Andi Tang, Huan Zhou^*, Tong Han, Lei Xie

CMES-Computer Modeling in Engineering & Sciences, Vol.130, No.1, pp. 331-364, 2022, DOI:10.32604/cmes.2021.017310

Abstract The sparrow search algorithm (SSA) is a newly proposed meta-heuristic optimization algorithm based on the sparrow foraging principle. Similar to other meta-heuristic algorithms, SSA has problems such as slow convergence speed and difficulty in jumping out of the local optimum. In order to overcome these shortcomings, a chaotic sparrow search algorithm based on logarithmic spiral strategy and adaptive step strategy (CLSSA) is proposed in this paper. Firstly, in order to balance the exploration and exploitation ability of the algorithm, chaotic mapping is introduced to adjust the main parameters of SSA. Secondly, in order to improve the diversity of the population… More >

Zainab Arshad¹, Sohail Masood Bhatti^2,*, Huma Tauseef³, Arfan Jaffar²

Intelligent Automation & Soft Computing, Vol.32, No.2, pp. 1195-1205, 2022, DOI:10.32604/iasc.2022.022160

Abstract According to the World Health Organization, 31% death rate in the World is because of cardiovascular diseases like heart arrhythmia and heart failure. Early diagnosis of heart problems may help in timely treatment of the patients and hence control death rate. Heart sounds are good signals of heart health if examined by an expert. Moreover, heart sounds can be analyzed with inexpensive and portable medical devices. Automatic heart sound classification can be very useful in diagnosing heart problems. Major focus of this research is to study the existing techniques for heart sound classification and develop a more sophisticated method. A… More >

Khalid Mahmood Aamir¹, Muhammad Ramzan^1,2, Saima Skinadar¹, Hikmat Ullah Khan³, Usman Tariq⁴, Hyunsoo Lee⁵, Yunyoung Nam^5,*, Muhammad Attique Khan⁶

CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 17-33, 2022, DOI:10.32604/cmc.2022.018613

Abstract This paper focuses on detecting diseased signals and arrhythmias classification into two classes: ventricular tachycardia and premature ventricular contraction. The sole purpose of the signal detection is used to determine if a signal has been collected from a healthy or sick person. The proposed research approach presents a mathematical model for the signal detector based on calculating the instantaneous frequency (IF). Once a signal taken from a patient is detected, then the classifier takes that signal as input and classifies the target disease by predicting the class label. While applying the classifier, templates are designed separately for ventricular tachycardia and… More >

Jakkrit Onshaunjit, Jakkree Srinonchat^*

CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 355-367, 2022, DOI:10.32604/cmc.2022.017698

Abstract An ideal printed circuit board (PCB) defect inspection system can detect defects and classify PCB defect types. Existing defect inspection technologies can identify defects but fail to classify all PCB defect types. This research thus proposes an algorithmic scheme that can detect and categorize all 14-known PCB defect types. In the proposed algorithmic scheme, fuzzy c-means clustering is used for image segmentation via image subtraction prior to defect detection. Arithmetic and logic operations, the circle hough transform (CHT), morphological reconstruction (MR), and connected component labeling (CCL) are used in defect classification. The algorithmic scheme achieves 100% defect detection and 99.05%… More >

Ramya G. Franklin^1,*, B. Muthukumar²

Intelligent Automation & Soft Computing, Vol.31, No.2, pp. 835-851, 2022, DOI:10.32604/iasc.2022.019877

Abstract Electrocardiography (ECG) is a method for monitoring the human heart’s electrical activity. ECG signal is often used by clinical experts in the collected time arrangement for the evaluation of any rhythmic circumstances of a topic. The research was carried to make the assignment computerized by displaying the problem with encoder-decoder methods, by using misfortune appropriation to predict standard or anomalous information. The two Convolutional Neural Networks (CNNs) and the Long Short-Term Memory (LSTM) fully connected layer (FCL) have shown improved levels over deep learning networks (DLNs) across a wide range of applications such as speech recognition, prediction etc., As CNNs… More >

Atiqe Ur Rahman^1,*, Muhammad Saeed¹, Sultan S. Alodhaibi², Hamiden Abd El-Wahed Khalifa^3,4

