Discrete   logarithms  are applied      in many    cryptographic problems  . For instance ,   in public   key .  and for construction of sets with disti nct sums of  k-clcments.  The   purpose o r  this   paper

is  to  modify  the  method ol' informationl1·iding  using        discrete logarithms  , introduce new properties of St - sets ,   uscdthe direct product   of    groups   to construct  cyclic group and finally, present modified   method   for   knapsack &

The consensus algorithm is the core mechanism of blockchain and is used to ensure data consistency among blockchain nodes. The PBFT consensus algorithm is widely used in alliance chains because it is resistant to Byzantine errors. However, the present PBFT (Practical Byzantine Fault Tolerance) still has issues with master node selection that is random and complicated communication. The IBFT consensus technique, which is enhanced, is proposed in this study and is based on node trust value and BLS (Boneh-Lynn-Shacham) aggregate signature. In IBFT, multi-level indicators are used to calculate the trust value of each node, and some nodes are selected to take part in network consensus as a result of this calculation. The master node is chosen

In this paper, a compact genetic algorithm (CGA) is enhanced by integrating its selection strategy with a steepest descent algorithm (SDA) as a local search method to give I-CGA-SDA. This system is an attempt to avoid the large CPU time and computational complexity of the standard genetic algorithm. Here, CGA dramatically reduces the number of bits required to store the population and has a faster convergence. Consequently, this integrated system is used to optimize the maximum likelihood function lnL(φ1, θ1) of the mixed model. Simulation results based on MSE were compared with those obtained from the SDA and showed that the hybrid genetic algorithm (HGA) and I-CGA-SDA can give a good estimator of (φ1, θ1) for the ARMA(1,1) model. Anot

This research aims to clarify the advantages of using the regression method as analytical procedure in the tax audit to reducing the examination cost , time, effort, human and material resources, and represents an applied study in the General Commission of taxes. In order to achieve its objectives the research has used in the theoretical side the descriptive approach (analytical), and in the practical side regression method has been applied to the research sample represented by the soft drinks company that is subject to the tax settlement for the year 2014, where the value of sales has been verified by using the regression method without conductinga comprehensive examination. The most important results of the research indicate that the r

Time series is an important statistical method adopted in the analysis of phenomena, practices, and events in all areas during specific time periods and predict future values ​​contribute to give a rough estimate of the status of the study, so the study aimed to adopt the ARIMA models to forecast the volume of cargo handled and achieved in four ports (Umm Qasr Port, Khor Al Zubair Port, Abu Flus Port, and Maqal Port(, Monthly data on the volume of cargo handled for the years (2006-2018) were collected (156) observations. The study found that the most efficient model is ARIMA (1,1,1).

The volume of go

     This research introduced the derivation of mathematical equations to calculate the Cartesian and geographical coordinates of a site situated at a far distance from the observer position by using GPS data. The geographical coordinates (Ï•obs., λ obs., hobs.) for observer position were transformed to Cartesian coordinates (X obs., Y obs., Z obs.) of observer position itself. Then the Cartesian coordinates of unknown position mathematically were calculated from these calculated equations, and its transformed to geographical coordinates of (Ï•unk., λunk.) position.
 

This research aims to clarify the importance of an accounting information system that uses artificial intelligence to detect earnings manipulation. The research problem stems from the widespread manipulation of earning in economic entities, especially at the local level, exacerbated by the high financial and administrative corruption rates in Iraq due to fraudulent accounting practices. Since earning manipulation involves intentional fraudulent acts, it is necessary to implement preventive measures to detect and deter such practices. The main hypothesis of the research assumes that an accounting information system based on artificial intelligence cannot effectively detect the manipulation of profits in Iraqi economic entities. The researche

     Tectonically, the location of the Al-Ma'aniyah depression area is far from active boundary zones, their tectonic features have to reflect the original depositional environments with some horizontal movement due to rearrangement of the basement blocks during different actives orogenic movements. So, the analysis of aeromagnetic data were considered to estimate the thickness and structural pattern of the sedimentary cover sequences for this area. The aeromagnetic data, which are derived from Iraqi GEOSURV to Al-Ma′aniyah region is analyzed and processed for qualitative and quantitative interpretations. The process includes reducing the aeromagnetic data to pole RTP, separation the aeromagnetic data to regional an