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  • Open Access

    ARTICLE

    Securing Forwarding Layers from Eavesdropping Attacks Using Proactive Approaches

    Jiajun Yan, Ying Zhou*, Anchen Dai, Tao Wang

    CMC-Computers, Materials & Continua, Vol., , DOI:10.32604/cmc.2024.048922

    Abstract As an emerging network paradigm, the software-defined network (SDN) finds extensive application in areas such as smart grids, the Internet of Things (IoT), and edge computing. The forwarding layer in software-defined networks is susceptible to eavesdropping attacks. Route hopping is a moving target defense (MTD) technology that is frequently employed to resist eavesdropping attacks. In the traditional route hopping technology, both request and reply packets use the same hopping path. If an eavesdropping attacker monitors the nodes along this path, the risk of 100% data leakage becomes substantial. In this paper, we present an effective route hopping approach, called two-day… More >

  • Open Access

    ARTICLE

    A Spectral Convolutional Neural Network Model Based on Adaptive Fick’s Law for Hyperspectral Image Classification

    Tsu-Yang Wu1,2, Haonan Li2, Saru Kumari3, Chien-Ming Chen1,*

    CMC-Computers, Materials & Continua, Vol., , DOI:10.32604/cmc.2024.048347

    Abstract Hyperspectral image classification stands as a pivotal task within the field of remote sensing, yet achieving high-precision classification remains a significant challenge. In response to this challenge, a Spectral Convolutional Neural Network model based on Adaptive Fick’s Law Algorithm (AFLA-SCNN) is proposed. The Adaptive Fick’s Law Algorithm (AFLA) constitutes a novel metaheuristic algorithm introduced herein, encompassing three new strategies: Adaptive weight factor, Gaussian mutation, and probability update policy. With adaptive weight factor, the algorithm can adjust the weights according to the change in the number of iterations to improve the performance of the algorithm. Gaussian mutation helps the algorithm avoid… More >

  • Open Access

    ARTICLE

    HCSP-Net: A Novel Model of Age-Related Macular Degeneration Classification Based on Color Fundus Photography

    Cheng Wan1, Jiani Zhao1, Xiangqian Hong2, Weihua Yang2,*, Shaochong Zhang2,*

    CMC-Computers, Materials & Continua, Vol., , DOI:10.32604/cmc.2024.048307

    Abstract Age-related macular degeneration (AMD) ranks third among the most common causes of blindness. As the most conventional and direct method for identifying AMD, color fundus photography has become prominent owing to its consistency, ease of use, and good quality in extensive clinical practice. In this study, a convolutional neural network (CSPDarknet53) was combined with a transformer to construct a new hybrid model, HCSP-Net. This hybrid model was employed to tri-classify color fundus photography into the normal macula (NM), dry macular degeneration (DMD), and wet macular degeneration (WMD) based on clinical classification manifestations, thus identifying and resolving AMD as early as… More >

  • Open Access

    ARTICLE

    Securing Cloud-Encrypted Data: Detecting Ransomware-as-a-Service (RaaS) Attacks through Deep Learning Ensemble

    Amardeep Singh1, Hamad Ali Abosaq2, Saad Arif3, Zohaib Mushtaq4,*, Muhammad Irfan5, Ghulam Abbas6, Arshad Ali7, Alanoud Al Mazroa8

    CMC-Computers, Materials & Continua, Vol., , DOI:10.32604/cmc.2024.048036

    Abstract Data security assurance is crucial due to the increasing prevalence of cloud computing and its widespread use across different industries, especially in light of the growing number of cybersecurity threats. A major and ever-present threat is Ransomware-as-a-Service (RaaS) assaults, which enable even individuals with minimal technical knowledge to conduct ransomware operations. This study provides a new approach for RaaS attack detection which uses an ensemble of deep learning models. For this purpose, the network intrusion detection dataset “UNSW-NB15” from the Intelligent Security Group of the University of New South Wales, Australia is analyzed. In the initial phase, the rectified linear… More >

  • Open Access

    ARTICLE

    MSC-YOLO: Improved YOLOv7 Based on Multi-Scale Spatial Context for Small Object Detection in UAV-View

    Xiangyan Tang1,2, Chengchun Ruan1,2,*, Xiulai Li2,3, Binbin Li1,2, Cebin Fu1,2

    CMC-Computers, Materials & Continua, Vol., , DOI:10.32604/cmc.2024.047541

    Abstract Accurately identifying small objects in high-resolution aerial images presents a complex and crucial task in the field of small object detection on unmanned aerial vehicles (UAVs). This task is challenging due to variations in UAV flight altitude, differences in object scales, as well as factors like flight speed and motion blur. To enhance the detection efficacy of small targets in drone aerial imagery, we propose an enhanced You Only Look Once version 7 (YOLOv7) algorithm based on multi-scale spatial context. We build the MSC-YOLO model, which incorporates an additional prediction head, denoted as P2, to improve adaptability for small objects.… More >

  • Open Access

    REVIEW

    Targeting brain tumors with innovative nanocarriers: bridging the gap through the blood-brain barrier

