Improving" Jackknife Instrumental Variable Estimation method" using A class of immun algorithm with practical application
The current research aims at knowing the impact of the mind-clearing method in teaching second year intermediate students “reading book”. To achieve the study objective, the researchers intentionally chose Arjwan middle school, located in Baghdad Directorate of Education Al-Rusafa/2, which includes five classes for the second intermediate class. Division (A) was chosen randomly to represent the experimental group, which is taught in the mind-clearing method, while Division (B) represented the control group, which is taught in the traditional way. The sample of the research included (79) female students divided into (39) students in the experimental group, and (40) female students in the control group.To achieve the objective of the res
... Show MorePolycystic ovary syndrome(PCOS) is a heterogeneous disorder of uncertain etiology , it is the most common endocrinopathy in women and most common cause of anovulatery infertility ,characterized by chronic anovulation and hyperandrogenemia .The present study was designed to investigate the effect of silymarin which is known to have antioxidant and insulin sensitivity effects on the levels of glucose, insulin ,testosterone ,leutinizing hormone(LH) and progesterone .Ovulation rate and Homeostasis Model Assessment of insulin Resistance (HOMA) ratio were determined .A 3-months of treatment were conducted in 60 PCOS patients in three well-matched groups .The first one (n=20),received silymarin(750mg/day) .The second group received
... Show MoreThis study relates to the estimation of a simultaneous equations system for the Tobit model where the dependent variables ( ) are limited, and this will affect the method to choose the good estimator. So, we will use new estimations methods different from the classical methods, which if used in such a case, will produce biased and inconsistent estimators which is (Nelson-Olson) method and Two- Stage limited dependent variables(2SLDV) method to get of estimators that hold characteristics the good estimator .
That is , parameters will be estim
... Show MoreIn this research, a variable stiffness actuator is proposed to enhance the damping of the mechanical vibrating system. The frequency response analysis of the vibrating system is dependant in order to analyze and synthesis this semi-active damping, where the suggested process is using active filter to estimate the present frequency of the vibration system, and this will limit the value of the stiffness of the vibrated system. Two active filter s are needed, low-pass-filter (LPF) to choose the higher stiffness of the actuator at small frequencies as well as more damping and high-pass-filter (HPF) to choose the lower stiffness of the actuator at high frequencies as well as more damping, and so
... Show MoreThis paper deals with the mathematical method for extracting the Exponential Rayleighh distribution based on mixed between the cumulative distribution function of Exponential distribution and the cumulative distribution function of Rayleigh distribution using an application (maximum), as well as derived different statistical properties for distribution, and present a structure of a new distribution based on a modified weighted version of Azzalini’s (1985) named Modified Weighted Exponential Rayleigh distribution such that this new distribution is generalization of the distribution and provide some special models of the distribution, as well as derived different statistical properties for distribution
In the lifetime process in some systems, most data cannot belong to one single population. In fact, it can represent several subpopulations. In such a case, the known distribution cannot be used to model data. Instead, a mixture of distribution is used to modulate the data and classify them into several subgroups. The mixture of Rayleigh distribution is best to be used with the lifetime process. This paper aims to infer model parameters by the expectation-maximization (EM) algorithm through the maximum likelihood function. The technique is applied to simulated data by following several scenarios. The accuracy of estimation has been examined by the average mean square error (AMSE) and the average classification success rate (ACSR). T
... Show MorePractical application is an effective tool for preparing qualified scientific and technical cadres if applied correctly and efficiently. In addition to being the complementary part of everything that has been studied in the years of study, it is a scientific linking tool between theory and application. Here lies the importance of this research in clarifying the central and important role that practical application plays in general in raising the scientific level of the student, and the extent of the suitability of the curriculum and means of practical application and the extent and needs of the students applying at the Institute of Administration - Rusafa - Department of Information Technology and Libraries. This research attempted to answe
... Show MoreIn this paper, we investigate the basic characteristics of "magnetron sputtering plasma" using the target V2O5. The "magnetron sputtering plasma" is produced using "radio frequency (RF)" power supply and Argon gas. The intensity of the light emission from atoms and radicals in the plasma measured by using "optical emission spectrophotometer", and the appeared peaks in all patterns match the standard lines from NIST database and employed are to estimate the plasma parameters, of computes electron temperature and the electrons density. The characteristics of V2O5 sputtering plasma at multiple discharge provisos are studied at the "radio frequency" (RF) power ranging from 75 - 150 Wat
... Show MoreSupport 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
... Show MoreIn this research, the semiparametric Bayesian method is compared with the classical method to estimate reliability function of three systems : k-out of-n system, series system, and parallel system. Each system consists of three components, the first one represents the composite parametric in which failure times distributed as exponential, whereas the second and the third components are nonparametric ones in which reliability estimations depend on Kernel method using two methods to estimate bandwidth parameter h method and Kaplan-Meier method. To indicate a better method for system reliability function estimation, it has be
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