Study of using dolomite as starting material resource to produce magnesium oxychloride cement

In this paper, the starting materials necessary for producing magnesium oxychioride cement (MOC) 'ere produced from dolomite ore using leaching-carhonation-evaporation-pyrohvdrolvsis processes. The influences of the molar ratio of MgO/MgCI2 (Ms) and H2OIMgCI2 (I I,) on the properties of the MOC (cured for 7 days) were determined using physi co-mechanical methods. SliM and XRI) analyses were conducted to determine the change of phase and microstructure of the selected 7-day MOC depending on the production conduction. 'l'he experimental results show that the best mix proportion of 7-day MOC was found to he M0001114 and its thermal conductivit, tiexural strength, and compressive strength values were found to be 1.202 W/mK, 4.22 MPa, and 87.7 MPa, respectively. The water resistance of the MOC was improved by a small amount of I 13P04 (4% of MgO by weight). Consequently, if MOC is produced from dolomite, high-purity synthetic aragonite and CO2 would be obtained as byproducts, which are strongly demanded. © 2017 Japan Concrete Institute.Çukurova ÜniversitesiThis work was supported by the Research Fund Project [grant number MMF2013D18, ID:606] of Çukurova University

An online expectation-maximisation algorithm for nonnegative matrix factorisation models

In this paper we formulate the nonnegative matrix factorisation (NMF) problem as a maximum likelihood estimation problem for hidden Markov models and propose online expectation-maximisation (EM) algorithms to estimate the NMF and the other unknown static parameters. We also propose a sequential Monte Carlo approximation of our online EM algorithm. We show the performance of the proposed method with two numerical examples. © 2012 IFAC

Comparison of Ensemble-Based Multiple Instance Learning Approaches

© 2019 IEEE.Multiple instance learning (MIL) is concerned with learning from training set of bags including multiple feature vectors. This paradigm has various algorithms as a solution for multiple instance problem. Recently, ensemble learning has become one of the most preferred machine learning technique because its high classification ability. The main goal of ensemble learning is combining multiple learning models and obtaining a decision from all outputs of these models. Considering this motivation, the study presented in this paper proposes an ensemble-based multiple instance learning approach which merges standard algorithms (MIWrapper and SimpleMI) with ensemble learning methods (Bagging and AdaBoost) to improve classification ability. The proposed approach includes ensemble of combination of MIWrapper and SimpleMI learners with Naive Bayes, Support Vector Machines (SVM), Neural Networks (Multilayer Perceptron (MLP)), and Decision Tree (C4.5) as base classifiers. In the experimental studies, the proposed ensemble-based approach was compared with individual MIWrapper and SimpleMI algorithms in terms of accuracy. The obtained results indicate that the ensemble-based approach shows higher classification ability than the conventional solutions

Rubella vaccination during the preconception period or in pregnancy and perinatal and fetal outcomes

PubMed ID: 23094531The rubella vaccine is contraindicated in pregnancy. Between July and August 2009, the Turkish Republic Ministry of Health implemented a vaccine program to eradicate rubella in women in the reproductive period. In this program, many pregnant women were also vaccinated inadvertently. In this study, 62 pregnant women applied to our clinic who were vaccinated either during pregnancy or within one month before the last menstrual period. Seventeen of them were followed until the end of the pregnancy by fetal echocardiography and detailed ultrasonography. Rubella immunoglobulin (Ig) M and IgG antibodies were studied in the cord blood obtained at birth. All fetuses were examined by a pediatrician, an ophthalmologist and a pediatric cardiologist. A hearing test was also performed on all neonates. No signs of congenital rubella syndrome could be found