Home / Advanced Search

  • Title/Keywords

  • Author/Affliations

  • Journal

  • Article Type

  • Start Year

  • End Year

Update SearchingClear
  • Articles
  • Online
Search Results (73)
  • Open Access

    ARTICLE

    Secure and Invisible Dual Watermarking for Digital Content Based on Optimized Octonion Moments and Chaotic Metaheuristics

    Ahmed El Maloufy, Mohamed Amine Tahiri, Ahmed Bencherqui, Hicham Karmouni, Mhamed Sayyouri*

    CMC-Computers, Materials & Continua, Vol.85, No.3, pp. 5789-5822, 2025, DOI:10.32604/cmc.2025.068885 - 23 October 2025

    Abstract In the current digital context, safeguarding copyright is a major issue, particularly for architectural drawings produced by students. These works are frequently the result of innovative academic thinking combining creativity and technical precision. They are particularly vulnerable to the risk of illegal reproduction when disseminated in digital format. This research suggests, for the first time, an innovative approach to copyright protection by embedding a double digital watermark to address this challenge. The solution relies on a synergistic fusion of several sophisticated methods: Krawtchouk Optimized Octonion Moments (OKOM), Quaternion Singular Value Decomposition (QSVD), and Discrete Waveform… More >

  • Open Access

    ARTICLE

    Deep Learning Models for Detecting Cheating in Online Exams

    Siham Essahraui1, Ismail Lamaakal1, Yassine Maleh2,*, Khalid El Makkaoui1, Mouncef Filali Bouami1, Ibrahim Ouahbi1, May Almousa3, Ali Abdullah S. AlQahtani4, Ahmed A. Abd El-Latif5,6

    CMC-Computers, Materials & Continua, Vol.85, No.2, pp. 3151-3183, 2025, DOI:10.32604/cmc.2025.067359 - 23 September 2025

    Abstract The rapid shift to online education has introduced significant challenges to maintaining academic integrity in remote assessments, as traditional proctoring methods fall short in preventing cheating. The increase in cheating during online exams highlights the need for efficient, adaptable detection models to uphold academic credibility. This paper presents a comprehensive analysis of various deep learning models for cheating detection in online proctoring systems, evaluating their accuracy, efficiency, and adaptability. We benchmark several advanced architectures, including EfficientNet, MobileNetV2, ResNet variants and more, using two specialized datasets (OEP and OP) tailored for online proctoring contexts. Our findings More >

  • Open Access

    ARTICLE

    Computational Modeling to Predict Conservative Treatment Outcome for Patients with Plaque Erosion: An OCT-Based Patient-Specific FSI Modeling Study

    Yanwen Zhu1,#, Chen Zhao2,#, Yishuo Xu2, Zheyang Wu3, Akiko Maehara4, Liang Wang1, Dirui Zhang2, Ming Zeng2, Rui Lv5, Xiaoya Guo6, Mengde Huang1, Minglong Chen7, Gary S. Mintz4, Dalin Tang1,3,*, Haibo Jia2, Bo Yu2,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.144, No.2, pp. 1249-1270, 2025, DOI:10.32604/cmes.2025.067039 - 31 August 2025

    Abstract Image-based computational models have been used for vulnerable plaque progression and rupture predictions, and good results have been reported. However, mechanisms and predictions for plaque erosion are under-investigated. Patient-specific fluid-structure interaction (FSI) models based on optical coherence tomography (OCT) follow-up data from patients with plaque erosion and who received conservative antithrombotic treatment (using medication, no stenting) to identify risk factors that could be used to predict the treatment outcome. OCT and angiography data were obtained from 10 patients who received conservative antithrombotic treatment. Five participants had worse outcomes (WOG, stenosis severity ≥ 70% at one-year… More > Graphic Abstract

    Computational Modeling to Predict Conservative Treatment Outcome for Patients with Plaque Erosion: An OCT-Based Patient-Specific FSI Modeling Study

  • Open Access

    ARTICLE

    Survival outcomes with pelvic node dissection after partial cystectomy among octogenarians with muscle-invasive bladder cancer

    Arjun Pon Avudaiappan*, Pushan Prabhakar, Hannah Baker, Mukesh K. Roy, Manuel Ozambela Jr, Christopher Gomez, Murugesan Manoharan

    Canadian Journal of Urology, Vol.32, No.3, pp. 137-143, 2025, DOI:10.32604/cju.2025.064725 - 27 June 2025

    Abstract Introduction: Radical cystectomy with pelvic node dissection remains the standard of care for muscle-invasive bladder carcinoma (MIBC); however, there is a growing interest in bladder preservation alternatives among the elderly population. Guidelines indicate that partial cystectomy (PC) combined with pelvic node dissection (LND) can be considered as an alternative in carefully selected individuals. Using the National Cancer Database, we analyzed the overall survival (OS) between PC with and without LND among octogenarians. Methods: We identified octogenarians with localized muscle-invasive bladder carcinoma (cT2-3N0M0) and urothelial histology who underwent PC with or without LND between 2004 and… More >

