In this paper the experimentally obtained conditions for the fusion splicing with photonic crystal fibers (PCF) having large mode areas were reported. The physical mechanism of the splice loss and the microhole collapse property of photonic crystal fiber (PCF) were studied. By controlling the arc-power and the arc-time of a conventional electric arc fusion splicer (FSM-60S), the minimum loss of splicing for fusion two conventional single mode fibers (SMF-28) was (0.00dB), which has similar mode field diameter. For splicing PCF (LMA-10) with a conventional single mode fiber (SMF-28), the loss was increased due to the mode field mismatch.

     One technique used to prepare nanoparticles material is Pulsed Laser Ablation in Liquid (PLAL), Silver Oxide nanoparticles (AgO) were prepared by using  this technique, where silver target was submerged in ultra-pure water (UPW)  at room temperature after that Nd:Yag laser which characteristics by 1064 nm wavelength, Q-switched, and 6ns pulse duration was used to irradiated silver target. This preparation method was used to study the effects of laser irradiation on Nanoparticles synthesized by used varying laser pulse energy 1000 mJ, 500 mJ, and 100 mJ, with 500 pulses each time on the particle size. Nanoparticles are characterized using XRD, SEM, AFM, and UV-Visible spectroscopy. All the structural peaks determined by the XRD

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

       The effects of the permeation cement grout with fly ash on the sandy soil skeleton were studied in the present work in two phase; first phase the shear strength parameters, and the second phase effect of these grouted materials on volume grouted zone by injection (51) cm³ of slurry in sandy soil placed in steel cylinder model with dimension 15 cm in diameter and 30 cm in height. The soil sample was obtained from Karbala city and it is classified as poorly graded sand (SP) according to USCS. The soil samples were improved by cement grout with three percentages weight of water cement ratio (w:c); (0.1w:0.9c, 0.8w:0.2c, and 0.7w:0.3c), while the soil samples were dehydrated for one day

In this paper we estimate the coefficients and scale parameter in linear regression model depending on the residuals are of type 1 of extreme  value distribution for the largest values . This can be regard as an improvement for the studies with the smallest values . We study two estimation methods ( OLS  & MLE ) where we resort to Newton – Raphson (NR) and Fisher Scoring methods to get MLE estimate because the difficulty of using the usual approach with MLE . The relative efficiency criterion is considered beside to the statistical inference procedures for the extreme value regression model of type 1 for largest values . Confidence interval , hypothesis testing for both scale parameter and regression coefficients

A method was developed that offers a rapid, simple and accurate technique for the determination of chlorophenols at trace levels in aqueous samples with very limited volumes of organic solvents. These compounds were acetylated, then preliminarily extracted with n-hexane. The enriched chlorophenols were directly analyzed using gas chromatography with an electron-capture detector. The detection limits were in the range of 0.001–0.005 mg/L, except for 2-chlorophenol, which was always above 0.013 mg/L. Relative standard deviation for the spiked water samples ranged from 2.2 to 6.1%, while relative recoveries were in the range of 67.1 to 101.3%.

Poverty phenomenon is very substantial topic that determines the future of societies and governments and the way that they deals with education, health and economy. Sometimes poverty takes multidimensional trends through education and health. The research aims at studying multidimensional poverty in Iraq by using panelized regression methods, to analyze Big Data sets from demographical surveys collected by the Central Statistical Organization in Iraq. We choose classical penalized regression method represented by The Ridge Regression, Moreover; we choose another penalized method which is the Smooth Integration of Counting and Absolute Deviation (SICA) to analyze Big Data sets related to the different poverty forms in Iraq. Euclidian Distanc

Biogas is one of the most important sources of renewable energy and is considered as an environment friendly energy source. The major goal of this research is to see if rice husk (Rh) waste and pomegranate peels (PP) waste are suitable for anaerobic digestion and what effect NaOH pre-treatment has on biogas generation. Rice husk and pomegranate peels were tested in anaerobic digestion under patch anaerobic conditions as separate wastes as well as blended together in equal proportions. The cumulative biogas output for the blank test (no pretreatment) was 1923 and 2526 ml, respectively using a single rice husk (Rh) and pomegranate peel (PP) substrates. The 50% rice husk digestion and 50% of pomegranate peels for blank test gave the result 224

Nonlinear time series analysis is one of the most complex problems ; especially the nonlinear autoregressive with exogenous variable (NARX) .Then ; the problem of model identification and the correct orders determination considered the most important problem in the analysis of time series . In this paper , we proposed splines  estimation method for model identification , then we used three criterions for the correct orders determination. Where ; proposed method used to estimate the additive splines for model identification , And the rank determination depends on the additive property  to avoid the problem of curse dimensionally . The proposed method is one of the nonparametric methods , and the simulation results give a