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Study of Sunspot Effect on Radio Jove Telescope Observation

In this research, study the effect of sunspots on electromagnetic radio signals when it passed through F layer. The evaluation for this effect is carried out on radio Jove telescope frequency (20.1MHz) observations result. Radio emission for Jupiter storm burst observations over 11 years (1999-2009) from Hawaii, USA station (about 37611observations must be attended), are used in this research.
Two data limitations are applied on number of observation for Hawaii station, first due station location, second due to the reception of telescope antenna. The number of observations are reduced to 337 due to these limitation, but the actual number that be detected by station telescope is only 20.A model for ionospherical effect ,only due to sunspot number in observation day, is achieved in this paper. The behavior of this effect depending on actual observations (20 observations) is represented by polynomial equation of order degree three. The range of K sunspot value according the effect curve representation is determined by difference calculation between actual observation day sunspot number and the sunspot number must be to achieve the model curve this range is 2

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Publication Date
Sun Apr 15 2018
Journal Name
Strojniški Vestnik - Journal Of Mechanical Engineering
Comparative Experimental and Numerical Investigation on Electrical Discharge Drilling of AISI 304 using Circular and Elliptical Electrodes

This work introduces a new electrode geometry for making holes with high aspect ratios on AISI 304 using an electrical discharge drilling (EDD) process. In addition to commercially available cylindrical hollow electrodes, an elliptical electrode geometry has been designed, manufactured, and implemented. The principal aim was to improve the removal of debris formed during the erosion process that adversely affects the aspect ratio, dimensional accuracy, and surface integrity. The results were compared and discussed to evaluate the effectiveness of electrode geometry on the machining performance of EDD process with respect to the material removal rate (MRR,) the electrode wear rate (EWR), and the tool wear ratio (TWR). Dimensional features an

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Publication Date
Mon Feb 01 2016
Journal Name
Journal Of Economics And Administrative Sciences
International variables and their impact on the flow of foreign direct investment in Gulf Cooperation Council (GCC)

Abstract:

The six Arab Gulf states (Bahrain, Kuwait, Oman, Qatar, Saudi Arabia, UAE) play a vital role, especially with its geographical location and natural  resources (oil and gas) as well as other cultural and civilizational elements, in achieving  global economic balance and more specifically global energy security, naturally  because of  these countries have a comparative advantage in the field of fossil energy (oil and gas), thus this sector becomes more attractive for local and international investments alike. Being  the energy sector a leader sector in the economic development process, and the basic factor to achieve savings and financial surpluses in thes

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Publication Date
Wed Aug 30 2023
Journal Name
Iraqi Journal Of Science
IoT-Key Agreement Protocol Based on The Lowest Work-Load Versions of The Elliptic Curve Diffie-Hellman

     A key agreement protocol (KAP) is a fundamental block in any cryptosystem since it ensures secure communication between two parties. Furthermore, KAP should include advanced features in limited-resource environments such as IoT, in which this protocol must be lightweight and efficient in consuming resources. Despite the Elliptic Curve Diffie-Hellman (ECDH) algorithm having often been considered efficient in providing an acceptable security degree with less resource consumption, it has suffered from weakness against Man-In-The-Middle Attacks (MITMA). This paper presents two versions of the Variant Elliptic Curve Diffie-Hellman (VECDH) algorithms as a key agreement protocol. The security analysis indicates that the proposed algori

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Publication Date
Thu Apr 13 2023
Journal Name
International Journal Of Research In Social Sciences And Humanities
Subject Review: The Effectiveness Of Integrating E-Learning On Learning Outcome And Student Perceptions In Tertiary Education

The literature shows conflicting outcomes, making it difficult to determine how e-learning affects the performance of students in higher education. The effect of e-learning was studied and data has been gathered with the utilization of a variety of qualitative and quantitative methods, especially in relation to students' academic achievements and perceptions in higher education, according to literature review that has been drawn from articles published in the past two decades (2000-2020). The development of a sense of community in the on-line environment has been identified to be one of the main difficulties in e-learning education across this whole review. In order to create an efficient online learning community, it could be claim

