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  • Open Access


    High Linear Voltage Gain in QZNC Through Synchronizing Switching Circuits

    S. Harika1,*, R. Seyezhai1, A. Jawahar2

    Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 895-910, 2023, DOI:10.32604/iasc.2023.031829

    Abstract The solar powered systems require high step-up converter for efficient energy transfer. For this, quasi-impedance network converter has been introduced. The quasi-impedance network converter (QZNC) is of two types: type-1 and type-2 configuration. Both the type-1 and type-2 QZNC configurations have drooping voltage gain profile due to presence of high switching noise. To overcome this, a new quasi-impedance network converter synchronizing the switching circuit with low frequency noise has been proposed. In this paper, the proposed QZNC configuration utilizes the current controlling diode to prevent the output voltage drop. Thus, the suggested topology provides linear high voltage gain profile, low… More >

  • Open Access


    Cost and Efficiency Analysis of Steganography in the IEEE 802.11ah IoT Protocol

    Akram A. Almohammedi1,2,*, Vladimir Shepelev1, Sam Darshi3, Mohammed Balfaqih4, Fayad Ghawbar5

    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 3929-3943, 2022, DOI:10.32604/cmc.2022.026307

    Abstract The widespread use of the Internet of Things (IoT) applications has enormously increased the danger level of data leakage and theft in IoT as data transmission occurs through a public channel. As a result, the security of the IoT has become a serious challenge in the field of information security. Steganography on the network is a critical tool for preventing the leakage of private information and enabling secure and encrypted communication. The primary purpose of steganography is to conceal sensitive information in any form of media such as audio, video, text, or photos, and securely transfer it through wireless networks.… More >

  • Open Access


    YOLOv3 Attention Face Detector with High Accuracy and Efficiency

    Qiyuan Liu, Shuhua Lu*, Lingqiang Lan

    Computer Systems Science and Engineering, Vol.37, No.2, pp. 283-295, 2021, DOI:10.32604/csse.2021.014086

    Abstract In recent years, face detection has attracted much attention and achieved great progress due to its extensively practical applications in the field of face based computer vision. However, the tradeoff between accuracy and efficiency of the face detectors still needs to be further studied. In this paper, using Darknet-53 as backbone, we propose an improved YOLOv3-attention model by introducing attention mechanism and data augmentation to obtain the robust face detector with high accuracy and efficiency. The attention mechanism is introduced to enhance much higher discrimination of the deep features, and the trick of data augmentation is used in the training… More >

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