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Search Results (8)
  • Open Access


    Ghost Module Based Residual Mixture of Self-Attention and Convolution for Online Signature Verification

    Fangjun Luan1,2,3, Xuewen Mu1,2,3, Shuai Yuan1,2,3,*

    CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 695-712, 2024, DOI:10.32604/cmc.2024.048502

    Abstract Online Signature Verification (OSV), as a personal identification technology, is widely used in various industries. However, it faces challenges, such as incomplete feature extraction, low accuracy, and computational heaviness. To address these issues, we propose a novel approach for online signature verification, using a one-dimensional Ghost-ACmix Residual Network (1D-ACGRNet), which is a Ghost-ACmix Residual Network that combines convolution with a self-attention mechanism and performs improvement by using Ghost method. The Ghost-ACmix Residual structure is introduced to leverage both self-attention and convolution mechanisms for capturing global feature information and extracting local information, effectively complementing whole and… More >

  • Open Access


    A Fault Feature Extraction Model in Synchronous Generator under Stator Inter-Turn Short Circuit Based on ACMD and DEO3S

    Yuling He, Shuai Li, Chao Zhang*, Xiaolong Wang

    Structural Durability & Health Monitoring, Vol.17, No.2, pp. 115-130, 2023, DOI:10.32604/sdhm.2023.022317

    Abstract This paper proposed a new diagnosis model for the stator inter-turn short circuit fault in synchronous generators. Different from the past methods focused on the current or voltage signals to diagnose the electrical fault, the stator vibration signal analysis based on ACMD (adaptive chirp mode decomposition) and DEO3S (demodulation energy operator of symmetrical differencing) was adopted to extract the fault feature. Firstly, FT (Fourier transform) is applied to the vibration signal to obtain the instantaneous frequency, and PE (permutation entropy) is calculated to select the proper weighting coefficients. Then, the signal is decomposed by ACMD, More >

  • Open Access


    Secure Cancelable Template Based on Double Random Phase Encoding and Entropy Segmentation

    Ahmed M. Ayoup1,*, Ashraf A. M. Khalaf1, Fathi E. Abd El-Samie2, Fahad Alraddady3, Salwa M. Serag Eldin3

    CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 4067-4085, 2022, DOI:10.32604/cmc.2022.025767

    Abstract In this paper, a proposed cancellable biometric scheme is based on multiple biometric image identifiers, Arnold’s cat map and double random phase encoding (DRPE) to obtain cancellable biometric templates. The proposed segmentation scheme that is used to select the region of interest for generating cancelable templates is based on chaos entropy low correlation statistical metrics. The objective of segmentation is to reduce the computational cost and reliability of template creation. The left and right biometric (iris, fingerprint, palm print and face) are divided into non-overlapping blocks of the same dimensions. To define the region of… More >

  • Open Access


    Automatic Liver Tumor Segmentation in CT Modalities Using MAT-ACM

    S. Priyadarsini1,*, Carlos Andrés Tavera Romero2, Abolfazl Mehbodniya3, P. Vidya Sagar4, Sudhakar Sengan5

    Computer Systems Science and Engineering, Vol.43, No.3, pp. 1057-1068, 2022, DOI:10.32604/csse.2022.024788

    Abstract In the recent days, the segmentation of Liver Tumor (LT) has been demanding and challenging. The process of segmenting the liver and accurately spotting the tumor is demanding due to the diversity of shape, texture, and intensity of the liver image. The intensity similarities of the neighboring organs of the liver create difficulties during liver segmentation. The manual segmentation does not provide an accurate segmentation because the results provided by different medical experts can vary. Also, this manual technique requires a large number of image slices and time for segmentation. To solve these issues, the… More >

  • Open Access


    Cancellable Multi-Biometric Template Generation Based on Arnold Cat Map and Aliasing

    Ahmed M. Ayoup1,*, Ashraf A. M. Khalaf1, Walid El-Shafai2,3, Fathi E. Abd El-Samie2, Fahad Alraddady4, Salwa M. Serag Eldin4,5

    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 3687-3703, 2022, DOI:10.32604/cmc.2022.025902

    Abstract The cancellable biometric transformations are designed to be computationally difficult to obtain the original biometric data. This paper presents a cancellable multi-biometric identification scheme that includes four stages: biometric data collection and processing, Arnold's Cat Map encryption, decimation process to reduce the size, and final merging of the four biometrics in a single generated template. First, a 2D matrix of size 128 × 128 is created based on Arnold's Cat Map (ACM). The purpose of this rearrangement is to break the correlation between pixels to hide the biometric patterns and merge these patterns together for more security. More >

  • Open Access


    Identification of differential mRNA and lncRNA expression in AcMNPV-infected Sf9 cells


    BIOCELL, Vol.46, No.7, pp. 1675-1686, 2022, DOI:10.32604/biocell.2022.018166

    Abstract Sf9Sf9 are the ovarian cells of Spodoptera frugiperda that is the host of Autographa californica multiple nucleopolyhedrovirus (AcMNPV), and hence can serve as an effective test vehicle to understand the AcMNPV infection mechanism. In this study, through high-throughput sequencing technology using samples collected from Sf9 cells at different time points after AcMNPV infection, 3463 pieces of time-series differentially expressed RNA (1,200 mRNA and 2,263 lncRNA) are identified and justified by experimental verification of randomly selected samples from them, proving the validity of the bioinformatical analysis on this topic. Functional enrichment analysis and target prediction are performed on… More >

  • Open Access


    Cancelable Multi-biometric Template Generation Based on Dual-Tree Complex Wavelet Transform

    Ahmed M. Ayoup1,*, Ashraf A. M. Khalaf1, Fahad Alraddady2, Fathi E. Abd El-Samie3, Walid El-Shafai3,5, Salwa M. Serag Eldin2,4

    Intelligent Automation & Soft Computing, Vol.33, No.2, pp. 1289-1304, 2022, DOI:10.32604/iasc.2022.024381

    Abstract In this article, we introduce a new cancelable biometric template generation layout depending on selective encryption technology and Dual-Tree Complex Wavelet Transform (DT-CWT) fusion. The input face biometric is entered into the automatic face-segmentation (Viola-Jones) algorithm to detect the object in a short time. Viola-Jones algorithm can detect the left eye, right eye, nose, and mouth of the input biometric image. The encoder can choose the left or right eye to generate a cancelable biometric template. The selected eye image of size M × N is XORed with the created pseudo-random number (PRN) matrix CM × N to… More >

  • Open Access


    SwCS: Section-Wise Content Similarity Approach to Exploit Scientific Big Data

    Kashif Irshad1, Muhammad Tanvir Afzal2, Sanam Shahla Rizvi3, Abdul Shahid4, Rabia Riaz5, Tae-Sun Chung6,*

    CMC-Computers, Materials & Continua, Vol.67, No.1, pp. 877-894, 2021, DOI:10.32604/cmc.2021.014156

    Abstract The growing collection of scientific data in various web repositories is referred to as Scientific Big Data, as it fulfills the four “V’s” of Big Data–-volume, variety, velocity, and veracity. This phenomenon has created new opportunities for startups; for instance, the extraction of pertinent research papers from enormous knowledge repositories using certain innovative methods has become an important task for researchers and entrepreneurs. Traditionally, the content of the papers are compared to list the relevant papers from a repository. The conventional method results in a long list of papers that is often impossible to interpret… More >

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