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  • Open Access

    ARTICLE

    Deep Learning and Tensor-Based Multiple Clustering Approaches for Cyber-Physical-Social Applications

    Hongjun Zhang1,2, Hao Zhang2, Yu Lei3, Hao Ye1, Peng Li1,*, Desheng Shi1

    CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 4109-4128, 2024, DOI:10.32604/cmc.2024.048355

    Abstract The study delves into the expanding role of network platforms in our daily lives, encompassing various mediums like blogs, forums, online chats, and prominent social media platforms such as Facebook, Twitter, and Instagram. While these platforms offer avenues for self-expression and community support, they concurrently harbor negative impacts, fostering antisocial behaviors like phishing, impersonation, hate speech, cyberbullying, cyberstalking, cyberterrorism, fake news propagation, spamming, and fraud. Notably, individuals also leverage these platforms to connect with authorities and seek aid during disasters. The overarching objective of this research is to address the dual nature of network platforms by proposing innovative methodologies aimed… More >

  • Open Access

    REVIEW

    A Systematic Literature Review of Machine Learning and Deep Learning Approaches for Spectral Image Classification in Agricultural Applications Using Aerial Photography

    Usman Khan1, Muhammad Khalid Khan1, Muhammad Ayub Latif1, Muhammad Naveed1,2,*, Muhammad Mansoor Alam2,3,4, Salman A. Khan1, Mazliham Mohd Su’ud2,*

    CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 2967-3000, 2024, DOI:10.32604/cmc.2024.045101

    Abstract Recently, there has been a notable surge of interest in scientific research regarding spectral images. The potential of these images to revolutionize the digital photography industry, like aerial photography through Unmanned Aerial Vehicles (UAVs), has captured considerable attention. One encouraging aspect is their combination with machine learning and deep learning algorithms, which have demonstrated remarkable outcomes in image classification. As a result of this powerful amalgamation, the adoption of spectral images has experienced exponential growth across various domains, with agriculture being one of the prominent beneficiaries. This paper presents an extensive survey encompassing multispectral and hyperspectral images, focusing on their… More >

  • Open Access

    ARTICLE

    Design of a Multi-Stage Ensemble Model for Thyroid Prediction Using Learning Approaches

    M. L. Maruthi Prasad*, R. Santhosh

    Intelligent Automation & Soft Computing, Vol.39, No.1, pp. 1-13, 2024, DOI:10.32604/iasc.2023.036628

    Abstract This research concentrates to model an efficient thyroid prediction approach, which is considered a baseline for significant problems faced by the women community. The major research problem is the lack of automated model to attain earlier prediction. Some existing model fails to give better prediction accuracy. Here, a novel clinical decision support system is framed to make the proper decision during a time of complexity. Multiple stages are followed in the proposed framework, which plays a substantial role in thyroid prediction. These steps include i) data acquisition, ii) outlier prediction, and iii) multi-stage weight-based ensemble learning process (MS-WEL). The weighted… More >

  • Open Access

    ARTICLE

    Developing risk models and subtypes of autophagy-associated LncRNAs for enhanced prognostic prediction and precision in therapeutic approaches for liver cancer patients

    LU ZHANG*, JINGUO CHU*, YUSHAN YU

    Oncology Research, Vol.32, No.4, pp. 703-716, 2024, DOI:10.32604/or.2023.030988

    Abstract Background: Limited research has been conducted on the influence of autophagy-associated long non-coding RNAs (ARLncRNAs) on the prognosis of hepatocellular carcinoma (HCC). Methods: We analyzed 371 HCC samples from TCGA, identifying expression networks of ARLncRNAs using autophagy-related genes. Screening for prognostically relevant ARLncRNAs involved univariate Cox regression, Lasso regression, and multivariate Cox regression. A Nomogram was further employed to assess the reliability of Riskscore, calculated from the signatures of screened ARLncRNAs, in predicting outcomes. Additionally, we compared drug sensitivities in patient groups with differing risk levels and investigated potential biological pathways through enrichment analysis, using consensus clustering to identify subgroups… More >

  • Open Access

    ARTICLE

    Nonlinear Study on the Mechanical Performance of Built-Up Cold-Formed Steel Concrete-Filled Columns under Compression

    Oulfa Harrat1,*, Yazid Hadidane1, S. M. Anas2,*, Nadhim Hamah Sor3,4, Ahmed Farouk Deifalla5, Paul O. Awoyera6, Nadia Gouider1

    CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.3, pp. 3435-3465, 2024, DOI:10.32604/cmes.2023.044950

    Abstract Given their numerous functional and architectural benefits, such as improved bearing capacity and increased resistance to elastic instability modes, cold-formed steel (CFS) built-up sections have become increasingly developed and used in recent years, particularly in the construction industry. This paper presents an analytical and numerical study of assembled CFS two single channel-shaped columns with different slenderness and configurations (back-to-back, face-to-face, and box). These columns were joined by double-row rivets for the back-to-back and box configurations, whereas they were welded together for the face-to-face design. The built-up columns were filled with ordinary concrete of good strength. Finite element models were applied,… More > Graphic Abstract

    Nonlinear Study on the Mechanical Performance of Built-Up Cold-Formed Steel Concrete-Filled Columns under Compression

