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Copy Move Image Forgery Detection using Multi-Level Local Binary Pattern Algorithm
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Digital image manipulation has become increasingly prevalent due to the widespread availability of sophisticated image editing tools. In copy-move forgery, a portion of an image is copied and pasted into another area within the same image. The proposed methodology begins with extracting the image's Local Binary Pattern (LBP) algorithm features. Two main statistical functions, Stander Deviation (STD) and Angler Second Moment (ASM), are computed for each LBP feature, capturing additional statistical information about the local textures. Next, a multi-level LBP feature selection is applied to select the most relevant features. This process involves performing LBP computation at multiple scales or levels, capturing textures at different resolutions. By considering features from multiple levels, the detection algorithm can better capture both global and local characteristics of the manipulated regions, enhancing the accuracy of forgery detection. To achieve a high accuracy rate, this paper presents a variety of scenarios based on a machine-learning approach. In Copy-Move detection, artifacts and their properties are used as image features and support Vector Machine (SVM) to determine whether an image is tampered with. The dataset is manipulated to train and test each classifier; the target is to learn the discriminative patterns that detect instances of copy-move forgery. Media Integration and Call Center Forgery (MICC-F2000) were utilized in this paper. Experimental evaluations demonstrate the effectiveness of the proposed methodology in detecting copy-move. The implementation phases in the proposed work have produced encouraging outcomes. In the case of the best-implemented scenario involving multiple trials, the detection stage achieved a copy-move accuracy of 97.8 %. 

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Publication Date
Mon Jan 01 2024
Journal Name
Ieee Access
An Evolutionary Algorithm With Heuristic Operator for Detecting Protein Complexes in Protein Interaction Networks With Negative Controls
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Publication Date
Sun Nov 01 2020
Journal Name
Iop Conference Series: Materials Science And Engineering
SDN-RA: An Optimized Reschedule Algorithm of SDN Load Balancer for Data Center Networks Based on QoS
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Abstract<p>With the development of cloud computing during the latest years, data center networks have become a great topic in both industrial and academic societies. Nevertheless, traditional methods based on manual and hardware devices are burdensome, expensive, and cannot completely utilize the ability of physical network infrastructure. Thus, Software-Defined Networking (SDN) has been hyped as one of the best encouraging solutions for future Internet performance. SDN notable by two features; the separation of control plane from the data plane, and providing the network development by programmable capabilities instead of hardware solutions. Current paper introduces an SDN-based optimized Resch</p> ... Show More
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Publication Date
Wed May 01 2019
Journal Name
Iop Conference Series: Materials Science And Engineering
Application of Variable Pulsed Irrigation Algorithm (VPIA) for Runoff Losses Reduction: Case Study of Different Soil Types
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Abstract<p>The low-pressure sprinklers have been widely used to replace the high-pressure impact sprinklers in the lateral move sprinkler irrigation system due to its low operating cost and high efficiency. However, runoff losses under the low-pressure sprinkler irrigation machine can be significant. This study aims to evaluate the performance of the variable pulsed irrigation algorithm (VPIA) in reducing the runoff losses under low-pressure lateral move sprinkler irrigation machine for three different soil types. The VPIA uses the ON-OFF pulsing technique to reduce the runoff losses by controlling the number and width of the pulses considering the soil and the irrigation machine properties. Als</p> ... Show More
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Publication Date
Sun Feb 28 2021
Journal Name
Journal Of Economics And Administrative Sciences
The use of the genetic algorithm to estimate the parameters function of the hypoexponential distribution by simulation
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In this research, the focus was placed on estimating the parameters of the Hypoexponential distribution function using the maximum likelihood method and genetic algorithm. More than one standard, including MSE, has been adopted for comparison by Using the simulation method

