This work aim to prepare Ag/R6G/PMMA nanocomposite thin
films by In-situ plasma polymerization and study the changes in the
optical properties of fluorophore due to the presence of Ag
nanoparticles structures in the vicinity of the R6G laser dye. The
concentrations of R6G dye/MMA used are: 10-4M solutions were
prepared by dissolving the required quantity of the R6G dye in
MMAMonomer. Then Silver nanoparticles with 50 average particles
size were mixed with MMAmonomer with concentration of 0.3, 0.5,
0.7wt% to get R6G silver/MMA in liquid phase. The films were
deposited on glass substrates by dielectric barrier discharge plasma
jet. The Ag/R6G/PMMA nanocomposite thin films were
characterization by UV-Visible

Administrative procedures in various organizations produce numerous crucial records and data. These
records and data are also used in other processes like customer relationship management and accounting
operations.It is incredibly challenging to use and extract valuable and meaningful information from these data
and records because they are frequently enormous and continuously growing in size and complexity.Data
mining is the act of sorting through large data sets to find patterns and relationships that might aid in the data
analysis process of resolving business issues. Using data mining techniques, enterprises can forecast future
trends and make better business decisions.The Apriori algorithm has bee

The current research aims to prepare a proposed Programmebased sensory integration theory for remediating some developmental learning disabilities among children, researchers prepared a Programme based on sensory integration through reviewing studies related to the research topic that can be practicedby some active teaching strategies (cooperative learning, peer learning, Role-playing, and educational stories). The Finalformat consists of(39) training sessions.

This study was conducted in the plant protection department/ College of Agriculture/ University of Baghdad to evaluate the efficiency of physical agents ozone, ultraviolet radiation, microwave for destroying afla produced in corn seeds. An isolate af A.flavus producing Aflatoxin B1 was obtained from plant protection dept. college of Agric. University of Baghdad. Results showed destroy toxin AFLA B1 the effect of radiation microwave in the media of Japex degree 80 and 100 c^o 57.14% and 85.71%, respectively, and for 20 sec, compared to the treatment comparison 0.00% as found significant differences were apparent between transactions and the treatment of comparison, as and notes the existence of a significant dif

Incremental Sheet Metal Forming (ISMF) is a modern sheet metal forming technology which offers the possibility of manufacturing 3D complex parts of thin sheet metals using the CNC milling machine. The surface quality is a very important aspect in any manufacturing process. Therefore, this study focuses on the resultant residual stresses by forming parameters, namely; (tool shape, step over, feed rate, and slope angle) using Taguchi method for the products formed by single point incremental forming process (SPIF). For evaluating the surface quality, practical experiments to produce pyramid like shape have been implemented on aluminum sheets (AA1050) for thickness (0.9) mm. Three types of tool shape used in this work, the spherical tool ga

: The Aluminium (Al) material emerged as a plasmonic material in the wavelength ranges from the ultraviolet to the visible bands in different on-chip plasmonic applications. In this paper, we demonstrate the effect of using Al on the electromagnetic (EM) field distribution of a compact hybrid plasmonic waveguide (HPW) acting as a polarization rotator. We compare the performance of Al with other familiar metals that are widely used as plasmonic materials, which are Silver (Ag) and Gold (Au). Furthermore, we study the effect of reducing the geometrical dimensions of the used materials on the EM field distributions inside the HPW and, consequently, on the efficiency of the polarization rotation. We perform the study based o

     Deep learning (DL) plays a significant role in several tasks, especially classification and prediction. Classification tasks can be efficiently achieved via convolutional neural networks (CNN) with a huge dataset, while recurrent neural networks (RNN) can perform prediction tasks due to their ability to remember time series data. In this paper, three models have been proposed to certify the evaluation track for classification and prediction tasks associated with four datasets (two for each task). These models are CNN and RNN, which include two models (Long Short Term Memory (LSTM)) and GRU (Gated Recurrent Unit). Each model is employed to work consequently over the two mentioned tasks to draw a road map of deep learning mod