Okechukwu J. Obulezi^1,*, Hatem E. Semary², Sadia Nadir³, Chinyere P. Igbokwe⁴, Gabriel O. Orji¹, A. S. Al-Moisheer², Mohammed Elgarhy⁵

CMES-Computer Modeling in Engineering & Sciences, Vol.144, No.3, pp. 2991-3027, 2025, DOI:10.32604/cmes.2025.069553 - 30 September 2025

Abstract This study introduces the type-I heavy-tailed Burr XII (TIHTBXII) distribution, a highly flexible and robust statistical model designed to address the limitations of conventional distributions in analyzing data characterized by skewness, heavy tails, and diverse hazard behaviors. We meticulously develop the TIHTBXII’s mathematical foundations, including its probability density function (PDF), cumulative distribution function (CDF), and essential statistical properties, crucial for theoretical understanding and practical application. A comprehensive Monte Carlo simulation evaluates four parameter estimation methods: maximum likelihood (MLE), maximum product spacing (MPS), least squares (LS), and weighted least squares (WLS). The simulation results consistently show… More >

Prasanna Kottapalle^1,*, Tan Kuan Tak², Pravin Ramdas Kshirsagar³, Gopichand Ginnela⁴, Vijaya Krishna Akula⁵

CMC-Computers, Materials & Continua, Vol.84, No.2, pp. 3857-3892, 2025, DOI:10.32604/cmc.2025.065287 - 03 July 2025

Abstract Heart failure prediction is crucial as cardiovascular diseases become the leading cause of death worldwide, exacerbated by the COVID-19 pandemic. Age, cholesterol, and blood pressure datasets are becoming inadequate because they cannot capture the complexity of emerging health indicators. These high-dimensional and heterogeneous datasets make traditional machine learning methods difficult, and Skewness and other new biomarkers and psychosocial factors bias the model’s heart health prediction across diverse patient profiles. Modern medical datasets’ complexity and high dimensionality challenge traditional prediction models like Support Vector Machines and Decision Trees. Quantum approaches include QSVM, QkNN, QDT, and others.… More >

Yuhang Chen¹, Mahdi Bahaghighat^2,*, Aghil Esmaeili Kelishomi³, Jingyi Du^1,*

Computer Systems Science and Engineering, Vol.47, No.1, pp. 675-697, 2023, DOI:10.32604/csse.2023.038234 - 26 May 2023

Abstract In the digital world, a wide range of handwritten and printed documents should be converted to digital format using a variety of tools, including mobile phones and scanners. Unfortunately, this is not an optimal procedure, and the entire document image might be degraded. Imperfect conversion effects due to noise, motion blur, and skew distortion can lead to significant impact on the accuracy and effectiveness of document image segmentation and analysis in Optical Character Recognition (OCR) systems. In Document Image Analysis Systems (DIAS), skew estimation of images is a crucial step. In this paper, a novel,… More >

Aswathy Ravikumar, Harini Sriraman^*

CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 891-909, 2023, DOI:10.32604/cmc.2023.035848 - 06 February 2023

Abstract Pneumonia is an acute lung infection that has caused many fatalities globally. Radiologists often employ chest X-rays to identify pneumonia since they are presently the most effective imaging method for this purpose. Computer-aided diagnosis of pneumonia using deep learning techniques is widely used due to its effectiveness and performance. In the proposed method, the Synthetic Minority Oversampling Technique (SMOTE) approach is used to eliminate the class imbalance in the X-ray dataset. To compensate for the paucity of accessible data, pre-trained transfer learning is used, and an ensemble Convolutional Neural Network (CNN) model is developed. The More >

Firas Abedi¹, Subhi R.M. Zeebaree², Zainab Salih Ageed³, Hayder M.A. Ghanimi⁴, Ahmed Alkhayyat^5,*, Mohammed A.M. Sadeeq⁶, Sarmad Nozad Mahmood⁷, Ali S. Abosinnee⁸, Zahraa H. Kareem⁹, Ali Hashim Abbas¹⁰, Waleed Khaild Al-Azzawi¹¹, Mustafa Musa Jaber^12,13, Mohammed Dauwed¹⁴

CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 5691-5704, 2023, DOI:10.32604/cmc.2023.034435 - 28 December 2022

Abstract As the amount of medical images transmitted over networks and kept on online servers continues to rise, the need to protect those images digitally is becoming increasingly important. However, due to the massive amounts of multimedia and medical pictures being exchanged, low computational complexity techniques have been developed. Most commonly used algorithms offer very little security and require a great deal of communication, all of which add to the high processing costs associated with using them. First, a deep learning classifier is used to classify records according to the degree of concealment they require. Medical… More >

