This research included measuring the concentrations of natural radioactive isotopes U-238 and Th-232 and radiation dose rates for selected areas of Missan province, GR-460 system was used which has the potential to measure the concentrations of natural radioactive isotopes in (ppm) unit and measuring the radiation dose rates in μR/h unit. It was also used with the system the mobile device FH-40 which measures the radiation dose rates in units μSμ/h the measurement results showed the absence of a significant increase in the U-238 and Th-232 concentration where the concentration of isotopes of U-238 and natural Th-232 (3.35-5.46) ppm respectively it is authorized and universally accepted. In terms of radiation dose rates it ranged betwe

The objective of this research was to estimate the dose distribution delivered by radioactive gold nanoparticles (198 AuNPs or 199 AuNPs) to the tumor inside the human prostate as well as to normal tissues surrounding the tumor using the Monte-Carlo N-Particle code (MCNP-6.1. 1 code). Background Radioactive gold nanoparticles are emerging as promising agents for cancer therapy and are being investigated to treat prostate cancer in animals. In order to use them as a new therapeutic modality to treat human prostate cancer, accurate radiation dosimetry simulations are required to estimate the energy deposition in the tumor and surrounding tissue and to establish the course of therapy for the patient. Materials and methods A simple geometrical

     The aim of this study is to determine the effect of cold plasma on nails pH, creatine levels and the accumulative of some trace elements in humans nails. Creatine levels in the blood, as well as pH and trace elements, were measured before and after (1, 2) months of plasma exposure in both gender (men and women) between the ages of 22 and 25 years. Nails are exposed to  cold plasma with a voltage of (175 volts) and (2 gas flow). After one month of exposure, there was no significant change in the levels of all parameters, but after 2 months, the concentration of creatine and pH had  reached  a near- neutral value. In both men and women,  calcium concentration increased and showed a positive response to cold plasma, while the v

     In this study, gamma ray transmission method have been used to determine the total porosity in four samples: pure Alumina  ( Al₂O₃   ),  Al₂O₃ + (0.2wt%)MgO ,  Al₂O₃ + (0.6wt% )Y₂O₃  and Al₂O₃+ (8wt% ) ZrO₂ .

      The experimental setup for the gamma ray transmission consist of ¹³⁷Cs gamma source ( 662 KeV  ), a  NaI (Tl) scintillation detector measured the attenuation of strongly collimated  gamma beam through alumina samples.

The porosity obtained by the gamma ray transmission method were compare

      The present paper concern with minimax shrinkage estimator technique in order to estimate Burr X distribution shape parameter, when prior information about the real shape obtainable as original estimate while known scale parameter.

 Derivation for Bias Ratio, Mean squared error and the Relative Efficiency equations.

 Numerical results and conclusions for the expressions mentioned above were displayed. Comparisons for proposed estimator with most recent works were made.

This paper presents a method to classify colored textural images of skin tissues. Since medical images havehighly heterogeneity, the development of reliable skin-cancer detection process is difficult, and a mono fractaldimension is not sufficient to classify images of this nature. A multifractal-based feature vectors are suggested hereas an alternative and more effective tool. At the same time multiple color channels are used to get more descriptivefeatures.Two multifractal based set of features are suggested here. The first set measures the local roughness property, whilethe second set measure the local contrast property.A combination of all the extracted features from the three colormodels gives a highest classification accuracy with 99.4

 

    The combination of wavelet theory and neural networks has lead to the development of wavelet networks. Wavelet networks are feed-forward neural networks using wavelets as activation function. Wavelets networks have been used in classification and identification problems with some success.

  In this work we proposed a fuzzy wavenet network (FWN), which learns by common back-propagation algorithm to classify medical images. The library of medical image has been analyzed, first. Second, Two experimental tables’ rules provide an excellent opportunity to test the ability of fuzzy wavenet network due to the high level of information variability often experienced with this type of images.

&n

In this paper, membrane-based computing image segmentation, both region-based and edge-based, is proposed for medical images that involve two types of neighborhood relations between pixels. These neighborhood relations—namely, 4-adjacency and 8-adjacency of a membrane computing approach—construct a family of tissue-like P systems for segmenting actual 2D medical images in a constant number of steps; the two types of adjacency were compared using different hardware platforms. The process involves the generation of membrane-based segmentation rules for 2D medical images. The rules are written in the P-Lingua format and appended to the input image for visualization. The findings show that the neighborhood relations between pixels o

This paper concentrates on employing the -difference equations approach to prove another generating function, extended generating function, Rogers formula and Mehler’s formula for the polynomials , as well as thegenerating functions of Srivastava-Agarwal type. Furthermore, we establish links between the homogeneous -difference equations and transformation formulas.