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Binary Image Steganalysis Based on Distortion Level Co-Occurrence Matrix
Get PDFIn recent years, binary image steganography has developed so rapidly that the research of binary image steganalysis becomes more important for information security. In most state-of-the-art binary image steganographic schemes, they always find out the flippable pixels to minimize the embedding distortions. For this reason, the stego images generated by the previous schemes maintain visual quality and it is hard for steganalyzer to capture the embedding trace in spacial domain. However, the distortion maps can be calculated for cover and stego images and the difference between them is significant. In this paper, a novel binary image steganalytic scheme is proposed, which is based on distortion level co-occurrence matrix. The proposed scheme first generates the corresponding distortion maps for cover and stego images. Then the co-occurrence matrix is constructed on the distortion level maps to represent the features of cover and stego images. Finally, support vector machine, based on the gaussian kernel, is used to classify the features. Compared with the prior steganalytic methods, experimental results demonstrate that the proposed scheme can effectively detect stego images
Molecular Structure and Electronic Spectra of CoS under the Radiation Fields
Get PDFWe optimized the ground-state stable configuration of CoS molecule in different external radiation fields (0-0.04 atomic units (a.u.)) at the basis set level of 6-311G++ (d, p) using the B3LYP density functional theory. On this basis, the molecular structure, total energy, energy gap, and the intensities of infrared ray (IR) spectra, Raman spectra, and ultraviolet-visible (UV-Vis) absorption spectra of CoS molecule were computed using the same method. The results showed that the molecular structure changed greatly under the effect of the external radiation fields and had significant dependency on the radiation fields. The total energy of CoS molecule grew slightly at first and then significantly decreased in a monotonous manner. The bond length, dipole moment, and energy gap of the molecule all reduced at first and then increased, with the turning point all at F=0.025 a.u. of the radiation field. The absorption peak of IR spectra and Raman optical activity both had maximums at F=0.03 a.u. with significant red shift. In the external radiation field of F=0.030 a.u., the absorption wavelength of the UV-Vis absorption spectra showed large blue shift, and a strong absorption peak was observed
Embedding Image Through Generated Intermediate Medium Using Deep Convolutional Generative Adversarial Network
Get PDFDeep neural network has proven to be very effective in computer vision fields. Deep convolutional network can learn the most suitable features of certain images without specific measure functions and outperform lots of traditional image processing methods. Generative adversarial network (GAN) is becoming one of the highlights among these deep neural networks. GAN is capable of generating realistic images which are imperceptible to the human vision system so that the generated images can be directly used as intermediate medium for many tasks. One promising application of using GAN generated images would be image concealing which requires the embedded image looks like not being tampered to human vision system and also undetectable to most analyzers. Texture synthesizing has drawn lots of attention in computer vision field and is used for image concealing in steganography and watermark. The traditional methods which use synthesized textures for information hiding mainly select features and mathematic functions by human metrics and usually have a low embedding rate. This paper takes advantage of the generative network and proposes an approach for synthesizing complex texture-like image of arbitrary size using a modified deep convolutional generative adversarial network (DCGAN), and then demonstrates the feasibility of embedding another image inside the generated texture while the difference between the two images is nearly invisible to the human eyes
Multi-task Joint Sparse Representation Classification Based on Fisher Discrimination Dictionary Learning
Get PDFRecently, sparse representation classification (SRC) and fisher discrimination dictionary learning (FDDL) methods have emerged as important methods for vehicle classification. In this paper, inspired by recent breakthroughs of discrimination dictionary learning approach and multi-task joint covariate selection, we focus on the problem of vehicle classification in real-world applications by formulating it as a multi-task joint sparse representation model based on fisher discrimination dictionary learning to merge the strength of multiple features among multiple sensors. To improve the classification accuracy in complex scenes, we develop a new method, called multi-task joint sparse representation classification based on fisher discrimination dictionary learning, for vehicle classification. In our proposed method, the acoustic and seismic sensor data sets are captured to measure the same physical event simultaneously by multiple heterogeneous sensors and the multi-dimensional frequency spectrum features of sensors data are extracted using Mel frequency cepstral coefficients (MFCC). Moreover, we extend our model to handle sparse environmental noise. We experimentally demonstrate the benefits of joint information fusion based on fisher discrimination dictionary learning from different sensors in vehicle classification tasks
New Method for Computer Identification Through Electromagnetic Radiation
Get PDFThe electromagnetic waves emitted from devices can be a source of information leakage and can cause electromagnetic compatibility (EMC) problems. Electromagnetic radiation signals from computer displays can be a security risk if they are intercepted and reconstructed. In addition, the leaks may reveal the hardware information of the computer, which is more important for some attackers, protectors and security inspection workers. In this paper, we propose a statistical distribution based algorithm (SD algorithm) to extracted eigenvalues from electromagnetic radiate video signals, and then classified computers by using classifier based on Bayesian and SVM. We can identify computers automatically and accurately through electromagnetic radiation by using the algorithm in our experiment environment
