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  • Open Access

    ARTICLE

    Flexible Global Aggregation and Dynamic Client Selection for Federated Learning in Internet of Vehicles

    Tariq Qayyum1, Zouheir Trabelsi1,*, Asadullah Tariq1, Muhammad Ali2, Kadhim Hayawi3, Irfan Ud Din4

    CMC-Computers, Materials & Continua, Vol.77, No.2, pp. 1739-1757, 2023, DOI:10.32604/cmc.2023.043684 - 29 November 2023

    Abstract Federated Learning (FL) enables collaborative and privacy-preserving training of machine learning models within the Internet of Vehicles (IoV) realm. While FL effectively tackles privacy concerns, it also imposes significant resource requirements. In traditional FL, trained models are transmitted to a central server for global aggregation, typically in the cloud. This approach often leads to network congestion and bandwidth limitations when numerous devices communicate with the same server. The need for Flexible Global Aggregation and Dynamic Client Selection in FL for the IoV arises from the inherent characteristics of IoV environments. These include diverse and distributed… More >

  • Open Access

    ARTICLE

    Multi Head Deep Neural Network Prediction Methodology for High-Risk Cardiovascular Disease on Diabetes Mellitus

    B. Ramesh, Kuruva Lakshmanna*

    CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.3, pp. 2513-2528, 2023, DOI:10.32604/cmes.2023.028944 - 03 August 2023

    Abstract Major chronic diseases such as Cardiovascular Disease (CVD), diabetes, and cancer impose a significant burden on people and healthcare systems around the globe. Recently, Deep Learning (DL) has shown great potential for the development of intelligent mobile Health (mHealth) interventions for chronic diseases that could revolutionize the delivery of health care anytime, anywhere. The aim of this study is to present a systematic review of studies that have used DL based on mHealth data for the diagnosis, prognosis, management, and treatment of major chronic diseases and advance our understanding of the progress made in this… More > Graphic Abstract

    Multi Head Deep Neural Network Prediction Methodology for High-Risk Cardiovascular Disease on Diabetes Mellitus

  • Open Access

    ARTICLE

    Decision Analysis on IoV Routing Transmission and Energy Efficiency Optimization Algorithm with AmBC

    Baofeng Ji1,2,3,*, Mingkun Zhang1,2, Weixing Wang1, Song Chen4

    CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.3, pp. 2661-2673, 2023, DOI:10.32604/cmes.2023.028762 - 03 August 2023

    Abstract The improvement of the quality and efficiency of vehicle wireless network data transmission is always a key concern in the Internet of Vehicles (IoV). Routing transmission solved the limitation of transmission distance to a certain extent. Traditional routing algorithm cannot adapt to complex traffic environment, resulting in low transmission efficiency. In order to improve the transmission success rate and quality of vehicle network routing transmission, make the routing algorithm more suitable for complex traffic environment, and reduce transmission power consumption to improve energy efficiency, a comprehensive optimized routing transmission algorithm is proposed. Based on the… More >

  • Open Access

    ARTICLE

    Deep Learning Approach for Automatic Cardiovascular Disease Prediction Employing ECG Signals

    Muhammad Tayyeb1, Muhammad Umer1, Khaled Alnowaiser2, Saima Sadiq3, Ala’ Abdulmajid Eshmawi4, Rizwan Majeed5, Abdullah Mohamed6, Houbing Song7, Imran Ashraf8,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.2, pp. 1677-1694, 2023, DOI:10.32604/cmes.2023.026535 - 26 June 2023

    Abstract Cardiovascular problems have become the predominant cause of death worldwide and a rise in the number of patients has been observed lately. Currently, electrocardiogram (ECG) data is analyzed by medical experts to determine the cardiac abnormality, which is time-consuming. In addition, the diagnosis requires experienced medical experts and is error-prone. However, automated identification of cardiovascular disease using ECGs is a challenging problem and state-of-the-art performance has been attained by complex deep learning architectures. This study proposes a simple multilayer perceptron (MLP) model for heart disease prediction to reduce computational complexity. ECG dataset containing averaged signals More >

  • Open Access

    REVIEW

    The role of periodontal disease in atherosclerotic cardiovascular disease

    XIWEI ZHAO1,#, JINSONG WANG1,2,#, YIFAN XU1, JIAN ZHOU5,*, LEI HU1,3,4,*

    BIOCELL, Vol.47, No.7, pp. 1431-1438, 2023, DOI:10.32604/biocell.2023.028217 - 21 June 2023

    Abstract Atherosclerotic cardiovascular disease (ASCVD) includes a group of disorders of the heart and blood vessels and accounts for major morbidity and premature death worldwide. Periodontitis is a chronic inflammatory disease with the gradual destruction of supporting tissues around the teeth, including gingiva, periodontal ligament, alveolar bone, and cementum. Periodontitis has been found to potentially increase the risk of ASCVD. Generally, oral microorganisms and inflammation are the major factors for periodontitis to the incidence of ASCVD. Recently, evidence has shown that the loss of masticatory function is another important factor of periodontitis to the incidence of More > Graphic Abstract

    The role of periodontal disease in atherosclerotic cardiovascular disease

  • Open Access

    ARTICLE

    Optimized Three-Dimensional Cardiovascular Magnetic Resonance Whole Heart Imaging Utilizing Non-Selective Excitation and Compressed Sensing in Children and Adults with Congenital Heart Disease

