This paper deals with defining Burr-XII, and how to obtain its p.d.f., and CDF, since this distribution is one of failure distribution which is compound distribution from two failure models which are Gamma model and weibull model. Some equipment may have many important parts and the probability distributions representing which may be of different types, so found that Burr by its different compound formulas is the best model to be studied, and estimated its parameter to compute the mean time to failure rate. Here Burr-XII rather than other models is consider  because it is used to model a wide variety of phenomena including crop prices, household income, option market price distributions, risk and travel time. It has two shape-parame

With the rapid development of smart devices, people's lives have become easier, especially for visually disabled or special-needs people. The new achievements in the fields of machine learning and deep learning let people identify and recognise the surrounding environment. In this study, the efficiency and high performance of deep learning architecture are used to build an image classification system in both indoor and outdoor environments. The proposed methodology starts with collecting two datasets (indoor and outdoor) from different separate datasets. In the second step, the collected dataset is split into training, validation, and test sets. The pre-trained GoogleNet and MobileNet-V2 models are trained using the indoor and outdoor se

The aim of this paper is to measure the characteristics properties of 3 m radio telescope that installed inside Baghdad University campus. The measurements of this study cover some of the fundamental parameters at 1.42 GHz. These parameters concentrated principally on, the system noise temperature, signal to noise ratio and sensitivity, half power beam width, aperture efficiency, and effective area. These parameters are estimated via different radio sources observation like Cas-A, full moon, sky background, and solar drift scan observations. From the results of these observations, these parameters are found to be approximately 64 K, 1.2, 0.9 Jansky, 3.7°, 0.54, and 3.8 m2 respectively. The parameters values have vital affect to quantitativ

In recent years, the world witnessed a rapid growth in attacks on the internet which resulted in deficiencies in networks performances. The growth was in both quantity and versatility of the attacks. To cope with this, new detection techniques are required especially the ones that use Artificial Intelligence techniques such as machine learning based intrusion detection and prevention systems. Many machine learning models are used to deal with intrusion detection and each has its own pros and cons and this is where this paper falls in, performance analysis of different Machine Learning Models for Intrusion Detection Systems based on supervised machine learning algorithms. Using Python Scikit-Learn library KNN, Support Ve

A new data for Fusion power density has been obtained for T-3He and T-T fusion reactions, power density is a substantial term in the researches related to the fusion energy generation and ignition calculations of magnetic confined systems. In the current work, thermal nuclear reactivities, power densities of a fusion reactors and the ignition condition inquiry are achieved by using a new and accurate formula of cross section, the maximum values of fusion power density for T-3He and TT reaction are 1.1×107 W/m3 at T=700 KeV and 4.7×106 W/m3 at T=500 KeV respectively, While Zeff suggested to be 1.44 for the two reactions. Bremsstrahlung radiation has also been determined to reaching self- sustaining reactors, Bremsstrahlung values are 4.5×

Because of cost-effective production and abundant resources of calcium, Ca-ion batteries (CIBs) are an appropriate option to alternate Li-ion batteries (LIBs). A new category of anode materials for CIBs has emerged since the successful synthesis of carbon nanotubes, which are B and N doped derivatives of it. For high-performance CIBs, BC2N nanotube (BC2NNT) has been studied as promising anode materials. In order to comprehend electrochemical attributes, cycling stability, and adsorption behavior of BC2NNT, first-principles computations have been executed. Based on nuclear magnetic resonance computations, two types of hexagonal rings (B2C2N2 (I) and BC4N (II)) were specified that are non-aromatic. Ca has adsorption on B2C2N2 and BC4N with ad

Biodiesel as an attractive energy source; a low-cost and green synthesis technique was utilized for biodiesel preparation via waste cooking oil methanolysis using waste snail shell derived catalyst. The present work aimed to investigate the production of biodiesel fuel from waste materials. The catalyst was greenly synthesized from waste snail shells throughout a calcination process at different calcination time of 2–4 h and temperature of 750–950 ◦C. The catalyst samples were characterized using X-Ray Diffraction (XRD), Brunauer-Emmett-Teller (BET), Energy Dispersive X-ray (EDX), and Fourier Transform Infrared (FT-IR). The reaction variables varying in the range of 10:1–30:1 M ratio of MeOH: oil, 3–11 wt% catalyst loading, 50–

Classifying an overlapping object is one of the main challenges faced by researchers who work in object detection and recognition. Most of the available algorithms that have been developed are only able to classify or recognize objects which are either individually separated from each other or a single object in a scene(s), but not overlapping kitchen utensil objects. In this project, Faster R-CNN and YOLOv5 algorithms were proposed to detect and classify an overlapping object in a kitchen area.  The YOLOv5 and Faster R-CNN were applied to overlapping objects where the filter or kernel that are expected to be able to separate the overlapping object in the dedicated layer of applying models. A kitchen utensil benchmark image database and