Encryption is the way to ensure confidentiality of different data, digital images have special features as large data, bulky data, and strong correlation between pixels, which makes traditional encryption algorithms not suitable for image encryption. For this concern, we propose a novel lossless encryption scheme for digital images based on combination of matrix transformations and XOR operation. The numerical experimental results confirms that the proposed method achieves high security level against brute force attacks, statistical attacks and sensitivity analysis, moreover the suggested algorithm provides a good randomness properties, thus our method can be applied for image encryption and transmission in sensitive domains.

In this paper, different techniques of analysis have been used to study the effects of perturbations generated from a robotic mobile platform called Isiskate. These disturbances were applied on two categories of people: post-CVA subjects suffering from cerebrovascular accident and healthy individuals. Our aim is to analyze some assessment tools to distinguish between different postural behaviors. In relevant works, very few studies have addressed the use of nonlinear time-series methods in diagnosis of post-CVA pathological postural behavior. Furthermore, our tools are based on parametric and non-parametric identification procedures, that can yield to an insight on how to improve the examination time. As part of our analysis, the tests were established with several levels of sinusoidal vibrations, along the anterior–posterior (A/P) and medial–lateral (M/L) planes. The mobile platform allowed us to record a set of coordinates that includes center of pressure (COP) as a function of time. First, we have quantified some linear parameters and spectral characteristics using power spectral density (PSD). Thereafter, we have deduced stochastic parameters using stabilogram diffusion analysis (SDA), which revealed some interesting invariants. Then transfer functions between the platform velocity and COP trajectory were evaluated. They were carried out at frequencies from 0.1 Hz to 3.3 Hz. Furthermore, we accomplished a comparison of models based on both parametric and nonparametric identification methods. The combination of the proposed techniques has provided us an understanding of human control process by establishing a behavior model and helped us to distinguish patients with postural disorders. This improves postural analysis and facilitates the diagnosis of pathologies related to equilibrium which serves in rehabilitation.

We propose a new approach for modeling a High Electron Mobility Transistor (HEMT) using that of Gaussian Process Regression one (GPR), to improve the current-voltage characteristics of HEMT transistor for using in electronic and biological domain or any other domain that needs it. The study and development of a new Atlas Silvaco device are taking into account the impact of several geometric and electric parameters; we focus on the electrical performances of the double gate field plate In0.2Ga0.8As/Al0.3Ga0.7As HEMT including double heterostructure; we compare the numerical simulation using 2D Atlas Silvaco simulator with the extracted experimental results. Then we validate our model by GPR approach. The GPR approach opens promising opportunities for devices modeling without knowing too much the device physics properties. The obtained results give better performances which lead to fabricate devices with better electrical properties for promoting further investigation.