The Log-Logistic distribution is one of the important statistical distributions as it can be applied in many fields and biological experiments and other experiments, and its importance comes from the importance of determining the survival function of those experiments. The research will be summarized in making a comparison between the method of maximum likelihood and the method of least squares and the method of weighted least squares to estimate the parameters and survival function of the log-logistic distribution using the comparison criteria MSE, MAPE, IMSE, and this research was applied to real data for breast cancer patients. The results showed that the method of Maximum likelihood best in the case of estimating the paramete

The basis of the personality of each individual lies in the early years of his or her life. If the personality of the child has been well organized and if the motives have been fully expressed and effectively directed, the child will have a strong will, happy self-confidence and a strong personality. If there is a failure In the early years, the individual will be unable to meet his responsibilities in life and may be the victim of many psychological disorders. The family is a learning process through which children acquire the customs, traditions, attitudes and values ​​prevailing in their social environment. (Pre-and-after) play and its relationship to parenting methods of (democratic-bullying-overprotection- and neglect), which wi

This study discussed a biased estimator of the Negative Binomial Regression model known as (Liu Estimator), This estimate was used to reduce variance and overcome the problem Multicollinearity between explanatory variables, Some estimates were used such as Ridge Regression and Maximum Likelihood Estimators, This research aims at the theoretical comparisons between the new estimator (Liu Estimator) and the estimators

Reservoir quality assessment is important for detecting hydrocarbon-bearing zones and guiding future enhancement strategies. This study presents a detailed petrophysical evaluation of the Mishrif Formation in the Buzurgan Oilfield, which was selected due to its strategic value through its significant remaining reserves which making it an ideal candidate for advanced evaluation techniques. This study aims for shale content, porosity, permeability, water saturation, net to gross, and lithology determination. Well log and core data were used together to establish accurate property estimations. Permeability prediction through conventional methods, like core permeability-porosity correlations, was highly dispersive due to the heterogenei

The growth of developments in machine learning, the image processing methods along with availability of the medical imaging data are taking a big increase in the utilization of machine learning strategies in the medical area. The utilization of neural networks, mainly, in recent days, the convolutional neural networks (CNN), have powerful descriptors for computer added diagnosis systems. Even so, there are several issues when work with medical images in which many of medical images possess a low-quality noise-to-signal (NSR) ratio compared to scenes obtained with a digital camera, that generally qualified a confusingly low spatial resolution and tends to make the contrast between different tissues of body are very low and it difficult to co

Abstract

 Metal cutting processes still represent the largest class of manufacturing operations. Turning is the most commonly employed material removal process. This research focuses on analysis of the thermal field of the oblique machining process. Finite element method (FEM) software DEFORM 3D V10.2 was used together with experimental work carried out using infrared image equipment, which include both hardware and software simulations. The thermal experiments are conducted with AA6063-T6, using different tool obliquity, cutting speeds and feed rates. The results show that the temperature relatively decreased when tool obliquity increases at different cutting speeds and feed rates, also it

The deep learning algorithm has recently achieved a lot of success, especially in the field of computer vision. This research aims to describe the classification method applied to the dataset of multiple types of images (Synthetic Aperture Radar (SAR) images and non-SAR images). In such a classification, transfer learning was used followed by fine-tuning methods. Besides, pre-trained architectures were used on the known image database ImageNet. The model VGG16 was indeed used as a feature extractor and a new classifier was trained based on extracted features.The input data mainly focused on the dataset consist of five classes including the SAR images class (houses) and the non-SAR images classes (Cats, Dogs, Horses, and Humans). The Conv