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  • Open Access

    CASE REPORT

    Case Report: Laubry-Pezzi Syndrome: Confronting the Lethal Nexus of Life-Threatening Complications in Resource Constrained Settings

    Hayatu Uma1,*, Abdulaziz Aminu1, Raghu Cherukupalli2, Femi Akindotun Akintomide1, Abdul Habu3, Aisha Aminu Lawal1, Adamu Mohammad1

    Congenital Heart Disease, Vol.19, No.6, pp. 635-645, 2024, DOI:10.32604/chd.2025.056641 - 27 January 2025

    Abstract Laubry-Pezzi syndrome (L-PS) is a rare congenital heart disease characterized by a ventricular septal defect (VSD) and aortic valve prolapse. These cardiac lesions predispose individuals to infective endocarditis (IE), a life-threatening complication, especially in resource-constrained settings. A 17-year-old male presented with a three-week history of fever and headache, and a one-week history of abdominal pain, vomiting, and diarrhea. On presentation, he appeared toxic, was febrile, tachypneic, tachycardic, and blood pressure of 120/30 mmHg, and heart sounds were S1, S2. Abdominal examination revealed generalized tenderness. A provisional diagnosis of typhoid sepsis with intestinal perforation was considered.… More >

  • Open Access

    ARTICLE

    An Asynchronous Data Transmission Policy for Task Offloading in Edge-Computing Enabled Ultra-Dense IoT

    Dayong Wang1,*, Kamalrulnizam Bin Abu Bakar1, Babangida Isyaku2, Liping Lei3

    CMC-Computers, Materials & Continua, Vol.81, No.3, pp. 4465-4483, 2024, DOI:10.32604/cmc.2024.059616 - 19 December 2024

    Abstract In recent years, task offloading and its scheduling optimization have emerged as widely discussed and significant topics. The multi-objective optimization problems inherent in this domain, particularly those related to resource allocation, have been extensively investigated. However, existing studies predominantly focus on matching suitable computational resources for task offloading requests, often overlooking the optimization of the task data transmission process. This inefficiency in data transmission leads to delays in the arrival of task data at computational nodes within the edge network, resulting in increased service times due to elevated network transmission latencies and idle computational resources.… More >

  • Open Access

    ARTICLE

    IoT-CDS: Internet of Things Cyberattack Detecting System Based on Deep Learning Models

    Monir Abdullah*

    CMC-Computers, Materials & Continua, Vol.81, No.3, pp. 4265-4283, 2024, DOI:10.32604/cmc.2024.059271 - 19 December 2024

    Abstract The rapid growth and pervasive presence of the Internet of Things (IoT) have led to an unparalleled increase in IoT devices, thereby intensifying worries over IoT security. Deep learning (DL)-based intrusion detection (ID) has emerged as a vital method for protecting IoT environments. To rectify the deficiencies of current detection methodologies, we proposed and developed an IoT cyberattacks detection system (IoT-CDS) based on DL models for detecting bot attacks in IoT networks. The DL models—long short-term memory (LSTM), gated recurrent units (GRUs), and convolutional neural network-LSTM (CNN-LSTM) were suggested to detect and classify IoT attacks.… More >

  • Open Access

    ARTICLE

    Effective Controller Placement in Software-Defined Internet-of-Things Leveraging Deep Q-Learning (DQL)

    Jehad Ali1,*, Mohammed J. F. Alenazi2

    CMC-Computers, Materials & Continua, Vol.81, No.3, pp. 4015-4032, 2024, DOI:10.32604/cmc.2024.058480 - 19 December 2024

    Abstract The controller is a main component in the Software-Defined Networking (SDN) framework, which plays a significant role in enabling programmability and orchestration for 5G and next-generation networks. In SDN, frequent communication occurs between network switches and the controller, which manages and directs traffic flows. If the controller is not strategically placed within the network, this communication can experience increased delays, negatively affecting network performance. Specifically, an improperly placed controller can lead to higher end-to-end (E2E) delay, as switches must traverse more hops or encounter greater propagation delays when communicating with the controller. This paper introduces… More >

  • Open Access

    REVIEW

    Recent Technology Advancements in Smart City Management: A Review

    Chiranjeevi Karri1,2,*, José J. M. Machado3, João Manuel R. S. Tavares1, Deepak Kumar Jain4, Suresh Dannana5, Santosh Kumar Gottapu6, Amir H. Gandomi7,8

    CMC-Computers, Materials & Continua, Vol.81, No.3, pp. 3617-3663, 2024, DOI:10.32604/cmc.2024.058461 - 19 December 2024

    Abstract The rapid population growth, insecure lifestyle, wastage of natural resources, indiscipline behavior of human beings, urgency in the medical field, security of patient information, agricultural-related problems, and automation requirements in industries are the reasons for invention of technologies. Smart cities aim to address these challenges through the integration of technology, data, and innovative practices. Building a smart city involves integrating advanced technologies and data-driven solutions to enhance urban living, improve resource efficiency, and create sustainable environments. This review presents five of the most critical technologies for smart and/or safe cities, addressing pertinent topics such as More >

