Abstract

    In order to enhance the efficiency of flat plate solar water collectors without changing in its original shape and with low additional cost, twisted strips are inserted inside its riser pipes. Three flat plate collectors are used for test. Family of twisted strips are inserted inside each collector risers with different twisted ratios (T_R=3,4,5). The collectors are connected in parallel mode (Z-Configuration) and are exposed to the same conditions (solar radiation and ambient temperature) .The experimental results show that, the highest heat transfer rate occurs at twisted ratio (3) .Consequently, for the same twisted ratio the daily efficiencies for the solar collector at d

Finger vein recognition and user identification is a relatively recent biometric recognition technology with a broad variety of applications, and biometric authentication is extensively employed in the information age. As one of the most essential authentication technologies available today, finger vein recognition captures our attention owing to its high level of security, dependability, and track record of performance. Embedded convolutional neural networks are based on the early or intermediate fusing of input. In early fusion, pictures are categorized according to their location in the input space. In this study, we employ a highly optimized network and late fusion rather than early fusion to create a Fusion convolutional neural network

           In this research, radon concentrations in some types of healthy drinking water samples available in Iraq's market were measured using a technique called Durridge RAD-7-H₂O with closed loop. Then the rate of annual effective dose in human taken this water is determined.

          It was found that, radon concentrations in studied samples ranged between 1.2 Bq.m^-3 to 142 Bq.m^-3. The results of the radon concentrations and the rate of annual effective dose for drinking water samples were significantly lower than the USEPA and WHO recommended limits that equal 500 Bq/m³ and 1 mSv/y resp

The physical sports sector in Iraq suffers from the problem of achieving sports achievements in individual and team games in various Asian and international competitions, for many reasons, including the lack of exploitation of modern, accurate and flexible technologies and means, especially in the field of information technology, especially the technology of artificial neural networks. The main goal of this study is to build an intelligent mathematical model to predict sport achievement in pole vaulting for men, the methodology of the research included the use of five variables as inputs to the neural network, which are Avarage of Speed (m/sec in Before distance 05 meters latest and Distance 05 meters latest, The maximum speed achieved in t

Subsurface soil water retention (SWRT) is a recent technology for increasing the crop yield, water use efficiency and then the water productivity with less amount of applied water. The goal of this research was to evaluate the existing of SWRT with the influence of surface and subsurface trickle irrigation on economic water productivity of cucumber crop. Field study was carried out at the Hawr Rajab district of Baghdad governorate from October 1st, to December 31st, 2017. Three experimental treatments were used, treatment plot T1 using SWRT with subsurface trickle irrigation, plot T2 using SWRT with surface trickle irrigation, while plot T3 without using SWRT and using surface tickle irrigation system. The obtained results showed that the e

Software Defined Networking (SDN) with centralized control provides a global view and achieves efficient network resources management. However, using centralized controllers has several limitations related to scalability and performance, especially with the exponential growth of 5G communication. This paper proposes a novel traffic scheduling algorithm to avoid congestion in the control plane. The Packet-In messages received from different 5G devices are classified into two classes: critical and non-critical 5G communication by adopting Dual-Spike Neural Networks (DSNN) classifier and implementing it on a Virtualized Network Function (VNF). Dual spikes identify each class to increase the reliability of the classification