Fractal image compression gives some desirable properties like fast decoding image, and very good rate-distortion curves, but suffers from a high encoding time. In fractal image compression a partitioning of the image into ranges is required. In this work, we introduced good partitioning process by means of merge approach, since some ranges are connected to the others. This paper presents a method to reduce the encoding time of this technique by reducing the number of range blocks based on the computing the statistical measures between them . Experimental results on standard images show that the proposed method yields minimize (decrease) the encoding time and remain the quality results passable visually.

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

In this research, an experimental study was conducted to high light the impact of the exterior shape of a cylindrical body on the forced and free convection heat transfer coefficients when the body is hold in the entrance of an air duct. The impact of changing the body location within the air duct and the air speed are also demonstrated. The cylinders were manufactured with circular, triangular and square sections of copper for its high thermal conductivity with appropriate dimensions, while maintaining the surface area of all shapes to be the same. Each cylinder was heated to a certain temperature and put inside the duct at certain locations. The temperature of the cylinder was then monitored. The heat transfer coefficient were then cal

Deep learning convolution neural network has been widely used to recognize or classify voice. Various techniques have been used together with convolution neural network to prepare voice data before the training process in developing the classification model. However, not all model can produce good classification accuracy as there are many types of voice or speech. Classification of Arabic alphabet pronunciation is a one of the types of voice and accurate pronunciation is required in the learning of the Qur’an reading. Thus, the technique to process the pronunciation and training of the processed data requires specific approach. To overcome this issue, a method based on padding and deep learning convolution neural network is proposed to

Health insurance and its benefits are of great importance and impact on the employees who represent the human capital of each organization because they are related to the health reality. The study took into account the most important and the last of his writing of the concepts and literary reviews and enriched the theoretical part of the practical side has addressed the financial data and analysis for the period from 2013 to 2017 to know the impact and the relationship between the variables that They were reviewed on the theoretical side. The study came out with a number of results, on the basis of which practical conclusions were drawn and reflected what was observed on the basis of which the recommendations were formulated

Liquid-liquid membrane extraction technique, pertraction, using three types of solvents (methyl isobutyl ketone, n-butyl acetate, and n-amyl acetate) was used for recovery of penicillin V from simulated fermentation broth under various operating conditions of pH value (4-6) for feed and (6-8) for receiver phase, time (0-40 min), and agitation speed (300-500 rpm) in a batch laboratory unit system. The optimum conditions for extraction were at pH of 4 for feed, and 8 for receiver phase, rotation speed of 500 rpm, time of 40 min, and solvent of MIBK as membrane, where more than 98% of penicillin was extracted. 

Abstract

were determine the problem of current research to answer the  question on the consciousness of the Ministry of Agriculture to adopt Staffing  strategy and identify the shortcomings  as the independent variable, represented by the three dimensions (recruitment , selection, placement) and its impact on high performance, as  dependent   variable is described  in  four dimensions (leadership, strategy, structure and processes, culture), in this research were  Used  analytical descriptive  style . This research aims to identify the correlation and impact  of Staffing strategy at high-performance in Ministry of Agriculture , To clarify the relationship between

Many academics have concentrated on applying machine learning to retrieve information from databases to enable researchers to perform better. A difficult issue in prediction models is the selection of practical strategies that yield satisfactory forecast accuracy. Traditional software testing techniques have been extended to testing machine learning systems; however, they are insufficient for the latter because of the diversity of problems that machine learning systems create. Hence, the proposed methodologies were used to predict flight prices. A variety of artificial intelligence algorithms are used to attain the required, such as Bayesian modeling techniques such as Stochastic Gradient Descent (SGD), Adaptive boosting (ADA), Deci

Many academics have concentrated on applying machine learning to retrieve information from databases to enable researchers to perform better. A difficult issue in prediction models is the selection of practical strategies that yield satisfactory forecast accuracy. Traditional software testing techniques have been extended to testing machine learning systems; however, they are insufficient for the latter because of the diversity of problems that machine learning systems create. Hence, the proposed methodologies were used to predict flight prices. A variety of artificial intelligence algorithms are used to attain the required, such as Bayesian modeling techniques such as Stochastic Gradient Descent (SGD), Adaptive boosting (ADA), Decision Tre