his project try to explain the using ability of spatial techniques for land cover change detection on regional level with the time parameter and did select for explain these abilities study case (Hewaizah marsh ) . this area apply to many big changes with the time. These changes made action on characters and behaviors of this area as well as all activities in it . This Project concerting to recognize the Using importance of remote sensing and GIS Methodology in data collecting for the changes of land use and the methodology for the analyses and getting the results for the next using as a base data for development and drawing the plans as well as in regional planning .This project focus on practical

The purpose of the current research is to identify the reality and applicability of the entrepreneurial approach in its dimensions (creative, proactive, independent, risk tolerant, offensive) and its impact on the success factors of the project (organizational commitment, communication, project team, project monitoring) Access to information, treatment, storage), which is a significant and important link in the success and development of industrial projects with the possibility of studying and analyzing the provision of the appropriate environment for this.

 the research started from a problem expressed by a number of intellectual and practical questions aimed at answering them as well as To answer a

Comparison is the most common and effective technique for human thinking: the human mind always judges something new based on its comparison with similar things that are already known. Therefore, literary comparisons are always clear and convincing. In our daily lives, we are constantly forced to compare different things in terms of quantity, quality, or other aspects. It is known that comparisons are used in literature in order for speech to be clear and effective, but when these comparisons are used in everyday speech, it is in order to convey the meaning directly and quickly, because many of these expressions used daily are comparisons. In our research, we discussed this comparison as a means of metaphor and expression in Russia

The aim of this research is to use robust technique by trimming, as the analysis of maximum likelihood (ML) often fails in the case of outliers in the studied phenomenon. Where the (MLE) will lose its advantages because of the bad influence caused by the Outliers. In order to address this problem, new statistical methods have been developed so as not to be affected by the outliers. These methods have robustness or resistance. Therefore, maximum trimmed likelihood: (MTL) is a good alternative to achieve more results. Acceptability and analogies, but weights can be used to increase the efficiency of the resulting capacities and to increase the strength of the estimate using the maximum weighted trimmed likelihood (MWTL). In order to perform t

This article deals with the approximate algorithm for two dimensional multi-space fractional bioheat equations (M-SFBHE). The application of the collection method will be expanding for presenting a numerical technique for solving M-SFBHE based on “shifted Jacobi-Gauss-Labatto polynomials” (SJ-GL-Ps) in the matrix form. The Caputo formula has been utilized to approximate the fractional derivative and to demonstrate its usefulness and accuracy, the proposed methodology was applied in two examples. The numerical results revealed that the used approach is very effective and gives high accuracy and good convergence.

A simple setup of random number generator is proposed. The random number generation is based on the shot-noise fluctuations in a p-i-n photodiode. These fluctuations that are defined as shot noise are based on a stationary random process whose statistical properties reflect Poisson statistics associated with photon streams. It has its origin in the quantum nature of light and it is related to vacuum fluctuations. Two photodiodes were used and their shot noise fluctuations were subtracted. The difference was applied to a comparator to obtain the random sequence.

 Finding a path solution in a dynamic environment represents a challenge for the robotics researchers, furthermore, it is the main issue for autonomous robots and manipulators since nowadays the world is looking forward to this challenge. The collision free path for robot in an environment with moving obstacles such as different objects, humans, animals or other robots is considered as an actual problem that needs to be solved.  In addition, the local minima and sharp edges are the most common problems in all path planning algorithms. The main objective of this work is to overcome these problems by demonstrating the robot path planning and obstacle avoidance using D star (D*) algorithm based on Particle Swarm Optimization (PSO)

Although its wide utilization in microbial cultures, the one factor-at-a-time method, failed to find the true optimum, this is due to the interaction between optimized parameters which is not taken into account. Therefore, in order to find the true optimum conditions, it is necessary to repeat the one factor-at-a-time method in many sequential experimental runs, which is extremely time-consuming and expensive for many variables. This work is an attempt to enhance bioactive yellow pigment production by Streptomyces thinghirensis based on a statistical design. The yellow pigment demonstrated inhibitory effects against Escherichia coli and Staphylococcus aureus and was characterized by UV-vis spectroscopy which showed lambda maximum of

Within the framework of big data, energy issues are highly significant. Despite the significance of energy, theoretical studies focusing primarily on the issue of energy within big data analytics in relation to computational intelligent algorithms are scarce. The purpose of this study is to explore the theoretical aspects of energy issues in big data analytics in relation to computational intelligent algorithms since this is critical in exploring the emperica aspects of big data. In this chapter, we present a theoretical study of energy issues related to applications of computational intelligent algorithms in big data analytics. This work highlights that big data analytics using computational intelligent algorithms generates a very high amo