    KARAN WADHWA1, PAYAL CHAUHAN1, SHOBHIT KUMAR2, RAKESH PAHWA3,*, RAVINDER VERMA4, RAJAT GOYAL5, GOVIND SINGH1, ARCHANA SHARMA6, NEHA RAO3, DEEPAK KAUSHIK1,*

    Oncology Research, Vol., , DOI:10.32604/or.2024.047278

    Abstract Background:: Glioblastoma multiforme (GBM) is recognized as the most lethal and most highly invasive tumor. The high likelihood of treatment failure arises from the presence of the blood-brain barrier (BBB) and stem cells around GBM, which avert the entry of chemotherapeutic drugs into the tumor mass. Objective:: Recently, several researchers have designed novel nanocarrier systems like liposomes, dendrimers, metallic nanoparticles, nanodiamonds, and nanorobot approaches, allowing drugs to infiltrate the BBB more efficiently, opening up innovative avenues to prevail over therapy problems and radiation therapy. Methods:: Relevant literature for this manuscript has been collected from a comprehensive and systematic search of… More > Graphic Abstract

    Targeting brain tumors with innovative nanocarriers: bridging the gap through the blood-brain barrier

  • Open Access

    ARTICLE

    Fibroblast activation protein (FAP) as a prognostic biomarker in multiple tumors and its therapeutic potential in head and neck squamous cell carcinoma

    RUIFANG LI1, XINRONG NAN2,*, MING LI3,*, OMAR RAHHAL3

    Oncology Research, Vol., , DOI:10.32604/or.2024.046965

    Abstract Background: Fibroblast activation protein (FAP), a cell surface serine protease, plays roles in tumor invasion and immune regulation. However, there is currently no pan-cancer analysis of FAP. Objective: We aimed to assess the pan-cancer expression profile of FAP, its molecular function, and its potential role in head and neck squamous cell carcinoma (HNSC). Methods: We analyzed gene expression, survival status, immune infiltration, and molecular functional pathways of FAP in The Cancer Genome Atlas (TCGA) and Genotype Tissue Expression (GTEx) tumors. Furthermore, to elucidate the role of FAP in HNSC, we performed proliferation, migration, and invasion assays post-FAP overexpression or knock-down.… More >

  • Open Access

    ARTICLE

    LncRNA HOTAIR promotes DNA damage repair and radioresistance by targeting ATR in colorectal cancer

    HAIQING HU1,#,*, HAO YANG2,#, SHUAISHUAI FAN3, XUE JIA3, YING ZHAO3, HONGRUI LI3

    Oncology Research, Vol., , DOI:10.32604/or.2024.044174

    Abstract Long non-coding RNAs (lncRNAs) have been implicated in cancer progression and drug resistance development. Moreover, there is evidence that lncRNA HOX transcript antisense intergenic RNA (HOTAIR) is involved in colorectal cancer (CRC) progression. The present study aimed to examine the functional role of lncRNA HOTAIR in conferring radiotherapy resistance in CRC cells, as well as the underlying mechanism. The relative expression levels of HOTAIR were examined in 70 pairs of CRC tumor and para-cancerous tissues, as well as in radiosensitive and radioresistant samples. The correlations between HOTAIR expression levels and clinical features of patients with CRC were assessed using the… More >

  • Open Access

    REVIEW

    Wood By-Products as UV Protection: A Consequence Review

    Naglaa Salem El‑Sayed, Mohamed Hasanin, Samir Kamel*

    Journal of Renewable Materials, Vol., , DOI:10.32604/jrm.2024.049118

    Abstract

    In recent decades, the ozone layer has suffered considerable damage, increasing the entry of ultraviolet (UV) light into the atmosphere and reaching the earth’s surface, negatively affecting life. Accordingly, researchers aimed to solve this problem by synthesizing advanced UV-shielding materials. On the other hand, developing an easy and green strategy to prepare functional materials without standing properties based on naturally abundant and environmentally friendly raw materials is highly desirable for sustainable development. Because biomass-derived materials are sustainable and biodegradable, they present a promising substitute for petroleum-based polymers. The three main structural constituents of the plant biomass-based materials that are naturally… More > Graphic Abstract

    Wood By-Products as UV Protection: A Consequence Review

  • Open Access

    ARTICLE

    Transformation of MRI Images to Three-Level Color Spaces for Brain Tumor Classification Using Deep-Net

    Fadl Dahan*

    Intelligent Automation & Soft Computing, Vol., , DOI:10.32604/iasc.2024.047921

    Abstract In the domain of medical imaging, the accurate detection and classification of brain tumors is very important. This study introduces an advanced method for identifying camouflaged brain tumors within images. Our proposed model consists of three steps: Feature extraction, feature fusion, and then classification. The core of this model revolves around a feature extraction framework that combines color-transformed images with deep learning techniques, using the ResNet50 Convolutional Neural Network (CNN) architecture. So the focus is to extract robust feature from MRI images, particularly emphasizing weighted average features extracted from the first convolutional layer renowned for their discriminative power. To enhance… More >

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