  • Open Access

    ARTICLE

    Robust Network Security: A Deep Learning Approach to Intrusion Detection in IoT

    Ammar Odeh*, Anas Abu Taleb

    CMC-Computers, Materials & Continua, Vol.81, No.3, pp. 4149-4169, 2024, DOI:10.32604/cmc.2024.058052 - 19 December 2024

    Abstract The proliferation of Internet of Things (IoT) technology has exponentially increased the number of devices interconnected over networks, thereby escalating the potential vectors for cybersecurity threats. In response, this study rigorously applies and evaluates deep learning models—namely Convolutional Neural Networks (CNN), Autoencoders, and Long Short-Term Memory (LSTM) networks—to engineer an advanced Intrusion Detection System (IDS) specifically designed for IoT environments. Utilizing the comprehensive UNSW-NB15 dataset, which encompasses 49 distinct features representing varied network traffic characteristics, our methodology focused on meticulous data preprocessing including cleaning, normalization, and strategic feature selection to enhance model performance. A robust… More >

  • Open Access

    REVIEW

    Navigating IoT Security: Insights into Architecture, Key Security Features, Attacks, Current Challenges and AI-Driven Solutions Shaping the Future of Connectivity

    Ali Hassan1, N. Nizam-Uddin2, Asim Quddus3, Syed Rizwan Hassan4, Ateeq Ur Rehman5,*, Salil Bharany6

    CMC-Computers, Materials & Continua, Vol.81, No.3, pp. 3499-3559, 2024, DOI:10.32604/cmc.2024.057877 - 19 December 2024

    Abstract Enhancing the interconnection of devices and systems, the Internet of Things (IoT) is a paradigm-shifting technology. IoT security concerns are still a substantial concern despite its extraordinary advantages. This paper offers an extensive review of IoT security, emphasizing the technology’s architecture, important security elements, and common attacks. It highlights how important artificial intelligence (AI) is to bolstering IoT security, especially when it comes to addressing risks at different IoT architecture layers. We systematically examined current mitigation strategies and their effectiveness, highlighting contemporary challenges with practical solutions and case studies from a range of industries, such More >

  • Open Access

    ARTICLE

    EGSNet: An Efficient Glass Segmentation Network Based on Multi-Level Heterogeneous Architecture and Boundary Awareness

    Guojun Chen*, Tao Cui, Yongjie Hou, Huihui Li

    CMC-Computers, Materials & Continua, Vol.81, No.3, pp. 3969-3987, 2024, DOI:10.32604/cmc.2024.056093 - 19 December 2024

    Abstract Existing glass segmentation networks have high computational complexity and large memory occupation, leading to high hardware requirements and time overheads for model inference, which is not conducive to efficiency-seeking real-time tasks such as autonomous driving. The inefficiency of the models is mainly due to employing homogeneous modules to process features of different layers. These modules require computationally intensive convolutions and weight calculation branches with numerous parameters to accommodate the differences in information across layers. We propose an efficient glass segmentation network (EGSNet) based on multi-level heterogeneous architecture and boundary awareness to balance the model performance… More >

  • Open Access

    ARTICLE

    Transforming Healthcare: AI-NLP Fusion Framework for Precision Decision-Making and Personalized Care Optimization in the Era of IoMT

    Soha Rawas1, Cerine Tafran1, Duaa AlSaeed2, Nadia Al-Ghreimil2,*

    CMC-Computers, Materials & Continua, Vol.81, No.3, pp. 4575-4601, 2024, DOI:10.32604/cmc.2024.055307 - 19 December 2024

    Abstract In the rapidly evolving landscape of healthcare, the integration of Artificial Intelligence (AI) and Natural Language Processing (NLP) holds immense promise for revolutionizing data analytics and decision-making processes. Current techniques for personalized medicine, disease diagnosis, treatment recommendations, and resource optimization in the Internet of Medical Things (IoMT) vary widely, including methods such as rule-based systems, machine learning algorithms, and data-driven approaches. However, many of these techniques face limitations in accuracy, scalability, and adaptability to complex clinical scenarios. This study investigates the synergistic potential of AI-driven optimization techniques and NLP applications in the context of the… More >

  • Open Access

    PROCEEDINGS

    Catheters with Bioactive Coatings

    Shady Farah1,2,*

    The International Conference on Computational & Experimental Engineering and Sciences, Vol.32, No.2, pp. 1-1, 2024, DOI:10.32604/icces.2024.012639

    Abstract Catheters are among the most frequently used medical tools in modern therapies. Several diseases are treated by catheters (e.g. hydrocephalus) in cardiovascular, urological, gastrointestinal neurovascular, and ophthalmic diseases. Approximately 150 million intravascular catheters are implanted annually in the United States alone. However, although very efficient, following their insertion, catheters are subjected to numerous complications, including resistance to flow, blockage, and mechanical malfunctions, and being subjected to host-immune response and microbial infection. To overcome these complications, we proposed to develop the next generation of catheters with improved functionality and liquid flowability. We assume that polymeric coating More >

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