Computer literacy is an urgent necessity for university students, given the rapid development in the means of communication in which we live in this era, and the flow of abundant information. Mainly on the computer in all administrative and academic transactions, where first of all the registration for the semester is done through the computer. Computer culture has many characteristics and advantages that distinguish it from other sciences, includ-ing the concept of computer culture that cannot be defined absolutely, and it is difficult to define its levels, because the specifications of the computer-educated individual differ from one individual to another, and from time to time also, you find it a luxury in a country What, and you find it necessary in another country. In order to measure and know the level of computer cul-ture among university students, a computerized scale of (40) items with five multiple-choice alternatives was built. In order to know that they have the skills of searching for information electronically, a computerized scale of (21) items was prepared, and a five-point Likert scale was adopted. Results showed that they have computer literacy and therefore they have skills of searching for information electronically at all.
Wireless Body Area Network (WBAN) is a tool that improves real-time patient health observation in hospitals, asylums, especially at home. WBAN has grown popularity in recent years due to its critical role and vast range of medical applications. Due to the sensitive nature of the patient information being transmitted through the WBAN network, security is of paramount importance. To guarantee the safe movement of data between sensor nodes and various WBAN networks, a high level of security is required in a WBAN network. This research introduces a novel technique named Integrated Grasshopper Optimization Algorithm with Artificial Neural Network (IGO-ANN) for distinguishing between trusted nodes in WBAN networks by means of a classifica
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This work, deals with Kumaraswamy distribution. Kumaraswamy (1976, 1978) showed well known probability distribution functions such as the normal, beta and log-normal but in (1980) Kumaraswamy developed a more general probability density function for double bounded random processes, which is known as Kumaraswamy’s distribution. Classical maximum likelihood and Bayes methods estimator are used to estimate the unknown shape parameter (b). Reliability function are obtained using symmetric loss functions by using three types of informative priors two single priors and one double prior. In addition, a comparison is made for the performance of these estimators with respect to the numerical solution which are found using expansion method. The
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This research aims at measuring the relationship between moral intelligence and academic adjustment for sixth year primary School Pupils.
The research is assigned to sixth year primary school pupils- Baghdad –the 2nd karkh of the both genders .The total sample includes (500) pupils .The researchers has built two scales one for Moral Intelligence and another for Academic Adjustment and applied them on the total sample of the research .The researchers treated data by appropriate statistical means .The research has reached the following results:
- The pupils of sixth year primary school characterized by Moral Intelligence.
- The
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In this research, the semiparametric Bayesian method is compared with the classical method to estimate reliability function of three systems : k-out of-n system, series system, and parallel system. Each system consists of three components, the first one represents the composite parametric in which failure times distributed as exponential, whereas the second and the third components are nonparametric ones in which reliability estimations depend on Kernel method using two methods to estimate bandwidth parameter h method and Kaplan-Meier method. To indicate a better method for system reliability function estimation, it has be
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The continuous advancement in the use of the IoT has greatly transformed industries, though at the same time it has made the IoT network vulnerable to highly advanced cybercrimes. There are several limitations with traditional security measures for IoT; the protection of distributed and adaptive IoT systems requires new approaches. This research presents novel threat intelligence for IoT networks based on deep learning, which maintains compliance with IEEE standards. Interweaving artificial intelligence with standardization frameworks is the goal of the study and, thus, improves the identification, protection, and reduction of cyber threats impacting IoT environments. The study is systematic and begins by examining IoT-specific thre
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Activated carbon (AC) is a highly important adsorbent material, as it is a solid form of pure carbon that boasts a porous structure and a large surface area, making it effective for capturing pollutants. Thanks to its exceptional features, AC is widely used for purifying water that is contaminated with odors and removing dyes in a cost-effective manner. A variety of carbonic materials have been employed to prepare AC, and this study aimed to evaluate the suitability of utilizing waste mango and avocado seeds for this purpose, followed by testing their efficacy in removing dye from aqueous solutions. The results indicate that using waste mango and avocado as AC is technically feasible, achieving dye removal percentages of 98% and 93%,
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