This paper introduced an algorithm for lossless image compression to compress natural and medical images. It is based on utilizing various casual fixed predictors of one or two dimension to get rid of the correlation or spatial redundancy embedded between image pixel values then a recursive polynomial model of a linear base is used.

The experimental results of the proposed compression method are promising in terms of preserving the details and the quality of the reconstructed images as well improving the compression ratio as compared with the extracted results of a traditional linear predicting coding system.

In recent years, Bitcoin has become the most widely used blockchain platform in business and finance. The goal of this work is to find a viable prediction model that incorporates and perhaps improves on a combination of available models. Among the techniques utilized in this paper are exponential smoothing, ARIMA, artificial neural networks (ANNs) models, and prediction combination models. The study's most obvious discovery is that artificial intelligence models improve the results of compound prediction models. The second key discovery was that a strong combination forecasting model that responds to the multiple fluctuations that occur in the bitcoin time series and Error improvement should be used. Based on the results, the prediction acc

. In recent years, Bitcoin has become the most widely used blockchain platform in business and finance. The goal of this work is to find a viable prediction model that incorporates and perhaps improves on a combination of available models. Among the techniques utilized in this paper are exponential smoothing, ARIMA, artificial neural networks (ANNs) models, and prediction combination models. The study's most obvious discovery is that artificial intelligence models improve the results of compound prediction models. The second key discovery was that a strong combination forecasting model that responds to the multiple fluctuations that occur in the bitcoin time series and Error improvement should be used. Based on the results, the prediction a

Sickle cell disease (SCD) comprises an inherited blood disorder that is life long and affects many people globally. In spite of the development in treatment, SCA is a considerable cause of mortality and morbidity. The present study tries to assess the role of leukocytes represented by β integrin(CD18) and platelets and their productivity in the pathogenicity of disease during  the steady state and crisis in comparison with the healthy as-control group, SCD patients (15) enrolled during crisis and steady state (follow up) showed a significant increase in leukocytes and platelets cells productivity during crisis when compared to the steady state and in the steady state when compared to the healthy control group . In this study, SCD patho

   This paper suggesting a new modern method to evaluate the performance of hotel industry at Jordan instead of the classical method used by the industry and that is Bench Marking , this method can be done by comparing the performance of hotel industry at two serial years which helps in calculating a standard performance .

  The industry can use this standard to identify the variance, which make the evaluation of performance easier and support the efforts to develop the hotel industry at all levels and enable to give high quality services to customers.

    The study believed that this situation would not be achieved unless the hotel industry will app

Three important electrode arrays in 2D imaging surveys were tested in this study through synthetic model to determine which array is the most successful in defining the vertical and horizontal geological structures. These arrays are Wenner-Schlumberger, Wenner and Dipole - dipole. The numerical modeling was created through vertical fracture zone and three separate cavities surrounded by horizontal layers. The results showed that the Wenner-Schlumberger is the most suitable electrode array when both vertical and horizontal structures are present in the subsurface. It is the best in imaging the vertical and horizontal contacts and represented these structures more accurately than the Wenner and Dipole-dipole arrays.

The current study was applied in Al-Zafaraniya area southeast of the capital Baghdad from October 2021 to April 2022. This is to evaluate some heavy elements (Cd, Co, Cu, Fe, Pb, and Mn) in the street, storm, and suspended dust. Four sampling sites were selected, and codes A, B, C, and D were given to represent the industrial activity sites, service workshops, business activity, and residential areas.

        The results showed that the concentration rates of elements (Cd, Co, Cu, Fe, Pb, Mn) in street dust samples were (1.15, 6.6, 60.15, 26770, 44.4, 6, 489.8). In storm dust (2, 10, 49.3, 54760, 24.3, 827.2) ppm, respectively, the results of suspended dust revealed that the general rates of element concentrations were (0.7

Prediction of penetration rate (ROP) is important process in optimization of drilling due to its crucial role in lowering drilling operation costs. This process has complex nature due to too many interrelated factors that affected the rate of penetration, which make difficult predicting process. This paper shows a new technique of rate of penetration prediction by using artificial neural network technique. A three layers model composed of two hidden layers and output layer has built by using drilling parameters data extracted from mud logging and wire line log for Alhalfaya oil field. These drilling parameters includes mechanical (WOB, RPM), hydraulic (HIS), and travel transit time (DT). Five data set represented five formations gathered