The Catharanthus roseus plant was extracted and converted to nanoparticles in this work. The Soxhlet method was used to extract alkaloid compounds from the Catharanthus roseus plant and converted them to the nanoscale. Chitosan polymer was used as a linking material and converted to Chitosan nanoparticles (CSNPs). The extracted alkaloids were linked with Chitosan nanoparticles by maleic anhydride to get the final product (CSNPs-Linker-alkaloids). The pure Chitosan, Chitosan nanoparticles, and CSNPs-Linker-alkaloids were characterized by X-ray diffractometer, and Fourier Transform Infrared spectroscopy. X-ray results show that all samples have an orthorhombic structure with crystallite size in nanodimensions. FTIR spectra prove that

The evaluation of subsurface formations as applied to oil well drilling started around 50 years ago. Generally, the curent review articule includes all methods for coring, logging, testing, and sampling. Also the methods for deciphering logs and laboratory tests that are relevant to assessing formations beneath the surface, including a look at the fluids they contain are discussed. Casing is occasionally set in order to more precisely evaluate the formations; as a result, this procedure is also taken into account while evaluating the formations. The petrophysics of reservoir rocks is the branch of science interested in studying chemical and physical properties of permeable media and the components of reservoir rocks which are associated

A- The research problem: the research problem which is the garments industry, as a
whole it does not rely on a single system in the sizes of the clothing and the working
companies, see that it is not plausible that the sizes be unificd and consistent in all companies.
The current sizes in the domestic Iraqi markets are not suitable for some females ,on the other
hand the Iraqi industry suffers the lack of a modern standard for some Iraqis female bodies.
B- The Signifiance of the research: lies in the study of the diversity of the human body
sizes and naming them to reflect the desires and requirements of the consumer and try to find
a method to meet their expectations as well as to raise the level of garments industr

Currently, with the huge increase in modern communication and network applications, the speed of transformation and storing data in compact forms are pressing issues. Daily an enormous amount of images are stored and shared among people every moment, especially in the social media realm, but unfortunately, even with these marvelous applications, the limited size of sent data is still the main restriction's, where essentially all these applications utilized the well-known Joint Photographic Experts Group (JPEG) standard techniques, in the same way, the need for construction of universally accepted standard compression systems urgently required to play a key role in the immense revolution. This review is concerned with Different

Abstract Software-Defined Networking (commonly referred to as SDN) is a newer paradigm that develops the concept of a software-driven network by separating data and control planes. It can handle the traditional network problems. However, this excellent architecture is subjected to various security threats. One of these issues is the distributed denial of service (DDoS) attack, which is difficult to contain in this kind of software-based network. Several security solutions have been proposed recently to secure SDN against DDoS attacks. This paper aims to analyze and discuss machine learning-based systems for SDN security networks from DDoS attack. The results have indicated that the algorithms for machine learning can be used to detect DDoS