Artificial fish swarm algorithm (AFSA) is one of the critical swarm intelligent algorithms. In this
paper, the authors decide to enhance AFSA via diversity operators (AFSA-DO). The diversity operators will
be producing more diverse solutions for AFSA to obtain reasonable resolutions. AFSA-DO has been used to
solve flexible job shop scheduling problems (FJSSP). However, the FJSSP is a significant problem in the
domain of optimization and operation research. Several research papers dealt with methods of solving this
issue, including forms of intelligence of the swarms. In this paper, a set of FJSSP target samples are tested
employing the improved algorithm to confirm its effectiveness and evaluate its ex

This study aimed at identity baying the difficulties which face public basic school
principals in jar ash governorate in editing formal letters and correspondence and means of
debating with these problems to collect data the researchers developed a question air were
established the population of the study which represents its sample consisted of 129 principals
65 males and 64 females
The results of the study revealed that the principals face difficulties in office and file
management in preparing plans and reports and writing formal letters and answering them
saved recommendations were presented among which were organizing training sessions and
workshops to train the principals on how to dead with there problems.<

In this research, Artificial Neural Networks (ANNs) technique was applied in an attempt to predict the water levels and some of the water quality parameters at Tigris River in Wasit Government for five different sites. These predictions are useful in the planning, management, evaluation of the water resources in the area. Spatial data along a river system or area at different locations in a catchment area usually have missing measurements, hence an accurate prediction. model to fill these missing values is essential.
The selected sites for water quality data prediction were Sewera, Numania , Kut u/s, Kut d/s, Garaf observation sites. In these five sites models were built for prediction of the water level and water quality parameters.

Focusing of Gaussian laser beam through nonlinear media can induce spatial self- phase modulation which forms a far field intensity pattern of concentric rings. The nonlinear refractive index change of material depends on the number of pattern rings. In this paper, a formation of tunable nonlinear refractive index change of hybrid functionalized carbon nanotubes/silver nanoparticles acetone suspensions (F-MWCNTs/Ag-NPs) at weight mixing ratio of 1:3 and volume fraction of 6x10-6 , 9x10-6 , and 18x10-6 using laser beam at wavelength of 473nm was investigated experimentally. The results showed that tunable nonlinear refractive indices were obtained and increasing of incident laser power density led to increase the nonlinear refractive inde

Background: Survey of the occlusion in population groups usually include in their objections the academic assessment of occlusal feature, the planning resources for public health treatment programmers, the comparison of different population and the screening of groups for orthodontic treatment. Likewise a thorough investigation of the occurrence of malocclusions among school–students would be of major importance in the planning of orthodontic treatment in the public dental health services. For this purpose it is necessary to have detailed information on the prevalence of individual malocclusion among boys and girls at different ages distributed regionally, and moreover, an analysis of the need for orthodontic treatment in the different sc

 A particle swarm optimization algorithm and neural network like self-tuning PID controller for CSTR system is presented. The scheme of the discrete-time PID control structure is based on neural network and tuned the parameters of the PID controller by using a particle swarm optimization PSO technique as a simple and fast training algorithm. The proposed method has advantage that it is not necessary to use a combined structure of identification and decision because it used PSO. Simulation results show the effectiveness of the proposed adaptive PID neural control algorithm in terms of minimum tracking error and smoothness control signal obtained for non-linear dynamical CSTR system.