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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
Sun Apr 01 2018
Journal Name
Journal Of Economics And Administrative Sciences
Bayes Estimators for the Parameter of the Inverted Exponential Distribution Under different Double informative priors
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In this paper, we present a comparison of double informative priors which are assumed for the parameter of inverted exponential distribution.To estimate the parameter of inverted exponential distribution by using Bayes estimation ,will be  used two different kind of information in the Bayes estimation; two different priors have been selected for the parameter of inverted exponential distribution. Also assumed Chi-squared - Gamma distribution, Chi-squared - Erlang distribution, and- Gamma- Erlang distribution as double priors. The results are the derivations of these estimators under the squared error loss function with three different double priors.

Additionally Maximum likelihood estimation method

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Publication Date
Tue Sep 01 2020
Journal Name
Baghdad Science Journal
Bayesian and Non - Bayesian Inference for Shape Parameter and Reliability Function of Basic Gompertz Distribution
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In this paper, some estimators of the unknown shape parameter and reliability function  of Basic Gompertz distribution (BGD) have been obtained, such as MLE, UMVUE, and MINMSE, in addition to estimating Bayesian estimators under Scale invariant squared error loss function assuming informative prior represented by Gamma distribution and non-informative prior by using Jefferys prior. Using Monte Carlo simulation method, these estimators of the shape parameter and R(t), have been compared based on mean squared errors and integrated mean squared, respectively

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Publication Date
Sat Dec 01 2018
Journal Name
Nano Hybrids And Composites
Specific NH<sub>3</sub> Gas Sensor Worked at Room Temperature Based on MWCNTs-OH Network
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Functionalized Multi-Walled Carbon Nanotubes (MWCNTs-OH) network with thickness 4μm was made by the vacuum filtration from suspension (FFS) method. The morphology, structure and optical properties of the MWCNTs film were characterized by SEM and UV-Vis. spectra techniques. The SEM images reflected highly ordered network in the form of ropes or bundles with close-packing which looks like spaghetti. The absorbance spectrum revealed that the network has a good absorbance in the UV-Vis. region. The gas sensor system was used to test the MWCNT-OH network to detect NH3gas at room temperature. The resistance of the sensor was increased when exposed to the NH3gas. The sensitivities of the network w

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Publication Date
Thu Aug 11 2022
Journal Name
Arabian Journal For Science And Engineering
Synthesis and Characterization of Novel Nano Azo Compounds as a New pH Sensor
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Publication Date
Thu Sep 28 2023
Journal Name
History Of Medicine
Pregnancy and left ventricular remodeling: Echocardiography parameter
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Profound maternal hemodynamic changes occur in order to satisfy the demands of a growing foetus. Early in pregnancy, peripheral vascular resistance (PVR) lowers, generating a considerable rise in cardiac output. Many parameters are employed for measuring the LV systolic function with different echocardiographic modalities including: M-Mode echocardiography, two-dimensional echocardiography, three-dimensional echocardiography, tissue doppler imaging.

Publication Date
Sat Jan 01 2011
Journal Name
Journal Of Engineering
RADAR PARAMETER GENERATION TO IDENTIFY THE TARGET
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Due to the popularity of radar, receivers often “hear” a great number of other transmitters in
addition to their own return merely in noise. The dealing with the problem of identifying and/or
separating a sum of tens of such pulse trains from a number of different sources are often received on
the one communication channel. It is then of interest to identify which pulses are from which source,
based on the assumption that the different sources have different characteristics. This search deals with a
graphical user interface (GUI) to generate the radar pulse in order to use the required radar signal in any
specified location.

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Publication Date
Thu Jan 30 2025
Journal Name
Iraqi Journal Of Science
Improving the Reliability of Evolutionary Algorithm for Complex Detection in Noisy Protein-Protein Interaction Networks
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Evolutionary algorithms are better than heuristic algorithms at finding protein complexes in protein-protein interaction networks (PPINs). Many of these algorithms depend on their standard frameworks, which are based on topology. Further, many of these algorithms have been exclusively examined on networks with only reliable interaction data. The main objective of this paper is to extend the design of the canonical and topological-based evolutionary algorithms suggested in the literature to cope with noisy PPINs. The design of the evolutionary algorithm is extended based on the functional domain of the proteins rather than on the topological domain of the PPIN. The gene ontology annotation in each molecular function, biological proce

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Publication Date
Sat Apr 01 2023
Journal Name
Digital Communications And Networks
Dynamic channel estimation-aware routing protocol in mobile cognitive radio networks for smart IIoT applications
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Publication Date
Thu Sep 13 2018
Journal Name
Baghdad Science Journal
Dynamic Routing Method over Hybrid SDN for Flying Ad Hoc Networks
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Due to the high mobility and dynamic topology of the FANET network, maintaining communication links between UAVs is a challenging task. The topology of these networks is more dynamic than traditional mobile networks, which raises challenges for the routing protocol. The existing routing protocols for these networks partly fail to detect network topology changes. Few methods have recently been proposed to overcome this problem due to the rapid changes of network topology. We try to solve this problem by designing a new dynamic routing method for a group of UAVs using Hybrid SDN technology (SDN and a distributed routing protocol) with a highly dynamic topology. Comparison of the proposed method performance and two other algorithms is simula

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Publication Date
Fri Jun 30 2023
Journal Name
International Journal Of Intelligent Engineering And Systems
DeepFake Detection Improvement for Images Based on a Proposed Method for Local Binary Pattern of the Multiple-Channel Color Space
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DeepFake is a concern for celebrities and everyone because it is simple to create. DeepFake images, especially high-quality ones, are difficult to detect using people, local descriptors, and current approaches. On the other hand, video manipulation detection is more accessible than an image, which many state-of-the-art systems offer. Moreover, the detection of video manipulation depends entirely on its detection through images. Many worked on DeepFake detection in images, but they had complex mathematical calculations in preprocessing steps, and many limitations, including that the face must be in front, the eyes have to be open, and the mouth should be open with the appearance of teeth, etc. Also, the accuracy of their counterfeit detectio

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