Oilseed rape is used as both food and a renewable energy resource. Physiological parameters, such as the amino acid aspartic acid, can indicate the growth status of oilseed rape. Traditional detection methods are laborious, time consuming, costly, and not usable in the field. Here, we investigate near infrared spectroscopy (NIRS) as a fast and non-destructive detection method of aspartic acid i...

Three chemometric methods; partial least squares regression (PLS), principal component regression (PCR) and least-squares support vector machines (LS-SVM) were applied for simultaneous determination of carbidopa and levodopa in synthetic mixtures and real samples. The simultaneous determination of these drugs is a difficult problem due to spectral interferences. The proposed methods were used f...

We study the relationship between Support Vector Machines (SVM) and Least Squares SVM (LS-SVM). Our main result shows that under mild conditions, LS-SVM for binaryclass classifications is equivalent to the hard margin SVM based on the well-known Mahalanobis distance measure. We further study the asymptotics of the hard margin SVM when the data dimensionality tends to infinity with a fixed sampl...

guaranteed to find a global extremism. Another, the lease square (LS) versions of SVM, called as LS-SVM, is also investigated for classification [3] and regression (LS-SVMR) [4]. In these LS-SVM formulations on works with equality instead of inequality constraints and a sum squared error cost function as it is frequently used in the training of traditional neural networks. This reformulation gr...

In this research, we developed a predictive model based on least squares support vector machine (LS-SVM) that forecasts the future streamflow discharge using the past streamflow discharge data. A Gaussian Radial Basis Function (RBF) kernel framework was built on the data set to tune the kernel parameters and regularization constants of the model with respect to the given performance measure. Th...

Support vector machine (SVM) is an important technique for data classification. Traditional SVM assumes free access to data. If the are split and held by different users, privacy reasons, users likely unwilling submit their a third party In this paper, using additive homomorphic encryption random transformations (matrix transformation decomposition), we design privacy-preserving outsourcing sch...

In this work some quantitative structure activity relationship models were developed for prediction of three bioenvironmental parameters of 28 volatile organic compounds, which are used in assessing the behavior of pollutants in soil. These parameters are; half-life, non dimensional effective degradation rate constant and effective Péclet number in two type of soil. The most effective descripto...

This paper presents an on-line tool wear condition monitoring system for milling. The proposed system was developed taking the cost and performance in practice into account, in addition to a high success rate. The cutting vibration signal is obtained during the cutting process, and then extracting features using time-domain statistical and wavelet packet decomposition algorithms. It would resul...