Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

In this study, nano TiO₂ was prepared with titanium isopropoxide (TTIP) as a resource to titanium oxide. The catalyst was synthesized using phosphotungstic acid (PTA) and, stearyl trimethyl ammonium bromide (STAB) was used as the structure-directing material. Characterization of the product was done by the X-ray diffraction (XRD), X-ray fluorescent spectroscopy (XRF), nitrogen adsorption/desorption measurements, Atomic Force Microscope (AFM) and Fourier transform infrared (FTIR) spectra, were used to characterize the calcined TiO₂ nanoparticles by STAB and PWA. The TiO₂ nanomaterials were prepared in three crystalline forms (amorphous, anatase, anatase-rutile). The results showed that the

Human health was and still the most important problem and objective of all most researches. Finding out what causes in the decadence of healthiness of Iraqi population is our tendency in the present work, Uranium causing cancer that is affected by a correlation between age and gender of bladder cancer patients is studied in the present work. Mean of Uranium concentration (Uc) decreased with increasing age for all age group without dependency on gender. While, there is a wide dispersion in Mean Uc excretion between males and females, due to the effect of correlated gender with age, where female Mean Uc is maximum at age 50-69 year (2.355 µg/L), and it's higher than male Mean Uc (2.022 µg/L) in this age stage because of menopause, a

The main objective of this paper is to study the behavior of Non-Prismatic Reinforced Concrete (NPRC) beams with and without rectangular openings either when exposed to fire or not. The experimental program involves casting and testing 9 NPRC beams divided into 3 main groups. These groups were categorized according to heating temperature (ambient temperature, 400°C, and 700°C), with each group containing 3 NPRC beams (solid beams and beams with 6 and 8 trapezoidal openings). For beams with similar geometry, increasing the burning temperature results in their deterioration as reflected in their increasing mid-span deflection throughout the fire exposure period and their residual deflection after cooling. Meanwhile, the existing ope

Rheumatoid arthritis is a chronic, progressive, inflammatory autoimmune disease of unidentified etiology, associated with articular, extra-articular and systemic manifestation that require long-standing treatment. Taking patient’s beliefs about the prescribed medication in consideration had been shown to be an essential factor that affects adherence of the patient in whom having positive beliefs is an essential for better adherence. The purpose of the current study was to measure beliefs about medicines among a sample of Iraqi patients with Rheumatoid arthritis and to determine possible association between this belief and some patient-certain factors. This study is a cross-sectional study carried out on 250 already diagnosed rheumatoid

   A comparison of double informative and non- informative priors assumed for the parameter of Rayleigh distribution is considered. Three different sets of double priors are included, for a single unknown parameter of Rayleigh distribution. We have assumed three double priors: the square root inverted gamma (SRIG) - the natural conjugate family of priors distribution, the square root inverted gamma – the non-informative distribution, and the natural conjugate family of priors - the non-informative distribution as double priors .The data is generating form three cases from Rayleigh distribution for different samples sizes (small, medium, and large). And Bayes estimators for the parameter is derived under a squared erro

An Intelligent Internet of Things network based on an Artificial Intelligent System, can substantially control and reduce the congestion effects in the network. In this paper, an artificial intelligent system is proposed for eliminating the congestion effects in traffic load in an Intelligent Internet of Things network based on a deep learning Convolutional Recurrent Neural Network with a modified Element-wise Attention Gate. The invisible layer of the modified Element-wise Attention Gate structure has self-feedback to increase its long short-term memory. The artificial intelligent system is implemented for next step ahead traffic estimation and clustering the network. In the proposed architecture, each sensing node is adaptive and able to