The choice of binary Pseudonoise (PN) sequences with specific properties, having long period high complexity, randomness, minimum cross and auto- correlation which are essential for some communication systems. In this research a nonlinear PN generator is introduced . It consists of a combination of basic components like Linear Feedback Shift Register (LFSR), ?-element which is a type of RxR crossbar switches. The period and complexity of a sequence which are generated by the proposed generator are computed and the randomness properties of these sequences are measured by well-known randomness tests.

Recently Genetic Algorithms (GAs) have frequently been used for optimizing the solution of estimation problems. One of the main advantages of using these techniques is that they require no knowledge or gradient information about the response surface. The poor behavior of genetic algorithms in some problems, sometimes attributed to design operators, has led to the development of other types of algorithms. One such class of these algorithms is compact Genetic Algorithm (cGA), it dramatically reduces the number of bits reqyuired to store the poulation and has a faster convergence speed. In this paper compact Genetic Algorithm is used to optimize the maximum likelihood estimator of the first order moving avergae model MA(1). Simulation results

In this work, chemical spray pyrolysis deposition (CSP) technique was used to prepare a mixed In2O3-CdO thin films with different CdO content (10, 30 and 50)%volume ratio on glass substrates at 150 ᵒC substrate temperature. The surface morphology and structural properties were measured to find the optimum conditions to improve thin films properties for using as photo detector. Current –Time, the sensitivity and response speed vary for each mixture. Samples with 10% vol. CdO content has square pulse response with average rise time nearly 1s and fall time 1s.

This paper discusses an optimal path planning algorithm based on an Adaptive Multi-Objective Particle Swarm Optimization Algorithm (AMOPSO) for two case studies. First case, single robot wants to reach a goal in the static environment that contain two obstacles and two danger source. The second one, is improving the ability for five robots to reach the shortest way. The proposed algorithm solves the optimization problems for the first case by finding the minimum distance from initial to goal position and also ensuring that the generated path has a maximum distance from the danger zones. And for the second case, finding the shortest path for every robot and without any collision between them with the shortest time. In ord

In this paper, a least squares group finite element method for solving coupled Burgers' problem in   2-D is presented. A fully discrete formulation of least squares finite element method is analyzed, the backward-Euler scheme for the time variable is considered, the discretization with respect to space variable is applied as biquadratic quadrangular elements with nine nodes for each element. The continuity, ellipticity, stability condition and error estimate of least squares group finite element method are proved.  The theoretical results  show that the error estimate of this method is . The numerical results are compared with the exact solution and other available literature when the convection-dominated case to illustrate the effic

Background: The use of osseointegrated fixtures in dentistry has been demonstrated both histologically and clinically to be beneficial in providing long term oral rehabilitation in completely edentulous individual. Most patients suffer from denture instability; particularly with mandibular prosthesis, the use of dental implant will be benefit significantly from even a slight increase in retention. The concept of implanting two to four fixtures in a bony ridge to retain a complete denture prosthesis appealing therefore, as retention, stability and acceptable economic compromise to the expanse incurred with the multiple fixture supported fixed prosthesis. Materials and methods in this study the sample were eight patients selected from a hosp

<p>Recently, reconfigurable intelligent surfaces have an increasing role to enhance the coverage and quality of mobile networks especially when the received signal level is very weak because of obstacles and random fluctuation. This motivates the researchers to add more contributions to the fields of reconfigurable intelligent surfaces (RIS) in wireless communications. A substantial issue in reconfigurable intelligent surfaces is the huge overhead for channel state information estimation which limits the system’s performance, oppressively. In this work, a newly proposed method is to estimate the angle of arrival and path loss at the RIS side and then send short information to the base station rather than huge overhe

Face recognition is a crucial biometric technology used in various security and identification applications. Ensuring accuracy and reliability in facial recognition systems requires robust feature extraction and secure processing methods. This study presents an accurate facial recognition model using a feature extraction approach within a cloud environment. First, the facial images undergo preprocessing, including grayscale conversion, histogram equalization, Viola-Jones face detection, and resizing. Then, features are extracted using a hybrid approach that combines Linear Discriminant Analysis (LDA) and Gray-Level Co-occurrence Matrix (GLCM). The extracted features are encrypted using the Data Encryption Standard (DES) for security

The real and imaginary part of complex dielectric constant for InAs(001) by adsorption of oxsagen atoms has been calculated, using numerical analysis method (non-linear least square fitting). As a result a mathematical model built-up and the final result show a fairly good agreement with other genuine published works.