Future generations of wireless communications systems are expected to evolve toward allowing massive ubiquitous connectivity and achieving ultra-reliable and low-latency communications (URLLC) with extremely high data rates. Massive multiple-input multiple-output (m-MIMO) is a crucial transmission technique to fulfill the demands of high data rates in the upcoming wireless systems. However, obtaining a downlink (DL) training sequence (TS) that is feasible for fast channel estimation, i.e., meeting the low-latency communications required by future generations of wireless systems, in m-MIMO with frequency-division-duplex (FDD) when users have different channel correlations is very challenging. Therefore, a low-complexity solution for

ABSTRACT

This research included the preparation and characterization of new demulsifies from natural and synthetic polymers of chitosan and polyvinyl alcohol that are environmentally friendly and at the same time have high efficacy comparable to emulsifiers. imported foreign. The prepared compounds were examined using infrared spectroscopy and nuclear magnetic resonance spectroscopy, and all the spectral signals of the polymers were in good agreement with the chemical composition of the polymers. And the melting and decomposition that occur on polymers at high temperatures. The effect of the length and type of side chain in the compositions of polymers on the process of water separation of oil emulsions w

Background: Pain and the usage of local anesthetic agents are still real problem in pediatric dentistry, for these reasons, the use of minimal invasive dentistry (MID) in regard to the patient comfort is important especially for children, anxious and uncooperative patients. Chemomechanical caries removal (CMCR) methods involve the selective removal of the carious dentine hence it avoided the painful removal of the sound dentine and the anxiety resulted due to the vibration of the hand piece which is also decreased thus it appears to be more acceptable and comfortable to the patient. Aims of this study: This study was conducted among group of children to assess and compare the anxiety rating scale (during and after treatment) between the

The geometric morphometric technique was used to study the variables in the shape and size wings of different populations of mosquitoes Culex quinquefasciatus from different Iraqi provinces Babylon, Baghdad and Wasit. The results showed that the average of centroid size were 366, 387.5 and 407.4 Micron in Babylon, Baghdad and Kut, respectively. The statistical analysis showed that there were no significant differences in the average of centroid size of all specimens and they belong to the same species.

The efficiency evaluation of the railway lines performance is done through a set of indicators and criteria, the most important are transport density, the productivity of enrollee, passenger vehicle production, the productivity of freight wagon, and the productivity of locomotives. This study includes an attempt to calculate the most important of these indicators which transport density index from productivity during the four indicators, using artificial neural network technology. Two neural networks software are used in this study, (Simulnet) and (Neuframe), the results of second program has been adopted. Training results and test to the neural network data used in the study, which are obtained from the international in

This research aims to solve the problem of selection using clustering algorithm, in this research optimal portfolio is formation using the single index model, and the real data are consisting from the stocks Iraqi Stock Exchange in the period 1/1/2007 to 31/12/2019. because the data series have missing values ,we used the two-stage missing value compensation method, the knowledge gap was inability the portfolio models to reduce The estimation error , inaccuracy of the cut-off rate and the Treynor ratio combine stocks into the portfolio that caused to decline in their performance, all these problems required employing clustering technic to data mining and regrouping it within clusters with similar characteristics to outperform the portfolio