The problem motivation of this work deals with how to control the network overhead and reduce the network latency that may cause many unwanted loops resulting from using standard routing. This work proposes three different wireless routing protocols which they are originally using some advantages for famous wireless ad-hoc routing protocols such as dynamic source routing (DSR), optimized link state routing (OLSR), destination sequenced distance vector (DSDV) and zone routing protocol (ZRP). The first proposed routing protocol is presented an enhanced destination sequenced distance vector (E-DSDV) routing protocol, while the second proposed routing protocol is designed based on using the advantages of DSDV and ZRP and we named it as

Iraq faces significant economic challenges, owing in part to its reliance on oil revenue and the country's overburdened public sector. The supremacy of State-Owned Enterprises (SOEs), obstructive rules, a lack of access to finance, a shortage of skilled labor, and inadequate infrastructure all impede private sector growth. This research relied mainly on information from global development organizations, most markedly the World Bank, as well as policy documents, and it discovered a scarcity of pertinent educational writings. The following are the key findings of this research: Recent economic growth has not resulted in poverty reduction; the stretched history of war and insecurity in Iraq has hampered progress and development; the private se

People’s ability to quickly convey their thoughts, or opinions, on various services or items has improved as Web 2.0 has evolved. This is to look at the public perceptions expressed in the reviews. Aspect-based sentiment analysis (ABSA) deemed to receive a set of texts (e.g., product reviews or online reviews) and identify the opinion-target (aspect) within each review. Contemporary aspect-based sentiment analysis systems, like the aspect categorization, rely predominantly on lexicon-based, or manually labelled seeds that is being incorporated into the topic models. And using either handcrafted rules or pre-labelled clues for performing implicit aspect detection. These constraints are restricted to a particular domain or language which is

Agent technology has a widespread usage in most of computerized systems. In this paper agent technology has been applied to monitor wear test for an aluminium silicon alloy which is used in automotive parts and gears of light loads. In addition to wear test monitoring، porosity effect on
wear resistance has been investigated. To get a controlled amount of porosity, the specimens have
been made by powder metallurgy process with various pressures (100, 200 and 600) MPa. The aim of
this investigation is a proactive step to avoid the failure occurrence by the porosity.
A dry wear tests have been achieved by subjecting three reciprocated loads (1000, 1500 and 2000)g
for three periods (10, 45 and 90)min. The weight difference a

Due to the development that occurs in the technologies of information system many techniques was introduced and played important role in the connection between machines and peoples through internet, also it used to control and monitor of machines, these technologies called cloud computing and Internet of Things. With the replacement of computing resources with manufacturing resources cloud computing named converted into cloud manufacturing.

In this research cloud computing was used in the field of manufacturing to automate the process of selecting G-Code that Computer Numerical Control machine work it, this process was applied by the using of this machine with Radio Frequency Identification and a AWS Cloud services and some of py

This study was carried out to prepare and characterize domperidone nanoparticles to enhance solubility and the release rate. Domperidone is practically insoluble in water and has low and an erratic bioavailability range from 13%-17%. The domperidone nanoparticles were prepared by solvent/antisolvent precipitation method at different polymer:drug ratios of 1:1 and 2:1 using different polymers and grades of poly vinyl pyrolidone, hydroxy propyl methyl cellulose and sodium carboxymethyl cellulose as stabilizers. The effect of polymer type, ratio of polymer:drug, solvent:antisolvent ratio, stirring rate and stirring time on the particle size, were investigated and found to have a significant (p? 0.05) effect on particle size. The best formul

Isradipine belong to dihydropyridine (DHP) class of calcium channel blockers (CCBs). It is  used in the treatment of hypertension, angina pectoris, in addition to Parkinson disease. It goes under the BCS class II drug (low solubility-high permeability). The drug will experience extensive first-pass metabolism in liver, therefore, oral bio-availability will be approximately15 to 24 %.

 The aim of this study was to formulate and optimize a stable  nanoparticles of a highly hydrophobic drug, isradipine by anti-solvent microprecipitation Method to achieve the higher in vitro dissolution rate, so that it will be absorbed by intestinal lymphatic transport in order to avoid hepatic first-pass metabolism&nbs

This research introduces a developed analytical method to determine the nominal and maximum tensile stress and investigate the stress concentration factor. The required tooth fillets parametric equations and gears dimensions have been reformulated to take into account the asymmetric fillets radiuses, asymmetric pressure angle, and profile shifting non-standard modifications. An analytical technique has been developed for the determination of tooth weakest section location for standard, asymmetric fillet radiuses, asymmetric pressure angle and profile shifted involute helical and spur gears. Moreover, an analytical equation to evaluate gear tooth-loading angle at any radial distance on the involute profile of spur and hel

     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