Institution
Universidade de Pernambuco
Education•Recife, Brazil•
About: Universidade de Pernambuco is a education organization based out in Recife, Brazil. It is known for research contribution in the topics: Population & Artificial neural network. The organization has 6147 authors who have published 6948 publications receiving 73648 citations.
Topics: Population, Artificial neural network, Cloud computing, Particle swarm optimization, Software development
Papers published on a yearly basis
Papers
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TL;DR: The authors look at the causes of cloud failures and recommend ways to prevent them and to minimize their effects when they occur.
Abstract: Guaranteeing high levels of availability is a huge challenge for cloud providers. The authors look at the causes of cloud failures and recommend ways to prevent them and to minimize their effects when they occur.
30 citations
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TL;DR: The study indicated that the number of biomarkers and the magnitude of changes were higher in the HIT compared with LIT, and both HIT and LIT improved the inflammatory profile.
Abstract: Purpose: To investigate the effects of a low- versus high-intensity aerobic training on biomarkers of inflammation and endothelial dysfunction in adolescents with obesity. Methods: Sixty-two adolescents with obesity [age = 15 (14) y, body mass index = 34.87 (4.22) kg·m−2] were randomized to receive either a high-intensity training (HIT, n = 31) or a low-intensity training (LIT, n = 31) for 24 weeks. All participants also received nutritional, psychological, and clinical counseling. Leptin, total and subtype leukocyte counts, tumor necrosis factor-alpha, interleukin-6, myeloperoxidase, soluble intercellular adhesion molecule-1, and soluble vascular cell adhesion molecule-1 were obtained at baseline and after 24 weeks. Results: HIT reduced neutrophils [from 4.4 (1.9) to 3.6 (1.3) µL−1 × 103; P = .01] and monocytes [from 7.2 (2.5) to 5.2 (1.8) µL−1 × 102; P < .01], but LIT increased neutrophils [from 4.5 (1.7) to 5.2 (3.3) µL−1 × 103; P = .01]. Although tumor necrosis factor-alpha increased in LIT [from 13.3...
30 citations
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TL;DR: LFT and HFT are an effective resource that may be included in the routine of maternity wards after a randomized, controlled, double-blind clinical trial with placebo composed of 33 puerperae with post-episiotomy pain.
Abstract: Objective: To evaluate the effectiveness of low-frequency TENS (LFT) and high-frequency TENS (HFT) in post-episiotomy pain relief. Method: A randomized, controlled, double-blind clinical trial with placebo composed of 33 puerperae with post-episiotomy pain. TENS was applied for 30 minutes to groups: HFT (100 Hz; 100 µs), LFT (5 Hz; 100 µs), and placebo (PT). Four electrodes were placed in parallel near the episiotomy and four pain evaluations were performed with the numeric rating scale. The first and the second evaluation took place before TENS application and immediately after its removal and were done in the resting position and in the activities of sitting and ambulating. The third and fourth evaluation took place 30 and 60 minutes after TENS removal, only in the resting position. Intragroup differences were verified using the Friedman and Wilcoxon tests, and the intergroup analysis employed the Kruskal- Wallis test. Results: In the intragroup analysis, there was no significant difference in the PT during rest, sitting, and ambulation (P>0.05). In the HFT and LFT, a significant difference was observed in all activities (P<0.001). In the intergroup analysis, there was a significant difference in the resting position in the HFT and LFT (P<0.001). In the sitting activity, a significant difference was verified in the second evaluation in the HFT and LFT (P<0.008). No significant difference was verified among the groups in ambulation (P<0.20). Conclusions: LFT and HFT are an effective resource that may be included in the routine of maternity wards.
30 citations
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18 May 2013TL;DR: A model for assessing students based on real market practices while preserving the authenticity of the learning environment is proposed and important results are presented that show the applicability of the proposed model for teaching Software Engineering.
Abstract: The continuous growth of the use of Information and Communication Technology in different sectors of the market calls out for software professionals with the qualifications needed to solve complex and diverse problems. Innovative teaching methodologies, such as the "Software Internship" model and PBL teaching approaches that are learner-centered and focus on bringing market reality to the learning environment, have been developed and implemented with a view to meeting this demand. However, the effectiveness of these methods cannot always be satisfactorily proved. Prompted by this, this paper proposes a model for assessing students based on real market practices while preserving the authenticity of the learning environment. To evaluate this model, a case study on skills training for software specialists for the Telecom market is discussed, and presents important results that show the applicability of the proposed model for teaching Software Engineering.
30 citations
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26 Oct 2008TL;DR: A clearer mathematical description is presented and a computationally efficient and simply described quantum learning algorithm is presented in contrast to what has been proposed to the quantum weighted version of the q-LNN.
Abstract: Quantum analogues of the (classical) logical neural networks (LNN) models are proposed in (q-LNN for short). We shall here further develop and investigate the q-LNN composed of the quantum analogue of the probabilistic logic node (PLN) and the multiple-valued PLN (MPLN) variations, dubbed q-PLN and q-MPLN respectively. Besides a clearer mathematical description, we present a computationally efficient and simply described quantum learning algorithm in contrast to what has been proposed to the quantum weighted version.
30 citations
Authors
Showing all 6197 results
Name | H-index | Papers | Citations |
---|---|---|---|
Laura C. Rodrigues | 75 | 431 | 21539 |
José Guilherme Cecatti | 56 | 414 | 10550 |
Anibal Faundes | 51 | 314 | 10714 |
Robert E. Condon | 48 | 192 | 7376 |
Ricardo Almeida | 43 | 250 | 7304 |
Mark A. Carlson | 41 | 206 | 7844 |
Ricardo Arraes de Alencar Ximenes | 36 | 181 | 4414 |
Ivan G. Costa | 36 | 129 | 3740 |
Tshilidzi Marwala | 35 | 525 | 5596 |
Cláudia Lúcia de Moraes Forjaz | 34 | 202 | 4549 |
Nelson Wolosker | 33 | 348 | 4416 |
Raphael Mendes Ritti-Dias | 32 | 277 | 11334 |
Marcelo Moraes Valença | 32 | 207 | 3702 |
Mauro Virgílio Gomes de Barros | 32 | 163 | 8608 |
Rômulo Araújo Fernandes | 31 | 290 | 6403 |