The monitoring of lotic ecosystems is important for environmental health after war crisis. This study aimed to detect the fate of the sixteen polycyclic aromatic hydrocarbon compounds (PAHs) as priority pollutants in the water and sediment of Al-Hussainya River in Karbala Province. The results indicated that the concentrations in water samples ranged from 0.24–58.72 ηg.L^-1 for each of the benzo(a) pyrene and benzo(g, h, i)perylene. The concentrations in sediment samples have been observed to be in a range of 0.36–119.06 μg.g^-1 for naphthalene and benzo(g,h,i)perylene. Benzo(g,h,i)perylene recorded the highest concentrations in each of water and sediment samples as compared with the other compound

Hepatitis B is an inflammation of the liver that caused by Hepatitis B virus (HBV) which is DNA virus that infects the human and some kinds of animals such as chimpanzees and birds. This disease considered as the major disease of mankind and a serious global public health problem. HBsAg, HBeAg, HBcAb, HBeAb and HBsAb are markers used to detect the presence and the stage of infection. The current study included (181) individuals from both sexes, (137) males and (44) females. By ratio 3.11: 1.The mean age of patients 2.4033 ± 0.83519 (range 18-73) years as follows < 20 (11.6%), 21–40 (47.5%), 41–60 (29.8%) and > 60 (11.0%) . These patients are 73 (40.4%) Blood donors from Central Blood Bank, 88 (48.6%) Chronic kidney failure at Ibn –

Dumping policy considered as one of the policies occurs severe damages to the developing countries apparently this is happens due to the potential weakness in (productive, technical, legislative, legal institutions) comparing with other developed countries who are members in WTO.

Iraq consider as one of the developing countries that has been effected by the dumping policy, the events in Iraq since downfall of the formal regime, and the allied forces domination of Iraq have all together accelerated in the apace of deterioration , particularly , after the temporary coalition authority  has forced Iraq to adopt a free foreign trade policy& exclusion of the state from the market mechanism & to consolidate import and deac

Detection of early clinical keratoconus (KCN) is a challenging task, even for expert clinicians. In this study, we propose a deep learning (DL) model to address this challenge. We first used Xception and InceptionResNetV2 DL architectures to extract features from three different corneal maps collected from 1371 eyes examined in an eye clinic in Egypt. We then fused features using Xception and InceptionResNetV2 to detect subclinical forms of KCN more accurately and robustly. We obtained an area under the receiver operating characteristic curves (AUC) of 0.99 and an accuracy range of 97–100% to distinguish normal eyes from eyes with subclinical and established KCN. We further validated the model based on an independent dataset with

Deep learning convolution neural network has been widely used to recognize or classify voice. Various techniques have been used together with convolution neural network to prepare voice data before the training process in developing the classification model. However, not all model can produce good classification accuracy as there are many types of voice or speech. Classification of Arabic alphabet pronunciation is a one of the types of voice and accurate pronunciation is required in the learning of the Qur’an reading. Thus, the technique to process the pronunciation and training of the processed data requires specific approach. To overcome this issue, a method based on padding and deep learning convolution neural network is proposed to

In this article, Convolution Neural Network (CNN) is used to detect damage and no damage images form satellite imagery using different classifiers. These classifiers are well-known models that are used with CNN to detect and classify images using a specific dataset. The dataset used belongs to the Huston hurricane that caused several damages in the nearby areas. In addition, a transfer learning property is used to store the knowledge (weights) and reuse it in the next task. Moreover, each applied classifier is used to detect the images from the dataset after it is split into training, testing and validation. Keras library is used to apply the CNN algorithm with each selected classifier to detect the images. Furthermore, the performa

Whenever, the Internet of Things (IoT) applications and devices increased, the capability of the its access frequently stressed. That can lead a significant bottleneck problem for network performance in different layers of an end point to end point (P2P) communication route. So, an appropriate characteristic (i.e., classification) of the time changing traffic prediction has been used to solve this issue. Nevertheless, stills remain at great an open defy. Due to of the most of the presenting solutions depend on machine learning (ML) methods, that though give high calculation cost, where they are not taking into account the fine-accurately flow classification of the IoT devices is needed. Therefore, this paper presents a new model bas