Chitosan (CH) / Poly (1-vinylpyrrolidone-co-vinyl acetate) (PVP-co-VAc) blend (1:1) and nanocomposites reinforced with CaCO3 nanoparticles were prepared by solution casting method. FTIR analysis, tensile strength, Elongation, Young modulus, Thermal conductivity, water absorption and Antibacterial properties were studied for blend and nanocomposites. The tensile results show that the tensile strength and Young’s modulus of the nanocomposites were enhanced compared with polymer blend [CH/(PVP-co-VAc)] film. The mechanical properties of the polymer blend were improved by the addition of CaCO3 with significant increases in Young’s modulus (from 1787 MPa to ~7238 MPa) and tensile strength (from 47.87 MPa to 79.75 MPa). Strong interfacial

This research basically gives an introduction about the multiple intelligence
theory and its implication into the classroom. It presents a unit plan based upon the
MI theory followed by a report which explains the application of the plan by the
researcher on the first class student of computer department in college of sciences/
University of Al-Mustansiryia and the teacher's and the students' reaction to it.
The research starts with a short introduction about the MI theory is a great
theory that could help students to learn better in a relaxed learning situation. It is
presented by Howard Gardener first when he published his book "Frames of
Minds" in 1983 in which he describes how the brain has multiple intelligen

In the present work, silver nanoparticles were prepared. Nonlinear optical properties and
optical limiting of silver nanoparticles were investigated.Standard chemical synthesis method was used at
diffrent weight ratio(0.038, 0.058 and 0.078) of silver nitrate. Several testing were done to obtain the
characteristics of the sample. Z-Scan experiments were performed using 30 ns Q-switched Nd:YAG
laser at 1064 nm and 532 nm at different intensities. The results showed that the nonlinear refractive
index is directly proportional to the input intensities, which caused by the self-focusing of the material.
In addition, the optical limiting behavior has been studied. The results showed that the sample could be
used as an opt

The migration from IPv4 to IPv6 can not be achieved in a brief period, thus both protocols co-exist at certain years. IETF Next Generation Transition Working Group (NGtrans) developed IPv4/IPv6 transition mechanisms. Since Iraq infrastructure, including universities, companies and institutions still use IPv4 protocol only. This research article tries to highlight, discuss a required transition roadmap and extend the local knowledge and practice on IPv6. Also, it introduces a prototype model using Packet tracer (network simulator) deployed for the design and implementation of IPv6 migration. Finally, it compares and evaluates the performance of IPv6, IPv4 and dual stack using OPNET based on QoS metrics such as throughput, delay and point to

A novel Schiff base ligand (DBC) synthesized from 4-chlorobenzoic acid, along with its Cu (II) and Co (II) complexes, was prepared and characterized using FT-IR, 1H and 13C-NMR, UV-Vis spectroscopy, as well as magnetic and conductivity measurements. Based on this, a tetrahedral structure of [M(DBC)Cl2] was proposed for the complexes. Antioxidant activity of the compounds was assessed and compared to ascorbic acid, revealing that the copper complex exhibited superior antioxidant properties compared to the cobalt complex and the ligand. Furthermore, the antibiofilm potential of the copper and cobalt complexes was assessed against five clinically relevant bacterial species (P.aeruginosa, E.coli, K.pneumoniae, S.aureus and S.typhi) usin

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class