A quantitative structure-activity relationship (QSAR) study was conducted for the prediction of inhibitory activity of 1-phenyl[2H]-tetrahydro-triazine-3-one analogues as inhibitors of 5-Lipoxygenase. The inhibitory activities of the 1-phenyl[2H]-tetrahydro-triazine-3-one analogues modeled as a function of molecular structures using chemometrics methods such as multiple linear regression (MLR) ...

The paper presents a novel learning algorithm for the class of L2 Support Vector Machines classifiers dubbed Direct L2 SVM. The proposed algorithm avoids solving the quadratic programming problem and yet, it produces both the same exact results as the classic quadratic programming based solution in a significantly shorter CPU time. The connections between various L2 SVM algorithms will be highl...

| Mixture modelling is becoming an increasingly important tool in the remote sensing community as researchers attempt to resolve sub-pixel, area information. This paper compares a well-established technique, Linear Spectral Mixture Models (LSMM), with a much newer idea based on data selection, Support Vector Machines (SVM). It is shown that the constrained least squares LSMM is equivalent to th...

Tools to define the active ingredients and flavors of Traditional Chinese Medicines (TCMs) are limited by long analysis times, complex sample preparation and a lack of multiplexed analysis. The aim of the present study was to optimize and validate an electronic tongue (E-tongue) methodology to analyze the bitterness of TCMs. To test the protocol, 35 different TCM concoctions were measured using...

The bankruptcies of companies have been predicted with numerous methods. In this paper, the ensemble of Locally Linear model is compared to Linear Discriminant Analysis, Least Squares Support Vector Machines and Optimally Pruned Extreme Learning Machines. To create the ensemble, diffrerent basis for the locally linear models as well as different combinations of variables are used in order to ob...

In this paper, a data-driven modeling technique is proposed for temperature forecasting. Due to the high dimensionality, LASSO is used as feature selection approach. Considering spatio-temporal structure of the weather dataset, first LASSO is applied in a spatial and temporal scenario, independently. Next, a feature is included in the model if it is selected by both. Finally, Least Squares Supp...

ISSn: 0967-0335 © IM publications llp 2010 doi: 10.1255/jnirs.883 all rights reserved the measurement of physical and chemical parameters of soil is an important step toward sustainable farming practices, landscaping management and, more generally, the understanding of terrestrial ecosystem processes. Standard soil analytical procedures are often complex, time-consuming, and expensive for many ...