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  • 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 >

  • Open Access

    ARTICLE

    SDN-Enabled Content Dissemination Scheme for the Internet of Vehicles

    Abida Sharif1, Muhammad Imran Sharif1, Muhammad Attique Khan2, Nisar Ali2, Abdullah Alqahtani3, Majed Alhaisoni4, Ye Jin Kim5, Byoungchol Chang6,*

    CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 2383-2396, 2023, DOI:10.32604/cmc.2023.033894 - 31 March 2023

    Abstract The content-centric networking (CCN) architecture allows access to the content through name, instead of the physical location where the content is stored, which makes it a more robust and flexible content-based architecture. Nevertheless, in CCN, the broadcast nature of vehicles on the Internet of Vehicles (IoV) results in latency and network congestion. The IoV-based content distribution is an emerging concept in which all the vehicles are connected via the internet. Due to the high mobility of vehicles, however, IoV applications have different network requirements that differ from those of many other networks, posing new challenges. More >

  • Open Access

    ARTICLE

    A Semantic Adversarial Network for Detection and Classification of Myopic Maculopathy

    Qaisar Abbas1, Abdul Rauf Baig1,*, Ayyaz Hussain2

    CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1483-1499, 2023, DOI:10.32604/cmc.2023.036366 - 06 February 2023

    Abstract The diagnosis of eye disease through deep learning (DL) technology is the latest trend in the field of artificial intelligence (AI). Especially in diagnosing pathologic myopia (PM) lesions, the implementation of DL is a difficult task because of the classification complexity and definition system of PM. However, it is possible to design an AI-based technique that can identify PM automatically and help doctors make relevant decisions. To achieve this objective, it is important to have adequate resources such as a high-quality PM image dataset and an expert team. The primary aim of this research is… More >

  • Open Access

    ARTICLE

    Stochastic Analysis for the Dynamics of a Poliovirus Epidemic Model

    Ali Raza1, Dumitru Baleanu2,3,4, Zafar Ullah Khan5, Muhammad Mohsin6,*, Nauman Ahmed7, Muhammad Rafiq8, Pervez Anwar9

    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.1, pp. 257-275, 2023, DOI:10.32604/cmes.2023.023231 - 05 January 2023

    Abstract Most developing countries such as Afghanistan, Pakistan, India, Bangladesh, and many more are still fighting against poliovirus. According to the World Health Organization, approximately eighteen million people have been infected with poliovirus in the last two decades. In Asia, still, some countries are suffering from the virus. The stochastic behavior of the poliovirus through the transition probabilities and non-parametric perturbation with fundamental properties are studied. Some basic properties of the deterministic model are studied, equilibria, local stability around the stead states, and reproduction number. Euler Maruyama, stochastic Euler, and stochastic Runge-Kutta study the behavior of More >

  • Open Access

    ARTICLE

    Artificial Intelligence Enabled Decision Support System on E-Healthcare Environment

    B. Karthikeyan1,*, K. Nithya2, Ahmed Alkhayyat3, Yousif Kerrar Yousif4

    Intelligent Automation & Soft Computing, Vol.36, No.2, pp. 2299-2313, 2023, DOI:10.32604/iasc.2023.032585 - 05 January 2023

    Abstract In today’s digital era, e-healthcare systems exploit digital technologies and telecommunication devices such as mobile devices, computers and the internet to provide high-quality healthcare services. E-healthcare decision support systems have been developed to optimize the healthcare services and enhance a patient’s health. These systems enable rapid access to the specialized healthcare services via reliable information, retrieved from the cases or the patient histories. This phenomenon reduces the time taken by the patients to physically visit the healthcare institutions. In the current research work, a new Shuffled Frog Leap Optimizer with Deep Learning-based Decision Support System… More >

  • Open Access

    ARTICLE

    Deep Learning Enabled Intelligent Healthcare Management System in Smart Cities Environment

    Hanan Abdullah Mengash1, Lubna A. Alharbi2, Saud S. Alotaibi3, Sarab AlMuhaideb4, Nadhem Nemri5, Mrim M. Alnfiai6, Radwa Marzouk1, Ahmed S. Salama7, Mesfer Al Duhayyim8,*

    CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 4483-4500, 2023, DOI:10.32604/cmc.2023.032588 - 31 October 2022