Self-embedding Image Watermarking based on Combined Decision Using Pre-offset and Post-offset Blocks
Get PDFTo detect and recover random tampering areas, a combined-decision-based self-embedding watermarking scheme is proposed herein. In this scheme, the image is first partitioned into 2×2 size blocks. Next, the high 5 bits of a block’s average value is embedded into its offset block. The tampering type of block is detected by comparing the watermarks of its pre-offset and post-offset blocks. The theoretical analysis and experiments demonstrate that the proposed scheme not only has a lower ratio of false detection but also better performance with regard to avoiding random tampering
A Size-Dependent Functionally Graded Higher Order Plate Analysis Based on Modified Couple Stress Theory and Moving Kriging Meshfree Method
Get PDFA size-dependent computational approach for bending, free vibration and buckling analyses of isotropic and sandwich functionally graded (FG) microplates is in this study presented. We consider both shear deformation and small scale effects through the generalized higher order shear deformation theory and modified couple stress theory (MCST). The present model only retains a single material length scale parameter for capturing properly size effects. A rule of mixture is used to model material properties varying through the thickness of plates. The principle of virtual work is used to derive the discrete system equations which are approximated by moving Kriging interpolation (MKI) meshfree method. Numerical examples consider the inclusions of geometrical parameters, volume fraction, boundary conditions and material length scale parameter. Reliability and effectiveness of the present method are confirmed through numerical results
A Virtual Puncture Surgery System Based on Multi-Layer Soft Tissue and Force Mesh
Get PDFPuncture is a common operation in surgery, which involves all kinds of tissue materials with different geometry and mechanical properties. As a new cross-disciplinary research area, Virtual Surgery (VS) makes simulation of soft tissue in puncture operation possible in virtual environment. In this paper, we introduce a VS-based puncture system composed by three-layer soft tissue, simulated with spherical harmonic function (SHF), which is covered with a force mesh, constructed by mass spring model (MSM). The two models are combined together with a parameter of SHF named surface radius, which provides MSM with real-time deformation data needed in force calculation. Meanwhile, force calculation, divided into the surface spring force and the puncture damping force, makes the force presentation better accord to the corresponding tissue characteristics. Moreover, a deformation resumption algorithm is leveraged to simulate the resumption phenomenon of the broken tissue surface. In evaluation experiment, several residents are invited to grades our model along with other four mainstream soft tissue models in terms of 7 different indicators. After the evaluation, the scores are analyzed by a comprehensive weighted grading method. Experiment results show that the proposed model has better performance during puncture operation than other models, and can well simulate surface resumption phenomenon when tissue surface is broken
Numerical Study of Natural Convection in Square Tilted Solar Cavity Considering Extended Domain
Get PDFThis work presents a numerical investigation on heat transfer and fluid-dynamic aspects for a solar open cavities in an extended fluid flow domain. The vertical wall inside the open cavities facing the aperture is assumed to be isothermal while the other walls are kept insulated. Heat transfer steady laminar natural convection is studied by solving the non-dimensional governing equations of mass, momentum and energy in the framework of a finite volume method. The analysis are carried out under Rayleigh number range of 9.41×105 to 3.76×106, inclination 0° to 90° and opening ratio 0.25, 0.5 and 1. The model results for avaergar Nusselt number evaluation was in good agreement with other published work for similar configuration. The results show that convective average Nusselt number decreases by 93% when the inclination angle increased from 0° to 90° due to the trapped vortices that limit the airflow throughout the cavity. The air flowing through the cavit is maximum when the the inclination angle is zero even at higher values of Raylight number. Results show also that decreasing the opening ratio from 1 to 0.25 leads to a drop in heat loss by 22.79%. A simple correlation has been developed for calculating the the average Nusselt number as a function of Rayleigh number, opening ratio and inclination angle
Oxypropylation of Brazilian Pine-Fruit Shell Evaluated by Principal Component Analysis
No full textPine-fruit shell (PFS) is a lignocellulosic residue derived from the fruit of Araucaria angustifolia, a coniferous tree native of South America, part of a whole vegetation of the Atlantic Forest, found in the South and Southwest of Brazil. In this work PFS will be characterized and used in the production of PFS-based polyols through oxypropylation. Three series were chosen (PFS/propylene oxide (PO) (w/v, g/mL) of 30/70, 20/80 and 10/90) with four catalyst levels (5%, 10%, 15% and 20%, (w/w, PFS based)). Oxypropylation occurred at moderate conditions of temperature, pressure and time giving rise to liquid polyols with a homopolymer content (PPO) ranging from 4-65%, a hydroxyl number (IOH) between 257-605 mg KOH/g and viscosities (V) varying from 0.76 Pa.s to 373.90 Pa.s (20°C) for the series 20/80 and 10/90, while for the series 30/70, the viscosity reached values higher than 500 Pa.s, 20C. The unreacted PFS (UR) varied between 3.6% and 77.4% (PFS-basis). After the PFS-based polyols production and characterization, a principal component analysis (PCA) was performed in order to evaluate the established interactions between the used formulation variables and the obtained polyol properties. The PCA analysis allowed to clarify the interactions between PFS and PO contents and the final biopolyol properties (PPO, IOH, V and UR). This approach showed to be a simple method to rationally analyze the influence of the input formulation variables on the final polyol properties