Digging of geotechnical boreholes and soil resistance tests are time-consuming and expensive activities. Therefore selection of optimum number and suitable location of boreholes can reduce cost of their drilling and soil resistance tests. In this research, a model which is consisting of geo statistics model as an estimator and an optimized model is selected. The kriging calculates the variance ...

Is the order in which proteins assemble into complexes important for biological function? Here, we seek to address this by searching for evidence of evolutionary selection for ordered protein complex assembly. First, we experimentally characterize the assembly pathways of several heteromeric complexes and show that they can be simply predicted from their three-dimensional structures. Then, by m...

By treating error probability law as a parameter of interest, location and scale as nuisance parameters in location-scale model, this paper suggests that modified profile likelihood (MPL), considered as quasi-likelihood function of the error probability law, be used for its selection. This model selection method is proved to be consistent and achieves minimax rate optimality. Simulations show i...

Location selection is an essential decision problem for many industrial domains such as hotel, tourism site, energy, school, warehouse, factory, stores, retails and estate. This paper proposes the Primitive Cognitive Network Process (P-CNP) for the location selection problem considering multiple criteria. An illustrated example of hospital site selection demonstrates the usability of the propos...

Superconductor fault current limiter (SFCL) is an effective device to suppress high fault currents. This paper presents a comparative study of resistive and inductive fault current limiters from transient stability point of view.  Appropriate location and type of the limiters in a HV substation is selected by a qualitative approach based on the equal area criterion. Study system is simulated by...

Research on model/procedure selection has focused on selecting a single model globally. In many applications, especially for high-dimensional or complex data, however, the relative performance of the candidate procedures typically depends on the location, and the globally best procedure can often be improved when selection of a model is allowed to depend on location. We consider localized model...