ABSTRACT

      The current research aims at highlighting the role of engagement of a sample of employees who works in some of the Iraqi private banks in terms of their interaction , commitment and enthusiasm and the positive impact they own regarding their job and devote their efforts to achieve the core purpose  which is customer loyalty. The problem was expressed through a number of intellectual and practical questions.

In order to achieve the aim of the research the quantitative analytical method was used depending on a questionnaire as a basic tool to collect research data and the qualitative survey method depending on semi-structured interviews which were distrib

Gumbel distribution was dealt with great care by researchers and statisticians. There are traditional methods to estimate two parameters of Gumbel distribution known as Maximum Likelihood, the Method of Moments and recently the method of re-sampling called (Jackknife). However, these methods suffer from some mathematical difficulties in solving them analytically. Accordingly, there are other non-traditional methods, like the principle of the nearest neighbors, used in computer science especially, artificial intelligence algorithms, including the genetic algorithm, the artificial neural network algorithm, and others that may to be classified as meta-heuristic methods. Moreover, this principle of nearest neighbors has useful statistical featu

Electromyogram (EMG)-based Pattern Recognition (PR) systems for upper-limb prosthesis control provide promising ways to enable an intuitive control of the prostheses with multiple degrees of freedom and fast reaction times. However, the lack of robustness of the PR systems may limit their usability. In this paper, a novel adaptive time windowing framework is proposed to enhance the performance of the PR systems by focusing on their windowing and classification steps. The proposed framework estimates the output probabilities of each class and outputs a movement only if a decision with a probability above a certain threshold is achieved. Otherwise (i.e., all probability values are below the threshold), the window size of the EMG signa

Abstract: Word sense disambiguation (WSD) is a significant field in computational linguistics as it is indispensable for many language understanding applications. Automatic processing of documents is made difficult because of the fact that many of the terms it contain ambiguous. Word Sense Disambiguation (WSD) systems try to solve these ambiguities and find the correct meaning. Genetic algorithms can be active to resolve this problem since they have been effectively applied for many optimization problems. In this paper, genetic algorithms proposed to solve the word sense disambiguation problem that can automatically select the intended meaning of a word in context without any additional resource. The proposed algorithm is evaluated on a col

Objectives: The specific objectives of the present study were to assess the level of job satisfaction among
nursing staff who are working in the Ministry of Health and Ministry of Higher Education and Scientific
Research in the provinces of Erbil, Mosul and Kirkuk to determine the factors that affect their satisfaction.
Methodology:٨
descriptive design was carried-out from September 20, 2006 through April 1,'؛ 2007 in order
to assess the job satisfaction for nursing staff in governmental health agencies and educational setting.
Quantitative research methods were utilized to employ the study design. The study was conducted on three Iraqi
governorates (Mosul, Kirkuk, and Erbil). The sample of the study was collected

The increasing availability of computing power in the past two decades has been use to develop new techniques for optimizing solution of estimation problem. Today's computational capacity and the widespread availability of computers have enabled development of new generation of intelligent computing techniques, such as our interest algorithm, this paper presents one of new class of stochastic search algorithm (known as Canonical Genetic' Algorithm ‘CGA’) for optimizing the maximum likelihood function strategy is composed of three main steps: recombination, mutation, and selection. The experimental design is based on simulating the CGA with different values of are compared with those of moment method. Based on MSE value obtained from bot

Moment invariants have wide applications in image recognition since they were proposed.