This study aims to analyze spectra in real-time for λ Draconids, σ Hydrids, μ Virginid, and one sporadic meteor using spectroscopic chemical analysis and diagnose plasma parameters. Good-resolution spectroscopy and a CCD camera for meteor observation were used concurrently to examine the ablation spectra of these meteorites in situ. The Boltzmann and Lorentz methods were then used to determine the temperature and density of electrons, the length of Debye, and the frequency of plasma. Furthermore, spectra data can be analyzed and compared to data from other sources. Spectrum tests can be utilized to identify the chemical structure of meteorites' plasma.

Cancer is one of the dangerous diseases that afflict a person through injury to cells and tissues in the body, where a person is vulnerable to infection in any age group, and it is not easy to control and multiply between cells and spread to the body. In spite of the great progress in medical studies interested in this aspect, the options for those with this disease are few and difficult, as they require significant financial costs for health services and for treatment that is difficult to provide.

This study dealt with the determinants of liver cancer by relying on the data of cancerous tumours taken from the Iraqi Center for Oncology in the Ministry of Health 2017. Survival analysis has been used as a m

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

Maximizing the net present value (NPV) of oil field development is heavily dependent on optimizing well placement. The traditional approach entails the use of expert intuition to design well configurations and locations, followed by economic analysis and reservoir simulation to determine the most effective plan. However, this approach often proves inadequate due to the complexity and nonlinearity of reservoirs. In recent years, computational techniques have been developed to optimize well placement by defining decision variables (such as well coordinates), objective functions (such as NPV or cumulative oil production), and constraints. This paper presents a study on the use of genetic algorithms for well placement optimization, a ty

AW Ali T, Journal of the Faculty of Medicine, 2016 - Cited by 1

The present study was included the isolation of Keratinophilic fungi from water samples taken from 19 indoor public swimming pools in Baghdad during four season (summer ,fall ,spring ,and winter). Isolation period was September 2011and September 2012 . Samples were collected from different places in swimming pool . Sixteen keratinophilic fungal species, belonging to twenty –one genera were isolated using Surface Dilution Plating (SDP) and Hair Bait Technique (HBT) . Aspergillus genus was the most frequent and occurrence (19.84%), followed by Trichophyton (11.60%) and Fusarium (7.59% ) . The most common fungal infection occurred in summer season (42.16%) , and the most frequent month manifestation of species occurred in August

The ultimate goal of any sale contract is to maximize the combined returns of the parties, knowing that these returns are not realized (in long-term contracts) except in the final stages of the contract. Therefore, this requires the parties to the contract to leave some elements open, including the price, because the adoption of a fixed price and inflexible will not be appropriate to meet their desires when contracting, especially with ignorance of matters beyond their will and may affect the market conditions, and the possibility of modifying the fixed price through The elimination is very limited, especially when the parties to the contract are equally in terms of economic strength. Hence, in order to respond to market uncertainties, the

Trimethoprim derivative Schiff bases are versatile ligands synthesized with carbonyl groups from the condensation of primary amines (amino acids). Because of their broad range of biological activity, these compounds are very important in the medical and pharmaceutical fields. Biological activities such as antibacterial, antifungal and antitumor activity are often seen. Transition metal complexes derived from biological activity Schiff base ligands have been commonly used