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  • Open Access


    Influence of Confined Concrete Models on the Seismic Response of RC Frames

    Hüseyin Bilgin*, Bredli Plaku

    Structural Durability & Health Monitoring, Vol.18, No.3, pp. 197-222, 2024, DOI:10.32604/sdhm.2024.048645

    Abstract In this study, the influence of confined concrete models on the response of reinforced concrete structures is investigated at member and global system levels. The commonly encountered concrete models such as Modified Kent-Park, Saatçioğlu-Razvi, and Mander are considered. Two moment-resisting frames designed according to the pre-modern code are taken into consideration to reflect the example of an RC moment-resisting frame in the current building stock. The building is in an earthquake-prone zone located on Z3 Soil Type. The inelastic response of the building frame is modelled by considering the plastic hinges formed on each beam… More >

  • Open Access


    Investigating the Retrofit of RC Frames Using TADAS Yielding Dampers

    Mehrzad TahamouliRoudsari1,*, K. Cheraghi2, R. Aghayari2

    Structural Durability & Health Monitoring, Vol.16, No.4, pp. 343-359, 2022, DOI:10.32604/sdhm.2022.07927

    Abstract TADAS dampers are a type of passive structural control system used in the seismic design or retrofitting of structures. These types of dampers are designed so that they would yield before the main components of the structure during earthquake. This dissipates a large portion of the earthquake’s energy and reduces the energy dissipation demand in the main components of the structure. Considering its suitable performance, this damper has been the subject of numerous studies. However, there are still ambiguities regarding the effect of the number of these dampers on the retrofitting of reinforced concrete (RC)… More >

  • Open Access


    Improved Video Steganography with Dual Cover Medium, DNA and Complex Frames

    Asma Sajjad1, Humaira Ashraf1, NZ Jhanjhi2,3,*, Mamoona Humayun4, Mehedi Masud5, Mohammed A. AlZain6

    CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 3881-3898, 2023, DOI:10.32604/cmc.2023.030197

    Abstract The most valuable resource on the planet is no longer oil, but data. The transmission of this data securely over the internet is another challenge that comes with its ever-increasing value. In order to transmit sensitive information securely, researchers are combining robust cryptography and steganographic approaches. The objective of this research is to introduce a more secure method of video steganography by using Deoxyribonucleic acid (DNA) for embedding encrypted data and an intelligent frame selection algorithm to improve video imperceptibility. In the previous approach, DNA was used only for frame selection. If this DNA is… More >

  • Open Access


    High-Movement Human Segmentation in Video Using Adaptive N-Frames Ensemble

    Yong-Woon Kim1, Yung-Cheol Byun2,*, Dong Seog Han3, Dalia Dominic1, Sibu Cyriac1

    CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 4743-4762, 2022, DOI:10.32604/cmc.2022.028632

    Abstract A wide range of camera apps and online video conferencing services support the feature of changing the background in real-time for aesthetic, privacy, and security reasons. Numerous studies show that the Deep-Learning (DL) is a suitable option for human segmentation, and the ensemble of multiple DL-based segmentation models can improve the segmentation result. However, these approaches are not as effective when directly applied to the image segmentation in a video. This paper proposes an Adaptive N-Frames Ensemble (AFE) approach for high-movement human segmentation in a video using an ensemble of multiple DL models. In contrast… More >

  • Open Access


    Transforming Hand Drawn Wireframes into Front-End Code with Deep Learning

    Saman Riaz1, Ali Arshad2, Shahab S. Band3,*, Amir Mosavi4

    CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 4303-4321, 2022, DOI:10.32604/cmc.2022.024819

    Abstract The way towards generating a website front end involves a designer settling on an idea for what kind of layout they want the website to have, then proceeding to plan and implement each aspect one by one until they have converted what they initially laid out into its Html front end form, this process can take a considerable time, especially considering the first draft of the design is traditionally never the final one. This process can take up a large amount of resource real estate, and as we have laid out in this paper, by… More >

  • Open Access


    ResNet CNN with LSTM Based Tamil Text Detection from Video Frames

    I. Muthumani1,*, N. Malmurugan2, L. Ganesan3

    Intelligent Automation & Soft Computing, Vol.31, No.2, pp. 917-928, 2022, DOI:10.32604/iasc.2022.018030

