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  • Open Access


    Analyzing the Impact of Blockchain Models for Securing Intelligent Logistics through Unified Computational Techniques

    Mohammed S. Alsaqer1, Majid H. Alsulami2,*, Rami N. Alkhawaji3, Abdulellah A. Alaboudi2

    CMC-Computers, Materials & Continua, Vol.77, No.3, pp. 3943-3968, 2023, DOI:10.32604/cmc.2023.042379

    Abstract Blockchain technology has revolutionized conventional trade. The success of blockchain can be attributed to its distributed ledger characteristic, which secures every record inside the ledger using cryptography rules, making it more reliable, secure, and tamper-proof. This is evident by the significant impact that the use of this technology has had on people connected to digital spaces in the present-day context. Furthermore, it has been proven that blockchain technology is evolving from new perspectives and that it provides an effective mechanism for the intelligent transportation system infrastructure. To realize the full potential of the accurate and… More >

  • Open Access


    Real-Time Prediction Algorithm for Intelligent Edge Networks with Federated Learning-Based Modeling

    Seungwoo Kang1, Seyha Ros1, Inseok Song1, Prohim Tam1, Sa Math2, Seokhoon Kim1,3,*

    CMC-Computers, Materials & Continua, Vol.77, No.2, pp. 1967-1983, 2023, DOI:10.32604/cmc.2023.045020

    Abstract Intelligent healthcare networks represent a significant component in digital applications, where the requirements hold within quality-of-service (QoS) reliability and safeguarding privacy. This paper addresses these requirements through the integration of enabler paradigms, including federated learning (FL), cloud/edge computing, software-defined/virtualized networking infrastructure, and converged prediction algorithms. The study focuses on achieving reliability and efficiency in real-time prediction models, which depend on the interaction flows and network topology. In response to these challenges, we introduce a modified version of federated logistic regression (FLR) that takes into account convergence latencies and the accuracy of the final FL model… More >

  • Open Access


    Diagnosis of Autism Spectrum Disorder by Imperialistic Competitive Algorithm and Logistic Regression Classifier

    Shabana R. Ziyad1,*, Liyakathunisa2, Eman Aljohani2, I. A. Saeed3

    CMC-Computers, Materials & Continua, Vol.77, No.2, pp. 1515-1534, 2023, DOI:10.32604/cmc.2023.040874

    Abstract Autism spectrum disorder (ASD), classified as a developmental disability, is now more common in children than ever. A drastic increase in the rate of autism spectrum disorder in children worldwide demands early detection of autism in children. Parents can seek professional help for a better prognosis of the child’s therapy when ASD is diagnosed under five years. This research study aims to develop an automated tool for diagnosing autism in children. The computer-aided diagnosis tool for ASD detection is designed and developed by a novel methodology that includes data acquisition, feature selection, and classification phases.… More >

  • Open Access


    A Novel Unsupervised MRI Synthetic CT Image Generation Framework with Registration Network

    Liwei Deng1, Henan Sun1, Jing Wang2, Sijuan Huang3, Xin Yang3,*

    CMC-Computers, Materials & Continua, Vol.77, No.2, pp. 2271-2287, 2023, DOI:10.32604/cmc.2023.039062

    Abstract In recent years, radiotherapy based only on Magnetic Resonance (MR) images has become a hot spot for radiotherapy planning research in the current medical field. However, functional computed tomography (CT) is still needed for dose calculation in the clinic. Recent deep-learning approaches to synthesized CT images from MR images have raised much research interest, making radiotherapy based only on MR images possible. In this paper, we proposed a novel unsupervised image synthesis framework with registration networks. This paper aims to enforce the constraints between the reconstructed image and the input image by registering the reconstructed… More >

  • Open Access


    Targeted anti-tumor synergistic effects of Myc decoy oligodeoxynucleotides-loaded selenium nanostructure combined with chemoradiotherapy on LNCaP prostate cancer cells


    Oncology Research, Vol.32, No.1, pp. 101-125, 2024, DOI:10.32604/or.2023.044741

    Abstract In the present study, we investigated the synergistic effects of targeted methotrexate-selenium nanostructure containing Myc decoy oligodeoxynucleotides along with X-irradiation exposure as a combination therapy on LNCaP prostate cancer cells. Myc decoy ODNs were designed based on the promoter of Bcl-2 gene and analyzed by molecular docking and molecular dynamics assays. ODNs were loaded on the synthesized Se@BSA@Chi-MTX nanostructure. The physicochemical characteristics of nanostructures were determined by FTIR, DLS, UV-vis, TEM, EDX, in vitro release, and hemolysis tests. Subsequently, the cytotoxicity properties of them with and without X-irradiation were investigated by uptake, MTT, cell cycle, apoptosis, and… More > Graphic Abstract

