The structure of an RNA sequence encodes information about its biological function. A sequence is typically predicted to fold to a single minimum free energy conformation. But, an increasing number of RNA molecules are now known to fold into multiple stable structures. Discrete optimization methods are commonly used to predict foldings, and adding experimental data as auxiliary information impr...

The treatment of missing data in the social sciences has changed tremendously during the last decade. Modern missing data techniques such as multiple imputation and full-information maximum likelihood are used much more frequently. These methods assume that data are missing at random. One very common approach to increase the likelihood that missing at random is achieved consists of including ma...

Soil respiration inherently shows strong spatial variability. It is difficult to obtain an accurate characterization of soil respiration with an insufficient number of monitoring points. However, it is expensive and cumbersome to deploy many sensors. To solve this problem, we proposed employing the Bayesian Maximum Entropy (BME) algorithm, using soil temperature as auxiliary information, to stu...

Securing any MANET routing protocol requires measures to ensure that routing information advertised by a node is consistent with routing information assimilated by a node. MANET nodes accumulate routing information that needs to be stored within them self. For this we present an idea of using IOMTs to prevent a node from misrepresenting or hiding this accumulated information., During routing pr...

When there is a high correlation between the study and the  auxiliary variables, the rank of the auxiliary variable also correlates with the study variable. Then, the use of the rank as an additional auxiliary variable may be helpful to increase the efficiency of the estimator of the mean or total of the population.   In the present study, we propose two  generalized familie...

The treatment of missing data in the social sciences has changed tremendously during the last decade. Modern missing data techniques such as multiple imputation and full-information maximum likelihood are used much more frequently. These methods assume that data are missing at random. One very common approach to increase the likelihood that missing at random is achieved, consists of including m...

in this paper, an algorithm , based on genetics and auxiliary nodes, to reduce energy consumption in wireless sensor networks has been presented. in this research, by considering some parameters as energy and distance, a target function has been created, which is more optimum comparing to other methods. in this research cluster head is selected by genetic algorithm. in rawsn algorithm a new tec...

In this paper we present a family of scalable preconditioners for matrices arising in the discretization of H(div) problems using the lowest order Raviart-Thomas finite elements. Our approach belongs to the class of “auxiliary space”-based methods and requires only the finite element stiffness matrix plus some minimal additional discretization information about the topology and orientation of m...

With the rapid development of remote sensing technology, three dimensional coordinates and intensity information of observation target can be obtained directly from LIDAR system. It is one of the important issues in the study on LIDAR data processing that how to extract the object from the point cloud data captured by laser scanning effectively without the help of spectral information as well a...