Fei Wang, Qinpeng Meng, Jinchi Zhao, Xin Wang, Yuhong Liu, Qianru Zhang^*

FDMP-Fluid Dynamics & Materials Processing, Vol.20, No.4, pp. 829-846, 2024, DOI:10.32604/fdmp.2023.026917

Abstract Buildings with large open spaces in which chemicals are handled are often exposed to the risk of explosions. Computational fluid dynamics is a useful and convenient way to investigate contaminant dispersion in such large spaces. The turbulent Schmidt number (Sc_t) concept has typically been used in this regard, and most studies have adopted a default value. We studied the concentration distribution for sulfur hexafluoride (SF₆) assuming different emission rates and considering the effect of Sc_t. Then we examined the same problem for a light gas by assuming hydrogen gas (H₂) as the contaminant. When SF₆ was considered as the contaminant… More >

S. Jayanthi^*, S. Prasanna Devi

CMC-Computers, Materials & Continua, Vol.78, No.2, pp. 2137-2158, 2024, DOI:10.32604/cmc.2024.045975

Abstract In healthcare, the persistent challenge of arrhythmias, a leading cause of global mortality, has sparked extensive research into the automation of detection using machine learning (ML) algorithms. However, traditional ML and AutoML approaches have revealed their limitations, notably regarding feature generalization and automation efficiency. This glaring research gap has motivated the development of AutoRhythmAI, an innovative solution that integrates both machine and deep learning to revolutionize the diagnosis of arrhythmias. Our approach encompasses two distinct pipelines tailored for binary-class and multi-class arrhythmia detection, effectively bridging the gap between data preprocessing and model selection. To validate our system, we have rigorously… More >

Muhammad Aleem Raza¹, Muhammad Anwar², Kashif Nisar³, Ag. Asri Ag. Ibrahim^3,*, Usman Ahmed Raza¹, Sadiq Ali Khan⁴, Fahad Ahmad⁵

CMC-Computers, Materials & Continua, Vol.77, No.3, pp. 3817-3834, 2023, DOI:10.32604/cmc.2023.032275

Abstract With the help of computer-aided diagnostic systems, cardiovascular diseases can be identified timely manner to minimize the mortality rate of patients suffering from cardiac disease. However, the early diagnosis of cardiac arrhythmia is one of the most challenging tasks. The manual analysis of electrocardiogram (ECG) data with the help of the Holter monitor is challenging. Currently, the Convolutional Neural Network (CNN) is receiving considerable attention from researchers for automatically identifying ECG signals. This paper proposes a 9-layer-based CNN model to classify the ECG signals into five primary categories according to the American National Standards Institute (ANSI) standards and the Association… More >

Charis Tan^1,2 , Diana Zannino³, Carley Clendenning³, Sophie Offen⁴, Thomas L. Gentles⁵, Julian Ayer⁶, David Tanous⁷, Vishva Wijesekera⁸, Leeanne Grigg⁹, David Celermajer^2,4,10, Mark McGuire^2,4 , Yves d’Udekem^3,11,12, Rachael Cordina^2,4,10,*

Congenital Heart Disease, Vol.18, No.5, pp. 507-523, 2023, DOI:10.32604/chd.2023.028829

Abstract Objective: Sudden cardiac death (SCD) and malignant ventricular arrhythmia (VA) are increasingly recognized as important issues for people living with a Fontan circulation, but data are lacking. We sought to characterize the cohort who had sudden cardiac death, most likely related to VA and/or documented VA in the Australia and New Zealand Fontan Registry including risk factors and clinical outcomes. Methods: A retrospective cohort study was performed. Inclusion criteria were documented non-sustained ventricular tachycardia, sustained ventricular tachycardia, ventricular fibrillation, resuscitated cardiac arrest or SCD > 30 days post-Fontan completion. Results: Of 1611 patients, 20 (1.2%) had VA; 14 (1.0%) had… More >

Vitaliy Suvorov^1,2,*, Olga Loboda², Maria Balakina¹, Igor Kulczycki²

Congenital Heart Disease, Vol.18, No.5, pp. 491-505, 2023, DOI:10.32604/chd.2023.030583

