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Using Adaptive Neuro Fuzzy Inference System to Predict Rate of Penetration from Dynamic Elastic Properties
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Rate of penetration plays a vital role in field development process because the drilling operation is expensive and include the cost of equipment and materials used during the penetration of rock and efforts of the crew in order to complete the well without major problems. It’s important to finish the well as soon as possible to reduce the expenditures. So, knowing the rate of penetration in the area that is going to be drilled will help in speculation of the cost and that will lead to optimize drilling outgoings. In this research, an intelligent model was built using artificial intelligence to achieve this goal.  The model was built using adaptive neuro fuzzy inference system to predict the rate of penetration in Mishrif formation in Nasiriya oil field for the selected wells. The mean square error for the results obtained from the ANFIS model was 0.015. The model was trained and simulated using MATLAB and Simulink platform. Laboratory measurements were conducted on core samples selected from two wells. Ultrasonic device was used to measure the transit time of compressional and shear waves and to compare these results with log records. Ten wells in Nasiriya oil field had been selected based on the availability of the data. Dynamic elastic properties of Mishrif formation in the selected wells were determined by using Interactive Petrophysics (IP V3.5) software and based on the las files and log records provided. The average rate of penetration of the studied wells was determined and listed against depth with the average dynamic elastic properties and fed into the fuzzy system. The average values of bulk modulus for the ten wells ranged between (20.57) and (27.57) . For shear modulus, the range was from (8.63) to (12.95) GPa. Also, the Poisson’s ratio values varied from (0.297) to (0.307). For the first group of wells (NS-1, NS-3, NS-4, NS-5, and NS-18), the ROP values were taken from the drilling reports and the lowest ROP was at the bottom of the formation with a value of (3.965) m/hrs while the highest ROP at the top of the formation with a value (4.073) m/hrs. The ROP values predicted by the ANFIS for this group were (3.181) m/hrs and (4.865) m/hrs for the lowest and highest values respectively. For the second group of wells (NS-9, NS-15, NS-16, NS-19, and NS-21), the highest ROP obtained from drilling reports was (4.032) m/hrs while the lowest value was (3.96) m/hrs. For the predicted values by ANFIS model were (2.35) m/hrs and (4.3) m/hrs for the lowest and highest ROP values respectively.

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Publication Date
Thu Dec 30 2021
Journal Name
Gsc Biological And Pharmaceutical Sciences
Survey and revision of leaf miners to some plants from different localities of Iraq
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Publication Date
Thu Dec 30 2021
Journal Name
Gsc Biological And Pharmaceutical Sciences
Survey and revision of leaf miners to some plants from different localities of Iraq
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This investigation showed (31) species belonging to (15) genera under (five) families and two orders. The leafminers Dipter families (Agromozidae, Anthomyiidae, Drosophilidae), Agromyzid flies is the highest level of investigated many host plants, but other families have lowest host plants. The synonyms of species were provided from GBIF scarlet's. The date and localities of sampling collection were recorded.

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Publication Date
Mon Dec 05 2022
Journal Name
Baghdad Science Journal
Synthesis, Identification, Theoretical Study, and Effect of the New Heterocyclic System from Ciprofloxacin Derivatives on the Activity of Some Liver Enzymes
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The target of this study was to synthesize several new Ciprofloxacin drug analogs by providing a nucleophilic substitution procedure that provides new functionality at the carboxylic group location. The analogs were synthesized, designed, and characterized by 1HNMR, and FTIR. The synthetic path began from the reaction of ciprofloxacin drug with morpholine to give compound[B], ciprofloxacin derivative was linked with a variety of primary and secondary amines to give compounds[B1-B9]. The above-mentioned prepared compounds [B3 and B5] were applied to liver enzymes, and the increase in the activity of these enzymes was observed. In addition, a theoretical study was conducted to study the energies and properties of the prepared co

