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ijp-152
Effect of low level nozzle height on properties of copper oxide absorption layer prepared by fully computerized spray pyrolysis depositions
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The effect of approaching nozzle jet from the deposition surface
on structural, optical and morphology properties of copper oxide thin
films was studied. The film was prepared by homemade fully
computerized CNC spray pyrolysis deposition technique at
preparations speed (3, 4, 5, and 6 mm/sec). The repeated line mode
was used at deposition temperature equal 450 °C whereas the
spraying time was in the range of (15-30 min) according to the
deposition speed. The film exhibit polycrystalline structure with
preferred orientation along (-111), (022) and (011), (002) at a 2θ
value of (35.63o) and (38.8o) respectively. Optical band gaps were
recorded at these speed shows variance in value from (1.53-2.08 eV).
Films thickness were found to be in the range (128-412 nm) which
depends on preparation speed.

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Publication Date
Mon Sep 23 2019
Journal Name
Baghdad Science Journal
A Semi-Supervised Machine Learning Approach Using K-Means Algorithm to Prevent Burst Header Packet Flooding Attack in Optical Burst Switching Network
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Optical burst switching (OBS) network is a new generation optical communication technology. In an OBS network, an edge node first sends a control packet, called burst header packet (BHP) which reserves the necessary resources for the upcoming data burst (DB). Once the reservation is complete, the DB starts travelling to its destination through the reserved path. A notable attack on OBS network is BHP flooding attack where an edge node sends BHPs to reserve resources, but never actually sends the associated DB. As a result the reserved resources are wasted and when this happen in sufficiently large scale, a denial of service (DoS) may take place. In this study, we propose a semi-supervised machine learning approach using k-means algorithm

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