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.
In this work, a new development of predictive voltage-tracking control algorithm for Proton Exchange Membrane Fuel Cell (PEMFCs) model, using a neural network technique based on-line auto-tuning intelligent algorithm was proposed. The aim of proposed robust feedback nonlinear neural predictive voltage controller is to find precisely and quickly the optimal hydrogen partial pressure action to control the stack terminal voltage of the (PEMFC) model for N-step ahead prediction. The Chaotic Particle Swarm Optimization (CPSO) implemented as a stable and robust on-line auto-tune algorithm to find the optimal weights for the proposed predictive neural network controller to improve system performance in terms of fast-tracking de
... Show MoreObjective(s): The study aims to evaluating the quality of nursing care provided to children under five years to compare between quality related to type of health sectors; to determine the quality of nursing care and to compare between such care in Baquba Health Care Sector I and II.
Methodology: A descriptive study is carried out for the period from December 15th 2019 to May 1st 2020. A purposive "non- probability" sample, of (60) staff nurse and (60) children is selected. An adopted questionnaire has been selected for the study which consists of three parts. The first part is nurses’ socio-demographic characteristic; the second part is ch
... Show MoreIn this paper, an intelligent tracking control system of both single- and double-axis Piezoelectric Micropositioner stage is designed using Genetic Algorithms (GAs) method for the optimal Proportional-Integral-Derivative (PID) controller tuning parameters. The (GA)-based PID control design approach is a methodology to tune a (PID) controller in an optimal control sense with respect to specified objective function. By using the (GA)-based PID control approach, the high-performance trajectory tracking responses of the Piezoelectric Micropositioner stage can be obtained. The (GA) code was built and the simulation results were obtained using MATLAB environment. The Piezoelectric Micropositioner simulation model with th
... Show MoreHeuristic approaches are traditionally applied to find the optimal size and optimal location of Flexible AC Transmission Systems (FACTS) devices in power systems. Genetic Algorithm (GA) technique has been applied to solve power engineering optimization problems giving better results than classical methods. This paper shows the application of GA for optimal sizing and allocation of a Static Compensator (STATCOM) in a power system. STATCOM devices used to increase transmission systems capacity and enhance voltage stability by regulate the voltages at its terminal by controlling the amount of reactive power injected into or absorbed from the power system. IEEE 5-bus standard system is used as an example to illustrate the te
... Show Moreسها علي حسين, هويدة إسماعيل إبراهيم, Journal of Physical Education, 2017 - Cited by 1
Severe periodontitis is ranked as the sixth most prevalent disease affecting humankind, with an estimated 740 million people affected worldwide. The diagnosis of periodontal diseases mainly relies upon assessment of conventional clinical parameters. However, these parameters reflect past, rather than current, clinical status or future disease progression and, likely, outcome of periodontal treatment. Specific and sensitive biomarkers for periodontal diseases have been examined widely to address these issues and some biomarkers have been translated as point-of-care (PoC) tests. The aim of this review was to provide an update on PoC tests for use in the diagnosis and management of periodontal diseases. Among the PoC tests developed so
... Show MoreThis study has been conducted to examin the effect of sodium propionate at different level of 0.03,0.06,0.10% on the number of bacteria and mold and to extend the storage life of laboratory processed biscuit. The results indicated that the use of 0.10% sodium propionate prolonged the storage peroid until the third month, while the use of 0.20% sodium propionate showed no growth of bacteria up to six month of storage, three types of bacteria has been isolated from processed biscuit, namely, Staphylococcus aureus, Bacillus cereus, Esherichia coli. using 0.10% sodium propionate showed no growth of mold up to three month of storage ,while using of 0.15 % and 0.20% sodium propionate prevent the growth
... Show MoreThis study has been conducted to examin the effect of potassium sorbate at different level of 0.03,0.06,0.10% on the number of bacteria and mold and to extend the storage life of laboratory processed biscuit. The results indicated that the use of 0.03% potassium sorbate prolonged the storage peroid until the third month .three types of bacteria has been isolated from processed biscuit, namely, Staphylococcus aureus, Bacillus cereus, Esherichia coli using 0.06% potassium sorbate showed no growth of bacteria up to six month of storage ,while using of 0.03% and 0.06% potassium sorbate prevent the growth of mold up to three and six months of storage respectively. Both Aspergillus and Penicillium were isolated from the processed biscuit.