Gaussian process (GP) regression is a Bayesian non-parametric regression model, showing good performance in various applications. However, it is quite rare to see research results on log-likelihood maximization algorithms. Instead of the commonly used conjugate gradient method, the Hessian matrix is first derived/simplified in this paper and the trust-region optimization method is then presente...

S.typhimurium is a gram negative bacterium causing serious enteric or extraintestinal infections in human, cattle and birds. These kinds of infections may lead to some permanent or nonpermanent complications like endophthalmitis, Guillain-Barre syndrome and osteomyelitis . Multi-resistant strains of S.typhimurium have been reported from several countries, and these infections are a major public...

The use of artificial neural networks has increased in many areas of engineering. In particular, this method has been applied to many geotechnical engineering problems and demonstrated some degree of success. A review of the literature reveals that it has been used successfully in modeling soil behavior, site characterization, earth retaining structures, settlement of structures, slope stabilit...

The conjugate gradient-fast multipole method (CG-FMM) is one of the powerful methods for analysis of large-scale electromagnetic problems. It is also known that CPU time and computer memory can be reduced by CG-FMM but such computational cost of CG-FMM depends on shape and electrical properties of an analysis model. In this paper, relation between the number of multipoles and number of segments...

Accurate reconstruction of the object from sparse-view sampling data is an appealing issue for ultrasound diffraction tomography (UDT). In this paper, we present a reconstruction method based on compressed sensing framework for sparse-view UDT. Due to the piecewise uniform characteristics of anatomy structures, the total variation is introduced into the cost function to find a more faithful spa...