Visual mouth information has been proved to be very helpful for understanding the speech contents. The synthesis of the corresponding face video directly from the speech signals is strongly demanded since it can significantly reduce the amount of video information for transmission. In this paper, we present a novel statistical learning approach that learns the mappings from input voice signals ...

By undertaking a cointegration analysis with annual data over the period 1985~2005 in China, the estimation results show that there is cointegration relationship between electrical energy consumption and economic growth taking into account industry structure changes and technical efficiency. The model shows that three explanatory variables, the GDP per capita, heavy industry share and efficienc...

The interpolation of spatial data has been considered in many different forms. The various forms of kriging are among the best known in the earth sciences although techniques such as inverse distance weighting were and are in use for spatially located data. In the numerical analysis literature various forms of splines and more recently radial basis functions have been developed and used. Becaus...

Support vector machines(SVMs) have demonstrated good performance to correctly classify samples into appropriate classes which contain tens of thousands of genes. The key to the success of using SVMs is choosing an appropriate kernel. Widely used kernels are linear, polynomial, radial basis function and sigmoidal. We compared the performance of kernels when all genes were used and when fewer num...

Network-level multi-step road condition forecasting is an important step in accurate road maintenance planning, where correct maintenance activities are defined in place and time of road networks. Forecasting methods have developed from engineering models to non-linear machine learning methods that make use of the collected condition and traffic data of the road network. Least Squares Support V...

The aim of this paper is to propose a novel technique for Arabic/Farsi handwritten digit recognition. We constructed an invariant and efficient feature set by combination of four directional Chain Code Histogram (CCH) and Histogram of Oriented Gradient (HOG). To achieve higher recognition rate, we extracted local features at two levels with grids 2×2, 1×1 and it causes a partial overlapping of ...

Information technology enables trading of financial products to be much more efficient and effective. In nowadays, 90% of the trading volumes of stocks come from algorithmic trading in market microstructure. In this project, we explore to apply LAMSTAR network to predict the price movement in market microstructure. More specifically, the historical price movement, the current order book statist...

In this paper a robust regions-of-suspicion (ROS) diagnosis system on mammograms, recognizing all types of abnormalities is presented and evaluated. A new type of descriptors, based on Shapelet decomposition, derive the source images that generate the observed ROS in mammograms. The Shapelet decomposition coefficients can be used efficiently to detect ROS areas using Support-Vector-Machines (SV...

In this work we propose a novel automatic cast iron segmentation approach based on the Optimum-Path Forest classifier (OPF). Microscopic images from nodular, gray and malleable cast irons are segmented using OPF, and Support Vector Machines (SVM) with Radial Basis Function and SVM without kernel mapping. Results show accurate and fast segmented images, in which OPF outperformed SVMs. Our work i...