Zernike Moments has been popularly used in many shape-based image retrieval studies due to its powerful shape representation. However its strength and weaknesses have not been clearly highlighted in the previous studies. Thus, its powerful shape representation could not be fully utilized. In this paper, a method to fully capture the shape representation properties of Zernike Moments is implemented and tested on a single object for binary and grey level images. The proposed method works by determining the boundary of the shape object and then resizing the object shape to the boundary of the image. Three case studies were made. Case 1 is the Zernike Moments implementation on the original shape object image. In Case 2, the centroid of the s

When the drawdown pressure amounts to a value below the dew point pressure, a minor droplet of condensate is shaped and accumulated in the close area of wellbore. As the accumulation happens, the saturation of the liquid will grow and a reduction in gas relative permeability will happen, therefore it will affect the productivity. Generally, condensate baking problem in gas wells is being deliberated and studied and numerous techniques have been suggested to solve the problem. The studying of condensate banking dynamics is essential to evaluate the productivity and behavior of the wells of the gas fields.

Elemental capture spectroscopy (ECS) is an important tool in the petroleum industry for determining the composition and properties of rock formations in a reservoir. Knowledge of the types and abundance of different minerals in the reservoir is crucial for accurate petrophysical interpretation, reservoir engineering practices, and stratigraphic correlation. ECS measures the elemental content of the rock, which directly impacts several physical properties that are essential for reservoir characterization, such as porosity, fluid saturation, permeability, and matrix density. The ability to accurately determine these properties leads to better reservoir mapping, improved production, and more effective resource management. Accurately de

A skip list data structure is really just a simulation of a binary search tree. Skip lists algorithm are simpler, faster and use less space. this data structure conceptually uses parallel sorted linked lists. Searching in a skip list is more difficult than searching in a regular sorted linked list. Because a skip list is a two dimensional data structure, it is implemented using a two dimensional network of nodes with four pointers. the implementation of the search, insert and delete operation taking a time of upto . The skip list could be modified to implement the order statistic operations of RANKand SEARCH BY RANK while maintaining the same expected time. Keywords:skip list , parallel linked list , randomized algorithm , rank.

Abstract :- In this paper, silver nanoparticles had been prepared by chemical reduction method. Many tests had been done to it such as UV-Visible spectrophotometer, XRD, AFM&SEM test. finally an attempt had been done to get the optimum condition to control the grain size of silver Nanoparticles by variation the heating period and other parameters which has an effect in silver Nanoparticles synthesis process. in this method we can get a silver nanoparticles in the size range from 52 to 97 nm.

The aim of this research is to test the relationship of influence and correlation between strategic performance and its five dimensions (financial dimension, after internal processes, after internal customer satisfaction, after learning and growth, environmental and social dimension), by adopting international indicators in agricultural projects To determine the extent of the differences between the research variable and its dimensions, and then try to come out with a number of recommendations that contribute to the evaluation of agricultural projects and their performance by diagnosing and treating deviations, and based on the importance of the research topic in agricultural institutions. Institutions of the Environment and Soci

Information from 54 Magnetic Resonance Imaging (MRI) brain tumor images (27 benign and 27 malignant) were collected and subjected to multilayer perceptron artificial neural network available on the well know software of IBM SPSS 17 (Statistical Package for the Social Sciences). After many attempts, automatic architecture was decided to be adopted in this research work. Thirteen shape and statistical characteristics of images were considered. The neural network revealed an 89.1 % of correct classification for the training sample and 100 % of correct classification for the test sample. The normalized importance of the considered characteristics showed that kurtosis accounted for 100 % which means that this variable has a substantial effect

In this paper, the process for finding an approximate solution of nonlinear three-dimensional (3D) Volterra type integral operator equation (N3D-VIOE) in R³ is introduced. The modelling of the majorant function (MF) with the modified Newton method (MNM) is employed to convert N3D-VIOE to the linear 3D Volterra type integral operator equation (L3D-VIOE). The method of trapezoidal rule (TR) and collocation points are utilized to determine the approximate solution of L3D-VIOE by dealing with the linear form of the algebraic system. The existence of the approximate solution and its uniqueness are proved, and illustrative examples are provided to show the accuracy and efficiency of the model.

Mathematical Subject Classificat