Transportation Construction Work-Zone Safety Impact on Time-Related Incentive Contracting Projects

Work-zone safety on highway projects continues to be a national concern, and project safety performance is one of the indicators of project success. Many contractors and State Transportation Agencies believe that expedited construction time under incentive contracting contributes to reducing the safety risk of road users traveling through work zones. However, the truth of this belief has never been measured or supported by any statistical evidence. Therefore, this research investigates the statistical relationship between time-related incentive road construction projects and frequency of vehicle crashes in California to understand the impact of time-related incentive provisions on project safety performance. The research team collected incentive and non-incentive project data from the California Department of Transportation. Additionally, vehicle crash data was collected from the California Statewide Integrated Traffic Records System. Using Geographic Information System (GIS) software, the locations of construction projects and crashes at the project locations were then pinpointed on GIS centerline layers. The research team performed statistical analyses to test the relationship between the frequency and characteristics of crashes at incentive project sites and ones at non-incentive project sites before, during, and after construction. Finally, the analysis results for both time-related incentive projects and non-incentive projects were summarized to provide project planners and managers with a better understanding of the impact of time-related incentive contracting on project safety performance

Korean Twitter Emotion Classification Using Automatically Built Emotion Lexicons and Fine-Grained Features

In recent years many people have begun to express their thoughts and opinions on Twit-ter. Naturally, Twitter has become an ef-fective source to investigate people’s emo-tions for numerous applications. Classifying only positive and negative tweets has been ex-ploited in depth, whereas analyzing finer emo-tions is still a difficult task. More elaborate emotion lexicons should be developed to deal with this problem, but existing lexicon sets are mostly in English. Moreover, building such lexicons is known to be extremely labor-intensive or resource-intensive. Finer-grained features need to be taken into account when determining finer-emotions, but many exist-ing works still utilize coarse features that have been widely used in analyzing only the po-larity of emotion. In this paper, we present a method to automatically build fine-grained emotion lexicon sets and suggest features that improve the performance of machine learning based emotion classification in Korean Twitter texts.

Beyond Black Box Densities: Parameter Learning for the Deviated Components

As we collect additional samples from a data population for which a known density function estimate may have been previously obtained by a black box method, the increased complexity of the data set may result in the true density being deviated from the known estimate by a mixture distribution. To model this phenomenon, we consider the \emph{deviating mixture model} $(1-\lambda^{*})h_0 + \lambda^{*} (\sum_{i = 1}^{k} p_{i}^{*} f(x|\theta_{i}^{*}))$, where $h_0$ is a known density function, while the deviated proportion $\lambda^{*}$ and latent mixing measure $G_{*} = \sum_{i = 1}^{k} p_{i}^{*} \delta_{\theta_i^{*}}$ associated with the mixture distribution are unknown. Via a novel notion of distinguishability between the known density $h_{0}$ and the deviated mixture distribution, we establish rates of convergence for the maximum likelihood estimates of $\lambda^{*}$ and $G^{*}$ under Wasserstein metric. Simulation studies are carried out to illustrate the theory.Comment: Accepted at NeurIPS 2022. Dat Do and Nhat Ho contributed equally to this wor

Optical activity and transport in twisted bilayer graphene: the essence of spatial dispersion effects

This study investigates optical activity and quantum transport in twisted bilayer graphene (TBG) systems, demonstrating that the former results from spatial dispersion effects. The transfer matrix method is used to solve the propagation of electromagnetic waves through two graphene layers that act as the coupling surfaces of a dielectric slab. The resulting optical conductivity tensor is decomposed into a local and a drag part, with the drag transverse conductivity $\sigma_{xy}^{(drag)}$ governing the TBG system's optical property. An effective continuum model is employed to analyze electron state formation and calculate relevant parts of the optical conductivity tensor. Correlation of electron motions leads to incomplete cancellation and a finite $\sigma_{xy}^{(drag)}$ in the chiral TBG lattice. The study also calculates DC conductivity, showing TBG supports quantum conductivity proportional to $e^2/h$ at the intrinsic Fermi energy.Comment: arXiv admin note: substantial text overlap with arXiv:2205.1267