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The Accuracy of Electrocardiographic Criteria for Predicting Left Ventricular Hypertrophy in adult Patients with Systemic Hypertension
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ABSTRACT: BACKGROUND: Left ventricular hypertrophy is a significant risk factor for cardiovascular complications such as ischemic heart disease, heart failure, sudden death, atrial fibrillation, and stroke. A proper non-expensive tool is required for detection of this pathology. Different electrocardiographic (ECG) criteria were investigated; however, the results were conflicting regarding the accuracy of these criteria. OBJECTIVE: To assess the accuracy of three electrocardiographic criteria in diagnosis of left ventricular hypertrophy in adult patients with hypertension using echocardiography as a reference test. PATIENTS AND METHODS: This is a hospital-based cross sectional observational study which included 340 adult patients with a history of hypertension (240 patients with left ventricular hypertrophy and 100 patients without depending on Echocardiographic results). Three electrocardiographic criteria including Sokolow Lyon Voltage, Cornell voltage, and Cornell voltage duration were evaluated for their sensitivity and specificity in detection of left ventricular hypertrophy in those patients. RESULTS: Each of older ages (over 50 years) (OR= (OR=6.25, 95%CI=3.75-10.39, p<0.001), male gender (OR=0.58, 95% CI= 0.36-0.93, p= 0.018) and type 2 diabetes mellitus (OR=8.14, 95%CI= 4.04-16.41, p<0.001) were significantly associated with development of left ventricular hypertrophy in patients with hypertension. The sensitivity and specificity of Sokolow Lyon Voltage, Cornell voltage, and Cornell voltage duration were 17.5% and 96%; 13.33% and 97%; and 10% and 98%, respectively. CONCLUSION: Older ages, male gender, and type 2 diabetes mellitus can increase the risk of left ventricular hypertrophy in hypertensive patients. All the studied criteria have low sensitivity and high specificity in recognition of the left ventricular hypertrophy in patients with hypertension, with no advantage of definite criterion over the others.

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Publication Date
Tue Oct 15 2019
Journal Name
International Journal Of Electrical And Computer Engineering (ijece)
Combining Convolutional Neural Networks and Slantlet Transform For An Effective Image Retrieval Scheme
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In the latest years there has been a profound evolution in computer science and technology, which incorporated several fields. Under this evolution, Content Base Image Retrieval (CBIR) is among the image processing field. There are several image retrieval methods that can easily extract feature as a result of the image retrieval methods’ progresses. To the researchers, finding resourceful image retrieval devices has therefore become an extensive area of concern. Image retrieval technique refers to a system used to search and retrieve images from digital images’ huge database. In this paper, the author focuses on recommendation of a fresh method for retrieving image. For multi presentation of image in Convolutional Neural Network (CNN),

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Publication Date
Sat Dec 30 2023
Journal Name
Traitement Du Signal
Optimizing Acoustic Feature Selection for Estimating Speaker Traits: A Novel Threshold-Based Approach
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Publication Date
Sun Apr 30 2023
Journal Name
Iraqi Geological Journal
Evaluating Machine Learning Techniques for Carbonate Formation Permeability Prediction Using Well Log Data
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Machine learning has a significant advantage for many difficulties in the oil and gas industry, especially when it comes to resolving complex challenges in reservoir characterization. Permeability is one of the most difficult petrophysical parameters to predict using conventional logging techniques. Clarifications of the work flow methodology are presented alongside comprehensive models in this study. The purpose of this study is to provide a more robust technique for predicting permeability; previous studies on the Bazirgan field have attempted to do so, but their estimates have been vague, and the methods they give are obsolete and do not make any concessions to the real or rigid in order to solve the permeability computation. To

