Background: An accurate and automatic computer-aided multi-class decision support system to classify the magnetic resonance imaging (MRI) scans of the human brain as normal, Alzheimer, AIDS, cerebral calcinosis, glioma, or metastatic, which helps the radiologists to diagnose the disease in brain MRIs is created. Methods: The performance of the proposed system is validated by using benchmark MRI...

Parametric identification approaches in the Linear Parameter-Varying (LPV) setting require optimal prior selection of a set of functional dependencies, used in the parametrization of the model coefficients, to provide accurate model estimates of the underlying system. Consequently, data-driven estimation of these functional dependencies has a paramount importance, especially when very limited a...

The aim of this study was to investigate the potential of the infrared spectroscopy technique for nondestructive measurement of fat content in milk powder. Fat is an important component of milk powder. It is very important to be able to detect the fat content in milk powder using a rapid and nondestructive method. Near and mid infrared spectroscopy techniques were used to achieve this purpose. ...

Crossing the legs at the knees, during BP measurement, is one of the several physiological stimuli that considerably influence the accuracy of BP measurements. Therefore, it is paramount to develop an appropriate prediction model for interpreting influence of crossed legs on BP. This research work described the use of principal component analysis- (PCA-) fused forward stepwise regression (FSWR)...

As a new type of dam, roller compacted concrete dam (RCCD) develops very fast in recent years. Deformation plays an important role in the RCCD’s safety. The deformation of RCCD is influenced mainly by three parts: water pressure, temperature and time effect. As to any of the three parts, there are many factors. Therefore, the deformation of RCCD is a complicated system. The least squares suppor...

The Bayesian evidence framework is applied in this paper to least squares support vector machine (LS-SVM) regression in order to infer nonlinear models for predicting a financial time series and the related volatility. On the first level of inference, a statistical framework is related to the LS-SVM formulation which allows one to include the time-varying volatility of the market by an appropri...

Infected petals are often regarded as the source for the spread of fungi Sclerotinia sclerotiorum in all growing process of rapeseed (Brassica napus L.) plants. This research aimed to detect fungal infection of rapeseed petals by applying hyperspectral imaging in the spectral region of 874-1734 nm coupled with chemometrics. Reflectance was extracted from regions of interest (ROIs) in the hypers...

Bruise may cause spoilage, reduce commodity economic value, and give rise to food quality safety concerns. Therefore, it is crucial detect whether a loquat bruised when save storage transportation costs. At present, the bruise of loquats mainly discriminated by operator’s naked eye, which affected personal habits, light intensity, subjective psychological factors. The detection method time-cons...

The aim of this work was to analyze the variety of soil by laser-induced breakdown spectroscopy (LIBS) coupled with chemometrics methods. 6 certified reference materials (CRMs) of soil samples were selected and their LIBS spectra were captured. Characteristic emission lines of main elements were identified based on the LIBS curves and corresponding contents. From the identified emission lines, ...

In order to achieve continuous navigation capability in areas such as tunnels, urban canyons, and indoors a new approach using least squares support vector machine LS-SVM and H∞ filter HF for integration of INS/WSN is proposed. In the integrated system, HF estimates the errors of position and velocity while the signals in WSNs are available. Meanwhile, the compensation model is trained by LS-SV...