Information security contributes directly to increase the level of trust between the government’s departments by providing an assurance of confidentiality, integrity, and availability of sensitive governmental information. Many threats that are caused mainly by malicious acts can shutdown the egovernment services. Therefore the governments are urged to implement security in e-government projects.
Some modifications were proposed to the security assessment multi-layer model (Sabri model) to be more comprehensive model and more convenient for the Iraqi government. The proposed model can be used as a tool to assess the level of security readiness of government departments, a checklist for the required security measures and as a common security reference in the government organizations of Iraq. In order to make this model more practical, applicable and to represent the security readiness with a numerical value, evaluation modeling has been done for this model by using fuzzy logic tool of MATLAB R2010a program.
Since the risk assessment is considered as a major part in the information security management system, an effective and practical method to assess security risk is proposed by combining FEMRA (fuzzy expert model risk assessment) and Wavelet Neural Network (WNN). The fuzzy system is used to generate the training data set in order to make the required training for WNN. The proposed method is applied when a risk assessment case study is made at the computer center of Baghdad University. It is found from the numerical results that the risk levels obtained by WNN are (with maximum of 58.23) too close to these calculated from FEMRA (with maximum of 60), with an average error of 5.51%. According to these results, the proposed method is effective and reasonable and can provide the support toward establishing the e-government.
Maximum power point tracking (MPPT) is used in photovoltaic (PV) systems to enhance efficiency and maximize the output power of PV module, regardless the variation of temperature, irradiation, and the electrical characteristics of the load. A new MPPT system has been presented in this research, consisting of a synchronous DC-DC step-down Buck converter controlled by an Arduino microcontroller based unit. The MPPT process with Perturb and Observe method is performed with a DC-DC converter circuit to overcome the problem of voltage mismatch between the PV modules and the loads. The proposing system has high efficiency, lower cost and can be easily modified to handle more energy sources. The test results indicate that the u
... Show MoreEstablishing coverage of the target sensing field and extending the network’s lifetime, together known as Coverage-lifetime is the key issue in wireless sensor networks (WSNs). Recent studies realize the important role of nature-inspired algorithms in handling coverage-lifetime problem with different optimization aspects. One of the main formulations is to define coverage-lifetime problem as a disjoint set covers problem. In this paper, we propose an evolutionary algorithm for solving coverage-lifetime problem as a disjoint set covers function. The main interest in this paper is to reflect both models of sensing: Boolean and probabilistic. Moreover, a heuristic operator is proposed as a local refinement operator to improve the quality
... Show MoreIn this paper, the deterministic and the stochastic models are proposed to study the interaction of the Coronavirus (COVID-19) with host cells inside the human body. In the deterministic model, the value of the basic reproduction number determines the persistence or extinction of the COVID-19. If , one infected cell will transmit the virus to less than one cell, as a result, the person carrying the Coronavirus will get rid of the disease .If the infected cell will be able to infect all cells that contain ACE receptors. The stochastic model proves that if are sufficiently large then maybe give us ultimate disease extinction although , and this facts also proved by computer simulation.
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Social media and news agencies are major sources for tracking news and events. With these sources' massive amounts of data, it is easy to spread false or misleading information. Given the great dangers of fake news to societies, previous studies have given great attention to detecting it and limiting its impact. As such, this work aims to use modern deep learning techniques to detect Arabic fake news. In the proposed system, the attention model is adapted with bidirectional long-short-term memory (Bi-LSTM) to identify the most informative words in the sentence. Then, a multi-layer perceptron (MLP) is applied to classify news articles as fake or real. The experiments are conducted on a newly launched Arabic dataset called the Ara
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Before setting a turbine in a wind farms allocated for power generation, it must be know the appropriate turbine class for that site depending on the turbulence intensity of the winds in the studied area and the IEC-61400 standard. The importance of identifying a class of wind turbine is due to the complex environmental conditions that produce turbulent air which, in turn, may cause damage to the turbine blades and weakness in the performance. Therefore, the ambient turbulence intensity is a very important factor in determining the performance and productivity of the wind turbines.
In this research we calculate Turbulence Intensity "TI" in the province of Nasiriyah, south of Iraq (Lat. 31.052049 , Lon. 46.261021) for the years 2008, 2
Structure of network, which is known as community detection in networks, has received a great attention in diverse topics, including social sciences, biological studies, politics, etc. There are a large number of studies and practical approaches that were designed to solve the problem of finding the structure of the network. The definition of complex network model based on clustering is a non-deterministic polynomial-time hardness (NP-hard) problem. There are no ideal techniques to define the clustering. Here, we present a statistical approach based on using the likelihood function of a Stochastic Block Model (SBM). The objective is to define the general model and select the best model with high quality. Therefor
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Many developments happened in Service Oriented architecture models but with no details in its technology and requirement. This paper presents a new Service Oriented Architecture (SOA) to all Service Enterprise (SE) according to their demands. Therefore, the goal is to build a new complete architecture model for SOA methodologies according to current technology and business requirements that could be used in a real Enterprise environment. To do this, new types of services and new model called Lego Model are explained in details, and the results of the proposed architecture model in analyzed. Consequently, the complications are reduced to support business domains of enterprise and to start associating SOA methodologies in their corporate s
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It is recognized that organisms live and interact in groups, exposing them to various elements like disease, fear, hunting cooperation, and others. As a result, in this paper, we adopted the construction of a mathematical model that describes the interaction of the prey with the predator when there is an infectious disease, as well as the predator community's characteristic of cooperation in hunting, which generates great fear in the prey community. Furthermore, the presence of an incubation period for the disease provides a delay in disease transmission from diseased predators to healthy predators. This research aims to examine the proposed mathematical model's solution behavior to better understand these elements' impact on an eco-epidemi
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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 acc
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In this paper, a compartmental differential epidemic model of COVID-19 pandemic transmission is constructed and analyzed that accounts for the effects of media coverage. The model can be categorized into eight distinct divisions: susceptible individuals, exposed individuals, quarantine class, infected individuals, isolated class, infectious material in the environment, media coverage, and recovered individuals. The qualitative analysis of the model indicates that the disease-free equilibrium point is asymptotically stable when the basic reproduction number R0 is less than one. Conversely, the endemic equilibrium is globally asymptotically stable when R0 is bigger than one. In addition, a sensitivity analysis is conducted to determine which
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