In the last years, a new technology called Cloud computing has been developed. Empirical and previous studies, commonly examined in business field and other domains. In this study, the significant factors that affecting the adoption of cloud computing have been examined using a frequency analysis that have been explored by the previous studies. The results showed that the most effected factors were relative advantage which followed by security and privacy, complexity, innovativeness, and external support. In this study the model of technology organization-environment was used to examine the significant factors that affecting the adoption of cloud computing.

The aim of this research is to find a relation between self-protection and the social - ignorance of the univresity students. In applying the aims of the reaearch, the ressearcher has constructed two scales to measure
self - protection and the social - ignorance. After finding their validity and stability and their discriminative power, the researcher has applied them on a sample of (200) male and female. University students, who were selected randomly. The results of the research has arrived at finding a positive relation between self-protection and social - ignorance.

The researcher has recommended a concentration on the role of parents in raising their childern depending on themselves and making f

In this article, the types of renewable energies and the environmental effects of consuming these energies are studied. Energy is one of the things necessary for economic and social development and improving the quality of life, and the presence of continuous and sustainable economic energy is essential for any economic development and growth. Humankind has been aware of renewable energies such as biomass and geothermal energy for a long time and has used these energies as heat sources for shelter. With the beginning of the extraction of fossil fuels such as oil and coal and unlimited access to these products, the use of renewable energy sources, except in remote places and forest areas, has become limited and forgotten. Currently in Iraq,

Rate of zinc consumption during the cathodic protection of copper pipeline which carries saline water was measured by weight loss technique in the absence and presence of bacteria. Variables studied were solution flow rate, temperature, time and NaCl concentration. It was found that within the present range of variables; the rate of zinc consumption increases with the increase of all operating conditions. The presence of bacteria increases the zinc consumption. Fourth order multi-term model and one-term model were suggested to represent the consumption data. Nonlinear regression analysis was used to estimate the coefficients of these models, while statistical analysis was used to determine the effect of each coefficient. Both models were re

                The characteristics of sulfur nanoparticles were studied by using atomic force microscope (AFM) analysis. The atomic force microscope (AFM) measurements showed that the average size of sulfur nanoparticles synthesized using thiosulfate sodium solution through the extract of cucurbita pepo extra was 93.62 nm. Protecting galvanized steel from corrosion in salt media was achieved by using sulfur nanoparticles in different temperatures. The obtained data of thermodynamic in the presence of sulfur nanoparticles referred to high value as compares to counterpart in the absence of sulfur nanoparticles, the high inhibition efficiency (%IE) and corrosion resistance were at high temperature, the corrosion rate or weig

The aim of this research is to calculate mass transfer coefficient, k_d, during cathodic protection of low carbon steel in neutral seawater (3.5% W/V NaCl in distilled water with pH = 7). Two types of cathodic protection were used:

First: Sacrificial anode cathodic protection (SACP) were a pipeline of steel carrying seawater  using zinc as a sacrificial anode and with variable temperatures ranged (0 – 45^oC) and volumetric flow rate ranged (5 – 900 lit/hr). It was found that the k_d increases with increasing temperature and volumetric flow rate of seawater, where k_d ranged (0.24×10^-6 – 41.6×10^-6 m/s).

Second: Impressed current cathodic pr

Big data of different types, such as texts and images, are rapidly generated from the internet and other applications. Dealing with this data using traditional methods is not practical since it is available in various sizes, types, and processing speed requirements. Therefore, data analytics has become an important tool because only meaningful information is analyzed and extracted, which makes it essential for big data applications to analyze and extract useful information. This paper presents several innovative methods that use data analytics techniques to improve the analysis process and data management. Furthermore, this paper discusses how the revolution of data analytics based on artificial intelligence algorithms might provide

The issue of insurance against unlawful risks raises a jurisprudential and judicial debate between two opposing trends: the first considers coverage of these risks invalid due to their impact on public order or morals, while the second—which this research analyses—calls for the possibility of covering these risks in specific circumstances, based on contractual considerations in accordance with the principle that the contract is the law of the contracting parties, and based on the obligation to compensate the harmed third party—the victim—who has no connection to the unlawful act. In this context, our research highlights that contractual considerations can justify coverage of some unlawful risks, provided that the goal is to achieve

Big data analysis is essential for modern applications in areas such as healthcare, assistive technology, intelligent transportation, environment and climate monitoring. Traditional algorithms in data mining and machine learning do not scale well with data size. Mining and learning from big data need time and memory efficient techniques, albeit the cost of possible loss in accuracy. We have developed a data aggregation structure to summarize data with large number of instances and data generated from multiple data sources. Data are aggregated at multiple resolutions and resolution provides a trade-off between efficiency and accuracy. The structure is built once, updated incrementally, and serves as a common data input for multiple mining an