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Modified Optimization Algorithms for Infinite Integro-Differential Equations via Generalized Laguerre Polynomials
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This study emphasizes the infinite-boundary integro-differential equation. To examine the approximate solution of the problem, two modified optimization algorithms are proposed based on generalized Laguerre functions. In the first technique, the proposed method is applied to the original problem by approximating the solution using the truncated generalized Laguerre polynomial of the unknown function, optimizing coefficients through error minimization, and transforming the integro-differential equation into an algebraic equation. In contrast, the second approach incorporates a penalty term into the objective function to effectively enforce boundary and integral constraints. This technique reduces the original problem to a mathematical optimization problem, making it easier to manage. The proposed methods are examined through various experiments, including numerical applications such as thermal, pharmacokinetic, oscillatory, aerodynamic, and ecological models, to demonstrate the validity, efficiency, and applicability of the techniques. Error analysis indicates that the approximation becomes more accurate as the number of generalized Laguerre basis functions increases.

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Publication Date
Sun Sep 01 2019
Journal Name
Journal Of Physics: Conference Series
Impulsive Pressure Activity on MHD Flux Generalized Burgers Fluid
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Abstract<p>The main purpose of the work is to analyse studies of themagnetohydrodynamic “MHD” flow for a fluid of generalized Burgers’ “GB” within an annular pipe submitted under impulsive pressure “IP” gradient. Closed form expressions for the velocity profile, impulsive pressure gradient have been taken by performing the finite Hankel transform “FHT” and Laplace transform “LT” of the successive fraction derivatives. As a result, many figures are planned to exhibit the effects of (different fractional parameters “DFP”, relaxation and retardation times, material parameter for the Burger’s fluid) on the profile of velocity of flows. Furthermore, these figures are compa</p> ... Show More
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Publication Date
Thu Jul 01 2021
Journal Name
Journal Of Physics: Conference Series
Generalized Γ-n-Derivations on Prime Γ-Near-Rings
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Abstract<p>The main purpose of this paper is to define generalized Γ-n-derivation, study and investigate some results of generalized Γ-n-derivation on prime Γ-near-ring G and <italic>K</italic> be a nonzero semi-group ideal of <italic>G</italic> which force G to be a commutative ring.</p>
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Publication Date
Tue Jan 01 2019
Journal Name
Journal Of Global Pharma Technology
Modified ZnO for efficient photo-catalysis by Silver/Graphite oxide nanoparticles
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Publication Date
Sat Feb 01 2020
Journal Name
Civil Engineering Journal
Assessment of Moisture Susceptibility for Asphalt Mixtures Modified by Carbon Fibers
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Moisture induced damage in asphaltic pavement might be considered as a serious defect that contributed to growth other distresses such as permanent deformation and fatigue cracking. This paper work aimed through an experimental effort to assess the behaviour of asphaltic mixtures that fabricated by incorporating several dosages of carbon fiber in regard to the resistance potential of harmful effect of moisture in pavement. Laboratory tests were performed on specimens containing fiber with different lengths and contents. These tests are: Marshall Test, the indirect tensile test and the index of retained strength. The optimum asphalt contents were determined based on the Marshall method. The preparation of asphaltic mixtures involved

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Publication Date
Sat May 24 2025
Journal Name
Iraqi Journal For Computer Science And Mathematics
Intrusion Detection System for IoT Based on Modified Random Forest Algorithm
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An intrusion detection system (IDS) is key to having a comprehensive cybersecurity solution against any attack, and artificial intelligence techniques have been combined with all the features of the IoT to improve security. In response to this, in this research, an IDS technique driven by a modified random forest algorithm has been formulated to improve the system for IoT. To this end, the target is made as one-hot encoding, bootstrapping with less redundancy, adding a hybrid features selection method into the random forest algorithm, and modifying the ranking stage in the random forest algorithm. Furthermore, three datasets have been used in this research, IoTID20, UNSW-NB15, and IoT-23. The results are compared with the three datasets men

