In this paper, a compact genetic algorithm (CGA) is enhanced by integrating its selection strategy with a steepest descent algorithm (SDA) as a local search method to give I-CGA-SDA. This system is an attempt to avoid the large CPU time and computational complexity of the standard genetic algorithm. Here, CGA dramatically reduces the number of bits required to store the population and has a faster convergence. Consequently, this integrated system is used to optimize the maximum likelihood function lnL(φ1, θ1) of the mixed model. Simulation results based on MSE were compared with those obtained from the SDA and showed that the hybrid genetic algorithm (HGA) and I-CGA-SDA can give a good estimator of (φ1, θ1) for the ARMA(1,1) model. Anot

Pushover analysis is an efficient method for the seismic evaluation of buildings under severe earthquakes. This paper aims to develop and verify the pushover analysis methodology for reinforced concrete frames. This technique depends on a nonlinear representation of the structure by using SAP2000 software. The properties of plastic hinges will be defined by generating the moment-curvature analysis for all the frame sections (beams and columns). The verification of the technique above was compared with the previous study for two-dimensional frames (4-and 7-story frames). The former study leaned on automatic identification of positive and negative moments, where the concrete sections and steel reinforcement quantities the

Little is known about hesitancy to receive the COVID‐19 vaccines. The objectives of this study were (1) to assess the perceptions of healthcare workers (HCWs) and the general population regarding the COVID‐19 vaccines, (2) to evaluate factors influencing the acceptance of vaccination using the health belief model (HBM), and (3) to qualitatively explore the suggested intervention strategies to promote the vaccination.

Background: One of the most common problem associated with the used of soft denture lining material is microorganisms and fungal growth especially Candida albicans, which can result in chronic mucosal inflammation. The aim of this study was to evaluate the influence of chlorhexidine diacetate (CDA) salt Incorporation into soft denture lining material on antifungal activity; against Candida albicans, and the amount of chlorhexidine di-acetate salt leached out of soft liner/CDA composite. Furthermore, evaluate shear bond strength and hardness after CDA addition to soft liner Materials and methods: chlorhexidine diacetate salt was added to soft denture lining material at four different concentrations (0.05%, 0.1% and 0.2% by weight). Four hund

          The research deal with three variables of exceptional importance to organization business firms. These variables are emotional intelligence, transformational leadership, and organizational performance. The aim of this research is to determine the effect of emotional intelligence and transformational leadership on organizational performance at the banking sector, which is represented by Al-Rafidain Bank. The problem of the research is expressed by many questions related with the nature of the interrelationships and effects among research’s variables. The researcher has depended upon the descriptions - analytical approach. on a random sample of (80 ) managers

The problem of the research is that there is a weakness in speed endurance, which has a direct impact on achievement, as it leads to early fatigue, lack of concentration, and a low level of effectiveness of performance, which made the researchers interested in this problem and finding solutions to it. Hence the importance of the research is evident: preparing cardiorespiratory fitness training to develop speed endurance and rate adaptation. The heartbeat that occurs in runners is a continuous result of training and the use of a type of training that suits the requirements of the 1500-meter running competition. The researchers used the experimental approach with pre- and post-testing for the experimental and control groups. The resea

The map of permeability distribution in the reservoirs is considered one of the most essential steps of the geologic model building due to its governing the fluid flow through the reservoir which makes it the most influential parameter on the history matching than other parameters. For that, it is the most petrophysical properties that are tuned during the history matching. Unfortunately, the prediction of the relationship between static petrophysics (porosity) and dynamic petrophysics (permeability) from conventional wells logs has a sophisticated problem to solve by conventional statistical methods for heterogeneous formations. For that, this paper examines the ability and performance of the artificial intelligence method in perme