The current research was aimed at the following:
1. Measurement of Personality Type Observer of the University students.
2. Identify the differences in Personality Type Observer among the University students according to variable of Sex (male / female). And according to variable of Specialization (scientific / literary)
3. Measurement of Withdrawal of the University students.
4. Identify the differences in Withdrawal among the University students according to variable of Sex (male / female). And according to variable of Specialization (scientific / literary).
5. Identify the relationship between Personality Type Observer and Withdrawal.
To achieve this aims of the research, the researchers set up the instrument is scale of Personality Type Observer that consistent (24) item and Withdrawal that consistent (20) item. And the researcher applying this scale on the sample amounted to (200) University students. Then after data processing statistically, the researchers reached the following results:
1. University students have Personality Type Observer.2. There is no differences in Personality Type Observer among the University students according to variable of Sex (male / female). And There is differences according to variable of Specialization (scientific / literary) for literary
3. University students have Withdrawal.
4. There is no differences in Withdrawal among the University students according to variable of Sex (male / female). And There is no differences according to variable of Specialization (scientific / literary).
5. There is relationship between Personality Type Observer and Withdrawal.
In light of the results of this research the researchers came out with a number of recommendations and suggestions.
Cryptocurrency became an important participant on the financial market as it attracts large investments and interests. With this vibrant setting, the proposed cryptocurrency price prediction tool stands as a pivotal element providing direction to both enthusiasts and investors in a market that presents itself grounded on numerous complexities of digital currency. Employing feature selection enchantment and dynamic trio of ARIMA, LSTM, Linear Regression techniques the tool creates a mosaic for users to analyze data using artificial intelligence towards forecasts in real-time crypto universe. While users navigate the algorithmic labyrinth, they are offered a vast and glittering selection of high-quality cryptocurrencies to select. The
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Was chosen the subject of research and strategic intelligence and competitive because of its impact on the strategic success of the banking sector, the fact is the entrepreneurial in the Iraqi banking mar
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Twenty five samples out of sixty wound swabs taken from burn patients were identified as P. aeruginosabacteria by conventional methods. Antibiotics susceptibility tests were performed against thirteen antibiotics. P. aeruginosa samples were treated with 0.5 mg/ml of Safranin O solution then irradiated with 532nm Q-switched Nd:YAG laser at four energy densities (0.324, 0.704, 1.380, and 1.831 J/cm2) for different times of 5, 8 and 11 minutes with 5Hz repetition rate. The viability, susceptibility to antibiotic and production of pyocyanin were determined before and after irradiation. The results showed that the number of CFU/ml of P. aeruginosa decreased with increasing the dose of irradiation. Complete killing of cells was observed at 1.8
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