Deep learning (DL) plays a significant role in several tasks, especially classification and prediction. Classification tasks can be efficiently achieved via convolutional neural networks (CNN) with a huge dataset, while recurrent neural networks (RNN) can perform prediction tasks due to their ability to remember time series data. In this paper, three models have been proposed to certify the evaluation track for classification and prediction tasks associated with four datasets (two for each task). These models are CNN and RNN, which include two models (Long Short Term Memory (LSTM)) and GRU (Gated Recurrent Unit). Each model is employed to work consequently over the two mentioned tasks to draw a road map of deep learning mod

       Diesel generators are used in various locations throughout Baghdad city, central Iraq, when the public electricity  power is in outage. The main purpose of the current research is to investigate possible changes in certain biochemical parameters in the blood of operators of diesel generators in different locations Baghdad city, at both Rusafa and Karkh sides. The workers were divided according to the number of working years.

       Serum urea, creatinine, alkaline phosphatase (AlP), aspartate aminotransferase (AST), alanine aminotransferase (ALT), albumin, total serum bilirubin (TSB), and glomerular filtration rate (GFR) were analyzed in samples from forty wo

Abstract :H.pylori is an important cause of gastric duodenal disease, including gastric ulcers, Mucosa-associated lymphoid tissue (MALT), and gastric carcinoma. biosensors are becoming the most extensively studied discipline because the easy, rapid, low-cost, highly sensitive, and highly selective biosensors contribute to advances in next-generation medicines such as individualized medicine and ultrasensitive point-of-care detection of markers for diseases.  Five of ten patients diagnosed with H.pylori ranging in age from 15–85 participated in this research. who [gastritis, duodenitis, duodenal ulcer (DU), and peptic ulcer (PU)] Suspected H.pylori colonies w

In this paper, some estimators of the unknown shape parameter and reliability function  of Basic Gompertz distribution (BGD) have been obtained, such as MLE, UMVUE, and MINMSE, in addition to estimating Bayesian estimators under Scale invariant squared error loss function assuming informative prior represented by Gamma distribution and non-informative prior by using Jefferys prior. Using Monte Carlo simulation method, these estimators of the shape parameter and R(t), have been compared based on mean squared errors and integrated mean squared, respectively

The present work aims to study the removal of dyes from wastewater by reverse osmosis process. Two dyes were used direct blue 6, and direct yellow. Experiments were performed with feed concentration (75 – 450 ppm), operation temperature (30 – 50 oC) and time (0.2 – 2.0 hr). The membrane used is thin film composite membrane (TFC). It was found that modal permeate concentration decreases with increasing feed concentration and time operating, while permeate concentration increases with increasing feed temperature. Also it was found that product rate increase with increasing temperature, but it decrease with increasing feed concentration and time. The concentration of reject solution showed an increase with increasing feed concentratio

     Bone metastases are the main reason for death in males suffering from advanced prostate cancer. This study aimed to create zoledronic acid and graphene oxide conjugation for anticancer therapy. The process of conjugation was confirmed by several characterization methods including UV-VIS spectrophotometry, Fourier Transform Infrared Spectroscopy (FTIR), and atomic force microscope (AFM). the cytotoxicity of 400, 600, and 800 μg/ml to each GO, ZOL, and ZOL-GO was evaluated on a human hepatic cell line (WRL 68) and human prostate cancer cell line (PC3) using an MTT assay. The antitumor mechanisms of ZOL-GO were examined by cell cycle analysis. The results demonstrated That ZOL-GO caused a reduction in the cell viability of WRL 68

In this paper, Bayes estimators of Poisson distribution have been derived by using two loss functions: the squared error loss function and the proposed exponential loss function in this study, based on different priors classified as the two different informative prior distributions represented by erlang and inverse levy prior distributions and non-informative prior for the shape parameter of Poisson distribution. The maximum likelihood estimator (MLE) of the Poisson distribution has also been derived. A simulation study has been fulfilled to compare the accuracy of the Bayes estimates with the corresponding maximum likelihood estimate (MLE) of the Poisson distribution based on the root mean squared error (RMSE) for different cases of the