  • Open Access

    ARTICLE

    Context Encoding Deep Neural Network Driven Spectral Domain 3D-Optical Coherence Tomography Imaging in Purtscher Retinopathy Diagnosis

    Anand Deva Durai Chelladurai1, Theena Jemima Jebaseeli2, Omar Alqahtani1, Prasanalakshmi Balaji1,*, Jeniffer John Simon Christopher3

    CMC-Computers, Materials & Continua, Vol.84, No.1, pp. 1101-1122, 2025, DOI:10.32604/cmc.2025.062278 - 09 June 2025

    Abstract Optical Coherence Tomography (OCT) provides cross-sectional and three-dimensional reconstructions of the target tissue, allowing precise imaging and quantitative analysis of individual retinal layers. These images, based on optical inhomogeneities, reveal intricate cellular structures and are vital for tasks like retinal segmentation. The proposed study uses OCT images to identify significant differences in peripapillary retinal nerve fiber layer thickness. Incorporating spectral-domain analysis of OCT images significantly enhances the evaluation of Purtcher Retinopathy. To streamline this process, the study introduces a Context Encoding Deep Neural Network (CEDNN), which eliminates the time-consuming manual segmentation process while improving the… More >

  • Open Access

    ARTICLE

    Numerical Investigation to Enhance the Solar Collector Performance Using Nano-Encapsulated Octadecane Organic Paraffin PCM

    Malik A. Faisal*, Alireza Saraei

    Energy Engineering, Vol.122, No.5, pp. 2099-2117, 2025, DOI:10.32604/ee.2025.061569 - 25 April 2025

    Abstract Performance enhancement of flat plate solar collectors is an endless research direction as it represents the most used solar technology. The enhancement could be achieved via design alteration, absorber-installed protrusions, and integration with thermal energy storage. The objective of the current research is to evaluate a compacted solar collector integrated with octadecane organic paraffin PCM (phase change materials) as a thermal energy storage medium. The investigations have been performed numerically utilizing ANSYS software. Thermal storage contains the PCM securely encased behind the absorbent plate of the collector in four packing containers. The investigations have been… More >

  • Open Access

    ARTICLE

    Multiple Sclerosis Predictions and Sensitivity Analysis Using Robust Models

    Alex Kibet*, Gilbert Langat

    Journal of Intelligent Medicine and Healthcare, Vol.3, pp. 1-14, 2025, DOI:10.32604/jimh.2022.062824 - 04 April 2025

    Abstract Multiple Sclerosis (MS) is a disease that disrupts the flow of information within the brain. It affects approximately 1 million people in the US. And remains incurable. MS treatments can cause side effects and impact the quality of life and even survival rates. Based on existing research studies, we investigate the risks and benefits of three treatment options based on methylprednisolone (a corticosteroid hormone medication) prescribed in (1) high-dose, (2) low-dose, or (3) no treatment. The study currently prescribes one treatment to all patients as it has been proven to be the most effective on More >

  • Open Access

    ARTICLE

    Hybrid MNLTP Texture Descriptor and PDCNN-Based OCT Image Classification for Retinal Disease Detection

    Jahida Subhedar1,2, Anurag Mahajan1,*, Shabana Urooj3, Neeraj Kumar Shukla4,5

    CMC-Computers, Materials & Continua, Vol.82, No.2, pp. 2831-2847, 2025, DOI:10.32604/cmc.2025.059350 - 17 February 2025

    Abstract Retinal Optical Coherence Tomography (OCT) images, a non-invasive imaging technique, have become a standard retinal disease detection tool. Due to disease, there are morphological and textural changes in the layers of the retina. Classifying OCT images is challenging, as the morphological manifestations of different diseases may be similar. The OCT images capture the reflectivity characteristics of the retinal tissues. Retinal diseases change the reflectivity property of retinal tissues, resulting in texture variations in OCT images. We propose a hybrid approach to OCT image classification in which the Convolution Neural Network (CNN) model is trained using… More >

  • Open Access

    LETTER

    Re: Letter to the Editor - Proctor JG. Pentosan polysulfate and a pigmentary maculopathy: causation versus correlation?

    Jeffrey G. Proctor

    Canadian Journal of Urology, Vol.31, No.3, pp. 11869-11870, 2024

    Abstract This article has no abstract. More >

  • Open Access

    LETTER

    Re: Review - Proctor JG. Pentosan polysulfate and a pigmentary maculopathy: causation versus correlation?

    Jenelle Foote1, Sakshi Shiromani2, Nieraj Jain2

    Canadian Journal of Urology, Vol.31, No.3, pp. 11867-11868, 2024

    Abstract This article has no abstract. More >

Displaying 1-10 on page 1 of 73. Per Page