This effort is related to describe and assess the performance of the Iraqi cement sample planned for oil well-cementing jobs in Iraq. In this paper, major cementing properties which are thickening time, compressive strength, and free water in addition to the rheological properties and filtration of cement slurry underneath definite circumstances are experimentally tested. The consequences point to that the Iraqi cement after special additives encounter the requests of the API standards and can consequently is used in cementing jobs for oil wells. At this research, there is a comparative investigation established on experimental work on the effectiveness of some additives that considered as waste materials which are silica fume, baux

The poor hole cleaning efficiency could causes many problems such as high torque, drag, poor hydraulics and pipe stuck. These inherent problems result in an avoidable high operation cost which this study tried to address.  In this study, the effect of cutting density on hole cleaning efficiency in deviated and horizontal wells was investigated. Experiments were conducted using 40 feet (12 m) long of flow loop made from iron and PVC. However, the test section was made from PVC with (5.1m) long and (4” ID) for outer pipe and (2” OD) inner pipe. The cutting transport ratio (CTR) was determined from weight measurements for each test. Cutting Transport Ratio has been investigated for effects of the following parameters; flow rate, cu

This effort is related to describe and assess the performance of the Iraqi cement sample planned for oil well-cementing jobs in Iraq. In this paper, major cementing properties which are thickening time, compressive strength, and free water in addition to the rheological properties and filtration of cement slurry underneath definite circumstances are experimentally tested. The consequences point to that the Iraqi cement after special additives encounter the requests of the API standards and can consequently is used in cementing jobs for oil wells. At this research, there is a comparative investigation established on experimental work on the effectiveness of some additives that considered as waste materials which are silica fume, bauxite,

Mammary tumors (CMT) in dogs in Iraq may be induced by carcinogenic war ordnance. In our study, 10 virgin un- spayed military/pet bitches aged 5-15 years presented with abnormal masses in the abdomen with painful oedema, swelling, anorexia, weight loss, weakness and mild fever. Examination of regional lymph nodes and thoracic radiography confirmed metastasis. Tumors were excised and determined to be mostly adenocarcinomas involving multiple glands, solid in texture, 5-15 cm in size, mostly in the inguinal mammary glands at stage T3: >5 cm. Microscopy confirmed presence of adenocarcinoma in 8 dogs and solid carcinoma in 2 with half of tumors being grade III. Tumors had pleomorphic hyperchromatic cell nuclei in stroma, epithelial cells of duc

Pseudomonas aeruginosa is a Gram-negative opportunistic pathogen and a model bacterium for studying virulence and bacterial social traits. While it can be isolated in low numbers from a wide variety of environments including soil and water, it can readily be found in almost any human/animal-impacted environment. It is a major cause of illness and death in humans with immunosuppressive and chronic conditions, and infections in these patients are difficult to treat due to a number of antibiotic resistance mechanisms and the organism’s propensity to form multicellular biofilms. One hundred twenty clinical samples and forty hospital environmental samples (various sources) were collected from hospitals in Baghdad city during the period from Oc

      The study included 200 samples were collected   from   children  under two   years included (50 samples from each of Cerebrospinal fluid, Blood, Stool and Urine) from, Central Children Hospital and Children's Protections Educational Hospital. Isolates bacterial were obtained cultural, microscopic and biochemical examination and diagnosed to the species by using vitek2 system. The results showed there were contamination in 6.5% of clinical samples. The diagnosed colonies which gave pink color on the MacConkey agar , golden yellow color on the Trypton Soy agar and green color on the Birillent Enterobacter sakazakii agar and gave  a probability of 99% in the vit

Imitation learning is an effective method for training an autonomous agent to accomplish a task by imitating expert behaviors in their demonstrations. However, traditional imitation learning methods require a large number of expert demonstrations in order to learn a complex behavior. Such a disadvantage has limited the potential of imitation learning in complex tasks where the expert demonstrations are not sufficient. In order to address the problem, we propose a Generative Adversarial Network-based model which is designed to learn optimal policies using only a single demonstration. The proposed model is evaluated on two simulated tasks in comparison with other methods. The results show that our proposed model is capable of completing co

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

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

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