Search results for "1707"
showing 10 items of 274 documents
Functional design of power-split CVTs: An uncoupled hierarchical optimized model
2017
Abstract This paper provides a new model for the preliminary design of compound power-split CVTs. Unlike the existing models, the presented method allows the engineers to prioritize functionality and efficiency of the transmission, while delaying the choice of the involved gear sets’ layout as long as possible. The design approach follows a specific priority order, and each step deals with one particular issue, without mutual interference. A smart design-chart eases the assessment and the comparison of the only eligible alternatives, and eventually leads to a final feasible constructive scheme, which can be an excellent concept for further optimization and implementation. Moreover, the mode…
Global sensitivity analysis of the A-SCOPE model in support of future FLEX fluorescence retrievals
2014
In support of ESA's Earth Explorer 8 candidate mission FLEX (FLuorescence EXplorer), a Photosynthesis Study has been initiated to quantitatively link fluorescence to photosynthesis. This led to the development of A-SCOPE, a graphical user interface software package that integrates multiple biochemical models into the soil-vegetation-atmosphere-transfer model SCOPE. Its latest version (v1.53) has been successfully verified and was subsequently evaluated through a global sensitivity analysis. By using the method of Saltelli [4], the relative importance of each input variable to model outputs was quantified through first order and total effect sensitivity indices. Variations in leaf area index…
Hidden connections: Network effects on editorial decisions in four computer science journals
2018
Abstract This paper aims to examine the influence of authors’ reputation on editorial bias in scholarly journals. By looking at eight years of editorial decisions in four computer science journals, including 7179 observations on 2913 submissions, we reconstructed author/referee-submission networks. For each submission, we looked at reviewer scores and estimated the reputation of submission authors by means of their network degree. By training a Bayesian network, we estimated the potential effect of scientist reputation on editorial decisions. Results showed that more reputed authors were less likely to be rejected by editors when they submitted papers receiving negative reviews. Although th…
A survey on tubulin and arginine methyltransferase families sheds light on p. lividus embryo as model system for antiproliferative drug development
2019
Tubulins and microtubules (MTs) represent targets for taxane-based chemotherapy. To date, several lines of evidence suggest that effectiveness of compounds binding tubulin often relies on different post-translational modifications on tubulins. Among them, methylation was recently associated to drug resistance mechanisms impairing taxanes binding. The sea urchin is recognized as a research model in several fields including fertilization, embryo development and toxicology. To date, some &alpha
Time-Frequency Filtering for Seismic Waves Clustering
2014
This paper introduces a new technique for clustering seismic events based on processing, in time-frequency domain, the waveforms recorded by seismographs. The detection of clusters of waveforms is performed by a k-means like algorithm which analyzes, at each iteration, the time-frequency content of the signals in order to optimally remove the non discriminant components which should compromise the grouping of waveforms. This step is followed by the allocation and by the computation of the cluster centroids on the basis of the filtered signals. The effectiveness of the method is shown on a real dataset of seismic waveforms.
A multiscale approach to automatic and unsupervised retinal vessel segmentation using Self-Organizing Maps
2016
In this paper an automatic unsupervised method for retinal vessel segmentation is described. Self-Organizing Map, modified Fuzzy C-Means, STAPLE algorithms and majority voting strategy were adopted to identify a segmentation of the retinal vessels. The performance of the proposed method was evaluated on the DRIVE database.
Quantifying the complexity of short-term heart period variability through K nearest neighbor local linear prediction
2008
The complexity of short-term heart period (HP) variability was quantified exploiting the paradigm that associates the degree of unpredictability of a time series to its dynamical complexity. Complexity was assessed through k-nearest neighbor local linear prediction. A proper selection of the parameter k allowed us to perform either linear or nonlinear prediction, and the comparison of the two approaches to infer the presence of nonlinear dynamics. The method was validated on simulations reproducing linear and nonlinear time series with varying levels of predictability. It was then applied to HP variability series measured from healthy subjects during head-up tilt test, showing that short-te…
Experimental approach for testing the uncoupling between cardiovascular variability series
2002
In cardiovascular variability analysis, the significance of the coupling between two series is commonly assessed by defining a zero level on the magnitude-squared coherence (MSC). Although the use of the conventional value of 0.5 does not consider the dependence of MSC estimates on the analysis parameters, a theoretical threshold Tt is available only for the weighted covariance (WC) estimator. In this study, an experimental threshold for zero coherence Te was derived by a statistical test from the sampling distribution of MSC estimated on completely uncoupled time series. MSC was estimated by the WC method (Parzen window, spectral bandwidth B = 0.015, 0.02, 0.025, 0.03 Hz) and by the parame…
Cross-Technology WiFi/ZigBee Communications: Dealing With Channel Insertions and Deletions
2016
In this letter, we show how cross-technology interference can be exploited to set up a low-rate bidirectional communication channel between heterogeneous WiFi and ZigBee networks. Because of the environment noise and receivers' implementation, the cross-technology channel can be severely affected by insertions and deletions of symbols, whose effects need to be taken into account by the coding scheme and communication protocol.
Wi-Dia: Data-Driven Wireless Diagnostic Using Context Recognition
2018
The recent densification of Wi-Fi networks is exacerbating the effects of well-known pathologies including hidden nodes and flow starvation. This paper provides an automatic diagnostic tool for detecting the source roots of performance impairments by recognizing the wireless operating context. Our tool for Wi-Fi diagnostic, named Wi-Dia, exploits machine learning methods and uses features related to network topology and channel utilization, without impact on regular network operations and working in real-time. Real-time per-link Wi-Fi diagnosis enables recovering actions for context-specific treatments. Wi-Dia classifier recognizes different classes of interference; it is jointly trained us…