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A Spike Neural Controller for Traffic Load Parameter with Priority-Based Rate in Wireless Multimedia Sensor Networks
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Wireless Multimedia Sensor Networks (WMSNs) are a type of sensor network that contains sensor nodes equipped with cameras, microphones; therefore the WMSNS are able to   produce multimedia data such as video and audio streams, still images, and scalar data from the surrounding environment. Most multimedia applications typically produce huge volumes of data, this leads to congestion. To address this challenge, This paper proposes Modify Spike Neural Network control for Traffic Load Parameter with Exponential Weight of Priority Based Rate Control algorithm (MSNTLP with EWBPRC). The Modify Spike Neural Network controller (MSNC) can calculate the appropriate traffic load parameter μ for each parent node and then use in the EWPBRC algorithm to estimate the transmission rate of parent nodes and then assign a suitable transmission rate for each child node. A comparative study between (MSNTLP with EWBPRC) and fuzzy logic controller for traffic load parameter with Exponential Weight of Priority Based Rate Control algorithm (FTLP with EWBPRC) algorithm shows that the (MSNTLP with EWBPRC) is more efficient than (FTLP with EWBPRC) algorithm in terms of packet loss, queue delay and throughput. Another comparative study between (MSNTLP with EWBPRC) and EWBPRC with fixed traffic load parameter (µ) shows that the MSNTLP with EWBPRC is more efficient than EWBPRC with fixed traffic load parameter (µ) in terms of packet loss ratio and queue delay. A simulation process is developed and tested using the network simulator _2 (NS2) in a computer having the following properties: windows 7 (64-bit), core i7, RAM 8GB, hard 1TB.

 

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Publication Date
Thu Oct 31 2019
Journal Name
Journal Of Engineering And Applied Sciences
Feasibility Study of Applying a Pattern Waterflood Without and with Peripheral Injectors for Maximizing Oil Recovery Under Limited Water Sources Availability A Case Study of Heterogeneous Giant Carbonate Reservoir
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Publication Date
Thu Sep 12 2019
Journal Name
Al-kindy College Medical Journal
A Case Report -Bilateral Giant Achilles Tendon Xanthomas Resection with a Tendon transverse Technique
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Background : Xanthomatosis is a disease in which large tendon tumors can occur, especially in the Achilles tendon. This disease is a rare interesting orthopaedic condition.

Case Report:A case of a twenty eight year old girl patient with giant bilateral Achilles tendon xanthomas in which both tumors were resected.

There was no ulceration on the both sides. The patient was treated by total resection of the lesion and reconstruction using tendon transfer of the Peroneus brevis and Flexor hallusis longus. Postoperative treatment consisted of six weeks lower leg cast immobilization followed by partial weight bearing. After 4 months the patient was able to walk pain free without any difficultie

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Publication Date
Mon Jun 03 2019
Journal Name
Al-kindy College Medical Journal
A Case Report -Bilateral Giant Achilles Tendon Xanthomas Resection with a Tendon transverse Technique
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Background : Xanthomatosis is a disease in which large tendon tumors can occur, especially in the Achilles tendon. This disease is a rare interesting orthopaedic condition. Case Report:A case of a twenty eight year old girl patient with giant bilateral Achilles tendon xanthomas in which both tumors were resected. There was no ulceration on the both sides. The patient was treated by total resection of the lesion and reconstruction using tendon transfer of the Peroneus brevis and Flexor hallusis longus. Postoperative treatment consisted of six weeks lower leg cast immobilization followed by partial weight bearing. After 4 months the patient was able to walk pain free without any difficulties. It has been suggested that total resection with au

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Publication Date
Fri Jun 03 2022
Journal Name
Military Medical Science Letters
COVID-19 AMONG A SAMPLE OF IRAQI PATIENTS WITH RHEUMATIC DISEASES: A MULTICENTER STUDY
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Publication Date
Thu Jan 20 2022
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Birefringence for Elliptical-Core Fibers with Low Ellipticities
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Model birefringence was measured for elliptical-core fibers with low ellipticities, note the birefringence depends strongly on the frequency, especially when fiber is being operated near the higher mode cutoff where ν  for circular fiber of the single-mode type that correspond to the birefringence maximum. When ν  this also correspond to the birefringence maximum that can be introduced in an elliptical core fiber while still operating in the single-mode regime near the higher mode cutoff. Also the birefringence is proportional to the fiber core ellipticity when core ellipticity is much less than unity, but this birefringence deviates from the linear for the large core ellipticities.

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Publication Date
Thu Oct 17 2024
Journal Name
South Eastern European Journal Of Public Health
Evaluation of Lifestyle for Women with Breast Cancer
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Introduction: Breast cancer is a significant global health concern, affecting millions of women worldwide. While advancements in diagnosis and treatment have improved survival rates, the impact of this disease extends beyond physical health. It also significantly influences a woman's lifestyle and overall well-being. Objectives: The current study intends to analyze the lifestyle of breast cancer patients who are receiving therapy or are being followed up at the Oncology Teaching Hospital in Medical City, Baghdad, Iraq. Method: The present study uses a descriptive design with an application of an evaluation approach. A convenience sample of 100 women with breast cancer was selected from the Teaching Oncology Hospital at the Medical C

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Publication Date
Thu Jun 16 2022
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
Optimization algorithms for transportation problems with stochastic demand
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The purpose of this paper is to solve the stochastic demand for the unbalanced transport problem using heuristic algorithms to obtain the optimum solution, by minimizing the costs of transporting the gasoline product for the Oil Products Distribution Company of the Iraqi Ministry of Oil. The most important conclusions that were reached are the results prove the possibility of solving the random transportation problem when the demand is uncertain by the stochastic programming model. The most obvious finding to emerge from this work is that the genetic algorithm was able to address the problems of unbalanced transport, And the possibility of applying the model approved by the oil products distribution company in the Iraqi Ministry of Oil to m

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Publication Date
Tue May 16 2023
Journal Name
Journal Of Engineering
System Identification Algorithm for Systems with Interval Coefficients
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In 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.

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Publication Date
Mon Oct 30 2023
Journal Name
Iraqi Journal Of Science
On a Subclass of Meromorphic Univalent Functions With Fixed Second Coefficientsassociated with q-Differed Operator
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The main object of this article is to study and introduce a subclass of meromorphic univalent functions with fixed second positive defined by q-differed operator. Coefficient bounds, distortion and Growth theorems, and various are  the obtained results.

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Publication Date
Mon Dec 30 2024
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Reservoir permeability prediction based artificial intelligence techniques
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   Predicting permeability is a cornerstone of petroleum reservoir engineering, playing a vital role in optimizing hydrocarbon recovery strategies. This paper explores the application of neural networks to predict permeability in oil reservoirs, underscoring their growing importance in addressing traditional prediction challenges. Conventional techniques often struggle with the complexities of subsurface conditions, making innovative approaches essential. Neural networks, with their ability to uncover complicated patterns within large datasets, emerge as a powerful alternative. The Quanti-Elan model was used in this study to combine several well logs for mineral volumes, porosity and water saturation estimation. This model goes be

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