T-Crowd: Effective Crowdsourcing for Tabular Data

Crowdsourcing employs human workers to solve computer-hard problems, such as data cleaning, entity resolution, and sentiment analysis. When crowdsourcing tabular data, e.g., the attribute values of an entity set, a worker's answers on the different attributes (e.g., the nationality and age of a celebrity star) are often treated independently. This assumption is not always true and can lead to suboptimal crowdsourcing performance. In this paper, we present the T-Crowd system, which takes into consideration the intricate relationships among tasks, in order to converge faster to their true values. Particularly, T-Crowd integrates each worker's answers on different attributes to effectively learn his/her trustworthiness and the true data values. The attribute relationship information is also used to guide task allocation to workers. Finally, T-Crowd seamlessly supports categorical and continuous attributes, which are the two main datatypes found in typical databases. Our extensive experiments on real and synthetic datasets show that T-Crowd outperforms state-of-the-art methods in terms of truth inference and reducing the cost of crowdsourcing

Positive loop-closed automata: a decidable class of hybrid systems

AbstractThe model-checking problem for real-time and hybrid systems is very difficult, even for a well-formed class of hybrid systems—the class of linear hybrid automata—the problem is still undecidable in general. So an important question for the analysis and design of real-time and hybrid systems is the identification of subclasses of such systems and corresponding restricted classes of analysis problems that can be settled algorithmically. In this paper, we show that for a class of linear hybrid automata called positive loop-closed automata, the satisfaction problem for linear duration properties can be solved by linear programming. We extend the traditional regular expressions with duration constraints and use them as a language to describe the behaviour of this class of linear hybrid automata. The extended notation is called duration-constrained regular expressions. Based on this formalism, we show that the model-checking problem can be reduced formally to linear programs

Simulating the Range Expansion of Spartina alterniflora

Environmental factors play an important role in the range expansion of Spartina alterniflora in estuarine salt marshes. CA models focusing on neighbor effect often failed to account for the influence of environmental factors. This paper proposed a CCA model that enhanced CA model by integrating constrain factors of tidal elevation, vegetation density, vegetation classification, and tidal channels in Chongming Dongtan wetland, China. Meanwhile, a positive feedback loop between vegetation and sedimentation was also considered in CCA model through altering the tidal accretion rate in different vegetation communities. After being validated and calibrated, the CCA model is more accurate than the CA model only taking account of neighbor effect. By overlaying remote sensing classification and the simulation results, the average accuracy increases to 80.75% comparing with the previous CA model. Through the scenarios simulation, the future of Spartina alterniflora expansion was analyzed. CCA model provides a new technical idea and method for salt marsh species expansion and control strategies research

Theoretical Analysis of Random Scattering Induced by Microlensing

Theoretical investigations into the deflection angle caused by microlenses offer a direct path to uncovering principles of the cosmological microlensing effect. This work specifically concentrates on the the probability density function (PDF) of the light deflection angle induced by microlenses. We have made several significant improvements to the widely used formula from Katz et al. First, we update the coefficient from 3.05 to 1.454, resulting in a better fit between the theoretical PDF and our simulation results. Second, we developed an elegant fitting formula for the PDF that can replace its integral representation within a certain accuracy, which is numerically divergent unless arbitrary upper limits are chosen. Third, to facilitate further theoretical work in this area, we have identified a more suitable Gaussian approximation for the fitting formula.Comment: 15 pages, 6 figures, accepted for publication in Research in Astronomy and Astrophysic

Plasma-induced unconventional shock waves on oil surfaces

Electric corona discharge in a multi-phase system results in complex electro-hydrodynamic phenomena. We observed unconventional shock wave propagation on an oil thin film sprayed over a polymer-coated conductor. A hair-thin single shock wave arose when the high voltage bias of an overhung steel needle was abruptly removed. However, such solitary waves possess neither interference nor reflection properties commonly known for ordinary waves, and also differ from the solitons in a canal or an optical fiber. We also observed time-retarded movement for dispersed oil droplets at various distances from the epicenter which have no physical contact, as if a wave propagating on a continuous medium. Such a causality phenomenon for noncontact droplets to move resembling wave propagation could not be possibly described by the conventional surface wave equation. Our systematic studies reveal a mechanism involving oil surface charges driven by reminiscent electric fields in the air when the needle bias is suddenly removed