CMES-Computer Modeling in Engineering & Sciences, Vol.128, No.2, pp. 743-777, 2021, DOI:10.32604/cmes.2021.016736

Abstract Hypersoft set is an extension of soft set as it further partitions each attribute into its corresponding attribute-valued set. This structure is more flexible and useful as it addresses the limitation of soft set for dealing with the scenarios having disjoint attribute-valued sets corresponding to distinct attributes. The main purpose of this study is to make the existing literature regarding neutrosophic parameterized soft set in line with the need of multi-attribute approximate function. Firstly, we conceptualize the neutrosophic parameterized hypersoft sets under the settings of fuzzy set, intuitionistic fuzzy set and neutrosophic set along with some of their elementary properties… More >

Nimmala Mangathayaru^1,*, Padmaja Rani², Vinjamuri Janaki³, Kalyanapu Srinivas⁴, B. Mathura Bai¹, G. Sai Mohan¹, B. Lalith Bharadwaj¹

CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 2425-2443, 2021, DOI:10.32604/cmc.2021.016534

Abstract Arrhythmia is ubiquitous worldwide and cardiologists tend to provide solutions from the recent advancements in medicine. Detecting arrhythmia from ECG signals is considered a standard approach and hence, automating this process would aid the diagnosis by providing fast, cost-efficient, and accurate solutions at scale. This is executed by extracting the definite properties from the individual patterns collected from Electrocardiography (ECG) signals causing arrhythmia. In this era of applied intelligence, automated detection and diagnostic solutions are widely used for their spontaneous and robust solutions. In this research, our contributions are two-fold. Firstly, the Dual-Tree Complex Wavelet Transform (DT-CWT) method is implied… More >

Fabrizio Drago^*, Irma Battipaglia, Pietro Paolo Tamborrino, Luigina Porco, Camilla Calvieri, Mario Salvatore Russo, Vincenzo Pazzano, Romolo Remoli, Massimo Stefano Silvetti

Congenital Heart Disease, Vol.16, No.6, pp. 561-572, 2021, DOI:10.32604/CHD.2021.016623

Abstract Background: Cryoablation of accessory pathways (APs) is effective and very safe in children, as previously reported by our group. The aim of this retrospective study was to evaluate the current efficacy of 3D non-fluoroscopic cryoablation of right sided APs in children, comparing results obtained with the Ensite Velocity^TM and the more recent Ensite Precision^TM 3D mapping systems. Methods and Results: From January 2016 to December 2019, 102 pediatric patients [mean age 12.5 ± 2.8, 62 males (61% of total cohort)] with right APs underwent 3D non-fluoroscopic transcatheter cryoablation at our Institution. Fifteen (14.7%) patients had previously undergone catheter ablation. Acute… More >

Abdullah M. Almarashi^*

CMES-Computer Modeling in Engineering & Sciences, Vol.127, No.2, pp. 621-643, 2021, DOI:10.32604/cmes.2021.014407

Abstract In this paper, a modified form of the traditional inverse Lomax distribution is proposed and its characteristics are studied. The new distribution which called modified logarithmic transformed inverse Lomax distribution is generated by adding a new shape parameter based on logarithmic transformed method. It contains two shape and one scale parameters and has different shapes of probability density and hazard rate functions. The new shape parameter increases the flexibility of the statistical properties of the traditional inverse Lomax distribution including mean, variance, skewness and kurtosis. The moments, entropies, order statistics and other properties are discussed. Six methods of estimation are… More >

D. R. V. S. R. K. Sastry¹, Peri K. Kameswaran², Mohammad Hatami^3,*

FDMP-Fluid Dynamics & Materials Processing, Vol.17, No.2, pp. 285-300, 2021, DOI:10.32604/fdmp.2021.014429

Abstract The problem of Marangoni mixed convection in the presence of an inclined magnetic field with uniform strength in a nanofluid (formed by the dispersion of two metallic nanoparticles, i.e., Copper (Cu), and alumina (Al₂O₃) in water) is addressed numerically. The effects of viscous dissipation and Ohmic heating are also considered. The original set of governing partial differential equations is reduced to a set of non-linear coupled ordinary differential equations employing the similarity transformation technique. The simplified equations are numerically solved through MATLAB ‘bvp4c’ algorithm. The results are presented in terms of graphs for several parameters. It is found that enhancing… More >