Information systems and data exchange between government institutions are growing rapidly around the world, and with it, the threats to information within government departments are growing. In recent years, research into the development and construction of secure information systems in government institutions seems to be very effective. Based on information system principles, this study proposes a model for providing and evaluating security for all of the departments of government institutions. The requirements of any information system begin with the organization's surroundings and objectives. Most prior techniques did not take into account the organizational component on which the information system runs, despite the relevance of this feature in the application of access and control methods in terms of security. Based on this, we propose a model for improving security for all departments of government institutions by addressing security issues early in the system's life cycle, integrating them with functional elements throughout the life cycle, and focusing on the system's organizational aspects. The main security aspects covered are system administration, organizational factors, enterprise policy, and awareness and cultural aspects.
Reaxys Chemistry database information SciVal Topics Metrics Abstract A novel CoO–ZnO nanocomposite was synthesized by the photo irradiation method using a solution of cobalt and zinc complexes and used as a coating applied by electrophoretic deposition (EPD) for corrosion protection of stainless steel (SS) in saline solution. The samples were characterized using powder XRD, scanning electron microscopy (SEM) and electrochemical polarization. It was also found that the coating was still stable after conducting the corrosion test: it contained no cracks and CoO–ZnO nanocomposites clearly appeared on the surface. SEM showed that the significant surface cracking disappeared. XRD confirmed that CoO–ZnO nanocomposites comprised CoO and Zn
... Show MoreThe current paper proposes a new estimator for the linear regression model parameters under Big Data circumstances. From the diversity of Big Data variables comes many challenges that can be interesting to the researchers who try their best to find new and novel methods to estimate the parameters of linear regression model. Data has been collected by Central Statistical Organization IRAQ, and the child labor in Iraq has been chosen as data. Child labor is the most vital phenomena that both society and education are suffering from and it affects the future of our next generation. Two methods have been selected to estimate the parameter
... Show MoreThe hydrological process has a dynamic nature characterised by randomness and complex phenomena. The application of machine learning (ML) models in forecasting river flow has grown rapidly. This is owing to their capacity to simulate the complex phenomena associated with hydrological and environmental processes. Four different ML models were developed for river flow forecasting located in semiarid region, Iraq. The effectiveness of data division influence on the ML models process was investigated. Three data division modeling scenarios were inspected including 70%–30%, 80%–20, and 90%–10%. Several statistical indicators are computed to verify the performance of the models. The results revealed the potential of the hybridized s
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The concept of joint integration of important concepts in macroeconomic application, the idea of cointegration is due to the Granger (1981), and he explained it in detail in Granger and Engle in Econometrica (1987). The introduction of the joint analysis of integration in econometrics in the mid-eighties of the last century, is one of the most important developments in the experimental method for modeling, and the advantage is simply the account and use it only needs to familiarize them selves with ordinary least squares.
Cointegration seen relations equilibrium time series in the long run, even if it contained all the sequences on t
... Show MoreThe Machine learning methods, which are one of the most important branches of promising artificial intelligence, have great importance in all sciences such as engineering, medical, and also recently involved widely in statistical sciences and its various branches, including analysis of survival, as it can be considered a new branch used to estimate the survival and was parallel with parametric, nonparametric and semi-parametric methods that are widely used to estimate survival in statistical research. In this paper, the estimate of survival based on medical images of patients with breast cancer who receive their treatment in Iraqi hospitals was discussed. Three algorithms for feature extraction were explained: The first principal compone
... Show MoreA study to find the optimum separators pressures of separation stations has been performed. Stage separation of oil and gas is accomplished with a series of separators operating at sequentially reduced pressures. Liquid is discharged from a higher-pressure separator into the lower-pressure separator. The set of working separator pressures that yields maximum recovery of liquid hydrocarbon from the well fluid is the optimum set of pressures, which is the target of this work.
A computer model is used to find the optimum separator pressures. The model employs the Peng-Robinson equation of state (Peng and Robinson 1976) for volatile oil. The application of t
The seizure epilepsy is risky because it happens randomly and leads to death in some cases. The standard epileptic seizures monitoring system involves video/EEG (electro-encephalography), which bothers the patient, as EEG electrodes are attached to the patient’s head.
Seriously, helping or alerting the patient before the seizure is one of the issue that attracts the researchers and designers attention. So that there are spectrums of portable seizure detection systems available in markets which are based on non-EEG signal.
The aim of this article is to provide a literature survey for the latest articles that cover many issues in the field of designing portable real-time seizure detection that includes the use of multiple
... Show MoreIn this research a new system identification algorithm is presented for obtaining an optimal set of mathematical models for system with perturbed coefficients, then this algorithm is applied practically by an “On Line System Identification Circuit”, based on real time speed response data of a permanent magnet DC motor. Such set of mathematical models represents the physical plant against all variation which may exist in its parameters, and forms a strong mathematical foundation for stability and performance analysis in control theory problems.