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The method of converting color images from the RGB color system to grayscale images is a simple operation by using the fixed weights method of conversion, but using the same weights to restore the color of the same images is not an effective operation of all types of images because the grayscale image contains little information and it isn't worthy of conversion operation. The basic idea in this paper is to employ the mathematics equations which extracted from the grayscale image in conversion operation, this paper presents the method of coloring the grayscale image by using the weights derived from the characteristics of the grayscale image. Skewness, Mean and Standard deviation moments have been extracted from the features of grayscale images and its adoption the determine weights of the RGB color system. This method proved its success in coloring images compared to the traditional method adoption of fixed weights for coloring images because it relies on fixed weights for converting all grayscale images.

In this paper we presented a new way based on neural network has been developed for solutione of two dimension partial differential equations . A modified neural network use to over passing the Disadvantages of LM algorithm, in the beginning we suggest signaler value decompositions of Jacobin matrix (J) and inverse of Jacobin matrix( J-1), if a matrix rectangular or singular Secondly, we suggest new calculation of μk , that ismk=|| E (w)||2 look the nonlinear execution equations E(w) = 0 has not empty solution W* and we refer to the second norm in all cases ,whereE(w): is continuously differentiable and E(x) is Lipeschitz continuous, that is=|| E(w 2)- E(w 1)||£ L|| w 2- w 1|| ,where L is Lipeschitz constant.

We concentrate on bi-shadowing property, it has important properties and applications in mathematics. In this paper some general properties of this concept are proved. Let be a metric space be maps have bi-shadowing property. We show the maps and have bi-shadowing property. Let be maps on a metric space have bi-shadowing property. We show the maps and have bi-shadowing property.

Data mining is the process of discovering patterns in a data set by keyword. Keyword search is the most effective way to discover information in documents. But somewhere, sometimes just searching for a keyword is not enough; with research restricting that keyword has become a necessity. Like in social media abuse of word is increasing. Many systems worked on only detecting an inappropriate word; not on restriction of that word. So here in this paper keyword search method is proposed for social media which not only finds the inappropriate words, but also restrict that word from publishing on the media.

The wireless sensor network (WSN) consists mostly of a large number of nodes in a large area where not all nodes are directly connected. The applications of comprise a wide variety of scenarios.The mobile nodes are free to move because this network has selfــstructured topology. Routing protocols are responsible for detecting and maintaining paths in the network, and it classified into reactive (OnـــDemand), proactive (Table driven), and hybrid. In this paper represents a performance study of some WSN routing protocols: the Dynamic Source Routing (DSR), Ad hoc On-Demand Distance Vector (AODV), and Destination-Sequenced Distance-Vector (DSDV). The comparison made according to important metrics like packet delivery ratio (PDR), total packets dropped, Average end-to-end delay (Avg EED), and normalized routing load under the Transmission Control Protocol (TCP) and User Datagram Protocol (UDP) traffic connection and with varying number of nodes, pause time; and varying speed. In this work used (NSــ2.35) that installed on (Ubuntu 14.04) operating system to implementing the scenario. Conclude that the DSR has better performance in TCP connection; while the DSDV has better performance in UDP protocol.

This paper proposes a simulation of Photovoltaic energy used to supply an induction motor with acomparison of two types of inverters.In general, the greater number of motorswhich"are used incommercial and industrial applicationsare"induction motors. To use PV source to run the induction motor, an interface circuits are used which are a dc-dc"converter and an inverter, the PV cell has nonlinear behavior,"adc-dc converter is used along with Maximum Power Point Tracker controllerto improve theefficiency by boosting the output voltage of the PV module and to match the load demand."The dc output voltage of PV modulethen"converted to AC, two types of inverter are presented, A conventional Voltage Source Inverter system and multilevel inverter system which employselective harmonic eliminationmethod fed three phase induction motor, these two types of inverters are simulated using Matlab/Simulink and their results are presented. The FFT spectrum is presented of the output currents to analyze the harmonics reduction, which shows that the"multilevel inverter is better than VSI system"according to harmonics reduction and increment in output voltage and power.

Due to the occurred increasing in information sharing, internet popularization, E-commerce transactions, and data transferring, security and authenticity become an important and necessary subject. In this paper an automated schema was proposed to generate a strong and complex password which is based on entering initial data such as text (meaningful and simple information or not), with the concept of encoding it, then employing the Genetic Algorithm by using its operations crossover and mutation to generated different data from the entered one. The generated password is non-guessable and can be used in many and different applications and internet services like social networks, secured system, distributed systems, and online services. The proposed password generator achieved diffusion, randomness, and confusions, which are very necessary, required and targeted in the resulted password, in addition to the notice that the length of the generated password differs from the length of initial data, and any simple changing and modification in the initial data produces more and clear modification in the generated password. The proposed work was done using visual basic programing language.

In recent decades, and to this day computer technology has been used in applications and various fields including the medical field, which prompted many researchers to employ this technique in the design of decision support systems using many of the algorithms and methods for this purpose. In this paper, k-means and back propagation are proposed to classify medical datasets and then compare the performance of these methods, practical experiments show back propagation has best results than k-means.

The most important features of our time is to compete and development in all fields of life, among the most important these fields is building and construction, although the important role that represents construction projects in real life, but it is exposed to a number of problems and most of these problems are the delay in the completion of the non-receipt of the project on schedule,The reasons for this delay were not to using the scientific planning and review the projects like the method of networking analysis. By this paper, we tried to show new technique to estimate the time of achievement of activities of the project depending on the properties of prime numbers for fuzzy network.

Air pollution must take more attention because its effects on human health. One of the most important air pollutants is ground-level ozone O3, which plays an important role in air quality and climate change on the earth. Ozone affected by the other air pollutants, so this paper attempt to study the relationship between hourly, daily and monthly ground-level ozone concentration and hourly, daily and monthly air pollutant concentrations and its effect on ground-level ozone concentration. The other air pollutants are: sulfur dioxide SO2, nitrogen oxides NOx, nitrogen monoxide NO, nitrogen dioxide NO2 and carbon dioxide CO2. The monitoring station is in Babylon University in the south of Al-Hilla city, Iraq for the period 2015-2016. By using statistical analysis, correlation coefficient and some statistics for all air pollutants are computed. Results are: the maximum average ozone concentration is in the summer months June, July and August 39.30 ppb, 45.05 ppb and 36.63 ppb respectively and along the day the peak average ozone concentration is in the afternoon because of high temperature and high solar radiation intensity which is increasing the photochemical activity of ozone. There is no significant correlation between ozone and sulfur dioxide SO2, carbon dioxide CO2 (ρ > 0.05). High significant correlation is appeared between ozone and nitrogen oxides forms (ρ < 0.01). To express the complex relation between ozone and nitrogen oxide forms, proportions such as NO/NO2 and (NOx-NO)/NO is determined which explain the ozone photochemical activity. Ozone concentration decreases with increasing of NO/NO2 and increases with (NOx-NO)/NOx increasing.

This paper is concerning with essential degree of approximation using regular neural networks and how a multivariate function in spaces for can be approximated using a forward regular neural network. So, we can have the essential approximation ability of a multivariate function in spaces for using regular FFN.