6,765 research outputs found

    2-Arc-transitive metacyclic covers of complete graphs

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    Regular covers of complete graphs whose fibre-preserving automorphism groups act 2-arc-transitively are investigated. Such covers have been classified when the covering transformation groups K are cyclic groups Z(d) for an integer d >= 2, metacyclic abelian groups Z(p)(2), or nonmetacyclic abelian groups Z(p)(3) for a prime p (see S.F. Du et al. (1998) [5] for the first two metacyclic group cases and see S.F. Du et al. (2005) [3] for the third nonmetacyclic group case). In this paper, a complete classification is achieved of all such covers when K is any metacyclic group. (C) 2014 Elsevier Inc. All rights reserved.116Ysciescopu

    Effect of aging on the reinforcement efficiency of carbon nanotubes in epoxy matrix

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    The reinforcement efficiency of carbon nanotubes (CNTs) in epoxy matrix was investigated in the elastic regime. Cyclic uniaxial tensile tests were performed at constant strain amplitude and increasing maximum strain. Post-curing of the epoxy and its composite at a temperature close to the glass transition temperature allowed us to explore the effect of aging on the reinforcement efficiency of CNT. It is found that the reinforcement efficiency is compatible with a mean field mixture rule of stress reinforcement by random inclusions. It also diminishes when the maximum strain increased and this effect is amplified by aging. The decrease of elastic modulus with increasing cyclic maximum strain is quite similar to the one observed for filled elastomers with increasing strain amplitude, a phenomenon often referred as the Payne effect

    Energy Consumption Forecasting Using Ensemble Learning Algorithms

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    DCAI 2019: Distributed Computing and Artificial Intelligence, 16th International Conference, Special SessionsThe increase of renewable energy sources of intermittent nature has brought several new challenges for power and energy systems. In order to deal with the variability from the generation side, there is the need to balance it by managing consumption appropriately. Forecasting energy consumption becomes, therefore, more relevant than ever. This paper presents and compares three different ensemble learning methods, namely random forests, gradient boosted regression trees and Adaboost. Hour-ahead electricity load forecasts are presented for the building N of GECAD at ISEP campus. The performance of the forecasting models is assessed, and results show that the Adaboost model is superior to the other considered models for the one-hour ahead forecasts. The results of this study compared to previous works indicates that ensemble learning methods are a viable choice for short-term load forecast.This work has received funding from National Funds through FCT (Fundaçao da Ciencia e Tecnologia) under the project SPET – 29165, call SAICT 2017.info:eu-repo/semantics/publishedVersio

    Open defecation and childhood stunting in India: an ecological analysis of new data from 112 districts.

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    Poor sanitation remains a major public health concern linked to several important health outcomes; emerging evidence indicates a link to childhood stunting. In India over half of the population defecates in the open; the prevalence of stunting remains very high. Recently published data on levels of stunting in 112 districts of India provide an opportunity to explore the relationship between levels of open defecation and stunting within this population. We conducted an ecological regression analysis to assess the association between the prevalence of open defecation and stunting after adjustment for potential confounding factors. Data from the 2011 HUNGaMA survey was used for the outcome of interest, stunting; data from the 2011 Indian Census for the same districts was used for the exposure of interest, open defecation. After adjustment for various potential confounding factors--including socio-economic status, maternal education and calorie availability--a 10 percent increase in open defecation was associated with a 0.7 percentage point increase in both stunting and severe stunting. Differences in open defecation can statistically account for 35 to 55 percent of the average difference in stunting between districts identified as low-performing and high-performing in the HUNGaMA data. In addition, using a Monte Carlo simulation, we explored the effect on statistical power of the common practice of dichotomizing continuous height data into binary stunting indicators. Our simulation showed that dichotomization of height sacrifices statistical power, suggesting that our estimate of the association between open defecation and stunting may be a lower bound. Whilst our analysis is ecological and therefore vulnerable to residual confounding, these findings use the most recently collected large-scale data from India to add to a growing body of suggestive evidence for an effect of poor sanitation on human growth. New intervention studies, currently underway, may shed more light on this important issue

    Synthetic and Real Inputs for Tool Segmentation in Robotic Surgery

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    Semantic tool segmentation in surgical videos is important for surgical scene understanding and computer-assisted interventions as well as for the development of robotic automation. The problem is challenging because different illumination conditions, bleeding, smoke and occlusions can reduce algorithm robustness. At present labelled data for training deep learning models is still lacking for semantic surgical instrument segmentation and in this paper we show that it may be possible to use robot kinematic data coupled with laparoscopic images to alleviate the labelling problem. We propose a new deep learning based model for parallel processing of both laparoscopic and simulation images for robust segmentation of surgical tools. Due to the lack of laparoscopic frames annotated with both segmentation ground truth and kinematic information a new custom dataset was generated using the da Vinci Research Kit (dVRK) and is made available

    Super-resolution far-field ghost imaging via compressive sampling

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    Much more image details can be resolved by improving the system's imaging resolution and enhancing the resolution beyond the system's Rayleigh diffraction limit is generally called super-resolution. By combining the sparse prior property of images with the ghost imaging method, we demonstrated experimentally that super-resolution imaging can be nonlocally achieved in the far field even without looking at the object. Physical explanation of super-resolution ghost imaging via compressive sampling and its potential applications are also discussed.Comment: 4pages,4figure

    The effects of laryngeal mask airway passage simulation training on the acquisition of undergraduate clinical skills: a randomised controlled trial

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    Background\ud Effective use of the laryngeal mask airway (LMA) requires learning proper insertion technique in normal patients undergoing routine surgical procedures. However, there is a move towards simulation training for learning practical clinical skills, such as LMA placement. The evidence linking different amounts of mannequin simulation training to the undergraduate clinical skill of LMA placement in real patients is limited. The purpose of this study was to compare the effectiveness in vivo of two LMA placement simulation courses of different durations. \ud \ud Methods\ud Medical students (n = 126) enrolled in a randomised controlled trial. Seventy-eight of these students completed the trial. The control group (n = 38) received brief mannequin training while the intervention group (n = 40) received additional more intensive mannequin training as part of which they repeated LMA insertion until they were proficient. The anaesthetists supervising LMA placements in real patients rated the participants' performance on assessment forms. Participants completed a self-assessment questionnaire. \ud \ud Results\ud Additional mannequin training was not associated with improved performance (37% of intervention participants received an overall placement rating of > 3/5 on their first patient compared to 48% of the control group, X2X^2 = 0.81, p = 0.37). The agreement between the participants and their instructors in terms of LMA placement success rates was poor to fair. Participants reported that mannequins were poor at mimicking reality. \ud \ud Conclusions\ud The results suggest that the value of extended mannequin simulation training in the case of LMA placement is limited. Educators considering simulation for the training of practical skills should reflect on the extent to which the in vitro simulation mimics the skill required and the degree of difficulty of the procedure. \ud \u

    Channel selection for multispectral color imaging using binary differential evolution

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    2013-2014 > Academic research: refereed > Publication in refereed journalVersion of RecordPublishe

    Autofocus for multispectral camera using focus symmetry

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    Author name used in this publication: Si-Jie ShaoAuthor name used in this publication: John H. Xin2011-2012 > Academic research: refereed > Publication in refereed journalVersion of RecordPublishe
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