In this paper, the density of state (DOS) at Fe metal contact to Titanium dioxide semiconductor (TiO2) has been studied and investigated using quantum consideration approaches. The study and calculations of (DOS) depended on the orientation and driving energies. was a function of TiO2 and Fe materials' refractive index and dielectric constant. Attention has focused on the effect of on the characteristic of (DOS), which increased with the increasing of refractive index and dielectric constant of Fe metal and vice versa. The results of (DOS) and its relation with and values of system have been discussed. As for contact system is increased, (DOS) values increased at first, but the relation is disturbed later and transforms into an inve

Abstract

Abstract has many advantages as has historically been one of the regions leading cultural centers . for centuries , it has been a center of commertial and financial operations in Iraq. it is also rich in archeological sites and natural resources, but because of its wars and implementation of urban development strategies are effective and sustainable , so contracted the secretariat of Baghdad with the company (khatib and scirntiffic) for the preparation of the comprehensive development plan for the city of Baghdad in 2030 and funded by the world bank and the fact that the plan was approved ( three stages of it ) and only one phase remains the fourth stage, which is under discussion the aim of the

An Optimal Algorithm for HTML Page Building Process

Krawtchouk polynomials (KPs) and their moments are promising techniques for applications of information theory, coding theory, and signal processing. This is due to the special capabilities of KPs in feature extraction and classification processes. The main challenge in existing KPs recurrence algorithms is that of numerical errors, which occur during the computation of the coefficients in large polynomial sizes, particularly when the KP parameter (p) values deviate away from 0.5 to 0 and 1. To this end, this paper proposes a new recurrence relation in order to compute the coefficients of KPs in high orders. In particular, this paper discusses the development of a new algorithm and presents a new mathematical model for computing the

Regression testing being expensive, requires optimization notion. Typically, the optimization of test cases results in selecting a reduced set or subset of test cases or prioritizing the test cases to detect potential faults at an earlier phase. Many former studies revealed the heuristic-dependent mechanism to attain optimality while reducing or prioritizing test cases. Nevertheless, those studies were deprived of systematic procedures to manage tied test cases issue. Moreover, evolutionary algorithms such as the genetic process often help in depleting test cases, together with a concurrent decrease in computational runtime. However, when examining the fault detection capacity along with other parameters, is required, the method falls sh

In this research a new system identification algorithm is presented for obtaining an optimal set of mathematical models for system with perturbed coefficients, then this algorithm is applied practically by an “On Line System Identification Circuit”, based on real time speed response data of a permanent magnet DC motor. Such set of mathematical models represents the physical plant against all variation which may exist in its parameters, and forms a strong mathematical foundation for stability and performance analysis in control theory problems.

The swarm intelligence and evolutionary methods are commonly utilized by researchers in solving the difficult combinatorial and Non-Deterministic Polynomial (NP) problems. The N-Queen problem can be defined as a combinatorial problem that became intractable for the large ‘n’ values and, thereby, it is placed in the NP class of problems. In the present study, a solution is suggested for the N-Queen problem, on the basis of the Meerkat Clan Algorithm (MCA). The problem of n-Queen can be mainly defined as one of the generalized 8-Queen problem forms, for which the aim is placing 8 queens in a way that none of the queens has the ability of killing the others with the use of the standard moves of the chess queen. The Meerkat Clan environm

This paper proposes a novel meta-heuristic optimization algorithm called the fine-tuning meta-heuristic algorithm (FTMA) for solving global optimization problems. In this algorithm, the solutions are fine-tuned using the fundamental steps in meta-heuristic optimization, namely, exploration, exploitation, and randomization, in such a way that if one step improves the solution, then it is unnecessary to execute the remaining steps. The performance of the proposed FTMA has been compared with that of five other optimization algorithms over ten benchmark test functions. Nine of them are well-known and already exist in the literature, while the tenth one is proposed by the authors and introduced in this article. One test trial was shown t

In many video and image processing applications, the frames are partitioned into blocks, which are extracted and processed sequentially. In this paper, we propose a fast algorithm for calculation of features of overlapping image blocks. We assume the features are projections of the block on separable 2D basis functions (usually orthogonal polynomials) where we benefit from the symmetry with respect to spatial variables. The main idea is based on a construction of auxiliary matrices that virtually extends the original image and makes it possible to avoid a time-consuming computation in loops. These matrices can be pre-calculated, stored and used repeatedly since they are independent of the image itself. We validated experimentally th