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Publication Date
Fri Nov 10 2017
Journal Name
Al–bahith Al–a'alami
The Relation of Results to Objectives of Media Research – an Evaluative: Study of Research of al-Baath al-iilami Journal from 2007 to 2016
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The main idea of this research is that the researcher believes that media research remains useless unless its goals and results are achieved by using the correct scientific tools. The researcher chooses 100 research papers of about 35% of the published ones, 10 of them are excluded because they are outside media. We use a simple and randomized sample including the three departments of media: journalism, television and radio journalism and public relations. The researcher adopts statistical methods such as Fay coefficient, correlation coefficient, Pearson correlation coefficient and straight line equation.
The researcher uses an analytical form followed by analysis of content, them the scale. The results are found in 58 researches, w

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Publication Date
Sun Oct 01 2023
Journal Name
Baghdad Science Journal
Best Proximity Point Theorem for α ̃–ψ ̃-Contractive Type Mapping in Fuzzy Normed Space
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The best proximity point is a generalization of a fixed point that is beneficial when the contraction map is not a self-map. On other hand, best approximation theorems offer an approximate solution to the fixed point equation . It is used to solve the problem in order to come up with a good approximation. This paper's main purpose is to introduce new types of proximal contraction for nonself mappings in fuzzy normed space and then proved the best proximity point theorem for these mappings. At first, the definition of fuzzy normed space is given. Then the notions of the best proximity point and - proximal admissible in the context of fuzzy normed space are presented. The notion of α ̃–ψ ̃- proximal contractive mapping is introduced.

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Publication Date
Mon Sep 01 2014
Journal Name
19th International Conference On Methods And Models In Automation And Robotics (mmar) 2014
A PSO-optimized type-2 fuzzy logic controller for navigation of multiple mobile robots
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Publication Date
Tue May 02 2023
Journal Name
Journal Of Optoelectronics And Advanced Materials
Preparation of samarium doped-PMMA composite by casting method to evaluate the optical properties and potential applications
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Samarium ions (Sm +3), a rare-earth element, have a significant optical emission within the visible spectrum. PMMA samples, mixed with different ratios of SmCl3.6H2O, were prepared via the casting method. The composite was tested using UV-visible, photoluminescence and thermogravimetric analysis (TGA). The FTIR spectrometry of PMMA samples showed some changes, including variation in band intensity, location, and width. Mixed with samarium decreases the intensity of the CO and CH2 stretching bands and band position. A new band appeared corresponding to ionic bonds between samarium cations with negative branches in the polymer. These variations indicate complex links between the Sm +3 ion and oxygen in the ether group. The optical absorption

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Publication Date
Mon Dec 20 2021
Journal Name
Baghdad Science Journal
An Experimental Study of the Server-based Unfairness Solutions for the Cross-Protocol Scenario of Adaptive Streaming over HTTP/3 and HTTP/2
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Since the introduction of the HTTP/3, research has focused on evaluating its influences on the existing adaptive streaming over HTTP (HAS). Among these research, due to irrelevant transport protocols, the cross-protocol unfairness between the HAS over HTTP/3 (HAS/3) and HAS over HTTP/2 (HAS/2) has caught considerable attention. It has been found that the HAS/3 clients tend to request higher bitrates than the HAS/2 clients because the transport QUIC obtains higher bandwidth for its HAS/3 clients than the TCP for its HAS/2 clients. As the problem originates from the transport layer, it is likely that the server-based unfairness solutions can help the clients overcome such a problem. Therefore, in this paper, an experimental study of the se

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Publication Date
Wed Jan 01 2020
Journal Name
Desalination And Water Treatment
Reducing endotoxin from dialysis water by using different disinfection processes
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Publication Date
Tue Jan 01 2019
Journal Name
International Journal Of Machine Learning And Computing
Facial Emotion Recognition from Videos Using Deep Convolutional Neural Networks
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Its well known that understanding human facial expressions is a key component in understanding emotions and finds broad applications in the field of human-computer interaction (HCI), has been a long-standing issue. In this paper, we shed light on the utilisation of a deep convolutional neural network (DCNN) for facial emotion recognition from videos using the TensorFlow machine-learning library from Google. This work was applied to ten emotions from the Amsterdam Dynamic Facial Expression Set-Bath Intensity Variations (ADFES-BIV) dataset and tested using two datasets.

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