Survival analysis is widely applied in data describing for the life time of item until the occurrence of an event of interest such as death or another event of understudy . The purpose of this paper is to use the dynamic approach in the deep learning neural network method, where in this method a dynamic neural network that suits the nature of discrete survival data and time varying effect. This neural network is based on the Levenberg-Marquardt (L-M) algorithm in training, and the method is called Proposed Dynamic Artificial Neural Network (PDANN). Then a comparison was made with another method that depends entirely on the Bayes methodology is called Maximum A Posterior (MAP) method. This method was carried out using numerical algorithms re

Milling process is a common machining operation that is used in the manufacturing of complex surfaces. Machining-induced residual stresses (RS) have a great impact on the performance of machined components and the surface quality in face milling operations with parameter cutting. The properties of engineering material as well as structural components, specifically fatigue life, deformation, impact resistance, corrosion resistance, and brittle fracture, can all be significantly influenced by residual stresses. Accordingly, controlling the distribution of residual stresses is indeed important to protect the piece and avoid failure. Most of the previous works inspected the material properties, tool parameters, or cutting parameters, bu

Sewage water is a mixture of water and solids added to water for various uses, so it needs to be treated to meet local or global standards for environmentally friendly waste production. The present study aimed to analyze the new Maaymyrh sewage treatment plant's quality parameters statistically at Hilla city. The plant is designed to serve 500,000 populations, and it is operating on a biological treatment method (Activated Sludge Process) with an average wastewater inflow of 107,000m³/day. Wastewater data were collected daily by the Mayoralty of Hilla from November 2019 to June 2020 from the influent and effluent in the (STP) new in Maaymyrh for five water quality standards, such as (BOD5), (COD), (TSS), (TP)

This study aims to find the effect of water-cement ratio on the compressive strength of concrete by using ultrasonic pulse velocity test (UPVT). Over 230 standard cube specimens were used in this study, with dimensions of 150mm, and concrete cubes were cured in water at 20 °C. Also, the specimens used in the study were made of concrete with varied water-cement ratio contents from 0.48 to 0.59. The specimens were taken from Diyarbakir-Turkey concrete centers and tested at the structure and material science lab, civil engineering, faculty of engineering from Dicle University.  The UPV measurement and compressive strength tests were carried out at the concrete age of 28 days. Their UPV and compressive strength ranged

The foreguts of a total of 515 fish of Chondrostoma regium (Heckel, 1843) (locally: Bala’aot Malloky) were studied. These fish were collected from Tigris River at Salah Al-Deen Province (between Al-Hagag & Yathrib) for 20 months between March and October of the next year. Detritus, plant in origin materials (19.6%, 23.0% & 24.9%); green and blue green algae, mostly Cladophora, Cosmarium and Merismpedia sp. (17.1%, 12.9% & 12.2%) and diatoms, mostly Diatoma, Chanathes, Amphora and Cyulbella sp. (16.9%, 8.8% & 8.2%) were the main food categories taken by these fishes according to occurrence (O%), volumetric methods (V%) and ranking index (R%). Debris (not part of the diet) took 45.3% of the studied fish foreguts by volume. Detritus was also

With the continuous progress of image retrieval technology, the speed of searching for the required image from a large amount of image data has become an important issue. Convolutional neural networks (CNNs) have been used in image retrieval. However, many image retrieval systems based on CNNs have poor ability to express image features. Content-based Image Retrieval (CBIR) is a method of finding desired images from image databases. However, CBIR suffers from lower accuracy in retrieving images from large-scale image databases. In this paper, the proposed system is an improvement of the convolutional neural network for greater accuracy and a machine learning tool that can be used for automatic image retrieval. It includes two phases

Effluent from incompetent wastewater treatment plants (WWTPs) contains a great variety of pollutants so support water treatments are essential. The present work studies the removal of phosphate species from aqueous solutions by adsorption on to spherical Calcined Sand -Clay mixture (CSCM) used a natural, local and low-cost adsorbent. Batch experiments were performed to estimate removal efficiency of phosphate. The adsorption experiments were carried out as function of pH, dose of adsorbent, initial concentration, temperature and time of adsorption. The efficient removal was accomplished for pH between 10 and 12. The experimental results also showed that the removal of phosphate by (CSCM) was rapid (the % removal 98.9%, 92%, 90%, 89% in 6

Examining and comparing the image quality of degenerative cervical spine diseases through the application of three MRI sequences; the Two-Dimension T2 Weighed Turbo Spin Echo (2D T2W TSE), the Three-Dimension T2 Weighted Turbo Spin Echo (3D T2W TSE), and the T2 Turbo Field Echo (T2_TFE). Thirty-three patients who were diagnosed as having degenerative cervical spine diseases were involved in this study. Their age range was 40-60 years old. The images were produced via a 1.5 Tesla MRI device using (2D T2W TSE, 3D T2W TSE, and T2_TFE) sequences in the sagittal plane. The image quality was examined by objective and subjective assessments. The MRI image characteristics of the cervical spines (C4-C5, C5-C6, C6-C7) showed significant difference