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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
Fri Jan 30 2026
Journal Name
Journal Of Physical Education
The Effect of Proposed Exercises Using Sponge Mat On the Level of Performing Offensive Skills in Sitting Volleyball
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Publication Date
Thu Feb 07 2019
Journal Name
Iraqi Journal Of Laser
Evaluation of Low Level Laser Therapy using 785 nm Diode Laser on the Enhancement of Chronic Wound Healing
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Low-intensity laser irradiation has been explored as an alternative, non-invasive method to encourage chronic wounds to heal. This study aimed to evaluate the effects of low level laser therapy (biostimulation) using semiconductor diode laser with wavelength (785 nm) on the enhancement of chronic wound healing. Fifty patients with chronic wounds were selected to be treated with Low Level Laser Therapy. Their ages ranged between 1 to 76 years. The wound sites were distributed in the lower limb, upper limb, trunk , perineum and head (70%,14%,12%,2%,2%, respectively). Application of laser therapy by noncontact method few millimeters from the skin for 15 minutes per one session twice weekly for two months ; ie,16 sessions for each patient. R

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Publication Date
Sun Jul 01 2018
Journal Name
Computers And Electronics In Agriculture
Detection of charcoal rot (Macrophomina phaseolina) toxin effects in soybean (Glycine max) seedlings using hyperspectral spectroscopy
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Publication Date
Fri Jan 01 2016
Journal Name
Advances In Computing
A New Abnormality Detection Approach for T1-Weighted Magnetic Resonance Imaging Brain Slices Using Three Planes
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Generally, radiologists analyse the Magnetic Resonance Imaging (MRI) by visual inspection to detect and identify the presence of tumour or abnormal tissue in brain MR images. The huge number of such MR images makes this visual interpretation process, not only laborious and expensive but often erroneous. Furthermore, the human eye and brain sensitivity to elucidate such images gets reduced with the increase of number of cases, especially when only some slices contain information of the affected area. Therefore, an automated system for the analysis and classification of MR images is mandatory. In this paper, we propose a new method for abnormality detection from T1-Weighted MRI of human head scans using three planes, including axial plane, co

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Publication Date
Mon Sep 30 2024
Journal Name
Iraqi Journal Of Science
Overlapping Structure Detection in Protein-Protein Interaction Networks Using a Modified Version of Particle Swarm Optimization
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In today's world, the science of bioinformatics is developing rapidly, especially with regard to the analysis and study of biological networks. Scientists have used various nature-inspired algorithms to find protein complexes in protein-protein interaction (PPI) networks. These networks help scientists guess the molecular function of unknown proteins and show how cells work regularly. It is very common in PPI networks for a protein to participate in multiple functions and belong to many complexes, and as a result, complexes may overlap in the PPI networks. However, developing an efficient and reliable method to address the problem of detecting overlapping protein complexes remains a challenge since it is considered a complex and har

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Publication Date
Fri Jan 30 2026
Journal Name
International Journal Of Engineering & Technology
An integrated multi layers approach for detecting unknown malware behaviours
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Malware represents one of the dangerous threats to computer security. Dynamic analysis has difficulties in detecting unknown malware. This paper developed an integrated multi – layer detection approach to provide more accuracy in detecting malware. User interface integrated with Virus Total was designed as a first layer which represented a warning system for malware infection, Malware data base within malware samples as a second layer, Cuckoo as a third layer, Bull guard as a fourth layer and IDA pro as a fifth layer. The results showed that the use of fifth layers was better than the use of a single detector without merging. For example, the efficiency of the proposed approach is 100% compared with 18% and 63% of Virus Total and Bel

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Publication Date
Sun Mar 07 2010
Journal Name
Baghdad Science Journal
Local and Global Uniqueness Theorems of the N-th Order Partial Differential Equations
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In this paper, we consider inequalities in which the function is an element of n-th partially order space. Local and Global uniqueness theorem of solutions of the n-the order Partial differential equation Obtained which are applications of Gronwall's inequalities.

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Publication Date
Tue Oct 26 2021
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
Achieving urban sustainability by revitalizing the performance of Islamic geometric pattern on residential façades
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Publication Date
Sun Oct 01 2017
Journal Name
Ieee Transactions On Neural Systems And Rehabilitation Engineering
A Framework of Temporal-Spatial Descriptors-Based Feature Extraction for Improved Myoelectric Pattern Recognition
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Scopus (129)
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Publication Date
Thu Mar 01 2007
Journal Name
Al-khwarizmi Engineering Journal
Low Cost Hardware Back Propagation Algorithm
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The first successful implementation of Artificial Neural Networks (ANNs) was published a little over a decade ago. It is time to review the progress that has been made in this research area. This paper provides taxonomy for classifying Field Programmable Gate Arrays (FPGAs) implementation of ANNs. Different implementation techniques and design issues are discussed, such as obtaining a suitable activation function and numerical truncation technique trade-off, the improvement of the learning algorithm to reduce the cost of neuron and in result the total cost and the total speed of the complete ANN. Finally, the implementation of a complete very fast circuit for the pattern of English Digit Numbers NN has four layers of 70 nodes (neurons) o

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