67,518 research outputs found
A study on the reliability of consecutive k-Out-of-n: G systems based on Copula
No full textThe computation of reliability characteristics of a system that consists of dependent components is sometimes difficult especially when the type of dependence is not known. This article introduces the copula method to calculate the reliability of dependent consecutive k-out-of-n: G systems. The components in these systems are dependent on each other and the dependency may be either linear or nonlinear. The copula is a popular tool for modeling the dependence structure of data. It contains the information about the dependency structure of a vector of random variables and can capture nonlinear dependence. Based on the copula theory, the article analyzes the consecutive k-out-of-n: G systems and gets the reliability indexes. Finally, some numerical examples are presented to illustrate the results obtained in this article.Peer reviewe
Using performance assessment in secondary school mathematics: an empirical study in a Singapore classroom
No full textThis article reports an exploratory study on using performance assessment in mathematics instruction in a high-performing secondary school in Singapore. An intact mathematics class participated in the study, and received chapter-based performance tasks as intervention during regular mathematics lessons for about one and a half school years. The performance tasks used included authentic and/or open-ended tasks. The students’ academic achievements and attitudes in mathematics were compared with a comparison class that did not receive the intervention. Both quantitative and qualitative data were collected, mainly through questionnaire surveys, performance task tests, conventional school exams, and interviews with students and teachers. The results suggest that the students receiving the intervention performed significantly better than their counterparts in solving conventional exam problems, and in general they also showed more positive changes in attitudes towards mathematics and mathematics learning. The students from the experimental class also expressed positive views about the benefits of using performance tasks in promoting their ability in higher order thinking, though no statistically significant difference was detected between the two classes of students in solving unconventional tasks before and after intervention. Overall, the results appear to support teachers’ using contextualised problems in real life situations and open-ended investigations in students’ learning of mathematic
Measurement of the differential and double-differential Drell-Yan cross sections in proton-proton collisions at root s=7 TeV
No full textMeasurements of the differential and double-differential Drell-Yan cross sections are presented using an integrated luminosity of 4.5 (4.8) fb−1 in the dimuon (dielectron) channel of proton-proton collision data recorded with the CMS detector at the LHC at s√ = 7 TeV. The measured inclusive cross section in the Z-peak region (60–120 GeV) is σ(ℓℓ) = 986.4 ± 0.6 (stat.) ± 5.9 (exp. syst.) ± 21.7 (th. syst.) ± 21.7 (lum.) pb for the combination of the dimuon and dielectron channels. Differential cross sections dσ/dm for the dimuon, dielectron, and combined channels are measured in the mass range 15 to 1500 GeV and corrected to the full phase space. Results are also presented for the measurement of the double-differential cross section d2σ/dm d|y| in the dimuon channel over the mass range 20 to 1500 GeV and absolute dimuon rapidity from 0 to 2.4. These measurements are compared to the predictions of perturbative QCD calculations at next-to-leading and next-to-next-to-leading orders using various sets of parton distribution functions
Supporting Information for Tomographic Evidence for the Presence of a South-dipping Subduction System in the Mesozoic Southern Tethyan Ocean, G Cubed
No full textThis is the supporting information for the paper: Tomographic Evidence for the Presence of a South-dipping Subduction System in the Mesozoic Southern Tethyan Ocean by Peilong Yan, Nan Zhang, Huaiyu Yuan, Zheng-Xiang Li and Xiaoxu Liu. It includes Figures S1-S3 of this paper, which are "vote map" and standard deviation for the composite model, map-views and cross-sections of LLNL_G3D-JPS, and cross-sections of the 'Seis' anomaly from different seismic tomography models
Drell Yan processes at LHC
No full textWe study the main observables associated with the Drell-Yan processes at the LHC
Neural Multimodal Belief Tracker with Adaptive Attention for Dialogue Systems
No full textMultimodal dialogue systems are attracting increasing attention with a more natural and informative way for human-computer interaction. As one of its core components, the belief tracker estimates the user's goal at each step of the dialogue and provides a direct way to validate the ability of dialogue understanding. However, existing studies on belief trackers are largely limited to textual modality, which cannot be easily extended to capture the rich semantics in multimodal systems such as those with product images. For example, in fashion domain, the visual appearance of clothes play a crucial role in understanding the user's intention. In this case, the existing belief trackers may fail to generate accurate belief states for a multimodal dialogue system.In this paper, we present the first neural multimodal belief tracker (NMBT) to demonstrate how multimodal evidence can facilitate semantic understanding and dialogue state tracking. Given the multimodal inputs, while applying a textual encoder to represent textual utterances, the model gives special consideration to the semantics revealed in visual modality. It learns concept level fashion semantics by delving deep into image sub-regions and integrating concept probabilities via multiple instance learning. Then in each turn, an adaptive attention mechanism learns to automatically emphasize on different evidence sources of both visual and textual modalities for more accurate dialogue state prediction. We perform extensive evaluation on a multi-turn task-oriented dialogue dataset in fashion domain and the results show that our method achieves superior performance as compared to a wide range of baselines
Why hedge? Extent, nature, and determinants of derivative usage in U.S. municipalities
No full textUsing a hand-collected dataset of over 300 observations of large U.S. cities and counties, this paper investigates the extent, nature and determinants of derivatives usage in the municipal sector.Over half of our sample entities engage in derivative transactions and a vast majority of these transactions are intended to manage interest rate risk. Swaps, by far, are the most popular derivative instrument. In terms of the determinants of derivative usage,we find that the propensity to use derivatives as well as the extent of derivative usage is higher for municipalities that are larger and more financially constrained. We do not find growth to be related to municipal derivative usage. Contrary to suggestions made in the popular press, we fail to find managerial opportunism to be a significant factor in municipal derivative usage. We also find that more sophisticated managers of large municipalities and less sophisticated managers of small municipalities are more likely to engage in derivative transactions.Peer reviewe
Knowledge Ecosystems and Growth Proceedings 14th International Forum on Knowledge Asset Dynamics, 5-7 June 2019 Matera
No full textDistribution
No full textYuan Yan and Marc G. Genton explain this boosted log-normal distribution, which can be used to model wind speed data and stock market returns, among other things
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