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A Novel Algorithm for Predicting Antimicrobial Resistance in Unequal Groups of Bacterial Isolates
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Choosing antimicrobials is a common dilemma when the expected rate of bacterial resistance is high. The observed resistance values in unequal groups of isolates tested for different antimicrobials can be misleading. This can affect the decision to recommend one antibiotic over the other. We analyzed recalled data with the statistical consideration of unequal sample groups. Data was collected concerning children suspected to have typhoid fever at Al Alwyia Pediatric Teaching Hospital in Baghdad, Iraq. The study period extended from September 2021 to September 2022. A novel algorithm was developed to compare the drug sensitivity among unequal numbers of Salmonella typhi (S. Typhi) isolates tested with different antibacterials. According to the proposed algorithm, the predicted resistance values were more valid than the observed values. This proposed algorithm is expected to help the hospital antibiotic policy committee recommend the proper antibacterial agents for S. Typhi and further bacterial isolates.

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Publication Date
Sat Jan 01 2022
Journal Name
Aip Conference Proceedings
Artificial neural network model for predicting the desulfurization efficiency of Al-Ahdab crude oil
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Publication Date
Tue Dec 01 2020
Journal Name
Journal Of Engineering
Development of Regression Models for Predicting Pavement Condition Index from the International Roughness Index
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Flexible pavements are considered an essential element of transportation infrastructure. So, evaluations of flexible pavement performance are necessary for the proper management of transportation infrastructure. Pavement condition index (PCI) and international roughness index (IRI) are common indices applied to evaluate pavement surface conditions. However, the pavement condition surveys to calculate PCI are costly and time-consuming as compared to IRI. This article focuses on developing regression models that predict PCI from IRI. Eighty-three flexible pavement sections, with section length equal to 250 m, were selected in Al-Diwaniyah, Iraq, to develop PCI-IRI relationships. In terms of the quantity and severity of eac

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Publication Date
Fri Jan 01 2021
Journal Name
Journal Of Engineering
A Proposed Adaptive Bitrate Scheme Based on Bandwidth Prediction Algorithm for Smoothly Video Streaming
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A robust video-bitrate adaptive scheme at client-aspect plays a significant role in keeping a good quality of video streaming technology experience. Video quality affects the amount of time the video has turned off playing due to the unfilled buffer state. Therefore to maintain a video streaming continuously with smooth bandwidth fluctuation, a video buffer structure based on adapting the video bitrate is considered in this work. Initially, the video buffer structure is formulated as an optimal control-theoretic problem that combines both video bitrate and video buffer feedback signals. While protecting the video buffer occupancy from exceeding the limited operating level can provide continuous video str

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Publication Date
Sun Aug 31 2025
Journal Name
International Journal Of Intelligent Engineering And Systems
Enhanced Evolutionary Algorithm for Dynamic Community Detection Using a Vulnerable Node Reassignment-based Mutation
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Recently, detecting dynamic patterns for growing communities in social networks have attracted significant attention. The objective of dynamic community detection is to analyze and identify clusters in complex networks that change over time. Different optimization algorithms, including both single-objective and multi-objective approaches, have been employed to address the challenge of dynamic community detection. Although current evolutionary algorithms for identifying community structure can traverse extensive areas of partition space, they often become stuck in local minima. In addition, limited studies have addressed this issue by integrating local search strategies with evolutionary algorithms for community identification. This paper in

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Publication Date
Sun Jan 16 2011
Journal Name
Bayt Alhekma
formations of abstract nouns from groups of goagols
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Abstract The study aimed at reviewing translation theories proposed to address problems in translation studies. To the end, translation theories and their applications were reviewed in different studies with a focus on issues such as critical discourse analysis, cultural specific items and collocation translation.

Publication Date
Sat Aug 01 2026
Journal Name
Journal Of Molecular Structure
Synthesis, multidimensional characterization, biological evaluation, and computational insights into novel N2O2-tetradentate Schiff base metal complexes as potent antimicrobial agents
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Publication Date
Thu Feb 01 2024
Journal Name
Baghdad Science Journal
Detection of resistance genes (gyrA,qepA,drf1,drf17) for E.coli in Iraqi aquatic environment
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The control of water represents the safe key for fair and optimal use to protect water resources due to human activities, including untreated wastewater, which is considered a carrier of a large number of antibiotic-resistant bacterial species. This study aimed to investigate the prevalence of antibiotic-resistance to E. coli in Tigris River by the presence of resistance genes for aminoglycoside(qepA( ,quinolone (gyrA), and sulfa drugs( dfr1 ,dfr17) due to the frequent use of antibiotics and their release into wastewater of hospitals. Samples were collected from three sites on Tigris River: S1( station wastewater in Adhamiya), S2 (station wastewater in Baghdad Medical city hospital), S3 (station wastew

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Publication Date
Tue Dec 05 2023
Journal Name
Baghdad Science Journal
A Novel System for Confidential Medical Data Storage Using Chaskey Encryption and Blockchain Technology
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Secure storage of confidential medical information is critical to healthcare organizations seeking to protect patient's privacy and comply with regulatory requirements. This paper presents a new scheme for secure storage of medical data using Chaskey cryptography and blockchain technology. The system uses Chaskey encryption to ensure integrity and confidentiality of medical data, blockchain technology to provide a scalable and decentralized storage solution. The system also uses Bflow segmentation and vertical segmentation technologies to enhance scalability and manage the stored data. In addition, the system uses smart contracts to enforce access control policies and other security measures. The description of the system detailing and p

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Publication Date
Thu Jan 15 2026
Journal Name
Environmental Science And Pollution Research
Laser-assisted neem oil pre-treatment: A novel pathway for high-efficiency biodiesel production
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Biodiesel is popular as an eco-friendly fossil fuel alternative. Neem oil is manufactured from Azadirachta indica seeds. Transesterifying triglycerides with alcohol in the presence of a synthesized CaO nanocatalyst is the most common biodiesel synthesis procedure—recent advances, difficulties, and prospects in laser feedstock pretreatment to boost reactivity and reduce energy use. Oil pre-treatment with a 540-nm green laser is cost-effective and environmentally friendly. This study examined neem oil with and without laser pretreatment for biodiesel synthesis. CaO nanocatalysts were synthesised using Sol–gel and characterised using XRD and SEM. According to catalyst recyclability, the CaO nanocatalyst did not lose activity after five re

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Publication Date
Mon Jun 01 2026
Journal Name
Statistics, Optimization & Information Computing
Predicting Public Budget Surplus and Deficit Using a Hybrid 1D-CNN–LSTM Model
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The fiscal position of governments in rentier economies depends heavily on oil revenues. The relationship between oil prices and the budget surplus or deficit is often nonlinear and characterized by complex temporal dependencies, which may limit the predictive capability of conventional econometric models. Accordingly, this study aims to forecast the Iraqi budget surplus and deficit and compare the predictive performance of the ARDL, NARDL, LSTM, 1D-CNN, and hybrid 1D-CNN-LSTM models using oil prices as the primary predictive variable. The hybrid model integrates the feature-extraction capability of One-Dimensional Convolutional Neural Networks (1D-CNN) with the ability of Long Short-Term Memory (LSTM) networks to capture long-term

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