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Publication Date
Wed May 01 2024
Journal Name
Journal Of Physics: Conference Series
A modified ARIMA model for forecasting chemical sales in the USA
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Abstract<p>model is derived, and the methodology is given in detail. The model is constructed depending on some measurement criteria, Akaike and Bayesian information criterion. For the new time series model, a new algorithm has been generated. The forecasting process, one and two steps ahead, is discussed in detail. Some exploratory data analysis is given in the beginning. The best model is selected based on some criteria; it is compared with some naïve models. The modified model is applied to a monthly chemical sales dataset (January 1992 to Dec 2019), where the dataset in this work has been downloaded from the United States of America census (www.census.gov). Ultimately, the forecasted sales </p> ... Show More
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Publication Date
Sun Mar 17 2019
Journal Name
Baghdad Science Journal
Faber Polynomial Coefficient Estimates for Subclass of Analytic Bi-Bazilevic Functions Defined by Differential Operator
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In this work,  an explicit formula for a class of Bi-Bazilevic univalent functions involving differential operator is given, as well as the determination of upper bounds for the general Taylor-Maclaurin coefficient of a functions belong to this class, are established Faber polynomials are used as a coordinated system to study the geometry of the manifold of coefficients for these functions. Also determining bounds for the first two coefficients of such functions.

         In certain cases, our initial estimates improve some of the coefficient bounds and link them to earlier thoughtful results that are published earlier.

 

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Publication Date
Mon Mar 11 2019
Journal Name
Baghdad Science Journal
Developing Load Balancing for IoT - Cloud Computing Based on Advanced Firefly and Weighted Round Robin Algorithms
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The evolution of the Internet of things (IoT) led to connect billions of heterogeneous physical devices together to improve the quality of human life by collecting data from their environment. However, there is a need to store huge data in big storage and high computational capabilities.   Cloud computing can be used to store big data.  The data of IoT devices is transferred using two types of protocols: Message Queuing Telemetry Transport (MQTT) and Hypertext Transfer Protocol (HTTP). This paper aims to make a high performance and more reliable system through efficient use of resources. Thus, load balancing in cloud computing is used to dynamically distribute the workload across nodes to avoid overloading any individual r

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Publication Date
Fri Sep 26 2025
Journal Name
Applied Data Science And Analysis
Deep Learning in Genomic Sequencing: Advanced Algorithms for HIV/AIDS Strain Prediction and Drug Resistance Analysis
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Genome sequencing has significantly improved the understanding of HIV and AIDS through accurate data on viral transmission, evolution and anti-therapeutic processes. Deep learning algorithms, like the Fined-Tuned Gradient Descent Fused Multi-Kernal Convolutional Neural Network (FGD-MCNN), can predict strain behaviour and evaluate complex patterns. Using genotypic-phenotypic data obtained from the Stanford University HIV Drug Resistance Database, the FGD-MCNN created three files covering various antiretroviral medications for HIV predictions and drug resistance. These files include PIs, NRTIs and NNRTIs. FGD-MCNNs classify genetic sequences as vulnerable or resistant to antiretroviral drugs by analyzing chromosomal information and id

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Publication Date
Wed Dec 13 2017
Journal Name
Al-khwarizmi Engineering Journal
Ant Colony Optimization Based Force-Position Control for Human Lower Limb Rehabilitation Robot
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The aim of human lower limb rehabilitation robot is to regain the ability of motion and to strengthen the weak muscles. This paper proposes the design of a force-position control for a four Degree Of Freedom (4-DOF) lower limb wearable rehabilitation robot. This robot consists of a hip, knee and ankle joints to enable the patient for motion and turn in both directions. The joints are actuated by Pneumatic Muscles Actuators (PMAs). The PMAs have very great potential in medical applications because the similarity to biological muscles. Force-Position control incorporating a Takagi-Sugeno-Kang- three- Proportional-Derivative like Fuzzy Logic (TSK-3-PD) Controllers for position control and three-Proportional (3-P) controllers for force contr

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