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 accuracy criterion and matching curve-fitting in this work demonstrated that if the residuals of the revised model are white noise, the forecasts are unbiased. Future work investigating robust hybrid model forecasting using fuzzy neural networks would be very interesting.
<span lang="EN-GB">Transmitting the highest capacity throughput over the longest possible distance without any regeneration stage is an important goal of any long-haul optical network system. Accordingly, Polarization-Multiplexed Quadrature Phase-Shift-Keying (PM-QPSK) was introduced lately to achieve high bit-rate with relatively high spectral efficiency. Unfortunately, the required broad bandwidth of PM-QPSK increases the linear and nonlinear impairments in the physical layer of the optical fiber network. Increased attention has been spent to compensate for these impairments in the last years. In this paper, Single Mode Fiber (SMF), single channel, PM-QPSK transceiver was simulated, with a mix of optical and electrical (Digi
... Show MoreTV medium derives its formal shape from the technological development taking place in all scientific fields, which are creatively fused in the image of the television, which consists mainly of various visual levels and formations. But by the new decade of the second millennium, the television medium and mainly (drama) became looking for that paradigm shift in the aesthetic formal innovative fields and the advanced expressive performative fields that enable it to develop in treating what was impossible to visualize previously. In the meantime, presenting what is new and innovative in the field of unprecedented and even the familiar objective and intellectual treatments. Thus the TV medium has sought for work
... Show MoreUntil recently, researchers have utilized and applied various techniques for intrusion detection system (IDS), including DNA encoding and clustering that are widely used for this purpose. In addition to the other two major techniques for detection are anomaly and misuse detection, where anomaly detection is done based on user behavior, while misuse detection is done based on known attacks signatures. However, both techniques have some drawbacks, such as a high false alarm rate. Therefore, hybrid IDS takes advantage of combining the strength of both techniques to overcome their limitations. In this paper, a hybrid IDS is proposed based on the DNA encoding and clustering method. The proposed DNA encoding is done based on the UNSW-NB15
... Show MoreIn this research,we are studied impact strength, bending and compression strength of composites including the epoxy resin as a matrix , with gawaian red wood flour ,Russian white wood flour ,glass powder and rock wool fibers as reinforcement materials with volume fraction (20%) for all samples,and compared them in different conditions of temperatures. The results have shown that the impact strength increased with the reinforcement with (particles and fibers),and at high temperatures for all samples prepared,and also observed an increase in elasticity coefficient of epoxy composites filled with (different particles) and decreased in elasticity coefficient of epoxy com
... Show MoreImage compression plays an important role in reducing the size and storage of data while increasing the speed of its transmission through the Internet significantly. Image compression is an important research topic for several decades and recently, with the great successes achieved by deep learning in many areas of image processing, especially image compression, and its use is increasing Gradually in the field of image compression. The deep learning neural network has also achieved great success in the field of processing and compressing various images of different sizes. In this paper, we present a structure for image compression based on the use of a Convolutional AutoEncoder (CAE) for deep learning, inspired by the diversity of human eye
... Show MoreThis paper focuses on developing a self-starting numerical approach that can be used for direct integration of higher-order initial value problems of Ordinary Differential Equations. The method is derived from power series approximation with the resulting equations discretized at the selected grid and off-grid points. The method is applied in a block-by-block approach as a numerical integrator of higher-order initial value problems. The basic properties of the block method are investigated to authenticate its performance and then implemented with some tested experiments to validate the accuracy and convergence of the method.
In the hybrid coolingsolar systems , a solar collectoris used to convertsolar energy intoheat sourcein order to super heat therefrigerant leave thecompressor,andthisprocess helpsin the transformation ofrefrigerant state from gaseous statetothe liquid statein upper two-thirdsof thecondenserinstead of the lower two-thirdssuchas in thetraditional air-conditioning systems and this willreduce theenergyneeded torun the process ofcooling.In this research two hybrid air-conditioning system with an evacuated tube solar collector were used, therefrigerant was R22 and the capacity was 2 tons each.The tilt angle of the evacuated tube solar collector was changed and the solar collector fluid was replaced into oil instead of water.A comparison wasi
... Show MoreIn this research, the nonparametric technique has been presented to estimate the time-varying coefficients functions for the longitudinal balanced data that characterized by observations obtained through (n) from the independent subjects, each one of them is measured repeatedly by group of specific time points (m). Although the measurements are independent among the different subjects; they are mostly connected within each subject and the applied techniques is the Local Linear kernel LLPK technique. To avoid the problems of dimensionality, and thick computation, the two-steps method has been used to estimate the coefficients functions by using the two former technique. Since, the two-
... Show MoreThis study aimed at evaluating the torsional capacity of reinforced concrete (RC) beams externally wrapped with fiber reinforced polymer (FRP) materials. An analytical model was described and used as a new computational procedure based on the softened truss model (STM) to predict the torsional behavior of RC beams strengthened with FRP. The proposed analytical model was validated with the existing experimental data for rectangular sections strengthened with FRP materials and considering torque-twist relationship and crack pattern at failure. The confined concrete behavior, in the case of FRP wrapping, was considered in the constitutive laws of concrete in the model. Then, an efficient algorithm was developed in MATLAB environment t
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