This study aimed to analyze and measure the relationship between oil revenues and financial sustainability in Iraq, the study used the stylistic approach inductive and deductive approach. Accompanied by the use of quantitative and analytical style, which was based on two variables oil revenues and net general budget on annual data covered the period (1990-2013). Among the most important findings of the study contain the time-series variables study on the root of the unit and is not stable in the general level, and become stable after the use of mathematical processors to gain access to a stable by taking the first difference of natural Ogartm of the series. The way (Johnson) to a long-term relationship between oil revenues and ne

Diagram of CFIA system: (A) Fe ³⁺ line; (B) SCN ⁻ line; (C) A.A carrier; (D) sample valve; (E) mixing/reaction coil quenched by A.A; (F) blue LED detector.

In this work, polyvinylpyrrolidone (PVP), Multi-walled carbon nanotubes (MWCNTs) nanocomposite was prepared and hybrid with Graphene (Gr) by casting method. The morphological and optical properties were investigated. Fourier Transformer-Infrared (FT-IR) indicates the presence of primary distinctive peaks belonging to vibration groups that describe the prepared samples. Scanning Electron Microscopy (SEM) images showed a uniform dispersion of graphene within the PVP-MWCNT nanocomposite. The results of the optical study show decrease in the energy gap with increasing MWCNT and graphene concentration. The absorption coefficient spectra indicate the presence of two absorption peaks at 282 and 287 nm attributed to the π-π* electronic tr

The performance and durability of asphalt pavements are strongly influenced by the rheological properties of asphalt binders, particularly under severe climatic and traffic conditions. This study investigates the synergistic effects of incorporating multi-walled carbon nanotubes (CNTs) at dosages ranging from 0.25% to 1% into AC 40-50 asphalt binders modified with 4% Styrene–Butadiene–Styrene (SBS). A comprehensive experimental program involving physical, rheological, and chemical characterization tests was conducted, including penetration, softening point, viscosity, storage stability, a Dynamic Shear Rheometer (DSR), Multiple Stress Creep Recovery (MSCR), Linear Amplitude Sweep (LAS), Fourier Transform Infrared Spectroscopy (F

Big data analysis has important applications in many areas such as sensor networks and connected healthcare. High volume and velocity of big data bring many challenges to data analysis. One possible solution is to summarize the data and provides a manageable data structure to hold a scalable summarization of data for efficient and effective analysis. This research extends our previous work on developing an effective technique to create, organize, access, and maintain summarization of big data and develops algorithms for Bayes classification and entropy discretization of large data sets using the multi-resolution data summarization structure. Bayes classification and data discretization play essential roles in many learning algorithms such a