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Publication Date
Thu Mar 30 2023
Journal Name
Iraqi Journal Of Science
Detection and Mitigation of Cache Pollution Attack Using Popularity Variation in Information Centric Networking Based on SDN

      Information centric networking (ICN) is the next generation of internet architecture with its ability to provide in-network caching that make users retrieve their data efficiently regardless of their location. In ICN, security is applied to data itself rather than communication channels or devices. In-network caches are vulnerable to many types of attacks, such as cache poisoning attacks, cache privacy attacks, and cache pollution attacks (CPA). An attacker floods non-popular content to the network and makes the caches evict popular ones. As a result, the cache hit ratio for legitimate users will suffer from a performance degradation and an increase in the content’s retrieval latency. In this paper, a popularity variation me

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Publication Date
Thu Jul 20 2023
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Bayesian Approach for estimating the unknown Scale parameter of Erlang Distribution Based on General Entropy Loss Function

We are used Bayes estimators for unknown scale parameter  when shape Parameter  is known of Erlang distribution. Assuming different informative priors for unknown scale  parameter. We derived The posterior density with posterior mean and posterior variance using different informative priors for unknown scale parameter  which are the inverse exponential distribution, the inverse chi-square distribution, the inverse Gamma distribution, and the standard Levy distribution as prior. And we derived Bayes estimators based on the general entropy loss function (GELF) is used the Simulation method to obtain the results. we generated different cases for the parameters of the Erlang model, for different sample sizes. The estimates have been comp

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Publication Date
Mon Feb 01 2021
Journal Name
Https://www.researchgate.net/journal/university-of-baghdad-engineering-journal-1726-4073
Electrical Conductivity as a General Predictor of Multiple Parameters in Tigris River Based on Statistical Regression Model

Surface water samples from different locations within Tigris River's boundaries in Baghdad city have been analyzed for drinking purposes. Correlation coefficients among different parameters were determined. An attempt has been made to develop linear regression equations to predict the concentration of water quality constituents having significant correlation coefficients with electrical conductivity (EC). This study aims to find five regression models produced and validated using electrical conductivity as a predictor to predict total hardness (TH), calcium (Ca), chloride (Cl), sulfate (SO4), and total dissolved solids (TDS). The five models showed good/excellent prediction ability of the parameters mentioned above, which is a very

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Publication Date
Mon Mar 20 2017
Journal Name
International Journal Of Social Sciences
THE EFFECTIVENESS OF USING YOUTUBE VIDEO ON EFL IRAQI COLLEGE STUDENTS' PERFORMANCE IN GRAMMAR AT MISSAN UNIVERSITY

FR Almoswai, BN Rashid, PEOPLE: International Journal of Social Sciences, 2017 - Cited by 22

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Publication Date
Thu Oct 29 2020
Journal Name
Complexity
Training and Testing Data Division Influence on Hybrid Machine Learning Model Process: Application of River Flow Forecasting

The 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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Publication Date
Sun Nov 01 2020
Journal Name
Iop Conference Series: Materials Science And Engineering
SDN-RA: An Optimized Reschedule Algorithm of SDN Load Balancer for Data Center Networks Based on QoS
Abstract<p>With the development of cloud computing during the latest years, data center networks have become a great topic in both industrial and academic societies. Nevertheless, traditional methods based on manual and hardware devices are burdensome, expensive, and cannot completely utilize the ability of physical network infrastructure. Thus, Software-Defined Networking (SDN) has been hyped as one of the best encouraging solutions for future Internet performance. SDN notable by two features; the separation of control plane from the data plane, and providing the network development by programmable capabilities instead of hardware solutions. Current paper introduces an SDN-based optimized Resch</p> ... Show More
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