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 %.
Nonlinear diffraction pattern can be induced by focusing CW
laser into a thin quartzes cuvette containing nanofluid. The number
of revealed pattern rings indicates to the nonlinear behavior of fluid.
Here, the nonlinear refractive index of each of functionalized single
wall carbon nanotube (F-SWCNTs) suspention and multi wall carbon
nanotube (F-MWCNTs) suspention have been investigated
experimentally .Each of CNTs suspention was at volume fraction of
13×10−5 and 6×10−5. Moreover the laser source at wavelength of
473 nm was used. The results show that SWCNTs suspention
possesses higher nonlinearty than other at the same volume fraction
The nuclear level density parameter in non Equi-Spacing Model (NON-ESM), Equi-Spacing Model (ESM) and the Backshifted Energy Dependent Fermi Gas model (BSEDFG) was determined for 106 nuclei; the results are tabulated and compared with the experimental works. It was found that there are no recognizable differences between our results and the experimental -values. The calculated level density parameters have been used in computing the state density as a function of the excitation energies for 58Fe and 246Cm nuclei. The results are in a good agreement with the experimental results from earlier published work.
Test anxiety for intermediate level The current study aims to measure the test anxiety of research’s sample and to identify the statistical differences of test anxiety, considering two variables gender and students classes level (first and third intermediate class). To do this, a stratified random sampling of (300) student from first and third intermediate classes had selected from both the karkh and Rusafa sides of Baghdad province for the academic year 2015-2016. The author tested the whole sample by using the test anxiety scale that had tested for its validity and reliability. The results revealed that the research’s sample as a whole was suffering from test anxiety, there were a statistical differences between male and female tha
... Show MoreThis work, in fact, is an English language teaching study (henceforth, ELT) which may provide the inspiration for much –needed research on issues such as testing students' level of achievement in articulatory phonetics at the university level. It attempts to answer two questions: 1)What is college students' level of achievement in articulatory phonetics? 2- Are there any statistical significant differences in the achievement of college students in articulatory phonetics between the production and recognition testing techniques? This research falls into three sections: Section one indicates the problem, the aims, the hypotheses, the procedures, the limits and the value of the study. Section two provides a general overview of the articul
... Show MoreMaterials with external dimensions of one or more nanometers are referred to as nanomaterials. These structures result from a number of manufacturing processes. They are used in many industries, including pharmaceuticals, which is the most significant one. Numerous variables, including size, shape, surface morphology, crystallinity, solubility, etc., affect physical properties. While new physical and chemical processes are being created constantly, the biological method is the ideal strategy for synthesizing nanoparticles since it is straightforward, safe, and economical. Different kinds of nanoparticles can be metabolically synthesized by a wide variety of biological sources, including plants, bacteria, fungi, and yeast. There are
... Show MoreGenerally, 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
... Show MoreIn 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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