Abstract

The aim of this paper is to model and optimize the fatigue life and hardness of medium carbon steel CK35 subjected to dynamic buckling. Different ranges of shot peening time (STP) and critical points of slenderness ratio which is between the long and intermediate columns, as input factors, were used to obtain their influences on the fatigue life and hardness, as main responses. Experimental measurements of shot peening time and buckling were taken and analyzed using (DESIGN EXPERT 8) experimental design software which was used for modeling and optimization purposes. Mathematical models of responses were obtained and analyzed by ANOVA variance to verify the adequacy of the models. The resul

ABSTRACT The isolation and characterization of (27) isolate of extreme halophilic bacteria was performed ninteen isolate belonged to the genus Halobacterium which included Hb.halobium. Hb. salinarium, Hb. volcanii. Growth curve and generation time in logarthmic phase was measured and found to be (12.8hr±0.32), (11.2hr±0.2), (9.8hr±0.87), respectivaly. Effect of various concentrations of NaCl, KCI, NH4Cl and MgSO4.7H2O was studied, NaCl was essential for the rod shape rapid growth Rat and pigmentation. Less than 1% concentration caused lysis of bacteria. Yeast extract was the best carbone source as compared with glucose and casamino acid.

Corncob is an agricultural biomass waste that was widely investigated as an adsorbent of contaminants after transforming it into activated carbon. In this research carbonization and chemical activation processes were achieved to synthesize corncob-activated carbon (CAC). Many pretreatment steps including crushing, grinding, and drying to obtain corncob powder were performed before the carbonization step. The carbonization of corncob powder has occurred in the absence of air at a temperature of 500 °C. The chemical activation was accomplished by using HCl as an acidic activation agent. Fourier transform infrared spectroscopy (FT-IR), scanning electron microscopy (SEM), X-ray diffraction (XRD), and Brunauer–Emmett–Teller (BET) facilitate

We have studied Bayesian method in this paper by using the modified exponential growth model, where this model is more using to represent the growth phenomena. We focus on three of prior functions (Informative, Natural Conjugate, and the function that depends on previous experiments) to use it in the Bayesian method. Where almost of observations for the growth phenomena are depended on one another, which in turn leads to a correlation between those observations, which calls to treat such this problem, called Autocorrelation, and to verified this has been used Bayesian method.

The goal of this study is to knowledge the effect of Autocorrelation on the estimation by using Bayesian method. F

Abstract

Personality is one of the most important elements that should be developed in university student. Thus, we have to develop the positive traits and neutralize the negative traits of students as well as we have to pay attention to the level of student achievement at the same time, the researcher designed a scale to measure the traits of study sample. The research come out with a number of recommendations and proposals, the most important of which Enhancing the positive characteristics of university students in order to reach them to the level of mature personality with mental health. Enhancing the positive role of the high level of achievement by motivating the stude

This paper interest to estimation the unknown parameters for generalized Rayleigh distribution model based on censored samples of singly type one . In this paper the probability density function for generalized Rayleigh is defined with its properties . The maximum likelihood estimator method is used to derive the point estimation for all unknown parameters based on iterative method , as Newton – Raphson method , then derive confidence interval estimation which based on Fisher information matrix . Finally , testing whether the current model ( GRD ) fits to a set of real data , then compute the survival function and hazard function for this real data.