Iraq suffers from lack of water resources supply because the headwaters of the rivers located outside its borders and the influence of upstream countries on the quantities of flowing water, in addition to the increase of pressure on available water as a result of population increase and not adopting the principle of rationalization where misuse and wastage and lack of strategic vision to treat and manage water use in accordance with the economic implications fall.  This is reflected fallout on water security and subsequently on national and food security, while the issue of using water resources is development top priority in different countries in the world because of the importance of water effect on the security of indivi

The current research aims to identify: 1) the challenges facing blended education from the point of view of teachers of students with disabilities. 2) The challenges facing blended education from the point of view of teachers of students with disabilities according to the gender variable (males-females). 3) The challenges facing blended education from the point of view of teachers of students with disabilities, according to the academic qualifications of graduates

(institute-bachelors-masters). 4) The challenges facing blended education from the point of view of male and female teachers, according to the functional service period with students with disabilities (less than 8 years - from 9 to 15 years - 16 years and above). 5) the

In Iraq, because of the dramatic turnovers facing the country for three decades, pharmacists continue to experience significant professional challenges in both the public and private sectors. The present study aimed to explore the professional challenges and obstacles facing Iraqi pharmacists working in public hospitals. This qualitative study included face-to-face semi-structured interviews with open-ended questions with hospital pharmacists. The participants were selected purposefully (with ≥ 3 years of experience) to work at governmental hospitals in Karbala province between December 2022 and April 2023. The audio-recording interviews were scripted. Thematic analyses were used to generate themes and subthemes from the interview

A survey and revised checklist of the species belonging to the family of Compositae for the specimens which are collected and deposited previously at the herbarium of the Iraq Natural History Research Center and Museum, in addition to the current specimens collected for the period 2016-2021. A total of 85 species belonging to 49 genera and 16 tribes are revised with their synonyms, locality, and distributions, flowering and fruiting period.

The idea of ​​carrying out research on incomplete data came from the circumstances of our dear country and the horrors of war, which resulted in the missing of many important data and in all aspects of economic, natural, health, scientific life, etc.,. The reasons for the missing are different, including what is outside the will of the concerned or be the will of the concerned, which is planned for that because of the cost or risk or because of the lack of possibilities for inspection. The missing data in this study were processed using Principal Component  Analysis and self-organizing map methods using simulation. The variables of child health and variables affecting children's health were taken into account: breastfeed

    Identification of complex communities in biological networks is a critical and ongoing challenge since lots of network-related problems correspond to the subgraph isomorphism problem known in the literature as NP-hard. Several optimization algorithms have been dedicated and applied to solve this problem. The main challenge regarding the application of optimization algorithms, specifically to handle large-scale complex networks, is their relatively long execution time. Thus, this paper proposes a parallel extension of the PSO algorithm to detect communities in complex biological networks. The main contribution of this study is summarized in three- fold; Firstly, a modified PSO algorithm with a local search operator is proposed

The aim of this paper is to approximate multidimensional functions by using the type of Feedforward neural networks (FFNNs) which is called Greedy radial basis function neural networks (GRBFNNs). Also, we introduce a modification to the greedy algorithm which is used to train the greedy radial basis function neural networks. An error bound are introduced in Sobolev space. Finally, a comparison was made between the three algorithms (modified greedy algorithm, Backpropagation algorithm and the result is published in [16]).

The shear strength of soil is one of the most important soil properties that should be identified before any foundation design. The presence of gypseous soil exacerbates foundation problems. In this research, an approach to forecasting shear strength parameters of gypseous soils based on basic soil properties was created using Artificial Neural Networks. Two models were built to forecast the cohesion and the angle of internal friction. Nine basic soil properties were used as inputs to both models for they were considered to have the most significant impact on soil shear strength, namely: depth, gypsum content, passing sieve no.200, liquid limit, plastic limit, plasticity index, water content, dry unit weight, and initial