Free Radical Copolymerization of Styrene/ Methyl Methacrylate were prepared chemically under Nitrogen ,which was investigated, in the present of Benzoyl Peroxide as Initiator at concentration of 2 × 10-3 molar at 70 °C, which was carried out in Benzene as solvent to a certain low conversion . FT-IR spectra were used for determining of the monomer reactivity ratios ,which was obtained by employing the conventional linearization method of Fineman-Ross (F-R) and Kelen-Tüdos (K- T). The experimental results showed the average value for the Styrene r1 / Methyl Methacrylate r2 system, Sty r1 = 0.45 , MMA r2 = 0.38 in the (F–R) Method and r1 = 0.49 , r2 = 0.35 in the (K–T) Method, The Results of this indicated show the random distribution of monomers in the copolymer.Likewise The monomer reactivity ratios were evaluated Mathematically in comparison in the (F–R) Method with the data STY r1 = 0.61 , MMA r2 = 0.47 , and r1 = 0.45 , r2 =0.38 in the (K–T) Method. And were used the values r1 ,r2 for STY / MMA Copolymers in computing integral curves for the instantaneous Copolymer composition throughout the whole range of conversion.
The research aims to identify how to enhance the quality of the human resources, focusing on four dimensions (efficiency, effectiveness, flexibility, and reliability), by adopting an adventure learning method that combines theoretical and applied aspects at the same time, when developing human resources and is applied using information technology, and that Through its dimensions, which are (cooperation, interaction, communication, and understanding), as the research problem indicated a clear deficiency in the cognitive perception of the mechanism of employing adventure learning dimensions in enhancing human resources quality, so the importance of research was to present treatments and proposals to reduce this problem. To achieve
... Show MoreWithin the framework of big data, energy issues are highly significant. Despite the significance of energy, theoretical studies focusing primarily on the issue of energy within big data analytics in relation to computational intelligent algorithms are scarce. The purpose of this study is to explore the theoretical aspects of energy issues in big data analytics in relation to computational intelligent algorithms since this is critical in exploring the emperica aspects of big data. In this chapter, we present a theoretical study of energy issues related to applications of computational intelligent algorithms in big data analytics. This work highlights that big data analytics using computational intelligent algorithms generates a very high amo
... Show MoreSpecies of genus Chrotogonus (surface grasshoppers) are phytophagous and damaging to various economical important plants in their seedling stages. In order to know the biodiversity of surface grasshoppers, the detailed study has been conducted from four provinces of Pakistan. During this study, biodiversity, taxonomy, diagnosis, morphometric analysis, habitat, global distribution, and remarks of each species have been described. Total of 826 specimens were collected and sorted out into three species and three subspecies: C. (Chrotogonus) homalodemus homalodemus (Blanchard, 1836), C. (Chrotogonus) homalodemus (Blanchard, 1836), C. (Chrotogonus) trachypter
... Show MoreBP algorithm is the most widely used supervised training algorithms for multi-layered feedforward neural net works. However, BP takes long time to converge and quite sensitive to the initial weights of a network. In this paper, a modified cuckoo search algorithm is used to get the optimal set of initial weights that will be used by BP algorithm. And changing the value of BP learning rate to improve the error convergence. The performance of the proposed hybrid algorithm is compared with the stan dard BP using simple data sets. The simulation result show that the proposed algorithm has improved the BP training in terms of quick convergence of the solution depending on the slope of the error graph.
Geography of industry has been considered a branch of important economic geographical branches. This importance has been regarded as a reflection on the industrial sector contribution in economies of any state since they contribute into the total national product ; it also assimilates a huge number of labor hands . The industry of grains grinding has been considered as one of the main food industries having a main role in satisfying the need of the population from the foods. The industry is continued to use the food as daily meal . Here, it should predict the population in Baghdad and for every district until the end of 2025 and knowing either these grains grinders are able to meet and satisfy the needs of populations of flours, making s
... Show MoreThe aim of this research is to recognize the tasks undertaken by the headmasters of intermediate schools concerning time- administration, in accordance to the viewpoints of the headmasters of intermediate schools in the Administration of Education of Al-Karkh the Third. The sample of this research consists of (60) headmasters and &n
... Show MoreUsing the Internet, nothing is secure and as we are in need of means of protecting our data, the use of passwords has become important in the electronic world. To ensure that there is no hacking and to protect the database that contains important information such as the ID card and banking information, the proposed system stores the username after hashing it using the 256 hash algorithm and strong passwords are saved to repel attackers using one of two methods: -The first method is to add a random salt to the password using the CSPRNG algorithm, then hash it using hash 256 and store it on the website. -The second method is to use the PBKDF2 algorithm, which salts the passwords and extends them (deriving the password) before being ha
... Show MoreIn many scientific fields, Bayesian models are commonly used in recent research. This research presents a new Bayesian model for estimating parameters and forecasting using the Gibbs sampler algorithm. Posterior distributions are generated using the inverse gamma distribution and the multivariate normal distribution as prior distributions. The new method was used to investigate and summaries Bayesian statistics' posterior distribution. The theory and derivation of the posterior distribution are explained in detail in this paper. The proposed approach is applied to three simulation datasets of 100, 300, and 500 sample sizes. Also, the procedure was extended to the real dataset called the rock intensity dataset. The actual dataset is collecte
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