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Publication Date
Sun Oct 01 2017
Journal Name
Iecon 2017 - 43rd Annual Conference Of The Ieee Industrial Electronics Society
Optimal second order integral sliding mode control for a flexible joint robot manipulator
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The flexible joint robot manipulators provide various benefits, but also present many control challenges such as nonlinearities, strong coupling, vibration, etc. This paper proposes optimal second order integral sliding mode control (OSOISMC) for a single link flexible joint manipulator to achieve robust and smooth performance. Firstly, the integral sliding mode control is designed, which consists of a linear quadratic regulator (LQR) as a nominal control, and switching control. This control guarantees the system robustness for the entire process. Then, a nonsingularterminal sliding surface is added to give a second order integral sliding mode control (SOISMC), which reduces chartering effect and gives the finite time convergence as well. S

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Publication Date
Fri Mar 01 2019
Journal Name
Iran. J. Chem. Chem. Eng.
Biochar from orange (Citrus sinensis) peels by acid activation for methylene blue adsorption
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Publication Date
Mon Jul 01 2019
Journal Name
International Journal Of Heat And Mass Transfer
Hybrid heat transfer enhancement for latent-heat thermal energy storage systems: A review
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Publication Date
Wed Sep 29 2021
Journal Name
Molecules
A Comprehensive Review for Groundwater Contamination and Remediation: Occurrence, Migration and Adsorption Modelling
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The provision of safe water for people is a human right; historically, a major number of people depend on groundwater as a source of water for their needs, such as agricultural, industrial or human activities. Water resources have recently been affected by organic and/or inorganic contaminants as a result of population growth and increased anthropogenic activity, soil leaching and pollution. Water resource remediation has become a serious environmental concern, since it has a direct impact on many aspects of people’s lives. For decades, the pump-and-treat method has been considered the predominant treatment process for the remediation of contaminated groundwater with organic and inorganic contaminants. On the other side, this tech

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Publication Date
Tue Jun 30 2026
Journal Name
Journal Of Economics And Administrative Sciences
Nonparametric Control Charts Estimation Using Hybrid Cyber-Intelligence Algorithms for Stock Market Monitoring
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This paper introduces a novel nonparametric hybrid cyber-intelligence-based statistical process control and anomaly detection framework in time series data. It is developed to overcome the shortcomings of the classical control schemes in dealing with complex, abnormal, and noisy input data, especially when it is autocorrelated. The proposed methodology combines three technical pillars: First, it utilizes a bidirectional long-short-term memory architecture (Bi-LSTM) to capture long-term time dependency and learn nonlinear patterns, leaving only true deviations as residuals that remove trends and noises from the market. Second, it adopts the Golden Eagle Optimizer (GEO) algorithm for optimal parameter selection. This intelligent algor

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Publication Date
Sun Feb 01 2026
Journal Name
Chemistryselect
Gelatin Nanoparticles as a Carrier for Acriflavine and Triethylenetetramine: Cytotoxicity and Antibacterial Activity
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ABSTRACT<p> Despite extensive investigation as biocompatible drug carriers, gelatin nanoparticles (GNPs) have not been thoroughly assessed for carrying chemically distinct cationic molecules such as acriflavine (ACF) and triethylenetetramine (TETA). In this study, we hypothesize that GNPs can effectively encapsulate ACF and TETA, forming stable delivery systems with distinct antibacterial and cytotoxic activities. ACF encapsulated in gelatin was prepared adapting desolvation technique. The procedure involved stirring of an aqueous solution of gelatin and ACF at room temperature, the pH was titrated to eight using NaOH followed by addition of ethanol. The resulting nanopart</p> ... Show More
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Publication Date
Thu Jul 17 2025
Journal Name
International Journal Of Environmental Sciences
Inverse Kinematic Analysis For A 5 DOF Robotic Arm Using Deep Neural Network
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In this study, the kinematic analysis including the forward and inverse kinematic developed for a 5 degree of freedom robotic arm. The forward kinematic is elaborated using Denavit-Hartenberg (DH) convention. Inverse Kinematic is established using Deep Neural Network (DNN) model with five hidden layer each contain 50 neurons fully connected using ReLu activation. A data of inputs and outputs are created and trained. The inputs are the end-effector position and orientation. The outputs are the joint angles of the manipulator. The data is generated by the forward kinematics, where a set of joint angles that limited by their corresponding ranges are inserted to the forward kinematic equations to result the end-effector positions and or

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