In this paper, we characterize normal composition operators induced by holomorphic self-map , when and .Moreover, we study other related classes of operators, and then we generalize these results to polynomials of degree n.

In this work, a CW CO2 laser was used for cutting samples of the fiber-reinforced
plastics (FRP) of three different types of reinforcing material; aramide, glass and carbon.
Cutting process was investigated throughout the variation of some parameters of cutting
process and their effects on cutting quality as well as the effect of an inert gas exist in the
interaction region and finally using a mechanical chopper in order to enhance the cutting
quality. Results obtained explained the possibility to perform laser cutting with high
quality in these materials by good control of the parameters and conditions of the process.

The CdS quantum dots were prepared by chemical reaction
of cadmium oleylamine (Cd –oleylamine complex) with the
sulfite-oleylamine (S-oleylamine) with 1:6 mole ratios. The
optical properties structure and spectroscopy of the product
quantum dot were studied. The results show the dependence of the
optical properties on the crystal dimension and the formation of
the trap states in the energy band gap.

The vision and philosophy of the economic system in Iraq after 2003 were not clear-cut because of overlapping internal factors was the novelty of the political system and the lack of political and economic decision makers to understanding and conviction full need shaping a new administration for the Iraqi economy is able to succeed economic development programs, and external factors was determinedly organizations international application of shock reforming style and contrary to the social reality and the security which reflected negatively on the work and consistency Lisseeash financial balance between stability and growth and raise the level of consumer spending and the importance of research lies in the ability of fiscal policy to achie

Researchers are increasingly using multimodal biometrics to strengthen the security of biometric applications. In this study, a strong multimodal human identification model was developed to address the growing problem of spoofing attacks in biometric security systems. Through the use of metaheuristic optimization methods, such as the Genetic Algorithm(GA), Ant Colony Optimization(ACO), and Particle Swarm Optimization (PSO) for feature selection, this unique model incorporates three biometric modalities: face, iris, and fingerprint. Image pre-processing, feature extraction, critical image feature selection, and multibiometric recognition are the four main steps in the workflow of the system. To determine its performance, the model wa

The purpose of this paper is to solve the stochastic demand for the unbalanced transport problem using heuristic algorithms to obtain the optimum solution, by minimizing the costs of transporting the gasoline product for the Oil Products Distribution Company of the Iraqi Ministry of Oil. The most important conclusions that were reached are the results prove the possibility of solving the random transportation problem when the demand is uncertain by the stochastic programming model. The most obvious finding to emerge from this work is that the genetic algorithm was able to address the problems of unbalanced transport, And the possibility of applying the model approved by the oil products distribution company in the Iraqi Ministry of Oil to m

Among a variety of approaches introduced in the literature to establish duality theory, Fenchel duality was of great importance in convex analysis and optimization. In this paper we establish some conditions to obtain classical strong Fenchel duality for evenly convex optimization problems defined in infinite dimensional spaces. The objective function of the primal problem is a family of (possible) infinite even convex functions. The strong duality conditions we present are based on the consideration of the epigraphs of the c-conjugate of the dual objective functions and the ε-c-subdifferential of the primal objective functions.

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