The present study aims at identifying the styles, procedures of Iraqi universities to avoid plagiarism and evaluate these steps, also to evaluate the form prepared by the Directory of Scientific Supervision and Evaluation, Ministry of Higher Education and Scientific Research. The study uses documentary style, 150 teachers in the following colleges (Education Ibn Rushd, Languages and Arts) in university of Baghdad whom already used the aforementioned list were the sample of the study and they asked to give their opinions about the list.The study consists of five sections, first one deals with general view, second explains plagiarism and its types, shapes and reasons,third tackles with ways of detecting plagiarism, its programs, consequences and avoidance, while the fourth one deals with plagiarismin Arabic and international institutes, the last one represents results, recommendations and suggestion. The main results are: 1- There is no available database of theses and dissertations for all Iraqi Universities. 2- One list for all majors humanities and scientific is an obstacle due to the huge differences between two majors in the methodology and using the references.
For modeling a photovoltaic module, it is necessary to calculate the basic parameters which control the current-voltage characteristic curves, that is not provided by the manufacturer. Generally, for mono crystalline silicon module, the shunt resistance is generally high, and it is neglected in this model. In this study, three methods are presented for four parameters model. Explicit simplified method based on an analytical solution, slope method based on manufacturer data, and iterative method based on a numerical resolution. The results obtained for these methods were compared with experimental measured data. The iterative method was more accurate than the other two methods but more complexity. The average deviation of
... Show MoreThis manuscript presents several applications for solving special kinds of ordinary and partial differential equations using iteration methods such as Adomian decomposition method (ADM), Variation iterative method (VIM) and Taylor series method. These methods can be applied as well as to solve nonperturbed problems and 3rd order parabolic PDEs with variable coefficient. Moreover, we compare the results using ADM, VIM and Taylor series method. These methods are a commination of the two initial conditions.
In this paper we suggest new method to estimate the missing data in bivariate normal distribution and compare it with Single Imputation method (Unconditional mean and Conditional mean) by using simulation.
In 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
... Show Moreلقد إزدادت التطورات العلمية والتكنولوجية ولاسيما المعلوماتية زيادة في العلوم والحقائق والنظريات والإكتشافات بصورة مذهلة، وكذلك زيادة فروع في العلم والمعرفة ففي كل يوم نشهد قيام فروع أو تخصص معرفي جديد، إضافة إلى تفجر المعرفة التي ساهمت في بناء قنوات الفروع والتخصصات العلمية القديمة والجديدة (عبد الغفور 2001 ص8).
فالثورة في مجال العلم والمعرفة والمعلومات والإتصا
... Show MoreA mixture model is used to model data that come from more than one component. In recent years, it became an effective tool in drawing inferences about the complex data that we might come across in real life. Moreover, it can represent a tremendous confirmatory tool in classification observations based on similarities amongst them. In this paper, several mixture regression-based methods were conducted under the assumption that the data come from a finite number of components. A comparison of these methods has been made according to their results in estimating component parameters. Also, observation membership has been inferred and assessed for these methods. The results showed that the flexible mixture model outperformed the
... Show MoreA mixture model is used to model data that come from more than one component. In recent years, it became an effective tool in drawing inferences about the complex data that we might come across in real life. Moreover, it can represent a tremendous confirmatory tool in classification observations based on similarities amongst them. In this paper, several mixture regression-based methods were conducted under the assumption that the data come from a finite number of components. A comparison of these methods has been made according to their results in estimating component parameters. Also, observation membership has been inferred and assessed for these methods. The results showed that the flexible mixture model outperformed the others
... Show MoreBackground: Hyperfunction of the muscles of the upper lip is considered as the most common cause of excessive gingival display (EGD). The aim of this study was to demonstrate the effectiveness of botulinum toxin (BT) injection as a conservative treatment for EGD due to muscular hyperfunction and to compare the outcome of 2 injection methods. Material and methods: This study included 40 participants who were randomly assigned into 2 groups of 20 each, The first group received 2.5IU BT injection at 1 point per side (2-points group), while the second group received a total of 5 IU of BT at 2 points per side (4-points group). The outcome variables were the reduction in the central and lateral gingival display expressed as the difference between
... Show MoreMethods of estimating statistical distribution have attracted many researchers when it comes to fitting a specific distribution to data. However, when the data belong to more than one component, a popular distribution cannot be fitted to such data. To tackle this issue, mixture models are fitted by choosing the correct number of components that represent the data. This can be obvious in lifetime processes that are involved in a wide range of engineering applications as well as biological systems. In this paper, we introduce an application of estimating a finite mixture of Inverse Rayleigh distribution by the use of the Bayesian framework when considering the model as Markov chain Monte Carlo (MCMC). We employed the Gibbs sampler and
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