The present study was carried out in the nursery at Al – Dora (Baghdad). During spring 2015 under green hous conditions. The aim was to evaluate the effect of different concentration (0, 1.25 and 2.5) g./l of aqueous Ajwa date fruit extract on different cutting position (basal, sub terminal and terminal) for different dipping times (24, 48) hours, on cassia stem cuttings. After 2 months of planting the results showed that the 2.5 gm. /l of Ajwa date extract with basal cuttings for 48 dipping times accelerated the time of rooting to 3.7 weeks compared to 8 weeks in control treatment. This treatment increased rooting percentage to 77.7% compared to 0% in control treatment. It gave the highest value of both rooting numbers 2.2 per cutting and rooting lengths 2.89 cm. The results indicated that 2.5 gm./l of Ajwa date extract with sub terminal cuttings for 48 hours dipping times gave the highest results in leaves, leaflet numbers and leaflet area 2.88, 4.0 and 1.70 cm respectively. The analysis of ajwa date quantity showed the present of 50.38 and 48.82 μmole/g of catalase peroxidase enzymes respectively with the absence of IAA, GA3 and Zeatin hormones.
Using the Neural network as a type of associative memory will be introduced in this paper through the problem of mobile position estimation where mobile estimate its location depending on the signal strength reach to it from several around base stations where the neural network can be implemented inside the mobile. Traditional methods of time of arrival (TOA) and received signal strength (RSS) are used and compared with two analytical methods, optimal positioning method and average positioning method. The data that are used for training are ideal since they can be obtained based on geometry of CDMA cell topology. The test of the two methods TOA and RSS take many cases through a nonlinear path that MS can move through that region. The result
... Show MoreUsing the Neural network as a type of associative memory will be introduced in this paper through the problem of mobile position estimation where mobile estimate its location depending on the signal strength reach to it from several around base stations where the neural network can be implemented inside the mobile. Traditional methods of time of arrival (TOA) and received signal strength (RSS) are used and compared with two analytical methods, optimal positioning method and average positioning method. The data that are used for training are ideal since they can be obtained based on geometry of CDMA cell topology. The test of the two methods TOA and RSS take many cases through a nonlinear path that MS can move through tha
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