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Artificial Neural Network and Latent Semantic Analysis for Adverse Drug Reaction Detection
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Adverse drug reactions (ADR) are important information for verifying the view of the patient on a particular drug. Regular user comments and reviews have been considered during the data collection process to extract ADR mentions, when the user reported a side effect after taking a specific medication. In the literature, most researchers focused on machine learning techniques to detect ADR. These methods train the classification model using annotated medical review data. Yet, there are still many challenging issues that face ADR extraction, especially the accuracy of detection. The main aim of this study is to propose LSA with ANN classifiers for ADR detection. The findings show the effectiveness of utilizing LSA with ANN in extracting ADR.

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Publication Date
Sun Jun 01 2025
Journal Name
Results In Materials
Adsorption, thermodynamic and corrosion study of enalapril malate pharmaceutical drug as corrosion inhibitor for carbon steel in saline solution
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Unused and expired pharmaceutical drugs are a novel type of organic corrosion inhibitor. They are less expensive, more effective, and less harmful than conventional organic corrosion inhibitors. This study investigated the effects of concentration, adsorption mechanism and thermodynamic parameters of enalapril malate (ENAP) as a corrosion inhibitor for carbon steel in a saline solution (3.5 % NaCl). The polarization method was used to determine the corrosion rate and inhibition efficiency. Field emission scanning electron microscopy (FE-SEM) and atomic force spectroscopy (AFM) were used to investigate the surface morphology and topography of carbon steel after immersion in both uninhibited and inhibited media for 24 h. Fourier transform inf

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Publication Date
Thu Dec 28 2017
Journal Name
Al-khwarizmi Engineering Journal
Obstacles Avoidance for Mobile Robot Using Enhanced Artificial Potential Field
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In this paper, an enhanced artificial potential field (EAPF) planner is introduced. This planner is proposed to rapidly find online solutions for the mobile robot path planning problems, when the underlying environment contains obstacles with unknown locations and sizes. The classical artificial potential field represents both the repulsive force due to the detected obstacle and the attractive force due to the target. These forces can be considered as the primary directional indicator for the mobile robot. However, the classical artificial potential field has many drawbacks. So, we suggest two secondary forces which are called the midpoint

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Publication Date
Sun Jan 14 2018
Journal Name
Journal Of Engineering
Second Order Sliding Mode Controller Design for Pneumatic Artificial Muscle
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In this paper, first and second order sliding mode controllers are designed for a single link robotic arm actuated by two Pneumatic Artificial Muscles (PAMs). A new mathematical model for the arm has been developed based on the model of large scale pneumatic muscle actuator model. Uncertainty in parameters has been presented and tested for the two controllers. The simulation results of the second-order sliding mode controller proves to have a low tracking error and chattering effect as compared to the first order one. The verification has been done by using MATLAB and Simulink software.

 

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Publication Date
Fri Mar 01 2019
Journal Name
Al-khwarizmi Engineering Journal
Implementation of Neural Control for Continuous Stirred Tank Reactor (CSTR)
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In this paper a dynamic behavior and control of  a jacketed continuous stirred tank reactor (CSTR)  is developed using different control strategies, conventional feedback control (PI and PID), and neural network (NARMA-L2, and NN Predictive) control. The dynamic model for CSTR process is described by a first order lag system with dead time.

The optimum tuning of control parameters are found by two different methods; Frequency Analysis Curve method (Bode diagram) and Process Reaction Curve using the mean of Square Error (MSE) method. It is found that the Process Reaction Curve method is better than the Frequency Analysis Curve method and PID feedback controller is better than PI feedback controller.

The results s

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Publication Date
Fri Apr 01 2022
Journal Name
Telkomnika (telecommunication Computing Electronics And Control)
An adaptive neural control methodology design for dynamics mobile robot
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Publication Date
Thu Jul 31 2025
Journal Name
Lecture Notes In Networks And Systems
Integration Between Network Analysis and Business Process Reengineering and Their Role in Reduce Project Costs/Applied Research in the Oil Projects Company
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Publication Date
Fri Jun 01 2007
Journal Name
Journal Of Al-nahrain University Science
ON THE GREEDY RADIAL BASIS FUNCTION NEURAL NETWORKS FOR APPROXIMATION MULTIDIMENSIONAL FUNCTIONS
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The aim of this paper is to approximate multidimensional functions by using the type of Feedforward neural networks (FFNNs) which is called Greedy radial basis function neural networks (GRBFNNs). Also, we introduce a modification to the greedy algorithm which is used to train the greedy radial basis function neural networks. An error bound are introduced in Sobolev space. Finally, a comparison was made between the three algorithms (modified greedy algorithm, Backpropagation algorithm and the result is published in [16]).

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Publication Date
Tue Apr 02 2024
Journal Name
Engineering, Technology & Applied Science Research
Two Proposed Models for Face Recognition: Achieving High Accuracy and Speed with Artificial Intelligence
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In light of the development in computer science and modern technologies, the impersonation crime rate has increased. Consequently, face recognition technology and biometric systems have been employed for security purposes in a variety of applications including human-computer interaction, surveillance systems, etc. Building an advanced sophisticated model to tackle impersonation-related crimes is essential. This study proposes classification Machine Learning (ML) and Deep Learning (DL) models, utilizing Viola-Jones, Linear Discriminant Analysis (LDA), Mutual Information (MI), and Analysis of Variance (ANOVA) techniques. The two proposed facial classification systems are J48 with LDA feature extraction method as input, and a one-dimen

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Publication Date
Wed Mar 05 2025
Journal Name
Full Text Book Of Rimarcongress04
Natural and Artificial Radioactivity Estimation for Different types of Pasta Samples in Baghdad City
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Publication Date
Thu Jul 23 2026
Journal Name
Dirasat: Human And Social Sciences
The U.S.-China Competition in Artificial Intelligence and Its Implications for Shaping Military Strategies
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Objectives: This study investigates the U.S.-China competition in the field of artificial intelligence (AI), focusing on its implications for both countries’ military strategies. It also offers a forward-looking assessment of how this rivalry may influence international security and geopolitical stability. Methods: The research adopts an integrative theoretical framework combining realism—which emphasizes military power and strategic dominance—and technological innovation theory, which highlights the role of emerging technologies in global power shifts. A descriptive and analytical approach is employed, synthesizing academic literature, policy reports, and strategic documents from 2010 to 2030. Results: The U.S.-China AI compe

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