The main research objective for the VIHO project (Efficient Computer Support in Care for the Elderly) was to investigate how a home care and help service organization can be developed in order to be better prepared for future challenges, and how new technical systems could support the development process. We have studied the home help personnel’s need for support and investigated how the new or...

In this paper, a system identification method for hybrid systems switched by the magnitude of velocity is proposed. First, it is shown that the regression vector space of a mechanical system switched by the magnitude of velocity cannot be separated by a hyperplane. Then a method based on support vector machines with a polynomial kernel is proposed. The effectiveness of the proposed method is sh...

This paper proposes a robust support vector machine for pattern classification, which aims at solving the over-fitting problem when outliers exist in the training data set. During the robust training phase, the distance between each data point and the center of class is used to calculate the adaptive margin. The incorporation of the average techniques to the standard support vector machine (SVM...

The least squares support vector machine (LS-SVM) has shown to exhibit excellent classification performance in many applications. In this paper, we propose an incremental and decremental LS-SVM based on updating and downdating the QR decomposition. It can efficiently compute the updated solution when data points are appended or removed. The experiment results illustrated that the proposed incre...

In this paper we have proposed a symmetric, positive semi definite kernel function for support vector machine classifier. Pixel classification is a form of supervised image segmentation where the actual object classes present in the image are known a priori. In case of satellite image, this prior information plays a huge role to estimate the actual statistics of different land covers. The state...

We present a new technique for 3D surface object classification that combines a powerful shape representation approach with suitable pattern classification techniques. Spherical harmonic parameterization and normalization techniques are used to describe a surface shape and derive a dual high dimensional landmark representation. A point distribution model is applied to reduce the dimensionality....

In the modern Digital Era, Data Mining is the powerful area for analyzing the large data sets to get unexpected relationships (models). The analysis of statistical data on sequential data points measured at regular time interval over a period of time is time series analysis. Time series analysis is used in predicting future occurrence of a time based event. One of the main areas where time seri...

Support Vector Machine (SVM) is a powerful technique for data classification. The SVM constructs an optimal separating hyper-plane as a decision surface, to divide the data points of different categories in the vector space. The Kernel functions are used to extend the concept of the optimal separating hyper-plane for the non-linearly separable cases so that the data can be linearly separable. T...

The ability to delineate geologic facies and to estimate their properties from sparse data is essential for modeling physical and biochemical processes occurring in the subsurface. If such data are poorly differentiated, this challenging task is complicated further by preventing a clear distinction between different hydrofacies even at locations where data are available. We study the problem of...