Asymptotic Properties of Random Matrices of Long-Range Percolation Model

We study the spectral properties of matrices of long-range percolation model. These are N\times N random real symmetric matrices H=\{H(i,j)\}_{i,j} whose elements are independent random variables taking zero value with probability 1-\psi((i-j)/b), b\in \mathbb{R}^{+}, where $\psi$ is an even positive function with \psi(t)\le{1} and vanishing at infinity. We study the resolvent G(z)=(H-z)^{-1}, Imz\neq{0} in the limit N,b\to\infty, b=O(N^{\alpha}), 1/3<\alpha<1 and obtain the explicit expression T(z_{1},z_{2}) for the leading term of the correlation function of the normalized trace of resolvent g_{N,b}(z)=N^{-1}Tr G(z). We show that in the scaling limit of local correlations, this term leads to the expression (Nb)^{-1}T(\lambda+r_{1}/N+i0,\lambda+r_{2}/N-i0)= b^{-1}\sqrt{N}|r_{1}-r_{2}|^{-3/2}(1+o(1)) found earlier by other authors for band random matrix ensembles. This shows that the ratio $b^{2}/N$ is the correct scale for the eigenvalue density correlation function and that the ensemble we study and that of band random matrices belong to the same class of spectral universality.Comment: No comment

High-speed Underwater Wireless Optical Communication: Potential, Challenges, and Possible Solutions

Traditional underwater communication systems rely on acoustic modems due their reliability and long range. However their limited data rates, lead to the exploration of alternative techniques. In this talk, we briefly go over the potential offered by underwater wireless optical communication systems. We then summarize some of the underwater channel challenges going from severe absorption and scattering that need to be surpassed before such kind of systems can be deployed in practice. We finally present some of the on-going research directions in the area of underwater wireless optical communication systems in order to (i) better characterize and model the underwater optical channel and (ii) design, develop, and test experimentally new suitable modulation and coding techniques suitable for this environment.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

The U.S.-Iran Track II Dialogue (20022008): Lessons Learned and Implications for the Rockefeller Brothers Fund's Grantmaking Strategy

From 2002 through 2008, the Rockefeller Brothers Fund (RBF) supported a Track II dialogue involving influential American and Iranian citizens, co-organized and co-facilitated with the UnitedNations Association of the United States of America (UNA-USA), under the able leadership of Ambassador William Luers. Recognizing that the U.S.-Iranian relationship presents perhaps the most important and troubling foreign policy challenge facing both countries, the Track II dialogue was launched in December 2002.The purpose of this paper is to examine the RBF's experience with the practice of Track II dialogues in light of other experiments with similar dialogues both as a conflict prevention and management tool and as an important component of a peacemaking strategy

Deep learning for face detection using matlab

This project report presents face detection using Convolutional Neural Network algorithm and Deep Learning combination (DCT / DL) throughout MATLAB simulation and modeling. It reveals that the research project has successfully managed to establish an accurate accurate human face detection and crystal-clear human face recognition systems. The system will annul the face image that are tilted, the images on non-human faces as well as the images of human faces that have watermarks. The test results on face tracking when the image has watermarks. Under this condition, it looks like the CNN and deep learning could not identify the image correctly and wrong result is showing for the second image. This indicates that there is a limitation for the CNN and deep learning algorithm. The disadvantage is, it cannot detects the watermark image, as this image is protected. This process will proceed to Convolutional Neural Network algorithm to identify the human face from a given image. If the image belongs to human features then there will be a tracking box marking clearly the appointed face with a yellow square. This marker will be clearly pointing and shaping a yellowish box of the appointed and selected face or image.The novelty of this research project is that the CNN and deep learning (CNN / DL) methods to trace, scan and detect the human face in a very successful and effective manners taking into account the following distinguished features: the face of the human facing to the front view and not tilted or the face does not make any angles unless angels within 5 to 10 degrees only. The face must not be hiding or nor recognizable or positioned on another object. The face must be real and is not printed on any object like wood or plastic. The water mark must not be printed on the face image picture, otherwise the CNN / DL will not recognize it as human face. The working of the algorithm depends on the deep learning where the system needs to learn the image, identify the faces and store the images into database. By creating a folder called image folder, it will be easy for the MATLAB access into the folder to find the images that content human face and none human face. High resolution for face detection was approximately 85%. The algorithm was able to distinguish between human and non-human faces. By doing this we saved a lot of time in almost half

Long-time solvability of the Navier-Stokes-Boussinesq equations with almost periodic initial large data

We investigate large time existence of solutions of the Navier-Stokes-Boussinesq equations with spatially almost periodic large data when the density stratification is sufficiently large. In 1996, Kimura and Herring \cite{KH} examined numerical simulations to show a stabilizing effect due to the stratification. They observed scattered two-dimensional pancake-shaped vortex patches lying almost in the horizontal plane. Our result is a mathematical justification of the presence of such two-dimensional pancakes. To show the existence of solutions for large times, we use $\ell^1$-norm of amplitudes. Existence for large times is then proven using techniques of fast singular oscillating limits and bootstrapping argument from a global-in-time unique solution of the system of limit equations