Aklouche Leila¹, Monteau Jean-Yves², Rezzoug Sid-Ahmed¹, Maugard Thierry³, Guihard Luc², Cohendoz Stephane¹, Maache-Rezzoug Zoulikha^1,*

Journal of Renewable Materials, Vol.7, No.6, pp. 535-546, 2019, DOI:10.32604/jrm.2019.04361

Abstract Specific heat (Cp) and effective thermal conductivity (λ) of native maize starch (NS) were measured by DSC and transient heat transfer method, respectively, at different moisture contents and temperatures. The dependency of temperature (T) and moisture content (W) on the two parameters were investigated. The thermophysical properties of treated starch (TS) by four hydrothermal processes (RP-HMT, IV-HMT, DV-HMT and FV-HMT) were measured and compared to native strach. Hydrothermal treatments were performed at 3 bars (133°C) for 10 min. For Cp and λ measurements, moisture content varied for NS from 5 to 21.5% d.b. and from 8.8 to 25% d.b., respectively,… More >

Liming Yang¹, Yongping Gao², Qun Sun³

CMES-Computer Modeling in Engineering & Sciences, Vol.104, No.6, pp. 493-506, 2015, DOI:10.3970/cmes.2015.104.493

Abstract Minimax probability machine (MPM) has been recently proposed and shown its advantage in pattern recognition. In this paper, we present a new minimax probabilistic approach (MPA),which can provide an explicit lower bound on prediction accuracy. Applying the Chebyshev-Cantelli inequality, the MPA is posed as a second order cone program formulation and solved effectively. Following that, this method is exploited directly to recognize the purity of hybrid seeds using near-infrared spectroscopic data. Experimental results in different spectral regions show that the proposed MPA is competitive with the existing minimax probability machine and support vector machine in generalization, while requires less computational… More >