Optimized SVD-based robust watermarking in the fractional Fourier domain

Digital watermarking is one of the most effective methods for protecting multimedia from different kind of threats. It has been used for many purposes, like copyright protection, ownership identification, tamper detection, etc. Many watermarking applications require embedding techniques that provide robustness against common watermarking attacks, like compression, noise, filtering, etc. In this paper, an optimized robust watermarking method is proposed using Fractional Fourier Transform and Singular Value Decomposition. The approach provides a secure way for watermarking through the embedding parameters that are required for the watermark extraction. It is a block-based method, where each watermark bit is embedded in its corresponding image block. First, the transform is applied to each block, and then the singular values are evaluated through which the embedding modification is performed. The optimum fractional powers, of the transform, and the embedding strength factor are evaluated through a Meta-heuristic optimization to optimize the watermark imperceptibility and robustness. The Artificial Bee Colony is used as the Meta-heuristic optimization method. A fitness function is employed, at the optimization process, through which the maximum achievable robustness can be provided without degrading the watermarking quality below a predetermined quality threshold Qth. The effectiveness of the proposed method is demonstrated through a comparison with recent watermarking techniques in terms of the watermarking performance. The watermarking quality and robustness are evaluated for different quality threshold values. Experimental results show that the proposed approach achieves a better quality compared to that of other existing watermarking methods. On the other hand, the robustness is examined against the most common applied attacks. It is noticed that the proposed method can achieve a higher robustness degree when decreasing the quality threshold value.     

User profiling for big social media data using standing ovation model

Multimedia Tools and Applications - Online Social Networks (OSNs) have recently been the subject of numerous studies that have attempted to develop effective methods for classifying and analyzing...     

Effect of captopril, losartan, and bradykinin on early steps of insulin action

Insulin initiates its metabolic and growth-promoting effects by binding to the alpha subunit of its receptor, thereby activating the kinase in the beta subunit. This event leads to tyrosyl phosphorylation of its cytosolic substrate, insulin receptor substrate 1 (IRS-1), which in turn associates with and activates phosphatidylinositol (PI) 3-kinase. The clinical use of ACE inhibitors has been associated with increased insulin sensitivity. However, the exact molecular mechanism is unknown. In the present study, we examined the phosphorylation status of the insulin receptor and IRS-1, as well as the association between IRS-1 and PI 3-kinase in the liver and muscle of 20-month-old rats treated acutely with captopril, using immunoprecipitation with antipeptide antibodies to the insulin receptor and IRS-1, and immunoblotting with antiphosphotyrosine and anti-PI 3-kinase antibodies. Insulin stimulation increased receptor autophosphorylation to 462 +/- 253% (P < 0.05) in the liver and 697 +/- 78% (P < 0.001) in the muscle of ACE inhibitor-treated rats. There were also increases to 250 +/- 17% (P < 0.001) and 280 +/- 50% (P < 0.05) in the insulin-stimulated IRS-1 phosphorylation levels in the liver and muscle, respectively, of animals treated with captopril. The insulin-stimulated IRS-1 association with PI 3-kinase rose to 305 +/- 20% (P < 0.001) in liver and 267 +/- 48% (P < 0.05) in muscle. Losartan, an ANG receptor blocker, had no significant effect on insulin-stimulated IRS-1 phosphorylation in both tissues. The acute administration of bradykinin increased insulin-stimulated tyrosine phosphorylation of the insulin receptor and IRS-1 in the liver and muscle. These data demonstrate that ACE inhibitors modulate the early steps of insulin signaling, and that this effect may be simulated by the administration of bradykinin.     

Supporting ontology adaptation and versioning based on a graph of relevance

Ontologies recently have become a topic of interest in computer science since they are seen as a semantic support to explicit and enrich data-models as well as to ensure interoperability of data. Moreover, supporting ontology adaptation becomes essential and extremely important, mainly when using ontologies in changing environments. An important issue when dealing with ontology adaptation is the management of several versions. Ontology versioning is a complex and multifaceted problem as it should take into account change management, versions storage and access, consistency issues, etc. The purpose of this paper is to propose an approach and tool for ontology adaptation and versioning. A series of techniques are proposed to ‘safely’ evolve a given ontology and produce a new consistent version. The ontology versions are ordered in a graph according to their relevance. The relevance is computed based on four criteria: conceptualisation, usage frequency, abstraction and completeness. The techniques to carry out the versioning process are implemented in the Consistology tool, which has been developed to assist users in expressing adaptation requirements and managing ontology versions.     

Significant G peak temperature shift in Raman spectra of graphene on copper

Linear G peak position temperature dependence in Raman spectra of graphene synthesized by chemical vapor deposition from decane on copper (220) with a shift factor of ?(5.4 ± 0.4) × 10^?2 cm^?1K^?1 was observed. The obtained value substantially exceeds values previously obtained for graphene by other authors, and was associated with the substrate interaction effects.     

Eutectic Morphology in Alloy Pb – 3.2% Cd – 0.08% Sr for Battery Grids

Metal Science and Heat Treatment - Ageing of supersaturated solid solution in Pb – 3.2% Cd – 0.08% Sr alloy is studied at 20 and 80°C by measuring hardness, and light and scanning...     

A Fully Coupled Thermomechanical Model of Friction Stir Welding(FSW) and Numerical Studies on Process Parameters of Lightweight Aluminum Alloy Joints

This paper presents a new thermomechanical model of friction stir welding which is capable of simulating the three major steps of friction stir welding(FSW) process, i.e., plunge, dwell, and travel stages. A rate-dependent Johnson–Cook constitutive model is chosen to capture elasto-plastic work deformations during FSW. Two different weld schedules(i.e., plunge rate, rotational speed, and weld speed) are validated by comparing simulated temperature profiles with experimental results. Based on this model, the influences of various welding parameters on temperatures and energy generation during the welding process are investigated. Numerical results show that maximum temperature in FSW process increases with the decrease in plunge rate, and the frictional energy increases almost linearly with respect to time for different rotational speeds. Furthermore, low rotational speeds cause inadequate temperature distribution due to low frictional and plastic dissipation energy which eventually results in weld defects. When both the weld speed and rotational speed are increased, the contribution of plastic dissipation energy increases significantly and improved weld quality can be expected.     

Preparation of Electrolytic Quasi-Solid-State Nanofibers for Dye-Sensitized Solar Cells

JOM - Nanofibers were prepared from a poly(acrylonitrile-co-vinyl acetate) [P(AN-co-VAC)]/polyvinylidene fluoride (PVDF) blend and used as a quasi-solid (QS) electrolyte for dye-sensitized solar...     

Flexible and Autonomous Integrated System for Characterizing Metal Oxide Gas Sensor Response in Dynamic Environment

Characterization and calibration of gas sensor is a complex problem due to the dynamic behavior of gases and the limitations of current technology. This article reports a flexible, robust, and autonomous integrated system that is able to perform characterization on metal oxide-based gas sensors in dynamic environments. The system controls the concentration and flow of the relevant gases into the gas chamber and simultaneously measuring the sensor response. This feature allows the characterization of the sensor under continuous dynamic flow of gases similar to conditions on a robot or flow pipes. Several experiments have been performed on the system using hydrogen sulfide. The results provide information on the general characteristics of the sensor as well as its sensitivity. The noise levels were studied with different reference voltages. Overall, the results verify that the system is reliable and able to produce repeatable measurements.