Abstract

 In this work, pure Polypyrrole (PPy) and Polypyrrole (PPy)/Graphene (GN) was synthesized by in-situ polymerization in different weight percentages (0.1, 0.3, 0.5, 1, 3 and 5 wt.% (g)) of GN nano particles using chemical oxidation method at room temperature. The FTIR, SEM and electrical properties were studies for the nano composites. The result show that when concentration of GN Nano particle increase, the electrical conductivity increased and the graphene sheets were merging to form a continuous area of the GN through the polypyrrole base material. The FTIR spectra shows that the characteristics absorption peaks of polypyrrole that is, 1546.80, 1463.87 and 3400.27 cm^-1(stretching vibration in the pyrrol

The transition structure is considered as the most important hydraulic structure controlling the w/s transtion, morever it decrease the scouring of outlet structure.

seven experiment samples for transition structure was used in this research at different angles ( 10° - 90° ).

       It was shown that froud number has a clear effect on the depth of the scouring, morever the high discharge rates cause an increase of the ratio between the length of the scour and its depth.

       In order to select the best flaring angle it was shown that the angle of 40° has the most discharge rate, least structure length and least angle scour depth, with the firmly of t

Codes of red, green, and blue data (RGB) extracted from a lab-fabricated colorimeter device were used to build a proposed classifier with the objective of classifying colors of objects based on defined categories of fundamental colors. Primary, secondary, and tertiary colors namely red, green, orange, yellow, pink, purple, blue, brown, grey, white, and black, were employed in machine learning (ML) by applying an artificial neural network (ANN) algorithm using Python. The classifier, which was based on the ANN algorithm, required a definition of the mentioned eleven colors in the form of RGB codes in order to acquire the capability of classification. The software's capacity to forecast the color of the code that belongs to an ob

Codes of red, green, and blue data (RGB) extracted from a lab-fabricated colorimeter device were used to build a proposed classifier with the objective of classifying colors of objects based on defined categories of fundamental colors. Primary, secondary, and tertiary colors namely red, green, orange, yellow, pink, purple, blue, brown, grey, white, and black, were employed in machine learning (ML) by applying an artificial neural network (ANN) algorithm using Python. The classifier, which was based on the ANN algorithm, required a definition of the mentioned eleven colors in the form of RGB codes in order to acquire the capability of classification. The software's capacity to forecast the color of the code that belongs to an object under de

is divided into two chapter:Chapter one to ensure asyslematic framework for research amd included aresearch problem and also inchuded on the importance of research and the need for him as well as to clarify. The second chapter inchuded a theoretical framework: theoretical framework has been divided into two section. The first topic: poetics transformations The second topic: poetics and scale of rheloric in the film After the comp of the theoretical framework; so the researcher analyzed the film (Antichrist) has arrived ataset of resuits was including

In this study abundance and composition of zooplanktons in the Indus River Estuary was conducted to examine habitat characteristics and its impact on tiny organisms. Overall 30,656 individuals were identified and segregated into seven major groups including Copepods, Cnidarians, Decapods, Mollusk, Pisces, Amphipods and Chaetognaths. For better understanding they were further divided into eighteen planktonic categories. Among them Lucifer spp. comprises of 52.21% was the most abundant group with a peak appeared in March whereas Chaetognaths were rarely observed in the entire study period. Species diversity exhibited a mixed trend with the highest values (0.776) of dominance observed in spring (March). The results of Canonical Corresponden

In this research, hand lay- up technique is used to prepare samples from epoxy resin reinforced with multi- walled carbon nanotubes in different weight fractions (0, 2, 3, 4, 5) wt%. The immersion effect by sodium hydroxide solution (NaOH) at normality (0.3N) for a period of (15 days) on the thermal conductivity of nanocomposites was studied, and compared to natural condition (before immersion). The thermal conductivity of epoxy nanocomposites specimens were carried out using Lee’s disk method. The experimental results showed that thermal conductivity increased with increase weight fraction before and after immersion for all specimens, while the immersion effect leads to decrease thermal conductive values compared to thermal conductivi

Starting from 4, - Dimercaptobiphenyl, a variety of phenolic Schiff bases (methylolic, etheric, epoxy) derivatives have been synthesized. All proposed structure were supported by FTIR, 1H-NMR, 13C-NMR Elemental analysis all analysis were performed in center of consultation in Jordan Universty.