This paper aims to decide the best parameter estimation methods for the parameters of the Gumbel type-I distribution under the type-II censorship scheme. For this purpose, classical and Bayesian parameter estimation procedures are considered. The maximum likelihood estimators are used for the classical parameter estimation procedure. The asymptotic distributions of these estimators are also derived. It is not possible to obtain explicit solutions of Bayesian estimators. Therefore, Markov Chain Monte Carlo, and Lindley techniques are taken into account to estimate the unknown parameters. In Bayesian analysis, it is very important to determine an appropriate combination of a prior distribution and a loss function. Therefore, two different prior distributions are used. Also, the Bayesian estimators concerning the parameters of interest under various loss functions are investigated. The Gibbs sampling algorithm is used to construct the Bayesian credible intervals. Then, the efficiencies of the maximum likelihood estimators are compared with Bayesian estimators via an extensive Monte Carlo simulation study. It has been shown that the Bayesian estimators are considerably more efficient than the maximum likelihood estimators. Finally, a real-life example is also presented for application purposes.
Support vector machines (SVMs) are supervised learning models that analyze data for classification or regression. For classification, SVM is widely used by selecting an optimal hyperplane that separates two classes. SVM has very good accuracy and extremally robust comparing with some other classification methods such as logistics linear regression, random forest, k-nearest neighbor and naïve model. However, working with large datasets can cause many problems such as time-consuming and inefficient results. In this paper, the SVM has been modified by using a stochastic Gradient descent process. The modified method, stochastic gradient descent SVM (SGD-SVM), checked by using two simulation datasets. Since the classification of different ca
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Green biosynthesized selenium nanoparticles from
المقدمة قديماً، قبل القرن التاسع عشر، كان التفكير في الضوء على أنه سيل من الجسيمات التي إما تصدر من العين، أو من الجسم الذي ننظر إليه. قاد فكرة أن الضوء عبارة عن جسيمات تنطلق من الأجسام التي نراها العالم إسحاق نيوتن(Isak Newton)، واستخدم هذه الفكرة لتفسير ظاهرتي الانعكاس والانكسار. بقي القبول لدى العلماء لفرض نيوتن سيد الموقف حتى عام 1678م. حيث اقترح الفيزيائي والفلكي الهولندي هوغنز (Huygens) أن الضوء عبارة عن نوع من الأم
... Show MoreTo evaluate the Interaction of Mn(II), Fe(II), Co(II), Ni(II),Cu(II), Zn(II) And Cd(II) Mixed- Ligand Complexes of cephalexin mono hydrate (antibiotics) And Furan-2-Carboxylic Acid To The Different DNA Sources. All the metal complexes were observed to cleave the DNA. A difference in the bands of complexes .The cleavage efficiency of the complexes compared with that of the control is due to their efficient DNA-binding ability and the other factors like solubility and bond length between the metal and ligand may also increase the DNA-binding ability. The ligands (Cephalexin mono hydrate (antibiotics) and Furan-2- Carboxylic acid and there newly synthesized metal complexes shows good antimicrobial activities and Binding DNA , thus, can be used
... Show MoreWe have investigated twenty five patients with type-2 diabetes mellitus aged (35-60) years and fifteen healthy persons as control group to detect Anti-Helicobacter pylori IgG antibody. All studied groups were carried out to measure fasting blood sugar, anti- Glutamic acid decarboxylase (GAD), anti-? islets cells antibody by IFAT, Anti-H. pylori IgG antibody by ELISA technique. There was significant elevation in the concentration of fasting blood sugar than in control group (P < 0.05), the patients had negative results for anti-GAD antibody and anti- ? islets cells antibody, there were significant differences (P < 0.05) of anti-H. pylori IgG antibody in 28 % of patients had type-2 diabetes than control group. This lead to suggestion that typ
... Show MoreIn the latest years there has been a profound evolution in computer science and technology, which incorporated several fields. Under this evolution, Content Base Image Retrieval (CBIR) is among the image processing field. There are several image retrieval methods that can easily extract feature as a result of the image retrieval methods’ progresses. To the researchers, finding resourceful image retrieval devices has therefore become an extensive area of concern. Image retrieval technique refers to a system used to search and retrieve images from digital images’ huge database. In this paper, the author focuses on recommendation of a fresh method for retrieving image. For multi presentation of image in Convolutional Neural Network (CNN),
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