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Correlating Capillary Pressure and Resistivity Index for Carbonate Reservoir
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Capillary pressure is a significant parameter in characterizing and modeling petroleum reservoirs. However, costly laboratory measurements may not be sufficiently available in some cases. The problem amplifies for carbonate reservoirs because relatively enormous capillary pressure curves are required for reservoir study due to heterogeneity. In this work, the laboratory measurements of capillary pressure and formation resistivity index were correlated as both parameters are functions of saturation. Forty-one core samples from an Iraqi carbonate reservoir were used to develop the correlation according to the hydraulic flow units concept. Flow zone indicator (FZI) and Pore Geometry and Structure (PGS) approaches were used to identify the reservoir hydraulic flow units. The experimentally derived correlations can be used to predict capillary pressure from resistivity, which is widely available from well-logs. FZI and PGS rock typing methods were applied to characterize the reservoir rock types. For both methods, the log-log plot of Leverett J-function and capillary pressure versus resistivity index for each rock type represent a power-law model relationship between these parameters. Despite the good permeability-porosity prediction results, the FZI approach did not yield a good correlation between J and I. PGS resulted in a better performance in terms of both permeability-porosity prediction and Pc with I correlation because PGS honors the pore geometry and structure relationship with the mean hydraulic radius more than FZI. This work introduces a new correlating approach that aims to assist in reservoir characterization and simulation.

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Publication Date
Thu Jun 01 2023
Journal Name
Heliyon
Heterogeneously catalyzed transesterification reaction using waste snail shell for biodiesel production
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Biodiesel as an attractive energy source; a low-cost and green synthesis technique was utilized for biodiesel preparation via waste cooking oil methanolysis using waste snail shell derived catalyst. The present work aimed to investigate the production of biodiesel fuel from waste materials. The catalyst was greenly synthesized from waste snail shells throughout a calcination process at different calcination time of 2–4 h and temperature of 750–950 ◦C. The catalyst samples were characterized using X-Ray Diffraction (XRD), Brunauer-Emmett-Teller (BET), Energy Dispersive X-ray (EDX), and Fourier Transform Infrared (FT-IR). The reaction variables varying in the range of 10:1–30:1 M ratio of MeOH: oil, 3–11 wt% catalyst loading, 50–

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Publication Date
Thu Mar 30 2017
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
In Situ Gelling Formulation of Naproxen for Oral Sustained Delivery System
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Naproxen is non-steroidal anti-inflammatory drug, which has antipyretic and anti-inflammatory effect. It is extensively bound to plasma albumin, and exhibits gastric toxicity, so it may be more efficient to deliver the drug in its sustained release dosage form and adequate blood level is achieved. Three liquid formulations with in situ gelling properties have been assessed for their potential for the oral sustained delivery of naproxen . The formulations were dilute solutions of: (a) pectin; (b) gellan gum and; (c) sodium alginate, all containing complexed calcium ion that form gels when these ions are released in the acidic environment of the stomach . The viscosity of the sols and drug release were measured, and was found to be depende

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Publication Date
Tue Dec 05 2023
Journal Name
Baghdad Science Journal
AlexNet-Based Feature Extraction for Cassava Classification: A Machine Learning Approach
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Cassava, a significant crop in Africa, Asia, and South America, is a staple food for millions. However, classifying cassava species using conventional color, texture, and shape features is inefficient, as cassava leaves exhibit similarities across different types, including toxic and non-toxic varieties. This research aims to overcome the limitations of traditional classification methods by employing deep learning techniques with pre-trained AlexNet as the feature extractor to accurately classify four types of cassava: Gajah, Manggu, Kapok, and Beracun. The dataset was collected from local farms in Lamongan Indonesia. To collect images with agricultural research experts, the dataset consists of 1,400 images, and each type of cassava has

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Publication Date
Wed Jun 01 2022
Journal Name
Bulletin Of Electrical Engineering And Informatics
Proposed model for data protection in information systems of government institutions
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Information systems and data exchange between government institutions are growing rapidly around the world, and with it, the threats to information within government departments are growing. In recent years, research into the development and construction of secure information systems in government institutions seems to be very effective. Based on information system principles, this study proposes a model for providing and evaluating security for all of the departments of government institutions. The requirements of any information system begin with the organization's surroundings and objectives. Most prior techniques did not take into account the organizational component on which the information system runs, despite the relevance of

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Publication Date
Thu Dec 16 2021
Journal Name
Translational Vision Science & Technology
A Hybrid Deep Learning Construct for Detecting Keratoconus From Corneal Maps
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Publication Date
Tue Aug 01 2023
Journal Name
Biomedical Signal Processing And Control
Decoding transient sEMG data for intent motion recognition in transhumeral amputees
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Publication Date
Mon Jan 01 2024
Journal Name
Bio Web Of Conferences
Dynamic TWGH: Client-Server Optimization for Scalable Combinatorial Test Suite Generation
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To ensure that a software/hardware product is of sufficient quality and functionality, it is essential to conduct thorough testing and evaluations of the numerous individual software components that make up the application. Many different approaches exist for testing software, including combinatorial testing and covering arrays. Because of the difficulty of dealing with difficulties like a two-way combinatorial explosion, this brings up yet another problem: time. Using client-server architectures, this research introduces a parallel implementation of the TWGH algorithm. Many studies have been conducted to demonstrate the efficiency of this technique. The findings of this experiment were used to determine the increase in speed and co

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Publication Date
Mon Sep 30 2019
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Synthesized 2nd Generation Zeolite as an Acid-Catalyst for Esterification Reaction
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MCM-48 zeolites have unique properties from the surfaces and structure point of view as it’s shown in the results ,and unique and very sensitive to be prepared, have been experimentally prepared and utilized as a second-generation/ acid - catalyst for esterification reactions of oleic acid as a model oil for a free fatty acid source with Ethanol. The characterization of the catalyst used in the reaction has been identified by various methods indicating the prepared MCM-48 is highly matching the profile of common commercial MCM-48 zeolite. The XRF results show domination of SiO2 on the chemical structure with 99.1% and  agreeable with the expected from MCM-48 for it's of silica-based, and the SEM results show the cubic c

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Publication Date
Thu Jan 04 2018
Journal Name
Journal Of Electrical Engineering And Technology
An efficient selective method for audio watermarking against de-synchronization attacks
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Publication Date
Fri Feb 28 2025
Journal Name
Journal Européen Des Systèmes Automatisés
Decision-Making Model for Aircraft Landing Based on Fuzzy Logic Approach
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An aircraft's landing stage involves inherent hazards and problems associated with many factors, such as weather, runway conditions, pilot experiences, etc. The pilot is responsible for selecting the proper landing procedure based on information provided by the landing console operator (LCO). Given the likelihood of human decisions due to errors and biases, creating an intelligent system becomes important to predict accurate decisions. This paper proposes the fuzzy logic method, which intends to handle the uncertainty and ambiguity inherent in the landing phase, providing intelligent decision support to the pilot while reducing the workload of the LCO. The fuzzy system, built using the Mamdani approach in MATLAB software, considers critical

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