  • Open Access

    REVIEW

    A Comprehensive Survey for Privacy-Preserving Biometrics: Recent Approaches, Challenges, and Future Directions

    Shahriar Md Arman1, Tao Yang1,*, Shahadat Shahed2, Alanoud Al Mazroa3, Afraa Attiah4, Linda Mohaisen4

    CMC-Computers, Materials & Continua, Vol.78, No.2, pp. 2087-2110, 2024, DOI:10.32604/cmc.2024.047870

    Abstract The rapid growth of smart technologies and services has intensified the challenges surrounding identity authentication techniques. Biometric credentials are increasingly being used for verification due to their advantages over traditional methods, making it crucial to safeguard the privacy of people’s biometric data in various scenarios. This paper offers an in-depth exploration for privacy-preserving techniques and potential threats to biometric systems. It proposes a noble and thorough taxonomy survey for privacy-preserving techniques, as well as a systematic framework for categorizing the field’s existing literature. We review the state-of-the-art methods and address their advantages and limitations in the context of various biometric… More >

  • Open Access

    REVIEW

    Advanced Thermochemical Conversion Approaches for Green Hydrogen Production from Crop Residues

    Omojola Awogbemi*, Ayotunde Adigun Ojo, Samson Adedayo Adeleye

    Journal of Renewable Materials, Vol.12, No.1, pp. 1-28, 2024, DOI:10.32604/jrm.2023.045822

    Abstract The huge volumes of crop residues generated during the production, processing, and consumption of farm products constitute an ecological nuisance when ineffectively managed. The conversion of crop residues to green hydrogen is one of the sustainable management strategies for ubiquitous crop residues. Production of green hydrogen from crop residue sources will contribute to deepening access to clean and affordable energy, mitigating climate change, and ensuring environmental sustainability. However, the deployment of conventional thermochemical technologies for the conversion of crop residues to green hydrogen is costly, requires long residence time, produces low-quality products, and therefore needs to be upgraded. The current… More >

  • Open Access

    ARTICLE

    Identification and validation of novel prognostic fatty acid metabolic gene signatures in colon adenocarcinoma through systematic approaches

    HENG ZHANG1,#, WENJING CHENG2,#, HAIBO ZHAO2, WEIDONG CHEN2, QIUJIE ZHANG2,*, QING-QING YU2,*

    Oncology Research, Vol.32, No.2, pp. 297-308, 2024, DOI:10.32604/or.2023.043138

    Abstract Background: Colorectal cancer (CRC) belongs to the class of significantly malignant tumors found in humans. Recently, dysregulated fatty acid metabolism (FAM) has been a topic of attention due to its modulation in cancer, specifically CRC. However, the regulatory FAM pathways in CRC require comprehensive elucidation. Methods: The clinical and gene expression data of 175 fatty acid metabolic genes (FAMGs) linked with colon adenocarcinoma (COAD) and normal cornerstone genes were gathered through The Cancer Genome Atlas (TCGA)-COAD corroborating with the Molecular Signature Database v7.2 (MSigDB). Initially, crucial prognostic genes were selected by uni- and multi-variate Cox proportional regression analyses; then, depending… More >

  • Open Access

    ARTICLE

    An Improved Lung Cancer Segmentation Based on Nature-Inspired Optimization Approaches

    Shazia Shamas1, Surya Narayan Panda1,*, Ishu Sharma1,*, Kalpna Guleria1, Aman Singh2,3,4, Ahmad Ali AlZubi5, Mallak Ahmad AlZubi6

    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.2, pp. 1051-1075, 2024, DOI:10.32604/cmes.2023.030712

    Abstract The distinction and precise identification of tumor nodules are crucial for timely lung cancer diagnosis and planning intervention. This research work addresses the major issues pertaining to the field of medical image processing while focusing on lung cancer Computed Tomography (CT) images. In this context, the paper proposes an improved lung cancer segmentation technique based on the strengths of nature-inspired approaches. The better resolution of CT is exploited to distinguish healthy subjects from those who have lung cancer. In this process, the visual challenges of the K-means are addressed with the integration of four nature-inspired swarm intelligent techniques. The techniques… More >

  • Open Access

    REVIEW

    Cellular and molecular insights into microbiota-mitochondria interplay, therapeutic biomarkers and interventional approaches in COVID-19: A review

    VIBHAV VARSHNEY1,*, PRASHANT SINGH KUSHWAH2, NEETU AGRAWAL1, AHSAS GOYAL1,*, GOVIND SINGH2

    BIOCELL, Vol.47, No.10, pp. 2141-2149, 2023, DOI:10.32604/biocell.2023.030853

    Abstract The persistent global pandemic, COVID-19, stems from the pathogenic influence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), yielding an unprecedented worldwide crisis. With reference to a WHO report, the count of COVID-19 cases had exceeded 754 million by February 03, 2023. Intriguingly, emerging research has spotlighted the intricate interplay of gut microbiota and mitochondrial entities, acting as potent immunomodulatory factors at the cellular and molecular levels. This interconnection operates through a series of dynamic mechanisms. SARS-CoV-2 infection perturbs the delicate equilibrium of gut microbiota, leading to dysbiosis—a signature biomarker. This imbalance is intrinsically linked to exacerbated COVID-19 progression. Mechanistically,… More >

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