110,719 research outputs found
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
Gated relational stacked denoising autoencoder with localized author embedding for global citation recommendation
No full textCitation recommendation is an effective and efficient way to facilitate authors finding desired references. This paper presents a novel neural network based model, called gated relational probabilistic stacked denoising autoencoder with localized author (GRSLA) embedding, for global citation recommendation task. Our model is comprised of two modules with different neural network architecture. For each citing and cited papers, we use a gated paper embedding module, which is extended from probabilistic stacked denoising autoencoder (PSDAE) by adding gated units, to obtain their paper vectors. The added gated units are able to utilize text information of cited paper to refine the vector representation of citing paper in multiple semantic levels. For an author in papers, we first apply topic model to obtain his/her semantic neighbors, and then use a localized author embedding (LAE) module to excavate author vector representation from semantic and explicit neighbors. Unlike most graph convolutional network (GCN) based methods, the LAE module is able to avoid computing global Laplacian in whole graph by taking limited neighbors. Moreover, the LAE module can also be stacked to absorb more neighbors, which makes our model have high extendibility. Based on the generation process of GRSLA, we also derive a learning algorithm of our model by maximum a posteriori (MAP) estimation. We conduct experiments on the AAN, DBLP and CORD-19 datasets, and the results show that GRSLA model works well than previous global citation recommendation methods
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
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
Capital asset accounting policies under GASB Statement No. 34: Characteristics, antecedents, and implications
No full textIn this paper, we study the evolution of state and local governments’ capital asset accounting policies from the adoption of GASB Statement No. 34 through the fiscal year ending in 2016. We document substantial cross-sectional and time-series variation in the capitalization thresholds and estimated useful lives pertaining to major classes of capital assets, including buildings, equipment, improvements, and infrastructure assets. Diversity in capital asset accounting policies potentially diminishes the comparability of capital asset accounting information across governments and over time. We also discuss matters related to the implementation and ongoing use of the modified approach for reporting infrastructure assets. Our findings are useful to the GASB as well as to users of government financial reports.Peer reviewe
A comparison of toughness of C-Mn steel with different grain sizes
No full textThe low-temperature toughness of C-Mn weld steel with different grain sizes was investigated with notched and precracked specimens. The results indicated that the fine grain steel, evaluated by notched specimens (Charpy V-notch and 4 point bending specimens), is tougher than that of the coarse grain steel over a temperature range from -196 °C to -30 °C. On the other hand, the coarse grain steel, evaluated with precracked specimens, has a remarkably greater plane strain fracture toughness compared to the fine grain steel. The microstructural analysis revealed that the fracture toughness of both the fine grain and the coarse grain steel is not directly related to the distance of the fracture initiation site from the precrack tip or the size of the ferrite grain. The behavioral discrepancy can be explained in terms of the ratio of local fracture stress to yield stress,i.e., σ <sub>f</sub> f/σ <sub>y</sub>. The fine grain steel had a higher σ <sub>f</sub> f/σ <sub>y</sub> in the notched specimens but a lower value in the precracked specimens compared to the coarse grain steel. The scatter of toughness data can be mainly attributed to the probabilistic distribution of the weakest particle. We suggested that σ <sub>f</sub> f/σ <sub>y</sub> may be a useful parameter for the engineering evaluation of toughness
On the market timing and feedback effect of hedging: evidence from U.S. oil and gas producers
No full textPeer reviewe
Strength modelling of Al-Cu-Mg Type alloys
No full textAge hardening of Al-Cu-Mg type alloys occurs in two stages separated by a constant hardness plateau when the alloys are aged at 110°C to 240?C after solution treatment and quenching. This work aims to develop a physically based two-stage hardening model to predict the yield strength of Al-Cu-Mg alloys with compositions in the (?+S) phase region. Experiments by means of hardness and tensile tests, differential scanning calorimetry and transmission electron microscopy (TEM) have been carried out to provide the relevant information for the calibration and validation of the model. The model considers a simplified precipitation sequence which involves a pre-precipitate structure followed by S phase. This pre-precipitate structure is referred to as Cu-Mg co-clusters instead of GPB zones based on atom probe and TEM studies from collaborators and a review of the literature. The competition between the Cu-Mg co-clusters and the S phase is modelled by assuming S phase forms at the expense of Cu-Mg co-clusters. In the model, the solvi of the Cu-Mg co-clusters and the S phase are calculated, the evolution of precipitates in terms of volume fraction, average size and the solute concentration in the matrix are described and the superposition of various contributions from precipitation strengthening, solution strengthening and dislocation strengthening are modelled. Strengthening by Cu-Mg co-clusters and S phase is described by the modulus strengthening mechanism and the Orowan bypassing mechanism, respectively. The predicted contributions to the critical resolved shear stress show that strengthening in the alloys is mainly due to the Cu-Mg co-clusters in the first stage of hardening and due to the S phase in the second stage of hardening. The model takes account of the composition dependency of precipitation rate for Cu-Mg co-clusters formation as well as the amount of Cu and Mg present in undissolved intermetallic phases. With a training root mean square error of 12MPa on an artificially aged 2024 alloy, the modelling accuracy on unseen yield strength data of two other alloys is 16MPa. Using a single set of parameters, the model has been applied to predict the hardness of a 2024-T351 alloy artificially aged at low temperature followed by short term underageing at higher temperature and then room temperature ageing. Good agreement between the predictions and the experiments indicates that the hardness changes during these multi-stage heat treatments can be well interpreted by considering Cu-Mg co-cluster dissolution, S precipitation and Cu-Mg co-cluster re-formation. Application to Al-xCu-1.7Mg alloys (x=0.2, 0.5, 0.8 and 1.1at.%) has shown good predictive capabilities of the model for the first stage of hardening. It is also shown that the model is applicable to Al-Cu-Mg alloys with Si contents at levels of 0.1-0.2wt.%. Modelling results of various Al-Cu-Mg alloys during natural ageing, artificial ageing and multi-stage heat treatments indicate that the model is capable of predicting the evolution of microstructure and the yield strength as a function of composition and heat treatments, and can provide a predictive tool for predicting the strength of Al-Cu-Mg based welds.<br/
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