Abstract Background: Three-dimensional printing technology may become a key factor in transforming clinical practice and in significant improvement of treatment outcomes. The introduction of this technique into pediatric cardiac surgery will allow us to study features of the anatomy and spatial relations of a defect and to simulate the optimal surgical repair on a printed model in every individual case. Methods: We performed the prospective cohort study which included 29 children with congenital heart defects. The hearts and the great vessels were modeled and printed out. Measurements of the same cardiac areas were taken in the same planes and points at… More > Graphic Abstract

N. Vijaya^a,*, Y. Hari Krishna^a , K. Kalyani^b, G.V.R. Reddy^a

Frontiers in Heat and Mass Transfer, Vol.11, pp. 1-11, 2018, DOI:10.5098/hmt.11.19

Abstract The present paper deals with the thermo physical properties of a Casson fluid through an oscillating vertical wall embedded through porous medium under the influence transverse magnetic field, radiation, constant heat source and first order chemical reaction. The radiative heat loss is modelled by using Rosseland approximation. Similarity variables were used to convert the partial differential equations into ordinary differential equation. The transformed ordinary differential equations are solved numerically using Runge - Kutta -Fehlberg method with shooting technique. In order to get perfect perception of the flow pattern we obtain the graphs of axial velocity, temperature and concentrations profiles for… More >

S. R. Deepa¹, M. Subramoniam^2,*, R. Swarnalatha³, S. Poornapushpakala², S. Barani²

Intelligent Automation & Soft Computing, Vol.37, No.1, pp. 745-761, 2023, DOI:10.32604/iasc.2023.034211

Abstract The non-invasive evaluation of the heart through EectroCardioGraphy (ECG) has played a key role in detecting heart disease. The analysis of ECG signals requires years of learning and experience to interpret and extract useful information from them. Thus, a computerized system is needed to classify ECG signals with more accurate results effectively. Abnormal heart rhythms are called arrhythmias and cause sudden cardiac deaths. In this work, a Computerized Abnormal Heart Rhythms Detection (CAHRD) system is developed using ECG signals. It consists of four stages; preprocessing, feature extraction, feature optimization and classifier. At first, Pan and Tompkins algorithm is employed to… More >

Fatma Taher¹, Hamoud Alshammari², Lobna Osman³, Mohamed Elhoseny⁴, Abdulaziz Shehab^5,2,*, Eman Elayat⁶

CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 4485-4499, 2023, DOI:10.32604/cmc.2023.036118

Abstract Cardiac diseases are one of the greatest global health challenges. Due to the high annual mortality rates, cardiac diseases have attracted the attention of numerous researchers in recent years. This article proposes a hybrid fuzzy fusion classification model for cardiac arrhythmia diseases. The fusion model is utilized to optimally select the highest-ranked features generated by a variety of well-known feature-selection algorithms. An ensemble of classifiers is then applied to the fusion’s results. The proposed model classifies the arrhythmia dataset from the University of California, Irvine into normal/abnormal classes as well as 16 classes of arrhythmia. Initially, at the preprocessing steps,… More >

Xin Liu¹, Zheng Liu^2,*, Zhilin Huang¹, Mingyu Ling¹, Kangchao Lin¹, Pengqing Chen¹, Xiaomin Huang¹, Yujia Zhai¹

CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.1, pp. 685-707, 2023, DOI:10.32604/cmes.2023.025058

Abstract Ergonomic reliability plays a significant role in the safe operation of devices. With the spread of infectious diseases around the world, in work environments with high loads and high infection rates, medical staff work in a state of high self-protection. The use of visual display terminal (VDT) for medical equipment has undergone fundamental changes, and the traditional medical equipment human-machine interface design needs to be improved. After the completion of design and development, a VDT design enters the experimental testing stage, which has significant limitations for simulating the work of medical staff in the high-load and high-infection environments. The testing… More >

Sandeep Kaur^*, Bharat Bhushan Sagar

CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 1541-1559, 2023, DOI:10.32604/cmc.2023.032857

Abstract Analysis and recognition of ancient scripts is a challenging task as these scripts are inscribed on pillars, stones, or leaves. Optical recognition systems can help in preserving, sharing, and accelerate the study of the ancient scripts, but lack of standard dataset for such scripts is a major constraint. Although many scholars and researchers have captured and uploaded inscription images on various websites, manual searching, downloading and extraction of these images is tedious and error prone. Web search queries return a vast number of irrelevant results, and manually extracting images for a specific script is not scalable. This paper proposes a… More >