In this paper, the developed sprite allocation method is designed to be coherent with the introduced block-matching method in order to minimize the allocation process time for digital video. The accomplished allocation process of sprite region consists of three main steps. The first step is the detection of sprite area; where the sequence of frames belong to Group of Video sequence are analysed to detect the sprite regions which survive for long time, and to determine the sprite type (i.e., whether it is static or dynamic). Then as a second step, the flagged survived areas are passed through the gaps/islands removal stage to enhance the detected sprite areas using post-processing operations. The third step is partitioning the sprite area in

Association rules mining (ARM) is a fundamental and widely used data mining technique to achieve useful information about data. The traditional ARM algorithms are degrading computation efficiency by mining too many association rules which are not appropriate for a given user. Recent research in (ARM) is investigating the use of metaheuristic algorithms which are looking for only a subset of high-quality rules. In this paper, a modified discrete cuckoo search algorithm for association rules mining DCS-ARM is proposed for this purpose. The effectiveness of our algorithm is tested against a set of well-known transactional databases. Results indicate that the proposed algorithm outperforms the existing metaheuristic methods.

This paper is concerned with introducing and studying the first new approximation operators using mixed degree system and second new approximation operators using mixed degree system which are the core concept in this paper. In addition, the approximations of graphs using the operators first lower and first upper are accurate then the approximations obtained by using the operators second lower and second upper sincefirst accuracy less then second accuracy. For this reason, we study in detail the properties of second lower and second upper in this paper. Furthermore, we summarize the results for the properties of approximation operators second lower and second upper when the graph G is arbitrary, serial 1, serial 2, reflexive, symmetric, tra

In this paper, we used four classification methods to classify objects and compareamong these methods, these are K Nearest Neighbor's (KNN), Stochastic Gradient Descentlearning (SGD), Logistic Regression Algorithm(LR), and Multi-Layer Perceptron (MLP). Weused MCOCO dataset for classification and detection the objects, these dataset image wererandomly divided into training and testing datasets at a ratio of 7:3, respectively. In randomlyselect training and testing dataset images, converted the color images to the gray level, thenenhancement these gray images using the histogram equalization method, resize (20 x 20) fordataset image. Principal component analysis (PCA) was used for feature extraction, andfinally apply four classification metho

Smart water flooding (low salinity water flooding) was mainly invested in a sandstone reservoir. The main reasons for using low salinity water flooding are; to improve oil recovery and to give a support for the reservoir pressure.

In this study, two core plugs of sandstone were used with different permeability from south of Iraq to explain the effect of water injection with different ions concentration on the oil recovery. Water types that have been used are formation water, seawater, modified low salinity water, and deionized water.

The effects of water salinity, the flow rate of water injected, and the permeability of core plugs have been studied in order to summarize the best conditions of low salinity

Used automobile oils were subjected to filtration to remove solid material and dehydration to remove water, gasoline and light components by using vacuum distillation under moderate pressure, and then the dehydrated waste oil is subjected to extraction by using liquid solvents. Two solvents, namely n-butanol and n-hexane were used to extract base oil from automobile used oil, so that the expensive base oil can be reused again.
The recovered base oil by using n-butanol solvent gives (88.67%) reduction in carbon residue, (75.93%) reduction in ash content, (93.73%) oil recovery, (95%) solvent recovery and (100.62) viscosity index, at (5:1) solvent to used oil ratio and (40 oC) extraction temperature, while using n-hexane solvent gives (6