    Abstract Text content in videos includes applications such as library video retrievals, live-streaming advertisements, opinion mining, and video synthesis. The key components of such systems include video text detection and acknowledgments. This paper provides a framework to detect and accept text video frames, aiming specifically at the cursive script of Tamil text. The model consists of a text detector, script identifier, and text recognizer. The identification in video frames of textual regions is performed using deep neural networks as object detectors. Textual script content is associated with convolutional neural networks (CNNs) and recognized by combining ResNet More >

  • Open Access


    Real-Time Violent Action Recognition Using Key Frames Extraction and Deep Learning

    Muzamil Ahmed1,2, Muhammad Ramzan3,4, Hikmat Ullah Khan2, Saqib Iqbal5, Muhammad Attique Khan6, Jung-In Choi7, Yunyoung Nam8,*, Seifedine Kadry9

    CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 2217-2230, 2021, DOI:10.32604/cmc.2021.018103

    Abstract Violence recognition is crucial because of its applications in activities related to security and law enforcement. Existing semi-automated systems have issues such as tedious manual surveillances, which causes human errors and makes these systems less effective. Several approaches have been proposed using trajectory-based, non-object-centric, and deep-learning-based methods. Previous studies have shown that deep learning techniques attain higher accuracy and lower error rates than those of other methods. However, the their performance must be improved. This study explores the state-of-the-art deep learning architecture of convolutional neural networks (CNNs) and inception V4 to detect and recognize violence… More >

  • Open Access


    PRNU Extraction from Stabilized Video: A Patch Maybe Better than a Bunch

    Bin Ma1, Yuanyuan Hu1, Jian Li1,*, Chunpeng Wang1, Meihong Yang2, Yang Zheng3

    Computer Systems Science and Engineering, Vol.36, No.1, pp. 189-200, 2021, DOI:10.32604/csse.2021.014138

    Abstract This paper presents an algorithm to solve the problem of Photo-Response Non-Uniformity (PRNU) noise facing stabilized video. The stabilized video undergoes in-camera processing like rolling shutter correction. Thus, misalignment exists between the PRNU noises in the adjacent frames owing to the global and local frame registration performed by the in-camera processing. The misalignment makes the reference PRNU noise and the test PRNU noise unable to extract and match accurately. We design a computing method of maximum likelihood estimation algorithm for extracting the PRNU noise from stabilized video frames. Besides, unlike most prior arts tending to… More >

  • Open Access


    Machine Learning-Based Seismic Fragility Analysis of Large-Scale Steel Buckling Restrained Brace Frames

    Baoyin Sun1, 2, Yantai Zhang3, Caigui Huang4, *

    CMES-Computer Modeling in Engineering & Sciences, Vol.125, No.2, pp. 755-776, 2020, DOI:10.32604/cmes.2020.09632

    Abstract Steel frames equipped with buckling restrained braces (BRBs) have been increasingly applied in earthquake-prone areas given their excellent capacity for resisting lateral forces. Therefore, special attention has been paid to the seismic risk assessment (SRA) of such structures, e.g., seismic fragility analysis. Conventional approaches, e.g., nonlinear finite element simulation (NFES), are computationally inefficient for SRA analysis particularly for large-scale steel BRB frame structures. In this study, a machine learning (ML)- based seismic fragility analysis framework is established to effectively assess the risk to structures under seismic loading conditions. An optimal artificial neural network model can More >

  • Open Access


    A Novel Forgery Detection in Image Frames of the Videos Using Enhanced Convolutional Neural Network in Face Images

    S. Velliangiri1,*, J. Premalatha2

    CMES-Computer Modeling in Engineering & Sciences, Vol.125, No.2, pp. 625-645, 2020, DOI:10.32604/cmes.2020.010869

    Abstract Different devices in the recent era generated a vast amount of digital video. Generally, it has been seen in recent years that people are forging the video to use it as proof of evidence in the court of justice. Many kinds of researches on forensic detection have been presented, and it provides less accuracy. This paper proposed a novel forgery detection technique in image frames of the videos using enhanced Convolutional Neural Network (CNN). In the initial stage, the input video is taken as of the dataset and then converts the videos into image frames. More >

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