their working mechanism. Our
complete pipeline improves the state-of-the-art by 11.8% and 12% on Human3.6M
and MPI-INF-3DHP, respectively, and runs at 30 FPS on a commodity graphics
card.Comment: ECCV 2018. Project page: https://www.cse.iitb.ac.in/~rdabral/3DPose
Component-aware Orchestration of Cloud-based Enterprise Applications, from TOSCA to Docker and Kubernetes
Enterprise IT is currently facing the challenge of coordinating the
management of complex, multi-component applications across heterogeneous cloud
platforms. Containers and container orchestrators provide a valuable solution
to deploy multi-component applications over cloud platforms, by coupling the
lifecycle of each application component to that of its hosting container. We
hereby propose a solution for going beyond such a coupling, based on the OASIS
standard TOSCA and on Docker. We indeed propose a novel approach for deploying
multi-component applications on top of existing container orchestrators, which
allows to manage each component independently from the container used to run
it. We also present prototype tools implementing our approach, and we show how
we effectively exploited them to carry out a concrete case study
Developing effective practice learning for tomorrow's social workers
This paper considers some of the changes in social work education in the UK, particularly focusing on practice learning in England. The changes and developments are briefly identified and examined in the context of what we know about practice learning. The paper presents some findings from a small scale qualitative study of key stakeholders involved in practice learning and education in social work and their perceptions of these anticipated changes, which are revisited at implementation. The implications for practice learning are discussed
ITS-rDNA phylogeny of Colletotrichum spp. causal agent of apple glomerella leaf spot.
Several diseases have affected apple production, among them there is Glomerella leaf spot (GLS) caused by Colletotrichum spp. The first report of this disease in apple was in plants nearby citrus orchards in São Paulo State, Brazil. The origin of this disease is still not clear, and studies based on the molecular phylogeny could relate the organisms evolutionarily and characterize possible mechanisms of divergent evolution. The amplification of 5.8S-ITS (Internal Transcribed Spacer) of rDNA of 51 pathogenic Colletotrichum spp. isolates from apples, pineapple guava and citrus produced one fragment of approximately 600 bases pairs (bp) for all the isolates analyzed. The amplified fragments were cleaved with restriction enzymes, and fragments from 90 to 500bp were obtained. The sequencing of this region allowed the generation of a phylogenetic tree, regardless of their hosts, and 5 isolated groups were obtained. From the "in silico" comparison, it was possible to verify a variation from 93 to 100% of similarity between the sequences studied and the Genbank data base. The causal agent of GLS is nearly related (clustered) to isolates of pineapple guava and to the citrus isolates used as control
Optimal conditions for conidial germination and infection of European pear leaves by Diplocarpon mespili.
The epidemiology of Entomosporium leaf spot (ELS) affecting European pear is poorly understood, which limits the development of an effective management strategy. In vitro assays were conducted to study the effect of temperature levels (5, 10, 15, 20, 25, and 30 °C) on Diplocarpon mespili conidial germination evaluated at different incubation times (0, 2, 4, 6, 8, 12, 24, and 48 h). Inoculation experiments were conducted to assess the effect of leaf wetness duration (0, 6, 12, 24, and 48 h) under constant temperature (20 °C) on ELS disease severity on leaves of cultivar ?Rocha?. The temperature × time interaction significantly affected conidial germination in both experiments and a response surface model was fitted to percent conidial germination data. The optimal temperature for conidial germination was estimated at 20 °C. The incubation period was estimated at 4 days for all leaf wetness durations, excepting the ?zero? duration for which no infection occurred. A minimum of 6 h of leaf wetness duration was required for D. mespili infection. Severity reached maximum values after 24 h of leaf wetness duration. A linear regression model described ELS severity increase over time in the absence of reinfection conditions and a monomolecular model described the increase of disease severity influenced by leaf wetness duration in both experiments
Characterization of Neofabraea actinidiae and N. brasiliensis as causal agents of apple bull's-eye rot in southern Brazil.
The causal agents of apple bull?s-eye rot in southern Brazil have recently been described as Neofabraea actinidiae and N. brasiliensis. Isolates of both species were evaluated for response of mycelial growth index (MGI) to different temperatures, enzyme production, mycelial growth inhibition and effective concentrations (EC 50 and EC 100 ) of the fungicides tri fl umizole, pyrimethanil and thiophanate methyl, as well as aggres- siveness on fruits of "Fuji " hybrid and " Pink Lady " . There was signi ficantly lower mycelium growth in N. brasiliensis compared with N. actinidiae at all temperatures tested. Neither species grew at 3 and 32°C. There were minor differences in production of enzymes in the two species, with all N. brasiliensis isolates showing no production of pectolyase at pH 7. The lowest EC 50 and EC 100 values were observed with thiophanate methyl. In general, " Fuji " fruits were more susceptible to Neofabraea infection and had larger lesions, while N. brasiliensis isolates showed greater aggressiveness on " Fuji " hybrid and " Pink lady " fruits compared with N. actinidiae
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