The behavior of thinking is consider one of the modern concepts that appear in the last 20 years, this concept has attracted the attention of psychologists and researchers for thinking has a great role in many fields like teaching ,educational,economical,cultural and social fields.
One of thinking manner is imaginal thinking that has a great role in human civilization. imaginal thinking lead to innovation ,poems, inventions and arts. imaginal thinkingled to highscores in talented schools by escalating their thinking range and solving problems that consider one of organized and free assumption thinking.
The development of problems thinking strategies reflect the development of organized brain process ability.
That studies assumes that increasing problems solving in childhood increasing problems solving in life.
Then this research aims to:
1-Estimate adults imaginal thinking according to age scale (23, 24, 25, 26)
2- Estimateadults'imaginal thinking according to social scale.
3- Estimate adults solving problems according to age scale (23, 24, 25, 26)
4-Estimate adults solving problems according to social scale.
5- Estimate the relation between age scale and social scale.
The samples are (400) male and female employees randomly selected .the researchers established imaginal thinking scale and problems solving scale according to (information process theory) ,then extracting the psychometrical features of these scales from stability and truth .
By analyzing research data, the results are:
1(-23,24,25,26) year adults have imaginal thinking.
2-Imaginal thinking affected by social by social scale varibles in 26 years adults.
3- The problems solving ability increasing in (23,24,25,26) years adults.
4- The problem solving ability is unaffected by social type in adults.
There is positive relation between imaginal thinking and problems solving among adults .
The research achieves many proposals and recommendations.
Keywords: imaginal thinking, problems solving, adults
This paper deals with modelling and control of Euler-Bernoulli smart beam interacting with a fluid medium. Several distributed piezo-patches (actuators and/or sensors) are bonded on the surface of the target beam. To model the vibrating beam properly, the effect of the piezo-patches and the hydrodynamic loads should be taken into account carefully. The partial differential equation PDE for the target oscillating beam is derived considering the piezo-actuators as input controls. Fluid forces are decomposed into two components: 1) hydrodynamic forces due to the beam oscillations, and 2) external (disturbance) hydrodynamic loads independent of beam motion. Then the PDE is discretized usi
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