    Abstract In recent times, cities are getting smart and can be managed effectively through diverse architectures and services. Smart cities have the ability to support smart medical systems that can infiltrate distinct events (i.e., smart hospitals, smart homes, and community health centres) and scenarios (e.g., rehabilitation, abnormal behavior monitoring, clinical decision-making, disease prevention and diagnosis postmarking surveillance and prescription recommendation). The integration of Artificial Intelligence (AI) with recent technologies, for instance medical screening gadgets, are significant enough to deliver maximum performance and improved management services to handle chronic diseases. With latest developments in digital data collection,… More >

  • Open Access

    ARTICLE

    An Intelligent Cardiovascular Diseases Prediction System Focused on Privacy

    Manjur Kolhar*, Mohammed Misfer

    Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 529-542, 2023, DOI:10.32604/iasc.2023.030098 - 29 September 2022

    Abstract Machine learning (ML) and cloud computing have now evolved to the point where they are able to be used effectively. Further improvement, however, is required when both of these technologies are combined to reap maximum benefits. A way of improving the system is by enabling healthcare workers to select appropriate machine learning algorithms for prediction and, secondly, by preserving the privacy of patient data so that it cannot be misused. The purpose of this paper is to combine these promising technologies to maintain the privacy of patient data during the disease prediction process. Treatment of… More >

  • Open Access

    ARTICLE

    DLMNN Based Heart Disease Prediction with PD-SS Optimization Algorithm

    S. Raghavendra1, Vasudev Parvati2, R. Manjula3, Ashok Kumar Nanda4, Ruby Singh5, D. Lakshmi6, S. Velmurugan7,*

    Intelligent Automation & Soft Computing, Vol.35, No.2, pp. 1353-1368, 2023, DOI:10.32604/iasc.2023.027977 - 19 July 2022

    Abstract In contemporary medicine, cardiovascular disease is a major public health concern. Cardiovascular diseases are one of the leading causes of death worldwide. They are classified as vascular, ischemic, or hypertensive. Clinical information contained in patients’ Electronic Health Records (EHR) enables clinicians to identify and monitor heart illness. Heart failure rates have risen dramatically in recent years as a result of changes in modern lifestyles. Heart diseases are becoming more prevalent in today’s medical setting. Each year, a substantial number of people die as a result of cardiac pain. The primary cause of these deaths is… More >

  • Open Access

    REVIEW

    Clinical relevance and therapeutic potential of IL-38 in immune and non-immune-related disorders

    Mohammad Reza Haghshenas1, Mina Roshan Zamir1, Mahboubeh Sadeghi1, Mohammad Javad Fattahi1, Kimia Mirshekari1, Abbas Ghaderi1,2,*

    European Cytokine Network, Vol.33, No.3, pp. 54-69, 2022, DOI:10.1684/ecn.2022.0480

    Abstract Interleukin-38 (IL-38) is the most recent member of the IL-1 family that acts as a natural inflammatory inhibitor by binding to cognate receptors, particularly the IL-36 receptor. In vitro, animal and human studies on autoimmune, metabolic, cardiovascular and allergic diseases, as well sepsis and respiratory viral infections, have shown that IL-38 exerts an anti-inflammatory activity by modulating the generation and function of inflammatory cytokines (e.g. IL-6, IL-8, IL-17 and IL-36) and regulating dendritic cells, M2 macrophages and regulatory T cells (Tregs). Accordingly, IL-38 may possess therapeutic potential for these types of diseases. IL-38 down-regulates CCR3+… More >

  • Open Access

    ARTICLE

    Computational Study of Anastomosis Angle of Arteriovenous Fistula for Hemodialysis

    Suraj Shembekar*, Dhananjay Zodpe, Pramod Padole

    Molecular & Cellular Biomechanics, Vol.19, No.4, pp. 165-175, 2022, DOI:10.32604/mcb.2022.021513 - 27 December 2022

    Abstract Arteriovenous fistula (AVF) is the endorsed method of vascular access for hemodialysis in end-stage renal disease (ESRD). However, more than 60% of AVF fail to mature for hemodialysis. Intimal hyperplasia leads to stenosis is the primary cause of fistula failure. Wall shear stress (WSS) is one of the important parameters that enact a crucial role in building of intimal hyperplasia. The prime purpose of this research work is to investigate the effect of anastomosis angle on WSS, pressure drop, venous outflow rate and identify the optimal angle of anastomosis of AVF, so that it helps… More >

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