Electrophoretic Deposition (EPD) process offers various advantages like the fabrication of the ceramic coatings and bodies with dense packing, good sinterability and homogenous microstructure. The variables namely (applied potential, deposition time and sintering temperature) affected the development of hydroxyapatite (HAP) coatings. The coating weight and thickness were found to increase with the increase in applied potential or coating time. Sintering temperature was found to affect in change phases of the metal, furthermore the firing shrinkage of the HAP coating on a constraining metal substrate leads to serve cracking. XRD Characterization indicates the formation of a contamination free phase pure, and the optical micrographs show th

This study aimed to measure  the accounting conservatism  and the lemited factors which  affected on it in the annual financial reports of insurance companies which listed on the Amman Stock Exchange during the period from 2005 to 2016, these factors were represented by firm age, firm debt and firm size.

Using the market value model (MV) To book value  ( BV) Beaver and Ryan (2000) The level of the accounting conservatism was measured. The study found that the insurance companies which are listed on the ASE exercise the accounting conservatism when they were  preparing financial reports. And when conducting a process  of the test of the affected of the factors (The age of the

The advancements in Information and Communication Technology (ICT), within the previous decades, has significantly changed people’s transmit or store their information over the Internet or networks. So, one of the main challenges is to keep these information safe against attacks. Many researchers and institutions realized the importance and benefits of cryptography in achieving the efficiency and effectiveness of various aspects of secure communication.This work adopts a novel technique for secure data cryptosystem based on chaos theory. The proposed algorithm generate 2-Dimensional key matrix having the same dimensions of the original image that includes random numbers obtained from the 1-Dimensional logistic chaotic map for given con

Most of the medical datasets suffer from missing data, due to the expense of some tests or human faults while recording these tests. This issue affects the performance of the machine learning models because the values of some features will be missing. Therefore, there is a need for a specific type of methods for imputing these missing data. In this research, the salp swarm algorithm (SSA) is used for generating and imputing the missing values in the pain in my ass (also known Pima) Indian diabetes disease (PIDD) dataset, the proposed algorithm is called (ISSA). The obtained results showed that the classification performance of three different classifiers which are support vector machine (SVM), K-nearest neighbour (KNN), and Naïve B

A new distribution, the Epsilon Skew Gamma (ESΓ ) distribution, which was first introduced by Abdulah [1], is used on a near Gamma data. We first redefine the ESΓ distribution, its properties, and characteristics, and then we estimate its parameters using the maximum likelihood and moment estimators. We finally use these estimators to fit the data with the ESΓ distribution

This research seeks to study the role of proactive leadership as an essential element that helps all federations that lead the wheel of sports, including the Iraqi Handball Federation, so that it builds a correct environment that helps manage the organizational errors that the Handball Federation may fall into, and this in turn helps in early detection of errors and obstacles that may occur. It is likely that the Federation will fall into the process of managing and organizing the Iraqi Handball League, in addition to increasing the clubs’ ability to assist the Iraqi Handball Federation by being proactive so as not to make mistakes. The research community included the administrative bodies of the clubs participating in the Iraqi E

The objective of this study is to apply Artificial Neural Network for heat transfer analysis of shell-and-tube heat exchangers widely used in power plants and refineries. Practical data was obtained by using industrial heat exchanger operating in power generation department of Dura refinery. The commonly used Back Propagation (BP) algorithm was used to train and test networks by divided the data to three samples (training, validation and testing data) to give more approach data with actual case. Inputs of the neural network include inlet water temperature, inlet air temperature and mass flow rate of air. Two outputs (exit water temperature to cooling tower and exit air temperature to second stage of air compressor) were taken in ANN.

The oil and gas industry relies heavily on IT innovations to manage business processes, but the exponential generation of data has led to concerns about processing big data, generating valuable insights, and making timely decisions. Many companies have adopted Big Data Analytics (BDA) solutions to address these challenges. However, determining the adoption of BDA solutions requires a thorough understanding of the contextual factors influencing these decisions. This research explores these factors using a new Technology-Organisation-Environment (TOE) framework, presenting technological, organisational, and environmental factors. The study used a Delphi research method and seven heterogeneous panelists from an Oman oil and gas company

Mersing is one of the places that have the potential for wind power development in Malaysia. Researchers often suggest it as an ideal place for generating electricity from wind power. However, before a location is chosen, several factors need to be considered. By analyzing the location ahead of time, resource waste can be avoided and maximum profitability to various parties can be realized. For this study, the focus is to identify the distribution of the wind speed of Mersing and to determine the optimal average of wind speed. This study is critical because the wind speed data for any region has its distribution. It changes daily and by season. Moreover, no determination has been made regarding selecting the average wind speed used for w

Hydrocarbon production might cause changes in dynamic reservoir properties. Thus the consideration of the mechanical stability of a formation under different conditions of drilling or production is a very important issue, and basic mechanical properties of the formation should be determined. There is considerable evidence, gathered from laboratory measurements in the field of Rock Mechanics, showing a good correlation between intrinsic rock strength and the dynamic elastic constant determined from sonic-velocity and density measurements. The values of the mechanical properties determined from log data, such as the dynamic elastic constants derived from the measurement of the elastic wave velocities in the material, should be more accurate t