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Publication Date
Thu May 30 2024
Journal Name
Iraqi Journal Of Science
An Evolutionary Algorithm for Improving the Quantity and Quality of the Detected Complexes from Protein Interaction Networks
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One of the recent significant but challenging research studies in computational biology and bioinformatics is to unveil protein complexes from protein-protein interaction networks (PPINs). However, the development of a reliable algorithm to detect more complexes with high quality is still ongoing in many studies. The main contribution of this paper is to improve the effectiveness of the well-known modularity density ( ) model when used as a single objective optimization function in the framework of the canonical evolutionary algorithm (EA). To this end, the design of the EA is modified with a gene ontology-based mutation operator, where the aim is to make a positive collaboration between the modularity density model and the proposed

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Publication Date
Fri Jul 30 2021
Journal Name
Iraqi Journal For Electrical And Electronic Engineering
EEG Motor-Imagery BCI System Based on Maximum Overlap Discrete Wavelet Transform (MODWT) and Machine learning algorithm
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The ability of the human brain to communicate with its environment has become a reality through the use of a Brain-Computer Interface (BCI)-based mechanism. Electroencephalography (EEG) has gained popularity as a non-invasive way of brain connection. Traditionally, the devices were used in clinical settings to detect various brain diseases. However, as technology advances, companies such as Emotiv and NeuroSky are developing low-cost, easily portable EEG-based consumer-grade devices that can be used in various application domains such as gaming, education. This article discusses the parts in which the EEG has been applied and how it has proven beneficial for those with severe motor disorders, rehabilitation, and as a form of communi

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Publication Date
Mon Jan 29 2024
Journal Name
Al-rafidain Journal Of Medical Sciences ( Issn 2789-3219 )
Role of Ultrasound in Antenatal Detection of Echogenic Amniotic Fluid and Pregnancy Outcome
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Background: Ultrasound is a valuable tool for evaluating fetal problems throughout pregnancy. Amniotic fluid anomalies have been associated with unfavorable maternal, fetal, and obstetrical outcomes. Objective: To determine the effect of echogenic amniotic fluid during term pregnancy on the presence of meconium stain liquor and pregnancy outcome. Methods: A cross-sectional study was conducted on 1080 term pregnant women who visited Al-Elwiya Maternity Teaching Hospital from May 1st, 2021, to May 1st, 2023. Ultrasound was used to analyze echogenic amniotic fluid and turbid liquor. The liquor state was tested either after an artificial membrane rupture in the vaginal delivery trial or during a cesarean section. Results: Echogenic amni

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Publication Date
Mon Jun 01 2020
Journal Name
Annals Of Tropical Medicine And Public Health
Molecular Detection of High-Risk Human Papillomavirus Genotypes from Cervical Lesions in Baghdad
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Objective Using two complementary techniques of virus detection human papillomavirus (HPV)[capture of hybrids (CH) and polymerase chain reaction (PCR)], relate the cytological study and/or cervical biopsy with high-risk HPV (HPV-HR) genotypes presence, as well as relating their viral load (VL). Methods About 272 women, who presented most cell alterations compatible with lesions cervical HPV, which has been detected in all high risk by the CH method and HPV genotype detection by PCR. Results In 22% of the patients it was not detected HPV DNA. Genotype 16 and/or 18 was prevalent and was found in 33% of the 212 women studied, meanwhile, mixed infections were found by several genotypes in 25%. In as for the histological lesions found, in 61 pat

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Publication Date
Sun Jun 30 2024
Journal Name
International Journal Of Intelligent Engineering And Systems
Eco-friendly and Secure Data Center to Detection Compromised Devices Utilizing Swarm Approach
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Modern civilization increasingly relies on sustainable and eco-friendly data centers as the core hubs of intelligent computing. However, these data centers, while vital, also face heightened vulnerability to hacking due to their role as the convergence points of numerous network connection nodes. Recognizing and addressing this vulnerability, particularly within the confines of green data centers, is a pressing concern. This paper proposes a novel approach to mitigate this threat by leveraging swarm intelligence techniques to detect prospective and hidden compromised devices within the data center environment. The core objective is to ensure sustainable intelligent computing through a colony strategy. The research primarily focusses on the

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Publication Date
Mon Jan 01 2024
Journal Name
Fifth International Conference On Applied Sciences: Icas2023
Facial deepfake performance evaluation based on three detection tools: MTCNN, Dlib, and MediaPipe
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