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On the Greedy Ridge Function Neural Networks for Approximation Multidimensional Functions
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The aim of this paper is to approximate multidimensional functions f∈C(R^s) by developing a new type of Feedforward neural networks (FFNS) which we called it Greedy ridge function neural networks (GRGFNNS). Also, we introduce a modification to the greedy algorithm which is used to train the greedy ridge function neural networks. An error bound are introduced in Sobolov space. Finally, a comparison was made between the three algorithms (modified greedy algorithm, Backpropagation algorithm and the result in [1]).

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Publication Date
Tue May 01 2018
Journal Name
The Journal Of Immunology
Marijuana THC treatment led to decreased metabolic functions of Staphylococcal enterotoxin B-activated lymphocytes
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Abstract<p>Studies from our laboratory have shown that Δ9-Tetrahydrocannabinol (THC), an ingredient found in marijuana plant Cannabis sativa, can attenuate acute lung injury induced by Staphylococcus enterotoxin B (SEB). In the current study, we investigated the role of THC on the metabolism of SEB-activated lymphocytes. To this end, we determined metabolic potential of SEB-activated lymphocytes treated with vehicle or THC by performing the Cell Mito Stress Test. The oxygen consumption rate (OCR) in THC-treated cells was decreased when compared to vehicle-treated group whereas the extracellular acidification rate (ECAR) was similar in both the groups. Specifically, electron transport chain inhi</p> ... Show More
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Publication Date
Sun Jun 01 2025
Journal Name
Journal Of Physics: Conference Series
Searching Ground State Properties of some Light Proton-Rich Nuclei Using Whittaker Wave Functions
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Abstract<p>In this work, the Whittaker wave functions were used to study the nuclear density distributions and elastic electron scattering charge form factors for proton-rich nuclei and their corresponding stable nuclei (<sup>10,8</sup>B, <sup>13,9</sup>C, <sup>14,12</sup>N and <sup>19,17</sup>F). The parameters of Whittaker’s basis were fixed to generate the experimental values of available size radii. The Whittaker basis was connected to harmonic-oscillator basis through boundary condition at match point. The nuclear shell model was opted with pure configuration for all studied nuclei to compute aforementioned studied quantities except <sup>10</sup></p> ... Show More
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Publication Date
Wed Nov 19 2014
Journal Name
Journal Of Biosciences
Caspase-like proteins: Acanthamoeba castellanii metacaspase and Dictyostelium discoideum paracaspase, what are their functions?
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Publication Date
Mon Jan 01 2018
Journal Name
African Journal Of Hospitality, Tourism And Leisure
An analytical study of the strategic flexibility variation as a function of the dynamic capabilities based on supply chain management (Case study: The General Petroleum Products Distribution Company in Baghdad)
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Publication Date
Thu Jun 28 2018
Journal Name
Journal Of The College Of Education For Women
The function and Formation of NORTH ATLANTIC TREATY ORGANZIAITON as (NATO) Post Cold War Period
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The problem of this study lies in that NATO was formed in the first place to protect Europe from Warsaw Pact. The geographical and military strategy have been changed with the change of its mission and expanding its operation scope with the leadership of the USA in the international scens. The latter has made this organization as the military arm to tighten its control over strategic regions.

            The research supposes that NATO state members confront security concerns and political and military issues that push to expand the organization. The importance of this study lies in knowing the new roles of NATO imposed by the United States. Therefore, the continuity and affi

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Publication Date
Sun Dec 30 2018
Journal Name
2018 Computing In Cardiology Conference (cinc)
Theoretical and Experimental Reflection Coefficients in Flexible Tubes as a Function of the Mach Number
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The standard formulation of Wave Intensity Analysis (WIA) assumes that the flow velocity (U) in the conduit is <;<; the velocity of propagation of waves (c) in the system, and Mach number, M=U/c, is negligible. However, in the large conduit arteries, U is relatively high due to ventricular contraction and c is relatively low due to the large compliance; thus M is > 0, and may not be ignored. Therefore, the aim of this study is to identify experimentally the relationship between M and the reflection coefficient in vitro. Combinations of flexible tubes, of 2 m in length with isotropic and uniform circular cross sectional area along their longitudinal axes, were used to present mother and daughter tubes to produce a range of reflection coeffic

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Publication Date
Thu Aug 01 2024
Journal Name
Water Practice &amp; Technology
Artificial neural network and response surface methodology for modeling oil content in produced water from an Iraqi oil field
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ABSTRACT<p>The majority of the environmental outputs from gas refineries are oily wastewater. This research reveals a novel combination of response surface methodology and artificial neural network to optimize and model oil content concentration in the oily wastewater. Response surface methodology based on central composite design shows a highly significant linear model with P value &lt;0.0001 and determination coefficient R2 equal to 0.747, R adjusted was 0.706, and R predicted 0.643. In addition from analysis of variance flow highly effective parameters from other and optimization results verification revealed minimum oily content with 8.5 ± 0.7 ppm when initial oil content 991 ppm, tempe</p> ... Show More
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Publication Date
Tue Apr 01 2014
Journal Name
Journal Of Engineering
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

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Publication Date
Mon Jun 19 2023
Journal Name
Journal Of Engineering
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 appli

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Publication Date
Wed Feb 01 2023
Journal Name
International Journal Of Electrical And Computer Engineering
Classification of COVID-19 from CT chest images using Convolutional Wavelet Neural Network
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<p>Analyzing X-rays and computed tomography-scan (CT scan) images using a convolutional neural network (CNN) method is a very interesting subject, especially after coronavirus disease 2019 (COVID-19) pandemic. In this paper, a study is made on 423 patients’ CT scan images from Al-Kadhimiya (Madenat Al Emammain Al Kadhmain) hospital in Baghdad, Iraq, to diagnose if they have COVID or not using CNN. The total data being tested has 15000 CT-scan images chosen in a specific way to give a correct diagnosis. The activation function used in this research is the wavelet function, which differs from CNN activation functions. The convolutional wavelet neural network (CWNN) model proposed in this paper is compared with regular convol

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