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Priority Based Transmission Rate Control with Neural Network Controller in WMSNs
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Wireless Multimedia Sensor Networks (WMSNs) are networks of wirelessly interconnected sensor nodes equipped with multimedia devices, such as cameras and microphones. Thus a WMSN will have the capability to transmit multimedia data, such as video and audio streams, still images, and scalar data from the environment. Most applications of WMSNs require the delivery of multimedia information with a certain level of Quality of Service (QoS). This is a challenging task because multimedia applications typically produce huge volumes of data requiring high transmission rates and extensive processing; the high data transmission rate of WMSNs usually leads to congestion, which in turn reduces the Quality of Service (QoS) of multimedia applications. To address this challenge, This paper proposes the Neural Control Exponential Weight of Priority Based Rate Control (NEWPBRC) algorithm for adjusting the node transmission rate and facilitate the problem of congestion occur in WMSNs. The proposed algorithm combines Neural Network Controller (NC) with the Exponential Weight of Priority Based Rate Control (EWPBRC) algorithms. The NC controller can calculate the appropriate weight parameter λ in the Exponential Weight (EW) algorithm for estimating the output transmission rate of the sink node, and then, on the basis of the priority of each child node, an appropriate transmission rate is assigned. The proposed algorithm can support four different traffic classes namely, Real Time traffic class (RT class); High priority, Non Real-Time traffic class (NRT1 class); Medium priority, Non Real-Time traffic class (NRT2 class); and Low priority,

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Publication Date
Sat Oct 01 2016
Journal Name
2016 6th International Conference On Information Communication And Management (icicm)
Enhancing case-based reasoning retrieval using classification based on associations
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Publication Date
Sat Feb 27 2021
Journal Name
Iraqi Journal Of Science
Asymptotic Stability for Some Types of Nonlinear Fractional Order Differential-Algebraic Control Systems
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The aim of this paper is to study the asymptotically stable solution of nonlinear single and multi fractional differential-algebraic control systems, involving feedback control inputs, by an effective approach that depends on necessary and sufficient conditions.

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Publication Date
Mon Oct 10 2022
Journal Name
International Journal Of Mathematics In Operational Research
Modelling time-series process of an agricultural crop production process by EWMA quality control chart
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Publication Date
Mon Jan 20 2020
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
The Continuous Classical Optimal Control governing by Triple Linear Parabolic Boundary Value Problem
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This paper deals with the continuous classical optimal control problem for triple partial differential equations of parabolic type with initial and boundary conditions; the Galerkin method is used to prove the existence and uniqueness theorem of the state vector solution for given continuous classical control vector. The proof of the existence theorem of a continuous classical optimal control vector associated with the triple linear partial differential equations of parabolic type is given. The derivation of the Fréchet derivative for the cost function is obtained. At the end, the theorem of the necessary conditions for optimality of this problem is stated and is proved.

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Publication Date
Fri Jul 21 2023
Journal Name
Journal Of Engineering
SIMULATION OF OPTIMAL SPEED CONTROL FOR A DC MOTOR USING LINEAR QUADRATIC REGULATOR (LQR)
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This paper describes DC motor speed control based on optimal Linear Quadratic Regulator (LQR) technique. Controller's objective is to maintain the speed of rotation of the motor shaft with a particular step response.The controller is modeled in MATLAB environment, the simulation results show that the proposed controller gives better performance and less settling time when compared with the traditional PID controller.

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Publication Date
Sun Oct 01 2017
Journal Name
Applied Energy
Hourly yield prediction of a double-slope solar still hybrid with rubber scrapers in low-latitude areas based on the particle swarm optimization technique
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Publication Date
Tue Jan 01 2019
Journal Name
Spe Europec Featured At 81st Eage Conference And Exhibition
Development of Artificial Neural Networks and Multiple Regression Analysis for Estimating of Formation Permeability
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Publication Date
Mon Feb 01 2021
Journal Name
Indonesian Journal Of Electrical Engineering And Computer Science
Comparative study of logistic regression and artificial neural networks on predicting breast cancer cytology
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<p>Currently, breast cancer is one of the most common cancers and a main reason of women death worldwide particularly in<strong> </strong>developing countries such as Iraq. our work aims to predict the type of tumor whether benign or malignant through models that were built using logistic regression and neural networks and we hope it will help doctors in detecting the type of breast tumor. Four models were set using binary logistic regression and two different types of artificial neural networks namely multilayer perceptron MLP and radial basis function RBF. Evaluation of validated and trained models was done using several performance metrics like accuracy, sensitivity, specificity, and AUC (area under receiver ope

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Scopus (3)
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Publication Date
Thu Mar 30 2023
Journal Name
Iraqi Journal Of Science
Evaluation the Efficacy of Ozone and Temperature to Control Mover Stages for Hairy Grain Beetle (khapra) in Laboratory Trogoderma granariumEverts Coleoptera : Dermestidae.)
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The effect of the following treatments were tested on the adult and larval stages of hairy grain beetle Trogoderma granarium (Everts).The treatments were the combination of ozone gaz with high temperatures ( 35، 40 and 45C) and tempreture alone in addition to control treatment. Results showed that (Z+H) and (H) treatments were more lethally effective (100%mortality) than other treatment on larvae and adult stages of insect. The results also showed that first treatment( Z+H) was more effective than the second treatment (H) on two stages ,the temperature alone treatment with 35,40C was not effective on larvae and adults ( male+femal) :while the temperature 45C alone and combined with Ozone gaz was more effective on two stages of insect .I

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Publication Date
Fri Jun 29 2018
Journal Name
Journal Of The College Of Education For Women
Audio Classification Based on Content Features
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Audio classification is the process to classify different audio types according to contents. It is implemented in a large variety of real world problems, all classification applications allowed the target subjects to be viewed as a specific type of audio and hence, there is a variety in the audio types and every type has to be treatedcarefully according to its significant properties.Feature extraction is an important process for audio classification. This workintroduces several sets of features according to the type, two types of audio (datasets) were studied. Two different features sets are proposed: (i) firstorder gradient feature vector, and (ii) Local roughness feature vector, the experimentsshowed that the results are competitive to

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