Densely deployment of sensors is generally employed in wireless sensor networks (WSNs) to ensure energy-efficient covering of a target area. Many sensors scheduling techniques have been recently proposed for designing such energy-efficient WSNs. Sensors scheduling has been modeled, in the literature, as a generalization of minimum set covering problem (MSCP) problem. MSCP is a well-known NP-hard optimization problem used to model a large range of problems arising from scheduling, manufacturing, service planning, information retrieval, etc. In this paper, the MSCP is modeled to design an energy-efficient wireless sensor networks (WSNs) that can reliably cover a target area. Unlike other attempts in the literature, which consider only a si

     This work presents an approach for the applying Triple DES (TRIPLE DES) based on using genetic algorithm by adding intelligent feature for TRIPLE DES with N round for genetic algorithm. Encapsulated cipher file with special program which send an acknowledgment to a sender to know who decipher or  broken to  crash it , Thus it is considered as the initial step to improve privacy. The outcome for proposed system gives a good indication that it is a promising system compared with other type of cipher system.

The  lossy-FDNR  based  aclive  fil ter has an  important   property among  many  design  realizations. 'This includes  a significant reduction in component count particularly in the number  of OP-AMP which consumes   power.  However  the·  problem  of  this   type  is the  large component spreads  which affect the fdter performance.

In  this  paper   Genetic   Algorithm   is  applied   to  minimize   the component  spread   (capacitance  and  resistance  p,read). The minimization of these spreads allow the fil

The effectiveness of detecting and matching of image features using multiple views of a specified scene using dynamic scene analysis is considered to be a critical first step for many applications in computer vision image processing. The Scale invariant feature transform (SIFT) can be applied very successfully of typical images captured by a digital camera.
In this paper, firstly the SIFT and its variants are systematically analyzed. Then, the performances are evaluated in many situations: change in rotation, change in blurs, change in scale and change in illumination. The outcome results show that each algorithm has its advantages when compared with other algorithms

In this research, the focus was on estimating the parameters on (min- Gumbel distribution), using the maximum likelihood method and the Bayes method. The genetic algorithmmethod was employed in estimating the parameters of the maximum likelihood method as well as  the Bayes method. The comparison was made using the mean error squares (MSE), where the best  estimator  is the one who has the least mean squared error. It was noted that the best estimator was (BLG_GE).

Excessive skewness which occurs sometimes in the data is represented as an obstacle against normal distribution. So, recent studies have witnessed activity in studying the skew-normal distribution (SND) that matches the skewness data which is regarded as a special case of the normal distribution with additional skewness parameter (α), which gives more flexibility to the normal distribution. When estimating the parameters of (SND), we face the problem of the non-linear equation and by using the method of Maximum Likelihood estimation (ML) their solutions will be inaccurate and unreliable. To solve this problem, two methods can be used that are: the genetic algorithm (GA) and the iterative reweighting algorithm (IR) based on the M

Often phenomena suffer from disturbances in their data as well as the difficulty of formulation, especially with a lack of clarity in the response, or the large number of essential differences plaguing the experimental units that have been taking this data from them. Thus emerged the need to include an estimation method implicit rating of these experimental units using the method of discrimination or create blocks for each item of these experimental units in the hope of controlling their responses and make it more homogeneous. Because of the development in the field of computers and taking the principle of the integration of sciences it has been found that modern algorithms used in the field of Computer Science genetic algorithm or ant colo