    Targeted anti-tumor synergistic effects of Myc decoy oligodeoxynucleotides-loaded selenium nanostructure combined with chemoradiotherapy on LNCaP prostate cancer cells

  • Open Access


    3D Road Network Modeling and Road Structure Recognition in Internet of Vehicles

    Dun Cao1, Jia Ru1, Jian Qin1, Amr Tolba2, Jin Wang1, Min Zhu3,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.2, pp. 1365-1384, 2024, DOI:10.32604/cmes.2023.030260

    Abstract Internet of Vehicles (IoV) is a new system that enables individual vehicles to connect with nearby vehicles, people, transportation infrastructure, and networks, thereby realizing a more intelligent and efficient transportation system. The movement of vehicles and the three-dimensional (3D) nature of the road network cause the topological structure of IoV to have the high space and time complexity. Network modeling and structure recognition for 3D roads can benefit the description of topological changes for IoV. This paper proposes a 3D general road model based on discrete points of roads obtained from GIS. First, the constraints… More >

  • Open Access


    An Adaptive Edge Detection Algorithm for Weed Image Analysis

    Yousef Alhwaiti1,*, Muhammad Hameed Siddiqi1, Irshad Ahmad2

    Computer Systems Science and Engineering, Vol.47, No.3, pp. 3011-3031, 2023, DOI:10.32604/csse.2023.042110

    Abstract Weeds are one of the utmost damaging agricultural annoyers that have a major influence on crops. Weeds have the responsibility to get higher production costs due to the waste of crops and also have a major influence on the worldwide agricultural economy. The significance of such concern got motivation in the research community to explore the usage of technology for the detection of weeds at early stages that support farmers in agricultural fields. Some weed methods have been proposed for these fields; however, these algorithms still have challenges as they were implemented against controlled environments.… More >

  • Open Access


    An Efficient Cyber Security and Intrusion Detection System Using CRSR with PXORP-ECC and LTH-CNN

    Nouf Saeed Alotaibi*

    CMC-Computers, Materials & Continua, Vol.76, No.2, pp. 2061-2078, 2023, DOI:10.32604/cmc.2023.039446

    Abstract Intrusion Detection System (IDS) is a network security mechanism that analyses all users’ and applications’ traffic and detects malicious activities in real-time. The existing IDS methods suffer from lower accuracy and lack the required level of security to prevent sophisticated attacks. This problem can result in the system being vulnerable to attacks, which can lead to the loss of sensitive data and potential system failure. Therefore, this paper proposes an Intrusion Detection System using Logistic Tanh-based Convolutional Neural Network Classification (LTH-CNN). Here, the Correlation Coefficient based Mayfly Optimization (CC-MA) algorithm is used to extract the… More >

  • Open Access


    Measuring the Tensile Strength Degradations of Mineral Grain Interfaces (MGIs) in the Granite After Thermo-hydro-mechanical (THM) Coupling

    Mengyi Li1, Zhijun Wu1,*

    The International Conference on Computational & Experimental Engineering and Sciences, Vol.25, No.1, pp. 1-2, 2023, DOI:10.32604/icces.2023.09829

    Abstract Buried in depth for decades of years, granite in the deep geological repository will be subjected to extremely complex effects of thermo-hydro-mechanical (THM) treatment, and the tensile strengths of mineral grain interfaces (MGIs) are inevitably impacted by the THM treatment [1, 2]. Originated by the failure modes of granite after THM treatment, the tensile strength of MGI plays an important role in determining the macro mechanical properties of THM-treated granite [3, 4]. However, the accurate characterization of the tensile strength degradations of MGIs with THM treatment is still lacking. In this study, the varied tensile… More >

  • Open Access


    Study on Intermittent Discharge Characteristics of Typical Solid Insulation Defects in Gas Insulated Switchgear

    Xu Yang1,2, Jing Zhang1,2, Chuanxian Luo1,2, Qinqing Huang1,2, Hui Xu1,2, Guozhi Zhang1,2,*

    Energy Engineering, Vol.120, No.9, pp. 2115-2132, 2023, DOI:10.32604/ee.2023.027198

    Abstract In response to the problem of frequent leakage and false alarm of partial discharge insulation defects in GIS, this paper conducts experimental research on intermittent discharge characteristics of common solid insulation defects in GIS. Using true GIS to build a multi-source testing platform for intermittent discharge of solid insulation defects, and using pulse current method, ultra-high frequency method, ultrasonic method, and gas characteristic component detection method to study the variation law of intermittent discharge characteristics of solid insulation defects. The results show that: the intermittent discharge state of metal fouling defects on the solid insulation… More >

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