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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 Apr 30 2016
Journal Name
Environmental Science And Pollution Research
Risk-based prioritization of pharmaceuticals in the natural environment in Iraq
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Publication Date
Tue Apr 02 2019
Journal Name
Artificial Intelligence Research
A three-stage learning algorithm for deep multilayer perceptron with effective weight initialisation based on sparse auto-encoder
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A three-stage learning algorithm for deep multilayer perceptron (DMLP) with effective weight initialisation based on sparse auto-encoder is proposed in this paper, which aims to overcome difficulties in training deep neural networks with limited training data in high-dimensional feature space. At the first stage, unsupervised learning is adopted using sparse auto-encoder to obtain the initial weights of the feature extraction layers of the DMLP. At the second stage, error back-propagation is used to train the DMLP by fixing the weights obtained at the first stage for its feature extraction layers. At the third stage, all the weights of the DMLP obtained at the second stage are refined by error back-propagation. Network structures an

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Publication Date
Thu Nov 30 2023
Journal Name
Iraqi Journal Of Science
Synthesis, Identification and Biological Study of New Pharmaceutical Model Based on Amino Acids with Some of Its Complexes
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           The synthesis of the MBIB ligand by the reaction of the BIB ligand with methionine in 1:1 ratio, and the metal complexes with Ni(II), Cu(II), and Pt(IV) were described. All synthesized compounds were characterized using spectroscopic methods such as FT-IR, 1H NMR, UV-VIS, thermal analysis (TG and DSC), atomic absorption (AAS), elemental microanalysis (C.H.N.S), melting point (m.p.), magnetic susceptibility, molar conductivity measurements, and chloride content. All the complexes were electrolytes, and the suggested geometric shapes for the complexes were octahedral. The magnetic properties of the platinum complex were diamagnetic, while those of the nickel and copper complexes were paramagnetic. All synthes

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Publication Date
Fri May 21 2021
Journal Name
International Journal Of Pavement Research And Technology
Developing Resilient Modulus Prediction Models Based on Experimental Results of Crushed Hornfels Mixes with Different Gradations and Plasticity
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Publication Date
Fri Jul 01 2016
Journal Name
Colloids And Surfaces A: Physicochemical And Engineering Aspects
Stability and thermophysical properties of water-based nanofluids containing triethanolamine-treated graphene nanoplatelets with different specific surface areas
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tA novel synthesis procedure is presented for preparing triethanolamine-treated graphene nanoplatelets(TEA-GNPs) with different specific areas (SSAs). Using ultrasonication, the covalently functionalizedTEA-GNPs with different weight concentrations and SSAs were dispersed in distilled water to prepareTEA-GNPs nanofluids. A simple direct coupling of GNPs with TEA molecules is implemented to synthesizestable water-based nanofluids. The effectiveness of the functionalization procedure was validated by thecharacterization and morphology tests, i.e., FTIR, Raman spectroscopy, EDS, and TEM. Thermal conduc-tivity, dispersion stability, and rheological properties were investigated. Using UV–vis spectrometer, ahighest dispersion stability of 0.876

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Publication Date
Mon Jun 01 2020
Journal Name
Journal Of Engineering
Pilot Based Channel Estimation and Synchronization in OFDM System
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Channel estimation and synchronization are considered the most challenging issues in Orthogonal Frequency Division Multiplexing (OFDM) system. OFDM is highly affected by synchronization errors that cause reduction in subcarriers orthogonality, leading to significant performance degradation. The synchronization errors cause two issues: Symbol Time Offset (STO), which produces inter symbol interference (ISI) and Carrier Frequency Offset (CFO), which results in inter carrier interference (ICI). The aim of the research is to simulate Comb type pilot based channel estimation for OFDM system showing the effect of pilot numbers on the channel estimation performance and propose a modified estimation method for STO with less numb

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Publication Date
Thu Jun 20 2019
Journal Name
Baghdad Science Journal
Taxonomy of Memory Usage in Swarm Intelligence-Based Metaheuristics
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Metaheuristics under the swarm intelligence (SI) class have proven to be efficient and have become popular methods for solving different optimization problems. Based on the usage of memory, metaheuristics can be classified into algorithms with memory and without memory (memory-less). The absence of memory in some metaheuristics will lead to the loss of the information gained in previous iterations. The metaheuristics tend to divert from promising areas of solutions search spaces which will lead to non-optimal solutions. This paper aims to review memory usage and its effect on the performance of the main SI-based metaheuristics. Investigation has been performed on SI metaheuristics, memory usage and memory-less metaheuristics, memory char

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Publication Date
Tue Feb 28 2023
Journal Name
Iraqi Journal Of Science
Data Hiding in 3D Model Based on Surface Properties
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    Data hiding strategies have recently gained popularity in different fields; Digital watermark technology was developed for hiding copyright information in the image visually or invisibly. Today, 3D model technology has the potential to alter the field because it allows for the production of sophisticated structures and forms that were previously impossible to achieve. In this paper, a new watermarking method for the 3D model is presented. The proposed method is based on the geometrical and topology properties of the 3D model surface to increase the security. The geometrical properties are based on computing the mean curvature for a surface and topology based on the number of edges around each vertex, the vertices

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Publication Date
Sun Jun 07 2009
Journal Name
Baghdad Science Journal
Compatibility between Pseudomonas fluorescens and Trichoderma harzianum in disease control of Fusarium tomato wilt under greenhouse condition .
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This study was conducted to evaluate the efficacy of 6 isolates of Pseudomonas fluorescens and Trichoderma harzianum and there combination against Fusarium tomato wilt disease caused by Fusarium oxysporum F.sp. Lycopersisi under green house condition .The isolates of bacteria (B3) and Trichoderma (T1) were found to be highly effective in reducing the disease incidence to 13.3% , 21% respectively , compared to control treatment (40%).Furthermore, disease severity was reduced to 28 and 30% respectively in comparison to control (90%) .Colonization of the roots (cfu /g fresh root weight )by the two isolates whether alon or together was extremely high . The combination treatment had a high ability in reducing disease incidenece and sev

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Publication Date
Thu Nov 08 2018
Journal Name
Iraqi National Journal Of Nursing Specialties
Impact of Life Events upon Onset of Depression Disorder In AL-Diwanyia Governorate : A Case-Control Study
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Objective: The aim of this study is to find out the impact of life events upon onset of depression, to describe the
prevalence of life events among depressed patients.
Methodology: Retrospective a case-control study conducted in AL-Diwanyia Teaching Hospital, Psychiatric
Department on A non-probability (purposive sample) of (60) depressed patients and (60) of healthy person were matched
with them from general population. The data were collected through the use of semi-structured interview by
questionnaire, which consists of two parts (1) divide, section A. cover letter and B. Sociodemographic data which consists
of 9-items, (2) Life events questionnaire consists of 51-items distributed to six dimensions include, family

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