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bsj-2334
Detection of wheat damping off and root rot disease pathogenic fungi and it bio control by pseudomonas fluorescens
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This study was conducted to determine the fungal cause and bio control of damping off and root rot of wheat plants by using pseudomonas fluorescens under greenhouse and field conditions. Results showed isolation of eight species from the soil and roots to deferent region of Baghdad government. Rhizoctonia solani (Rs) and Fusarium solani (Fs) were the predominant damping off fungus with frequency 60 and 52% respectively. Led the using of bacteria formulations such as crud suspension , pure bacteria filtration and pure living cells in culture medium inhibit all type fungi with rates ranging from 84-96% , 80- 93% and 75-88% respectively. Rs and Fs were more pathogenesis under greenhouse conditions, with incidence of 80 and 68% and disease severity up to 41,20 and 30,20% respectively. The results of test bacterial formulation (dry, liquid and bacterial filtrate ) with seeds, soil and water irrigation showed high effectiveness for all treatments with superiority of the treatment of seeds in reducing the incidence which reached for the three formulation 21-34% compared with the infested control of Fs, Rs which reached 70 and 55%, respectively. Field experiments results showed superiority of seeds bacterization with dry formulation to reduce the disease incidence to 38% compared with the infested control (75%).These results reflected on the increasing of the shoot and rot dry weight and increasing the productivity (63%) compared with the infested control treatment .

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Publication Date
Wed Sep 22 2021
Journal Name
Samarra Journal Of Pure And Applied Science
Toward Constructing a Balanced Intrusion Detection Dataset
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Several Intrusion Detection Systems (IDS) have been proposed in the current decade. Most datasets which associate with intrusion detection dataset suffer from an imbalance class problem. This problem limits the performance of classifier for minority classes. This paper has presented a novel class imbalance processing technology for large scale multiclass dataset, referred to as BMCD. Our algorithm is based on adapting the Synthetic Minority Over-Sampling Technique (SMOTE) with multiclass dataset to improve the detection rate of minority classes while ensuring efficiency. In this work we have been combined five individual CICIDS2017 dataset to create one multiclass dataset which contains several types of attacks. To prove the eff

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Publication Date
Tue Jul 01 2025
Journal Name
Iraqi Journal Of Science
Intrusion Detection Approach Based on DNA Signature
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Publication Date
Fri Feb 17 2023
Journal Name
Journal Of Al-qadisiyah For Computer Science And Mathematics
Deploying Facial Segmentation Landmarks for Deepfake Detection
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Deepfake is a type of artificial intelligence used to create convincing images, audio, and video hoaxes and it concerns celebrities and everyone because they are easy to manufacture. Deepfake are hard to recognize by people and current approaches, especially high-quality ones. As a defense against Deepfake techniques, various methods to detect Deepfake in images have been suggested. Most of them had limitations, like only working with one face in an image. The face has to be facing forward, with both eyes and the mouth open, depending on what part of the face they worked on. Other than that, a few focus on the impact of pre-processing steps on the detection accuracy of the models. This paper introduces a framework design focused on this asp

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Publication Date
Thu Feb 28 2019
Journal Name
Multimedia Tools And Applications
Shot boundary detection based on orthogonal polynomial
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Publication Date
Tue Aug 23 2022
Journal Name
Int. J. Nonlinear Anal. Appl.
Face mask detection based on algorithm YOLOv5s
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Determining the face of wearing a mask from not wearing a mask from visual data such as video and still, images have been a fascinating research topic in recent decades due to the spread of the Corona pandemic, which has changed the features of the entire world and forced people to wear a mask as a way to prevent the pandemic that has calmed the entire world, and it has played an important role. Intelligent development based on artificial intelligence and computers has a very important role in the issue of safety from the pandemic, as the Topic of face recognition and identifying people who wear the mask or not in the introduction and deep education was the most prominent in this topic. Using deep learning techniques and the YOLO (”You on

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Publication Date
Sun Feb 02 2025
Journal Name
Engineering, Technology & Applied Science Research
Automated Glaucoma Detection Techniques: A Literature Review
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Significant advances in the automated glaucoma detection techniques have been made through the employment of the Machine Learning (ML) and Deep Learning (DL) methods, an overview of which will be provided in this paper. What sets the current literature review apart is its exclusive focus on the aforementioned techniques for glaucoma detection using the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines for filtering the selected papers. To achieve this, an advanced search was conducted in the Scopus database, specifically looking for research papers published in 2023, with the keywords "glaucoma detection", "machine learning", and "deep learning". Among the multiple found papers, the ones focusing

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Publication Date
Fri Jul 21 2023
Journal Name
Journal Of Engineering
SIMULATION OF OPTIMAL SPEED CONTROL FOR A DC MOTOR USING LINEAR QUADRATIC REGULATOR (LQR)
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This paper describes DC motor speed control based on optimal Linear Quadratic Regulator (LQR) technique. Controller's objective is to maintain the speed of rotation of the motor shaft with a particular step response.The controller is modeled in MATLAB environment, the simulation results show that the proposed controller gives better performance and less settling time when compared with the traditional PID controller.

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Publication Date
Fri Mar 01 2013
Journal Name
Journal Of Economics And Administrative Sciences
Improving the Effectiveness of Internal Control System In Accordance with COSO Model
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        The research aims to improve the effectiveness of internal control system according to a model COSO, by identifying the availability of system components according to the model and then improve the effectiveness of each component by focusing on areas for improvement in each component, as it was addressed to a model COSO and then Maamth with the environment, the current Iraqi by introducing some improvements on the form of some mechanisms of corporate governance of the Council of Directors, and senior management, the Audit Committee, Committee appointments, especially that supplies application available in the laws and legislation, the current Iraqi, taking into consideration to make some

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Publication Date
Sun Feb 03 2019
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
Employ Frameworks and Modern Standards in Evaluating Internal Control System: Applied Research in the General Company for Vegetable Oil Industry
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In light of today's business world, who faces challenges and intense competition as a result of the rapid evolution of technical and informational, organizations had to respond to variables through the adoption of modern management techniques that reduce the effects of risks and activating the role of the internal control system in order to contribute to the early detection of risks and reduce the negative results expected .The research is to address the problem faced by organizations which still follow the traditional methods in the control activities, and the lack of knowledge of the management and their staff of the importance of the existence of risk management and internal control system takes into account these risks, and the limit

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Publication Date
Wed Sep 27 2023
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Genetic Polymorphism in TNF-α Promoter Region: Its Association with Severity and Susceptibility to Rheumatoid Arthritis in Iraqi Patients with Active Disease
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Objectives: To study the prevalence of rs1799964 (-1031 T/C) and rs361525 (- 238 G/A) SNPs and their effect on the disease activity, severity, and cytokines production in newly diagnosed Iraqi rheumatoid arthritis patients. Patients and Methods: sixty-three patients were diagnosed by a specialist physician while attending the rheumatology unit and twenty control participated. The inflammatory markers were measured and PCR amplification and sequencing were performed to demonstrate TNF-α SNPs. Results: Regarding (-1031 C/T) SNP, the TT genotype and allele C were significantly present in the controls, and the CT genotype was distributed significantly in the patients. The TT genotype was mostly distributed in the mild-moder

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