background: photon attenuation as an inevitable physical phenomenon influences on the diagnostic information of spect images and results to errors in accuracy of quantitative measurements. this can be corrected via different physical or mathematical approaches. as the correction equation in mathematical approaches is nonlinear, in this study a new method of linearization called ‘piece wise line...

In this article, we investigate clustering methods for multilevel functional data, which consist of repeated random functions observed for a large number of units (e.g., genes) at multiple subunits (e.g., bacteria types). To describe the within- and between variability induced by the hierarchical structure in the data, we take a multilevel functional principal component analysis (MFPCA) approac...

Output least-squares formulation with Tikhonov regularization is one of the most frequently used and reliable methods for parameter identification in PDEs. As the discretized optimization system of the formulation is nonlinear, illconditioned, and constrained with some PDEs, its numerical solution is very time-consuming and often unstable. In this paper, we present a multilevel model correction...

Graph partitioning is a well-known optimization problem of great interest in theoretical and applied studies. Since the 1990s, many multilevel schemes have been introduced as a practical tool to solve this problem. A multilevel algorithm may be viewed as a process of graph topology learning at different scales in order to generate a better approximation for any approximation method incorporated...

Several image processing applications aim to detect and mark remarkable features which in turn might be used to perform high-level tasks. In particular, image segmentation seeks to group pixels within meaningful regions. Commonly, gray levels belonging to the object are substantially different from the gray levels featuring the background. Thresholding is thus a simple but effective tool to iso...

Image entropy thresholding approach has drawn the attentions in image segmatation. The endeavor of this paper is focused on multilevel thresholding using the minimum cross enrtop criterion. In the literature, the particle swarm optimization (PSO) had been applied to conducting the thresold selection. The adopted algorithm used in this paper is the honey bee mating optimization (HBMO). In experi...

Multilevel thresholding is a method that is widely used in image segmentation. The thresholding problem is treated as an optimization problem with an objective function. In this article, a simple and histogram based approach is presented for multilevel thresholding in image segmentation. The proposed method combines Tsallis objective function and Particle Swarm Optimization (PSO). The PSO algor...

Selecting approaches with appropriate accuracy and suitable speed for the purpose of making decision is one of the managers’ challenges. Also investing decision is one of the main decisions of managers and it can be referred to securities transaction in financial markets which is one of the investments approaches. When some assets and barriers of real world have been considered, optimization of...