todays, in many modern applications, we search for frequent and repeating patterns in the analyzed data sets. in this search, we look for patterns that frequently appear in data set and mark them as frequent patterns to enable users to make decisions based on these discoveries. most algorithms presented in the context of data stream mining and frequent pattern detection, work either on uncertai...

In this paper, we propose a new framework for data stream mining, called the weighted sliding window model. The proposed model allows the user to specify the number of windows for mining, the size of a window, and the weight for each window. Thus, users can specify a higher weight to a more significant data section, which will make the mining result closer to user’s requirements. Based on the w...

A central problem in stereo matching by computing correlation or sum of squared differences (SSD) lies in selecting an appropriate window size. If the window is too small and does not cover enough intensity variation, it gives a poor disparity estimate, because the signal (intensity variation) to noise ratio is low. If, on the other hand, the window is too large and covers a region in which the...

Stereo correspondence mapping is the fundamental problem to achieve human like vision capabilities to machines and robots. Many local and global algorithms have been reported in literature in the last decade. Window-based cost aggregation methods for solving the correspondence problem have attracted researches as it can be implemented in real time using parallel processors. In this paper a new ...

In the intensity-based stereo matching algorithm, window-based and coarse-to-fine algorithms are known as typical approaches. The window-based algorithm matches intensity values within windows between two stereo images. The conventional window-based algorithms, however, face a trade-off between error rates of the disparity map in disparity continuity and discontinuity regions due to the window ...

introduction: scatter radiation is one of the major sources of error in nuclear medicine data processing. different methods of scatter correction have been introduced in order to improve the quality of data. however the best method is to avoid recording of scatter photons in acquisition. the only difference between scattered and non-scattered photons is the energy. pulse height analyzer is the ...

In geographically weighted regression, one must determine a window size which will be used to subset the data locally. Typically, a cross-validation procedure is used to determine a globally optimal window size. Preliminary investigations indicate that the global cross-validation score is heavily influenced by a small number of observations in the dataset. At present, the ramifications of this ...

This paper reviews resampling of nonuniformly sampled k-space data to a Cartesian grid and adds a new formula enabling quick computation of the shape parameter B of the KaiserBessel convolution window. In addition, a very recently conceived iterative estimation of the sampling density correction is explained and applied to sparse radial MRI scans. Keywords— rapid scanning, undersampling, griddi...

Introduction: Scatter radiation is one of the major sources of error in nuclear medicine data processing. Different methods of scatter correction have been introduced in order to improve the quality of data. However the best method is to avoid recording of scatter photons in acquisition. The only difference between scattered and non-scattered photons is the energy. Pulse height analyzer i...