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Comprehensive review of severe slugging phenomena and innovative mitigation techniques in oil and gas systems
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Publication Date
Tue Apr 30 2024
Journal Name
International Journal On Technical And Physical Problems Of Engineering
Deep Learning Techniques For Skull Stripping of Brain MR Images
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Deep Learning Techniques For Skull Stripping of Brain MR Images

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Publication Date
Sun Dec 30 2018
Journal Name
Baghdad Science Journal
Geomorphological Mapping of Razzaza–Habbaria Area using Remote Sensing Techniques
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Landforms on the earth surface are so expensive to map or monitor. Remote Sensing observations from space platforms provide a synoptic view of terrain on images. Satellite multispectral data have an advantage in that the image data in various bands can be subjected to digital enhancement techniques for highlighting contrasts in objects for improving image interpretability. Geomorphological mapping involves the partitioning of the terrain into conceptual spatial entities based upon criteria. This paper illustrates how geomorphometry and mapping approaches can be used to produce geomorphological information related to the land surface, landforms and geomorphic systems. Remote Sensing application at Razzaza–Habbaria area southwest of Razz

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Publication Date
Mon Jan 01 2024
Journal Name
Aip Conference Proceedings
Comparative analysis of deep learning techniques for lung cancer identification
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One of the diseases on a global scale that causes the main reasons of death is lung cancer. It is considered one of the most lethal diseases in life. Early detection and diagnosis are essential for lung cancer and will provide effective therapy and achieve better outcomes for patients; in recent years, algorithms of Deep Learning have demonstrated crucial promise for their use in medical imaging analysis, especially in lung cancer identification. This paper includes a comparison between a number of different Deep Learning techniques-based models using Computed Tomograph image datasets with traditional Convolution Neural Networks and SequeezeNet models using X-ray data for the automated diagnosis of lung cancer. Although the simple details p

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Publication Date
Sat May 01 2021
Journal Name
Journal Of Physics: Conference Series
The Prediction of COVID 19 Disease Using Feature Selection Techniques
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Abstract<p>COVID 19 has spread rapidly around the world due to the lack of a suitable vaccine; therefore the early prediction of those infected with this virus is extremely important attempting to control it by quarantining the infected people and giving them possible medical attention to limit its spread. This work suggests a model for predicting the COVID 19 virus using feature selection techniques. The proposed model consists of three stages which include the preprocessing stage, the features selection stage, and the classification stage. This work uses a data set consists of 8571 records, with forty features for patients from different countries. Two feature selection techniques are used in </p> ... Show More
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Publication Date
Fri Jul 01 2016
Journal Name
International Journal Of Computer Science And Mobile Computing
Hybrid Color Image Compression of Hard & Soft Mixed Thresholding Techniques
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Publication Date
Sat Nov 12 2016
Journal Name
International Journal Of Mechanical Engineering And Technology (ijmet)
PERFORMANCE OF TWO-WAY NESTING TECHNIQUES FOR SHALLOW WATER MODELS
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A new two-way nesting technique is presented for a multiple nested-grid ocean modelling system. The new technique uses explicit center finite difference and leapfrog schemes to exchange information between the different subcomponents of the nested-grid system. The performance of the different nesting techniques is compared, using two independent nested-grid modelling systems. In this paper, a new nesting algorithm is described and some preliminary results are demonstrated. The validity of the nesting method is shown in some problems for the depth averaged of 2D linear shallow water equation.

Publication Date
Fri Feb 10 2023
Journal Name
Energies
Well Placement Optimization through the Triple-Completion Gas and Downhole Water Sink-Assisted Gravity Drainage (TC-GDWS-AGD) EOR Process
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Gas and downhole water sink-assisted gravity drainage (GDWS-AGD) is a new process of enhanced oil recovery (EOR) in oil reservoirs underlain by large bottom aquifers. The process is capital intensive as it requires the construction of dual-completed wells for oil production and water drainage and additional multiple vertical gas-injection wells. The costs could be substantially reduced by eliminating the gas-injection wells and using triple-completed multi-functional wells. These wells are dubbed triple-completion-GDWS-AGD (TC-GDWS-AGD). In this work, we design and optimize the TC-GDWS-AGD oil recovery process in a fictitious oil reservoir (Punq-S3) that emulates a real North Sea oil field. The design aims at maximum oil recovery us

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Publication Date
Sun Jan 01 2017
Journal Name
Iraq Journal Of Agricultural Research
THE COMPARATIVE STUDY OF THE TOTAL COSTS AND NET REVENUE OF DIFFERENT TILLAGE SYSTEMS USING TWO TYPES OF SEEDLINGS IN THE PRODUCTION OF BARLEY GREEN VARIETY SAMEER IN THE GYPSUM SOILS
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Publication Date
Wed Jun 01 2022
Journal Name
Journal Of Engineering
Assessment Strategies of Fixed Firefighting system in Residential Multi-Story Building for Improving Fire Safety: A Review
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A fixed firefighting system is a key component of fire safeguarding and reducing fire danger. It is installed as a permanent component in a structure to protect the entire or a portion of the building and its contents. The study aims to review the previous studies that deal with the evaluation of fire safety measures and their use in resolving problems associated with fire threats in buildings. For this reason, a number of previous studies in this field were reviewed compared with the NFPA code. The findings revealed that regulatory developments over the last several decades had created an atmosphere conducive to innovation. This has resulted in a growth in the number of fixed firefighting system types now obtainable. Th

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Publication Date
Mon Feb 04 2019
Journal Name
Iraqi Journal Of Physics
Indoor risk assessment of radon gas in the science college buildings-University of Mustansiriyah using RAD-7 detector
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In the present work, a set of indoor Radon concentration measurements was carried out in a number of rooms and buildings of Science College in the University of Mustansiriyah for the first time in Iraq using RAD-7 detector which is an active method for short time measuring compared with the passive method in solid state nuclear track detectors (SSNTD's). The results show that, the Radon concentrations values vary from 9.85±1.7 Bq.m-3 to 94.21±34.7 Bq.m-3 with an average value 53.64±26 Bq.m-3 which is lower than the recommended action level 200-300 Bq/m3 [ICRP, 2009].
The values of the annual effective dose (A.E.D) vary from 0.25 mSv/y to 2.38 mSv/y, with an average value 1.46±0.67 mSv/y which is lower than the recommended the rang

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