Web news classification using neural networks based on PCA

In this paper, we propose a news web page classification method (WPCM). The WPCM uses a neural network with inputs obtained by both the principal components and class profile-based features (CPBF). The fixed number of regular words from each class will be used as a feature vectors with the reduced features from the PCA. These feature vectors are then used as the input to the neural networks for classification. The experimental evaluation demonstrates that the WPCM provides acceptable classification accuracy with the sports news datasets

Biologically Active Compounds. II. The Synthesis of β-CarboxY-γ-butyrolactone Derivatives

Amide derivatives of γ-substituted paraconic and aconic　acids have been　synthesized. Ultraviolet spectra of the aconic acid derivatives showed characteristic　fine structure in the region of 245 to 280 mμ

Studies on gas phase oxidation of propylene and acrolein

The gas phase thermal oxidation of propylene and acrolein has been examined at temperatures of 371 and 319℃ for the mixtures of 53.4% propylene with oxygen and 43.8% acrolein with oxygen respectively by gas chromatographic analysis. By using two columns containing dioctyl phthalate and active carbon respectively, analyses have been performed to ascertain and evaluate certain intermediates and products, such as aldehydes, acid, methanol, methane, ethylene, carbon monoxide, carbon dioxide, etc. Infrared absorption spectra of the reacted gases have also been used to identify the products. The oxidation of propylene is discussed in the light of the two proposed mechanisms. The analytical results indicate a high ratio of acetaldehyde to formaldehyde. Therefore, propylene is considered to be oxidized to acrolein, which is oxidized through acetaldehyde to the final products

New Stable Sulfonium Ylides. 1-Dimethylsulfuranylidene-l-phenylsulfonyl-2-propanone and Related Compounds

The preparation of the title compounds as a new type of stable S-ylides has been described. The reaction of 1-dimethylsulfuranylidene-1-phenylsulfonyl-2-propanone (IIb) with lithium aluminium hydride was found to result in the formation of trans-phenylpropenylsulfone (IV), phenylsulfonyl-2-propanone (Ib), and an unidentified paraffin as major products

A Study on Molecular Integrals II

Two-center exchange integrals of interatomically orthogonal 2s, 2p-hybrid orbitals are computed and tabulated as a function of the hybridization coefficient (angle parametera α) and the interatomic distance parameter ρ=δR for the case of tow like first row atoms

Modeling the correlations of crude oil properties based on sensitivity based linear learning method

This paper presented a new prediction model of pressure–volume–temperature (PVT) properties of crudeoil systems using sensitivity based linear learning method (SBLLM). PVT properties are very important in the reservoir engineering computations. The accurate determination of these properties, such as bubble-point pressure and oil formation volume factor, is important in the primary and subsequent development of an oil field. Earlier developed models are confronted with several limitations especially their instability and inconsistency during predictions. In this paper, a sensitivitybasedlinearlearningmethod (SBLLM) prediction model for PVT properties is presented using three distinct databases while comparing forecasting performance, using several kinds of evaluation criteria and quality measures, with neural network and the three common empirical correlations. In the formulation used, sensitivity analysis coupled with a linear training algorithm for each of the two layers is employed which ensures that the learning curve stabilizes soon and behaves homogenously throughout the entire process operation. In this way, the model will be able to adequately model PVT properties faster with high stability and consistency. Empirical results from simulations demonstrated that the proposed SBLLM model produced good generalization performance, with high stability and consistency, which are requisites of good prediction models in reservoir characterization and modeling