The modern systems that have been based upon the hash function are more suitable compared to the conventional systems; however, the complicated algorithms for the generation of the invertible functions have a high level of time consumption. With the use of the GAs, the key strength is enhanced, which results in ultimately making the entire algorithm sufficient. Initially, the process of the key generation is performed by using the results of n-queen problem that is solved by the genetic algorithm, with the use of a random number generator and through the application of the GA operations. Ultimately, the encryption of the data is performed with the use of the Modified Reverse Encryption Algorithm (MREA). It was noticed that the

The main aim of this paper is to explain the effect of the aggregation accounting information on the financial, investment, and operational, managerial decision-making and the evaluation of the financial statements after aggregate. The problem of this study is represented in administrative decision-making that takes place under differentiated accounting systems operating within a governmental economic unit that seeks at the same time to achieve a unified vision and goals for the organization. This study was conducted at the College of Administration and Economics /University of Baghdad, and it represents a sample from a community of governmental economic units that apply differentiated accounting systems. The study method is repr

The aim of this study is to shed light on the importance of biofuels as an alternative to conventional energy, in addition to the importance of preserving agricultural crops, which are the main source of this fuel, to maintain food security, especially in developing countries. The increase in global oil prices, in addition to the fear of global warming, are among the main factors that draw the world’s attention to searching for alternative sources of traditional energy, which are sustainable on the one hand, and on the other hand reduce carbon emissions. Therefore, the volume of global investment in renewable energy in general, and in liquid biofuels and biomass in particular, has increased. Global fears emerged that the excessive convers

Digital tampering identification, which detects picture modification, is a significant area of image analysis studies. This area has grown with time with exceptional precision employing machine learning and deep learning-based strategies during the last five years. Synthesis and reinforcement-based learning techniques must now evolve to keep with the research. However, before doing any experimentation, a scientist must first comprehend the current state of the art in that domain. Diverse paths, associated outcomes, and analysis lay the groundwork for successful experimentation and superior results. Before starting with experiments, universal image forensics approaches must be thoroughly researched. As a result, this review of variou

Magnesium-doped Zinc oxide (ZnO: Mg) nanorods (NRs) films and pure Zinc oxide deposited on the p-silicon substrates were prepared by hydrothermal method. The doping level of the Mg concentration (atoms ratio of Mg to Zn was chosen to be 0.75% and 1.5%. X-ray diffraction (XRD) and energy-dispersive X-ray spectroscopy (EDX) were performed to characterize the prepared films. X-ray diffraction analysis showed a decrease in the lattice parameters of the Mg-doped ZnO NRs. Under 10V applied bias voltage, the responsivity of p-n junction UV photodiode based on pure ZnO and Mg: ZnO with doping ratio (0.75% and 1.5%) was 0.06 A/W and (0.15A/W and 0.27A/W) at UV illumination of wavelength 365 nm respectively, 0.071 A/W and (0.084A/W and 0.11A/W) fo

In this paper, a handwritten digit classification system is proposed based on the Discrete Wavelet Transform and Spike Neural Network. The system consists of three stages. The first stage is for preprocessing the data and the second stage is for feature extraction, which is based on Discrete Wavelet Transform (DWT). The third stage is for classification and is based on a Spiking Neural Network (SNN). To evaluate the system, two standard databases are used: the MADBase database and the MNIST database. The proposed system achieved a high classification accuracy rate with 99.1% for the MADBase database and 99.9% for the MNIST database

In this study, the response and behavior of machine foundations resting on dry and saturated sand was investigated experimentally. In order to investigate the response of soil and footing to steady state dynamic loading, a physical model was manufactured. The manufactured physical model could be used to simulate steady state harmonic load at different operating frequencies. Total of (84) physical models were performed. The parameters that were taken into considerations include loading frequency, size of footing and different soil conditions. The footing parameters were related to the size of the rectangular footing and depth of embedment. Two sizes of rectangular steel model footing were used (100 200 12.5 mm) and (200 400 5.0 mm).

When soft tissue planning is important, usually, the Magnetic Resonance Imaging (MRI) is a medical imaging technique of selection. In this work, we show a modern method for automated diagnosis depending on a magnetic resonance images classification of the MRI. The presented technique has two main stages; features extraction and classification. We obtained the features corresponding to MRI images implementing Discrete Wavelet Transformation (DWT), inverse and forward, and textural properties, like rotation invariant texture features based on Gabor filtering, and evaluate the meaning of every