Interest has largely centered on the use of plant fibers to reinforce plastics, because these fibers are abundant and cheap. Carrot fibers (Curran) have been extracted from carrot, left over from carrot juice manufacture. The fibers of two sizes fine (50<µm) and coarse (100-150 µm) have been mixed with epoxy in four levels of loading (10, 20, 30, 40 wt %) respectively. Impact test, shore d hardness test and three point bending test of epoxy and carrot fiber-epoxy composites samples have been determined. The impact strength values of samples prepared with fine and coarse fibers increased as compared with pure epoxy sample. Hardness values increased, and the Young’s modulus values decreased with fiber content of both sizes.

Vehicular Ad Hoc Networks (VANETs) are integral to Intelligent Transportation Systems (ITS), enabling real-time communication between vehicles and infrastructure to enhance traffic flow, road safety, and passenger experience. However, the open and dynamic nature of VANETs presents significant privacy and security challenges, including data eavesdropping, message manipulation, and unauthorized access. This study addresses these concerns by leveraging advancements in Fog Computing (FC), which offers lowlatency, distributed data processing near-end devices to enhance the resilience and security of VANET communications. The paper comprehensively analyzes the security frameworks for fog-enabled VANETs, introducing a novel taxonomy that c

The aim of this work is to study the influence of the type of fiber glass –mat on fatigue behavior of composite material which is manufactured from polyester and E-glass (woven roving, chopped strand mat (CSM)) as a laminate with a constant fiber volume fraction (VF) of 33%. The results showed that the laminates reinforced with E-glass (woven roving) [0/90, ±45.0/90] and [0/90, CSM, 0/90] have lower fatigue strength than the laminates reinforced with E-glass [0/90]₃,[CSM]₃ and [CSM, 0/90, CSM]  although they had different tensile strength; the best laminate was [0/90]₃ .

Some new heterocyclic compounds containing, cyclohexenone, indazole, isoxazoline, pyrmidine and pyrazoline ring system were prepared from chalcones (1a,b). The starting chalcones (1a,b) were obtained by a base catalyzed condensation of appropriately substituted benzaldehydes and 2-acetylbenzofuran. The reaction of the prepared chalcones with ethylacetoacetate/hydrazine hydrate, hydroxylamine hydrochloride, urea, thiourea, hydrazine hydrate, phenyl hydrazine or hydrazide derivatives gave the mentioned heterocycles. All synthesized compounds have been characterized by physical and spectral methods.

Objectives: To assess the coping strategies of parents of children with autism and the relationship of
different strategies with their educational level.
Methodology: A descriptive analytical study was carried out from Feb. 14th, 2013 through April, 10th
, 2013 in
several private rehabilitation centers of autism in Baghdad city. A non- probability (purposive) sample of 100
autistic children and 100 of their parents (father or mother) was assessed by a questionnaire which consisted of
two parts; the first part is concerned with the demographic characteristics of the child and demographic
characteristics of the parents; the second part consisted of 50 questions about coping strategies that were
distributed on 8 doma

In this work, a deep computational study has been conducted to assign several qualities for the graph ⁠. Furthermore, determine the amount of the dihedral subgroups in the Held simple group He through utilizing the attributes of gamma.

Wildfire risk has globally increased during the past few years due to several factors. An efficient and fast response to wildfires is extremely important to reduce the damaging effect on humans and wildlife. This work introduces a methodology for designing an efficient machine learning system to detect wildfires using satellite imagery. A convolutional neural network (CNN) model is optimized to reduce the required computational resources. Due to the limitations of images containing fire and seasonal variations, an image augmentation process is used to develop adequate training samples for the change in the forest’s visual features and the seasonal wind direction at the study area during the fire season. The selected CNN model (Mob