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Distributed Heuristic Algorithm for Migration and Replication of Self-organized Services in Future Networks
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Nowadays, the mobile communication networks have become a consistent part of our everyday life by transforming huge amount of data through communicating devices, that leads to new challenges. According to the Cisco Networking Index, more than 29.3 billion networked devices will be connected to the network during the year 2023. It is obvious that the existing infrastructures in current networks will not be able to support all the generated data due to the bandwidth limits, processing and transmission overhead. To cope with these issues, future mobile communication networks must achieve high requirements to reduce the amount of transferred data, decrease latency and computation costs. One of the essential challenging tasks in this subject area is the optimal self-organized service placement. In this paper a heuristic-based algorithm for service placement in future networks was presented. This algorithm achieves the ideal placement of services replicas by monitoring the load within the server and its neighborhood, choosing the node that contributes with the highest received load, and finally replicating or migrating the service to it based on specific criteria, so that the distance of requests coming from clients becomes as small as possible because of placing services within nearby locations. It was proved that our proposed algorithm achieves an improved performance by meeting the services within a shorter time, a smaller bandwidth, and thus a lower communication cost. It was compared with the traditional client-server approach and the random placement algorithm. Experimental results showed that the heuristic algorithm outperforms other approaches and meets the optimal performance with different network sizes and varying load scenarios.

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Publication Date
Fri Jan 01 2016
Journal Name
International Journal Of Advanced Computer Science And Applications
Automatic Approach for Word Sense Disambiguation Using Genetic Algorithms
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Abstract: Word sense disambiguation (WSD) is a significant field in computational linguistics as it is indispensable for many language understanding applications. Automatic processing of documents is made difficult because of the fact that many of the terms it contain ambiguous. Word Sense Disambiguation (WSD) systems try to solve these ambiguities and find the correct meaning. Genetic algorithms can be active to resolve this problem since they have been effectively applied for many optimization problems. In this paper, genetic algorithms proposed to solve the word sense disambiguation problem that can automatically select the intended meaning of a word in context without any additional resource. The proposed algorithm is evaluated on a col

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Publication Date
Mon Jun 04 2018
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Darifenacin Hydrobromide loaded nanostructured lipid carrier for oral administration
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Darifenacin hydrobromide is a selective ?3 receptor antimuscarinic drug and it is used in the management of urinary frequency, urgency, and incontinence in detrusor instability. It slightly soluble in water, undergoes extensive hepatic first-pass metabolism and has short elimination half-life (3–4 hours). Therefore, It has low bioavailability (15.4 % - 18.6 %). Darifenacin hydrobromide loaded NLCs were formulated by emulsification sonication using different ratios of solid lipid to liquid lipid, different types of surfactants, and different concentration of surfactants. Formula sixteen was considered as an optimized formula based on its particle size, PDI, zeta potential and entrapment efficiency. Formula sixteen subjected t

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Publication Date
Sun Jun 30 2013
Journal Name
Al-kindy College Medical Journal
Diabetes Mellitus as a Risk Factor for Pulmonary Tuberculosis
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Background: In the past, an association between Tuberculosis (TB) and Diabetes Mellitus (DM) was widely accepted, today the potential public health and clinical importance of this relationship seems to be largely ignored. The national clinical and policy guidance in the UK on the central of TB, for example, does not consider the relationship with DM.Objectives: To determine the risk of association between diabetes mellitus and pulmonary TB.Methods: A retrospective study conducted in Ibn Zuhr hospital for chest diseases from Jan 2008 – sep 2010 , included in the study 402 patients with TB divided into diabetic & non diabetic, 96 (23.8%) were diabetic while other 306 were TB not diabetic.Results: Risk of TB among DM patients were cle

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Publication Date
Mon Jun 19 2023
Journal Name
Journal Of Engineering
OPTIMUM WATER ALLOCATION FOR ABO-ZIRIQ MARSH ECOLOGICAL RESTORATION
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Optimum allocation of water for restoration of Iraqi marshes is essential for different related authorities. Abo-Ziriq marsh area about 120 km2 is situated 40 km east of Al-Nassryia city. After comparing the measured annual water qualities with the Iraqi standards for surface water quality evaluation, Abo-Ziriq marsh water quality was in acceptable limit. Hydro balance computation were done for each month by using interface among the HEC-RAS, HEC-GeoRAS and ArcView GIS software and built a number of eco-hydro relationships to simulate the marsh ecosystem by using HEC-EFM program to estimate water allocation adequate for ecosystem requirement and constructs a GIS hydraulic reference map to show inundation area, depth grid and velocity dis

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Publication Date
Thu Dec 01 2011
Journal Name
Proceedings Of 2011 International Conference On Computer Science And Network Technology
A new proposed handoff scheme for mobile communication systems
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There are many studies dealt with handoff management in mobile communication systems and some of these studies presented handoff schemes to manage this important process in cellular network. All previous schemes used relative signal strength (RSS) measurements. In this work, a new proposed handoff scheme had been presented depending not only on the RSS measurements but also used the threshold distance and neighboring BSS power margins in order to improve the handoff management process. We submitted here a threshold RSS as a condition to make a handoff when a mobile station moves from one cell to another this at first, then we submitted also a specified margin between the current received signal and the ongoing BS's received signal must be s

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Publication Date
Fri Nov 01 2013
Journal Name
Al-nahrain Journal Of Science
Modified third order iterative method for solving nonlinear equations
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Many numerical approaches have been suggested to solve nonlinear problems. In this paper, we suggest a new two-step iterative method for solving nonlinear equations. This iterative method has cubic convergence. Several numerical examples to illustrate the efficiency of this method by Comparison with other similar methods is given.

Publication Date
Thu Jun 15 2017
Journal Name
Ieee Sensors Journal
Calibrating Distance Sensors for Terrestrial Applications Without Groundtruth Information
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Publication Date
Sat Jan 01 2022
Journal Name
Aip Conference Proceedings
The best interpolation methods for evaluate water table pollution
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Publication Date
Mon Mar 31 2025
Journal Name
Iraqi Statisticians Journal
Hypothesis Testing for Non-Normal Multiple Compact Regression Model
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Generalized multivariate transmuted Bessel distribution belongs to the family of probability distributions with a symmetric heavy tail. It is considered a mixed continuous probability distribution. It is the result of mixing the multivariate Gaussian mixture distribution with the generalized inverse normal distribution. On this basis, the paper will study a multiple compact regression model when the random error follows a generalized multivariate transmuted Bessel distribution. Assuming that the shape parameters are known, the parameters of the multiple compact regression model will be estimated using the maximum likelihood method and Bayesian approach depending on non-informative prior information. In addition, the Bayes factor was used

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Publication Date
Mon Dec 20 2021
Journal Name
Baghdad Science Journal
Generative Adversarial Network for Imitation Learning from Single Demonstration
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Imitation learning is an effective method for training an autonomous agent to accomplish a task by imitating expert behaviors in their demonstrations. However, traditional imitation learning methods require a large number of expert demonstrations in order to learn a complex behavior. Such a disadvantage has limited the potential of imitation learning in complex tasks where the expert demonstrations are not sufficient. In order to address the problem, we propose a Generative Adversarial Network-based model which is designed to learn optimal policies using only a single demonstration. The proposed model is evaluated on two simulated tasks in comparison with other methods. The results show that our proposed model is capable of completing co

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