Transportation and distribution are the most important elements in the work system for any company, which are of great importance in the success of the chain work. Al-Rabee factory is one of the largest ice cream factories in Iraq and it is considered one of the most productive and diversified factories with products where its products cover most areas of the capital Baghdad, however, it lacks a distribution system based on scientific and mathematical methods to work in the transportation and distribution processes, moreover, these processes need a set of important data that cannot in any way be separated from the reality of fuzziness industrial environment in Iraq, which led to use the fuzzy sets theory to reduce the levels of uncertainty.

In this paper, photometric analysis of two short period group of the eclipsing binaries (RS CVn); RT And and BH Vir is presented. New physical and geometric parameters were obtained by performing two computer modeling. The first model is software package PHOEBE based on the Wilson–Devinney method, and the second is Binary Maker 3 (BM3).Our results are in good agreement with those obtained using the same modeling.

In this paper the modified trapezoidal rule is presented for solving Volterra linear Integral Equations (V.I.E) of the second kind and we noticed that this procedure is effective in solving the equations. Two examples are given with their comparison tables to answer the validity of the procedure.

Type 2 diabetes mellitus which abbreviate as T2DM is a complex endocrine and metabolic disorder arisingfrom genetic and environmental factors interaction which in turn induce various degrees of insulin functionalalteration on peripheral tissues. Globally, T2DM has develop into a public health problem. Therefore, Thestudy included (75) patients(37 female and 38 males) suffering from T2DM who visit al-kadhimiya teachinghospital with age range 20-80 years and (70) as healthy controls with age range 20-70 years. All studiedgroups were evaluated CMV IgG by ELISA,B. urea, S. Creatinine, cholesterol and triglyceride the resultsshowed that B.urea, S.creatinine and serum cholesterol showed a non-significant differences between studiedgroup,

This  srudy   aimed  to   use  a   new  concentration   from   l\!J3T (Nitroblue tetrazolium) which using NADH   stain ( by used eight different concentrations from (0.2% to 0.06% ).

That stain is a mitochondrial and cytoplasmic histochemical stain which gi ves more infom1ation about the metabolic activity of muscle fiber, so it is valuable in determining the types of muscle fibers and good fiber differentiation type {T) and type (TT)  fibers), by reducing NBT in the location of enzyme and gives a blue color in different degrees according to the types of muscle fibers, and we noticed that the concentration 0.1% from NBT gives a good result and di

     Today in the digital realm, where images constitute the massive resource of the social media base but unfortunately suffer from two issues of size and transmission, compression is the ideal solution. Pixel base techniques are one of the modern spatially optimized modeling techniques of deterministic and probabilistic bases that imply mean, index, and residual. This paper introduces adaptive pixel-based coding techniques for the probabilistic part of a lossy scheme by incorporating the MMSA of the C321 base along with the utilization of the deterministic part losslessly. The tested results achieved higher size reduction performance compared to the traditional pixel-based techniques and the standard JPEG by about 40% and 50%,

This research describes a new model inspired by Mobilenetv2 that was trained on a very diverse dataset. The goal is to enable fire detection in open areas to replace physical sensor-based fire detectors and reduce false alarms of fires, to achieve the lowest losses in open areas via deep learning. A diverse fire dataset was created that combines images and videos from several sources. In addition, another self-made data set was taken from the farms of the holy shrine of Al-Hussainiya in the city of Karbala. After that, the model was trained with the collected dataset. The test accuracy of the fire dataset that was trained with the new model reached 98.87%.