    Ingo Paetsch1,*, Roman Gebauer2, Christian Paech2, Frank-Thomas Riede2, Sabrina Oebel1, Andreas Bollmann1, Christian Stehning3, Jouke Smink4, Ingo Daehnert2, Cosima Jahnke1

    Congenital Heart Disease, Vol.18, No.3, pp. 279-294, 2023, DOI:10.32604/chd.2023.029634 - 09 June 2023

    Abstract Background: In congenital heart disease (CHD) patients, detailed three-dimensional anatomy depiction plays a pivotal role for diagnosis and therapeutical decision making. Hence, the present study investigated the applicability of an advanced cardiovascular magnetic resonance (CMR) whole heart imaging approach utilizing nonselective excitation and compressed sensing for anatomical assessment and interventional guidance of CHD patients in comparison to conventional dynamic CMR angiography. Methods: 86 consecutive pediatric patients and adults with congenital heart disease (age, 1 to 74 years; mean, 35 years) underwent CMR imaging including a free-breathing, ECG-triggered 3D nonselective SSFP whole heart acquisition using compressed… More >

  • Open Access

    ARTICLE

    Quantitative Parameters Analysis for Prenatally Echocardiographic Diagnosis of Atrioventricular Septal Defects

    Xiaoxue Zhou1, Tingyang Yang2, Ye Zhang1, Yanping Ruan1, Jiancheng Han1, Xiaowei Liu1, Ying Zhao1, Xiaoyan Gu1, Tingting Liu1, Hairui Wang1, Yihua He1,*

    Congenital Heart Disease, Vol.18, No.3, pp. 387-397, 2023, DOI:10.32604/chd.2023.029060 - 09 June 2023

    Abstract Background: Atrioventricular septal defects (AVSDs) are screened and diagnosed usually rely on the imaging characteristics of fetal echocardiography (FE). However, diagnosis on images is heavily depended on sonographers’ experience and the quantitative data are rarely studied. Objective: This study aimed to realize the prenatal diagnosis of AVSDs by analyzing the quantitative data on FE. Methods: One hundred and thirteen cardiac quantitative data was analyzed in 370 normal and 49 AVSDs fetuses retrospectively. The top six with the highest diagnostic accuracy rate were acquired according to the area under the curve (AUC), and the diagnostic value of… More >

  • Open Access

    ARTICLE

    Secure Blockchain-Enabled Internet of Vehicles Scheme with Privacy Protection

    Jiansheng Zhang1, Yang Xin1,*, Yuyan Wang2, Xiaohui Lei2, Yixian Yang1

    CMC-Computers, Materials & Continua, Vol.75, No.3, pp. 6185-6199, 2023, DOI:10.32604/cmc.2023.038029 - 29 April 2023

    Abstract The car-hailing platform based on Internet of Vehicles (IoV) technology greatly facilitates passengers’ daily car-hailing, enabling drivers to obtain orders more efficiently and obtain more significant benefits. However, to match the driver closest to the passenger, it is often necessary to process the location information of the passenger and driver, which poses a considerable threat to privacy disclosure to the passenger and driver. Targeting these issues, in this paper, by combining blockchain and Paillier homomorphic encryption algorithm, we design a secure blockchain-enabled IoV scheme with privacy protection for online car-hailing. In this scheme, firstly, we… More >

  • Open Access

    ARTICLE

    Probability Based Regression Analysis for the Prediction of Cardiovascular Diseases

    Wasif Akbar1, Adbul Mannan2, Qaisar Shaheen3,*, Mohammad Hijji4, Muhammad Anwar5, Muhammad Ayaz6

    CMC-Computers, Materials & Continua, Vol.75, No.3, pp. 6269-6286, 2023, DOI:10.32604/cmc.2023.036141 - 29 April 2023

    Abstract Machine Learning (ML) has changed clinical diagnostic procedures drastically. Especially in Cardiovascular Diseases (CVD), the use of ML is indispensable to reducing human errors. Enormous studies focused on disease prediction but depending on multiple parameters, further investigations are required to upgrade the clinical procedures. Multi-layered implementation of ML also called Deep Learning (DL) has unfolded new horizons in the field of clinical diagnostics. DL formulates reliable accuracy with big datasets but the reverse is the case with small datasets. This paper proposed a novel method that deals with the issue of less data dimensionality. Inspired… More >

  • Open Access

    ARTICLE

    A Secure Energy Internet Scheme for IoV Based on Post-Quantum Blockchain

    Jiansheng Zhang1, Yang Xin1,*, Yuyan Wang2, Xiaohui Lei2, Yixian Yang1

    CMC-Computers, Materials & Continua, Vol.75, No.3, pp. 6323-6336, 2023, DOI:10.32604/cmc.2023.034668 - 29 April 2023

    Abstract With the increasing use of distributed electric vehicles (EV), energy management in the Internet of vehicles (IoV) has attracted more attention, especially demand response (DR) management to achieve efficient energy management in IoV. Therefore, it is a tendency to introduce distributed energy such as renewable energy into the existing supply system. For optimizing the energy internet (EI) for IoV, in this paper, we introduce blockchain into energy internet and propose a secure EI scheme for IoV based on post-quantum blockchain, which provides the new information services and an incentive cooperation mechanism for the current energy… More >

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