The Present Work includes the study of the population dynamics of Armadillidium vulgare in AL- Jadiriya region in Baghdad. Monthly samples were collected using a quadrat 0.0625 m2 from November 2007 to November 2008.. The population density of A.vulgare, ranged from 880 ind/m2 in May to251 ind/m2 in January respectively. This species showed high aggregation dispersion in the study area. The sex ratio showed that the number of females were more than that of males and significantly differd (P < 0.05) during the reproductive months. Furthermore, it was found that the juveniles of species were present at most time of the year, But the large sized groups have been observed during summer and spring. And showed a positive linear correlations betwe

The research involved attempt to inhibit the corrosion of Al-Si-Cu alloy in 2.5x10-3 mol.dm-3 NaOH solution (pH=11.4) by addition of six different inhibitors with three concentrations (1x10-3, 1x10-2, and 0.1 mol.dm-3). These inhibitors include three organic materials (sodium acetate, sodium benzoate, and sodium oxalate) and three inorganic materials (sodium chromate, disodium phosphate, and sodium sulphate). The data that concerning polarization behaviour are calculates which include the corrosion potential (Ecorr) and current density (icorr), cathodic and anodic Tafel slopes (bc & ba), and polarization resistance (Rp). Protection efficiency (P%) and activation energy (Ea) values were calculated for inhibition by the six inhibitors. The

The research study focused on the need to clarify the relationship between the Websites of Iraqi Newspapers and their roles in covering the internal crises in Iraq. The selection of Iraqi websites for the newspapers Al-Zaman and Al-Sabah was adopted as one of the most important media with a wide audience; and as a model of hot news and continuous coverage of those sites since 2003 so far. As a result, this necessitated the emergence of new types of methods of editing and writing news stories related to Iraq.

Consequently, the enormous and rapidly changing amount of Iraq news, the process of preparing and creating news has become a complex industry

The research aims to reveal the methods of visual intertextuality used in the websites of the oriented satellite channel which is Arabic-speaking when addressing normalization with Israel. It also indicates the sources and types of intertextual images, the methodological and semiotic mechanisms for analyzing the intertextuality of news images used on the website of Alhurra satellite channel for the period from 1/6 - 30/8/2022, which included (94) images. The researcher analyzed (37) images with intertextual dimensions, excluding (57) images, which did not carry connotations connected with the inputs and objectives of the research.

The research reach

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

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

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