. 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

The effect of annealing on the structural and optical properties of Antimony trisulfide (Sb2S3) is investigated. Sb2S3 powder is vaporized on clean glass substrates at room temperature under high vacuum pressure to form thin films. The structural research was done with the aid of X-ray diffraction (XRD) and atomic force microscopy (AFM). The amorphous to the polycrystalline transformation of these thin films was shown by X-ray diffraction analysis after thermal annealing. These films' morphology is explained. The absorption coefficient and optical energy gap of the investigated films are calculated using transmission spectra. Both samples have strong absorption in the visible spectrum, according to UV-visible absorption spectra. The optical

The crystal structure and unit cell dimensions of the (S03) compound have  been determined by employing the principles of crystallography.

The X-Ray diffraction spectra of (Sb203) which recorded as a function  of   different  annealing  temperatures  (100,150,200  and

250)±5c and for durations (0.5  hr,

0

1hr, l.Shr and 2hr), showed a

noticeable improvement, a decreasing in the unit cell dimensions and

an increasing in the number of diffraction spectra.

Indexing of diffraction spectra and refinement of  unit cell

dimensions showed that the compound (Sb203)  which is a

In this study, the effect of the annealing temperature on the material properties and the structural properties of cuprous oxide was studied in order to investigate how the annealing temperature affects the material properties, and the temperature varied between 200℃, 300℃, 400℃ and 500 ℃ and was unannealed. The physical properties of the cuprous oxide were measured by X-ray diffraction (XRD). The XRD patterns showed that the Cu₂O nanoparticles were highly pure, crystalline, and nano-sized. From the XRD results, we found the pure cuprite (Cu₂O) phase. The values of crystal size were discovered and calculated by the Halder-Wagner and Size-Strain Plot (SSP) methods, respectively. The crystallite size increased

Nanocrystalline TiO 2 and CuO doped TiO 2 thin films were successfully deposited on suitably cleaned glass substrate at constant room temperature and different concentrations of CuO (0.05,0.1,0.15,0.2) wt% using pulse laser deposition(PLD) technique at a constant deposition parameter such as : (pulse Nd:YAG laser with λ=1064 nm, constant energy 800 mJ, with repetition rate 6 Hz and No. of pulse (500). The films were annealed at different annealing temperatures 423K and 523 K. The effect of annealing on the morphological and electrical properties was studied. Surface morphology of the thin films has been studied by using atomic force microscopes which showed that the films have good crystalline and homogeneous surface. The Root M

In this research, thin films of CdO: Mg and n-CdO: Mg/ p-Si heterojunction with thickness (500±50) nm have been deposited at R.T (300 K) by thermal evaporation technique. These samples have been annealed at different annealing temperatures (373 and 473) K for one hour. Structural, optical and electrical properties of {CdO: Mg (1%)} films deposited on glass substrate as a function of annealing temperature are studied in detail. The C-V measurement of n-CdO: Mg/ p-Si heterojunction (HJ) at frequency (100 KHz) at different annealing temperatures have shown that these HJ were of abrupt type and the builtin potential (Vbi) increase as the annealing temperature increases. The I-V characteristics of heterojunction prepared under dark case at

 The transfer function model the basic concepts in the time series. This model is used in the case of multivariate time series. As for the design of this model, it depends on the available data in the time series and other information in the series so when the representation of the transfer function model depends on the representation of the data In this research, the transfer function has been estimated using the style nonparametric represented in two method  local linear regression and cubic smoothing spline method The method of semi-parametric represented use semiparametric single index model, With four proposals, , That the goal of this research is comparing the capabilities of the above mentioned m

The advancements in horizontal drilling combined with hydraulic fracturing have been historically proven as the most viable technologies in the exploitation of unconventional resources (e.g., shale and tight gas reservoirs). However, the number of fractures, well timing, and arrangement pattern can have a significant impact on the project economy. Therefore, such design and operating parameters need to be efficiently optimized for obtaining the best production performance from unconventional gas reservoirs. In this study, the process of selecting the optimal number of fractures was conducted on a section of a tight gas reservoir model (based on data from the Whicher Range (WR) tight gas field in Western Australia). Then, the optimal number

Nowadays, cloud computing has attracted the attention of large companies due to its high potential, flexibility, and profitability in providing multi-sources of hardware and software to serve the connected users. Given the scale of modern data centers and the dynamic nature of their resource provisioning, we need effective scheduling techniques to manage these resources while satisfying both the cloud providers and cloud users goals. Task scheduling in cloud computing is considered as NP-hard problem which cannot be easily solved by classical optimization methods. Thus, both heuristic and meta-heuristic techniques have been utilized to provide optimal or near-optimal solutions within an acceptable time frame for such problems. In th