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 %.
This paper presents a hybrid genetic algorithm (hGA) for optimizing the maximum likelihood function ln(L(phi(1),theta(1)))of the mixed model ARMA(1,1). The presented hybrid genetic algorithm (hGA) couples two processes: the canonical genetic algorithm (cGA) composed of three main steps: selection, local recombination and mutation, with the local search algorithm represent by steepest descent algorithm (sDA) which is defined by three basic parameters: frequency, probability, and number of local search iterations. The experimental design is based on simulating the cGA, hGA, and sDA algorithms with different values of model parameters, and sample size(n). The study contains comparison among these algorithms depending on MSE value. One can conc
... Show MoreWireless sensor networks (WSNs) represent one of the key technologies in internet of things (IoTs) networks. Since WSNs have finite energy sources, there is ongoing research work to develop new strategies for minimizing power consumption or enhancing traditional techniques. In this paper, a novel Gaussian mixture models (GMMs) algorithm is proposed for mobile wireless sensor networks (MWSNs) for energy saving. Performance evaluation of the clustering process with the GMM algorithm shows a remarkable energy saving in the network of up to 92%. In addition, a comparison with another clustering strategy that uses the K-means algorithm has been made, and the developed method has outperformed K-means with superior performance, saving ener
... Show MoreRecent advances in wireless communication systems have made use of OFDM technique to achieve high data rate transmission. The sensitivity to frequency offset between the carrier frequencies of the transmitter and the receiver is one of the major problems in OFDM systems. This frequency offset introduces inter-carrier interference in the OFDM symbol and then the BER performance reduced. In this paper a Multi-Orthogonal-Band MOB-OFDM system based on the Discrete Hartley Transform (DHT) is proposed to improve the BER performance. The OFDM spectrum is divided into equal sub-bands and the data is divided between these bands to form a local OFDM symbol in each sub-band using DHT. The global OFDM symbol is formed from all sub-bands together using
... Show MoreOptical burst switching (OBS) network is a new generation optical communication technology. In an OBS network, an edge node first sends a control packet, called burst header packet (BHP) which reserves the necessary resources for the upcoming data burst (DB). Once the reservation is complete, the DB starts travelling to its destination through the reserved path. A notable attack on OBS network is BHP flooding attack where an edge node sends BHPs to reserve resources, but never actually sends the associated DB. As a result the reserved resources are wasted and when this happen in sufficiently large scale, a denial of service (DoS) may take place. In this study, we propose a semi-supervised machine learning approach using k-means algorithm
... Show MoreIn 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.
The removal of heavy metal ions from wastewater by sorptive flotation using Amberlite IR120 as a resin, and flotation column, was investigated. A combined two-stage process is proposed as an alternative of the heavy metals removal from aqueous solutions. The first stage is the sorption of heavy metals onto Amberlite IR120 followed by dispersed-air flotation. The sorption of metal ions on the resin, depending on contact time, pH, resin dosage, and initial metal concentration was studied in batch method .Various parameters such as pH, air flow rate, and surfactant concentration were investigated in the flotation stage. Sodium lauryl sulfate (SLS) and Hexadecyltrimethyl ammonium bromide (HTAB) were used as anionic and cationic surfactant re
... Show MoreRefractive indices (nD), viscosities (η) and densities (ρ) were deliberated for the binary mixtures created by dipropyl amine with 1-octanol, 1-heptanol, 1-hexanol, 1-pentanol and tert-pentyl alcohol at temperature 298.15 K over the perfect installation extent. The function of Redlich-Kister were used to calculate and renovated of the refractive index deviations (∆nD), viscosity deviations (ηE), excess molar Gibbs free energy (∆G*E) and excess molar volumes (VmE) The standard errors and coefficients were respected by this function. The values of ∆nD, ηE, VmE and ∆G*E were plotted against mole fraction of dipropyl amine. In all cases the obtained ηE, ∆G*E, VmE and ∆nD values were negative at 298.15K. Effect of carbo
... Show MoreMalware 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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