In spite of increasing clinical cases which caused by enteroviruses transferred by water and no documents about entericviruses in the Iraqi water standards. The use of coliphages as an indicator of enteroviruses and fecal pollution were suggested two procedures were applied . The first is Two-Step Enrichment Method and the second is Single Agar Layer Method. Both methods gives good results in Identification of coliphages through testing fifty different water samples (Tap water, Surface water and Bottled water) the study shows the presence of coliphages in fourteen samples.

The way used to estimate the fuzzy reliability differs according to the nature of the information of failure time which has been dealt in this research.The information of failure times has no probable distribution to explain it , in addition it has fuzzy quality.The research includes fuzzy reliability estimation of three periods ,the first one from 1986 to 2013,the second one from 2013 to 2033 while the third one from 2033 to 2066 .Four failure time have been chosen to identify the membership function of fuzzy trapezoid represented in the pervious years after taking in consideration the estimation of most researchers, proffional    geologists and the technician who is incharge of maintaining of Mosul Dam project. B

Receipt date:08/26/2020 accepted date:9/8/2020 Publication date:12/31/2021

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        The research entitled (Moderation in Omani External Political Behavior 1970-2020. contained introduction and two sections conclusion and recommendations. The introduction included a general overview of the topic, and the importance of the political behavior o

Although allowable amounts of glycol contamination in diesel engine oil, no research has been conducted on how these levels and varying loads affect engine performance. The research used a four-stroke diesel engine to investigate the effect of different glycol contamination levels (0, 120, and 220 ppm) under two engine loads (4.5 and 9 kW). Brake specific fuel consumption, brake thermal efficiency, friction power, and exhaust gas temperature were measured to determine the engine performance. The experiment used the factorial arrangement in a completely randomized design (CRD) with three replicates. Increasing the contamination levels from 0 to 120 and then to 220 ppm under constant engine load significantly increased brake specific fuel con

Many academics have concentrated on applying machine learning to retrieve information from databases to enable researchers to perform better. A difficult issue in prediction models is the selection of practical strategies that yield satisfactory forecast accuracy. Traditional software testing techniques have been extended to testing machine learning systems; however, they are insufficient for the latter because of the diversity of problems that machine learning systems create. Hence, the proposed methodologies were used to predict flight prices. A variety of artificial intelligence algorithms are used to attain the required, such as Bayesian modeling techniques such as Stochastic Gradient Descent (SGD), Adaptive boosting (ADA), Deci

Many academics have concentrated on applying machine learning to retrieve information from databases to enable researchers to perform better. A difficult issue in prediction models is the selection of practical strategies that yield satisfactory forecast accuracy. Traditional software testing techniques have been extended to testing machine learning systems; however, they are insufficient for the latter because of the diversity of problems that machine learning systems create. Hence, the proposed methodologies were used to predict flight prices. A variety of artificial intelligence algorithms are used to attain the required, such as Bayesian modeling techniques such as Stochastic Gradient Descent (SGD), Adaptive boosting (ADA), Decision Tre

Botnet detection develops a challenging problem in numerous fields such as order, cybersecurity, law, finance, healthcare, and so on. The botnet signifies the group of co-operated Internet connected devices controlled by cyber criminals for starting co-ordinated attacks and applying various malicious events. While the botnet is seamlessly dynamic with developing counter-measures projected by both network and host-based detection techniques, the convention techniques are failed to attain sufficient safety to botnet threats. Thus, machine learning approaches are established for detecting and classifying botnets for cybersecurity. This article presents a novel dragonfly algorithm with multi-class support vector machines enabled botnet