Abstract: Colloidal gold nanoparticles (ringworm Palm or in the form of paper willow) have been prepared from HAuCl4 containing aqueous solution by hot chemical reduction method. The colloidal gold nanoparticles were characterized by SEM, EDX, and UV-VIS absorption spectroscopy. It was found that the variation of reduction time from boiling point affects the size of the nanoparticles and also in chemical reduction approach the size of nanoparticles can be controlled by varying the amount of variation the volume of reductant material with respect to the volume of HAuCL4.

Mandali Basin is located between latitudes (33◦ 39' 00" and 33^◦
54' 55") to the north and longitudes (45ο 11' 00" and 45ο 40' 00") to the
east; to the east of Diyala province at the Iraqi-Iranian border; the
basin area is approximately 491 km².
From the study of climate reality of the basin between 1990-
2013and assessment of the basic climate transactions, it was found
that the annual rate of rainfall is 253.02 mm, the relative humidity
(44.4%), the temperature (21.3 ◦C), wind speed (2.08 m /sec.),
sunshine (8.27 h/day) and evaporation of the basin class (a) (271.98
mm) and corrected potential evapotranspiration (80.03 mm). The
results of the data analysis show that, there are

The past decades of the last century and until now have witnessed many crises in the housing sector, and these crises were the result of many problems that led to a weak quality and quantity of housing stock, especially for lowincome people, and Goal 11 of the Sustainable Development Goals states, "Make cities and human settlements inclusive, safe, and capable of enduring and being sustainable, we have prepared this research that attempts to answer the following question: Is the current empowerment in the housing sector real and efficient support for people with limited income? The research assumes that empowerment in the housing sector has an important and effective role in reducing housing problems, the research aims to reach the most imp

Permeability data has major importance work that should be handled in all reservoir simulation studies. The importance of permeability data increases in mature oil and gas fields due to its sensitivity for the requirements of some specific improved recoveries. However, the industry has a huge source of data of air permeability measurements against little number of liquid permeability values. This is due to the relatively high cost of special core analysis.
The current study suggests a correlation to convert air permeability data that are conventionally measured during laboratory core analysis into liquid permeability. This correlation introduces a feasible estimation in cases of data loose and poorly consolidated formations, or in cas

 In this paper, we propose a method using continuous wavelets to study the multivariate fractional Brownian motion through the deviations of the transformed random process to find an efficient estimate of Hurst exponent using eigenvalue regression of the covariance matrix. The results of simulations experiments shown that the performance of the proposed estimator was efficient in bias but the variance get increase as signal change from short to long memory the MASE increase relatively. The estimation process was made by calculating the eigenvalues for the variance-covariance matrix of Meyer’s continuous wavelet details coefficients.

Estimating an individual's age from a photograph of their face is critical in many applications, including intelligence and defense, border security and human-machine interaction, as well as soft biometric recognition. There has been recent progress in this discipline that focuses on the idea of deep learning. These solutions need the creation and training of deep neural networks for the sole purpose of resolving this issue. In addition, pre-trained deep neural networks are utilized in the research process for the purpose of facial recognition and fine-tuning for accurate outcomes. The purpose of this study was to offer a method for estimating human ages from the frontal view of the face in a manner that is as accurate as possible and takes

 In this paper, we propose a method using continuous wavelets to study the multivariate fractional Brownian motion through the deviations of the transformed random process to find an efficient estimate of Hurst exponent using eigenvalue regression of the covariance matrix. The results of simulations experiments shown that the performance of the proposed estimator was efficient in bias but the variance get increase as signal change from short to long memory the MASE increase relatively. The estimation process was made by calculating the eigenvalues for the variance-covariance matrix of Meyer’s continuous wavelet details coefficients.