Preeti Agarwal^*, Priyaranjan Pal, Pradeep Kumar Mehta

Sound & Vibration, Vol.56, No.2, pp. 105-125, 2022, DOI:10.32604/sv.2022.014874 - 25 March 2022

Abstract The free vibration analysis of simply supported box-girder bridges is carried out using the finite element method. The fundamental frequency is determined in straight, skew, curved and skew-curved box-girder bridges. It is important to analyse the combined effect of skewness and curvature because skew-curved box-girder bridge behaviour cannot be predicted by simply adding the individual effects of skewness and curvature. At first, an existing model is considered to validate the present approach. A convergence study is carried out to decide the mesh size in the finite element method. An exhaustive parametric study is conducted to… More >

Chen Xu¹, Yawen Mao², Hongtian Chen^3,*, Hongfeng Tao¹, Fei Liu¹

CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.1, pp. 349-364, 2022, DOI:10.32604/cmes.2021.019027 - 24 January 2022

Abstract This paper is focused on the state estimation problem for nonlinear systems with unknown statistics of measurement noise. Based on the cubature Kalman filter, we propose a new nonlinear filtering algorithm that employs a skew t distribution to characterize the asymmetry of the measurement noise. The system states and the statistics of skew t noise distribution, including the shape matrix, the scale matrix, and the degree of freedom (DOF) are estimated jointly by employing variational Bayesian (VB) inference. The proposed method is validated in a target tracking example. Results of the simulation indicate that the More >

Siti Julia Rosli^1,2, Hasliza A Rahim^1,2,*, Khairul Najmy Abdul Rani^1,2, Ruzelita Ngadiran^2,3, Wan Azani Mustafa^3,4, Muzammil Jusoh^1,2, Mohd Najib Mohd Yasin^1,2, Thennarasan Sabapathy^1,2, Mohamedfareq Abdulmalek⁵, Wan Suryani Firuz Wan Ariffin², Ahmed Alkhayyat⁶

CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 3533-3556, 2022, DOI:10.32604/cmc.2022.021719 - 07 December 2021

Abstract The essential purpose of radar is to detect a target of interest and provide information concerning the target's location, motion, size, and other parameters. The knowledge about the pulse trains’ properties shows that a class of signals is mainly well suited to digital processing of increasing practical importance. A low autocorrelation binary sequence (LABS) is a complex combinatorial problem. The main problems of LABS are low Merit Factor (MF) and shorter length sequences. Besides, the maximum possible MF equals 12.3248 as infinity length is unable to be achieved. Therefore, this study implemented two techniques to… More >

Sagheer Abbas¹, Yousef Alhwaiti², Areej Fatima³, Muhammad A. Khan⁴, Muhammad Adnan Khan^5,*, Taher M. Ghazal^6,7, Asma Kanwal^1,8, Munir Ahmad¹, Nouh Sabri Elmitwally^2,9

CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 4563-4581, 2022, DOI:10.32604/cmc.2022.021102 - 11 October 2021

Abstract This paper presents a handwritten document recognition system based on the convolutional neural network technique. In today’s world, handwritten document recognition is rapidly attaining the attention of researchers due to its promising behavior as assisting technology for visually impaired users. This technology is also helpful for the automatic data entry system. In the proposed system prepared a dataset of English language handwritten character images. The proposed system has been trained for the large set of sample data and tested on the sample images of user-defined handwritten documents. In this research, multiple experiments get very worthy… More >

G. Prathiba^1,*, M. Santhi²

Intelligent Automation & Soft Computing, Vol.31, No.3, pp. 1611-1626, 2022, DOI:10.32604/iasc.2022.018975 - 09 October 2021

Abstract High-quality, high-resolution flash ADCs are used in reliable VLSI (Very Large-Scale Integrated) circuits to minimize the power consumption. An analogue electrical signal is converted into a discrete-valued sequence by these ADCs. This paper proposes a four-bit 1.2GS/s low-power Clocked Flash ADC (C-FADC). A low-power Clocked-Improved Threshold Inverter Quantization (CITIQ) comparator, an Adaptive Bubble Free (ABF) logic circuit, and a compact Binary Encoder (BE) are all part of the presented structure. A clock network in the comparator circuit reduces skew and jitters, while an ABF logic circuit detects and corrects fourth order bubble faults detected from More >