The present study is concern with the interaction between the naidid worms diversity and the species of aquatic plant within which the worms found . For this purpose, two species of aquatic plant were used, Ceratophyllum demersum and Eichhornia crassipes. 12 samples of aquatic plants were collected , as one sample monthly for a period from September 2012 to September 2013 from different site on Tigris river within Baghdad City. From C. demersum, 1428 individuals, were sorted during the study period, related to 17 species. 12 species of subfamily Naidinae which are Chaetogaster limnaei , C. diastrophus , Ophidonais serpentine , Dero ( Dero) digitata. , D.(D.) evelinae , Nais pseudobtosa , N.simplex, N.stolci , N.Paradalis , N.elingiu

The research aims to find out the impact of wages and benefits systems on the performance of employees, which included the research community on a sample of employees in the company, and the sample consisted of (50) employees and an employee, A questionnaire composed as prepared (23) paragraph, use the promised statistically methods in data collected by the questionnaire analysis. The research reached a number of results, the most prominent of which were: There is a correlation between wage systems, benefits and performance of employees, and the presence of the impact of the systems of wages and benefits to the performance of employees. The research was presented a set of recommendations including: increasing the effectiveness of

Massive multiple-input multiple-output (m-MIMO) is considered as an essential technique to meet the high data rate requirements of future sixth generation (6G) wireless communications networks. The vast majority of m-MIMO research has assumed that the channels are uncorrelated. However, this assumption seems highly idealistic. Therefore, this study investigates the m-MIMO performance when the channels are correlated and the base station employs different antenna array topologies, namely the uniform linear array (ULA) and uniform rectangular array (URA). In addition, this study develops analyses of the mean square error (MSE) and the regularized zero-forcing (RZF) precoder under imperfect channel state information (CSI) and a realist

<p>Vehicular ad-hoc networks (VANET) suffer from dynamic network environment and topological instability that caused by high mobility feature and varying vehicles density. Emerging 5G mobile technologies offer new opportunities to design improved VANET architecture for future intelligent transportation system. However, current software defined networking (SDN) based handover schemes face poor handover performance in VANET environment with notable issues in connection establishment and ongoing communication sessions. These poor connectivity and inflexibility challenges appear at high vehicles speed and high data rate services. Therefore, this paper proposes a flexible handover solution for VANET networks by integrating SDN and

In this work, a new development of predictive voltage-tracking control algorithm for Proton Exchange Membrane Fuel Cell (PEMFCs) model, using a neural network technique based on-line auto-tuning intelligent algorithm was proposed. The aim of proposed robust feedback nonlinear neural predictive voltage controller is to find precisely and quickly the optimal hydrogen partial pressure action to control the stack terminal voltage of the (PEMFC) model for N-step ahead prediction. The Chaotic Particle Swarm Optimization (CPSO) implemented as a stable and robust on-line auto-tune algorithm to find the optimal weights for the proposed predictive neural network controller to improve system performance in terms of fast-tracking de

This study aimed at identifying the extent to which the social worker used the techniques of group discussion in the professional practice with the groups of school activity in the schools of Tubas governorate in light of some variables (gender, years of experience, academic qualification). The analytical descriptive method was used due to its suitability for the objectives of the study.  A questionnaire was designed to collect data that included (30) items, distributed in three areas .The validity and reliability of the tool were verified and then distributed to the study sample.

The results of the study showed that the highest averages were in the discussion stage domain, where the pre-discussion stage was m

In this research, Artificial Neural Networks (ANNs) technique was applied in an attempt to predict the water levels and some of the water quality parameters at Tigris River in Wasit Government for five different sites. These predictions are useful in the planning, management, evaluation of the water resources in the area. Spatial data along a river system or area at different locations in a catchment area usually have missing measurements, hence an accurate prediction. model to fill these missing values is essential.
The selected sites for water quality data prediction were Sewera, Numania , Kut u/s, Kut d/s, Garaf observation sites. In these five sites models were built for prediction of the water level and water quality parameters.