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  • Open Access

    ARTICLE

    Hill Matrix and Radix-64 Bit Algorithm to Preserve Data Confidentiality

    Ali Arshad1,*, Muhammad Nadeem2, Saman Riaz1, Syeda Wajiha Zahra2, Ashit Kumar Dutta3, Zaid Alzaid4, Rana Alabdan5, Badr Almutairi6, Sultan Almotairi4,7

    CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 3065-3089, 2023, DOI:10.32604/cmc.2023.035695 - 31 March 2023

    Abstract There are many cloud data security techniques and algorithms available that can be used to detect attacks on cloud data, but these techniques and algorithms cannot be used to protect data from an attacker. Cloud cryptography is the best way to transmit data in a secure and reliable format. Various researchers have developed various mechanisms to transfer data securely, which can convert data from readable to unreadable, but these algorithms are not sufficient to provide complete data security. Each algorithm has some data security issues. If some effective data protection techniques are used, the attacker… More >

  • Open Access

    ARTICLE

    A New Speech Encoder Based on Dynamic Framing Approach

    Renyuan Liu1, Jian Yang1, Xiaobing Zhou1,*, Xiaoguang Yue2,3,4

    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.2, pp. 1259-1276, 2023, DOI:10.32604/cmes.2023.021995 - 06 February 2023

    Abstract Latent information is difficult to get from the text in speech synthesis. Studies show that features from speech can get more information to help text encoding. In the field of speech encoding, a lot of work has been conducted on two aspects. The first aspect is to encode speech frame by frame. The second aspect is to encode the whole speech to a vector. But the scale in these aspects is fixed. So, encoding speech with an adjustable scale for more latent information is worthy of investigation. But current alignment approaches only support frame-by-frame encoding… More >

  • Open Access

    ARTICLE

    Multimodal Spatiotemporal Feature Map for Dynamic Gesture Recognition

    Xiaorui Zhang1,2,3,*, Xianglong Zeng1, Wei Sun3,4, Yongjun Ren1,2,3, Tong Xu5

    Computer Systems Science and Engineering, Vol.46, No.1, pp. 671-686, 2023, DOI:10.32604/csse.2023.035119 - 20 January 2023

    Abstract Gesture recognition technology enables machines to read human gestures and has significant application prospects in the fields of human-computer interaction and sign language translation. Existing researches usually use convolutional neural networks to extract features directly from raw gesture data for gesture recognition, but the networks are affected by much interference information in the input data and thus fit to some unimportant features. In this paper, we proposed a novel method for encoding spatio-temporal information, which can enhance the key features required for gesture recognition, such as shape, structure, contour, position and hand motion of gestures,… More >

  • Open Access

    ARTICLE

    DERNNet: Dual Encoding Recurrent Neural Network Based Secure Optimal Routing in WSN

    A. Venkatesh1, S. Asha2,*

    Computer Systems Science and Engineering, Vol.45, No.2, pp. 1375-1392, 2023, DOI:10.32604/csse.2023.030944 - 03 November 2022

    Abstract A Wireless Sensor Network (WSN) is constructed with numerous sensors over geographical regions. The basic challenge experienced while designing WSN is in increasing the network lifetime and use of low energy. As sensor nodes are resource constrained in nature, novel techniques are essential to improve lifetime of nodes in WSN. Nodes energy is considered as an important resource for sensor node which are battery powered based. In WSN, energy is consumed mainly while data is being transferred among nodes in the network. Several research works are carried out focusing on preserving energy of nodes in… More >

  • Open Access

    ARTICLE

    Sea-Land Segmentation of Remote Sensing Images Based on SDW-UNet

    Tianyu Liu1,3,4, Pengyu Liu1,2,3,4,*, Xiaowei Jia5, Shanji Chen2, Ying Ma2, Qian Gao1,3,4

    Computer Systems Science and Engineering, Vol.45, No.2, pp. 1033-1045, 2023, DOI:10.32604/csse.2023.028225 - 03 November 2022

    Abstract Image segmentation of sea-land remote sensing images is of great importance for downstream applications including shoreline extraction, the monitoring of near-shore marine environment, and near-shore target recognition. To mitigate large number of parameters and improve the segmentation accuracy, we propose a new Squeeze-Depth-Wise UNet (SDW-UNet) deep learning model for sea-land remote sensing image segmentation. The proposed SDW-UNet model leverages the squeeze-excitation and depth-wise separable convolution to construct new convolution modules, which enhance the model capacity in combining multiple channels and reduces the model parameters. We further explore the effect of position-encoded information in NLP (Natural… More >

  • Open Access

    ARTICLE

    Vehicle Density Prediction in Low Quality Videos with Transformer Timeseries Prediction Model (TTPM)

    D. Suvitha*, M. Vijayalakshmi

    Computer Systems Science and Engineering, Vol.44, No.1, pp. 873-894, 2023, DOI:10.32604/csse.2023.025189 - 01 June 2022

    Abstract Recent advancement in low-cost cameras has facilitated surveillance in various developing towns in India. The video obtained from such surveillance are of low quality. Still counting vehicles from such videos are necessity to avoid traffic congestion and allows drivers to plan their routes more precisely. On the other hand, detecting vehicles from such low quality videos are highly challenging with vision based methodologies. In this research a meticulous attempt is made to access low-quality videos to describe traffic in Salem town in India, which is mostly an un-attempted entity by most available sources. In this… More >

  • Open Access

    ARTICLE

    Fault Diagnosis of Wind Turbine Generator with Stacked Noise Reduction Autoencoder Based on Group Normalization

    Sihua Wang1,2, Wenhui Zhang1,2,*, Gaofei Zheng1,2, Xujie Li1,2, Yougeng Zhao1,2

    Energy Engineering, Vol.119, No.6, pp. 2431-2445, 2022, DOI:10.32604/ee.2022.020779 - 14 September 2022

    Abstract In order to improve the condition monitoring and fault diagnosis of wind turbines, a stacked noise reduction autoencoding network based on group normalization is proposed in this paper. The network is based on SCADA data of wind turbine operation, firstly, the group normalization (GN) algorithm is added to solve the problems of stack noise reduction autoencoding network training and slow convergence speed, and the RMSProp algorithm is used to update the weight and the bias of the autoenccoder, which further optimizes the problem that the loss function swings too much during the update process. Finally, More >

  • Open Access

    ARTICLE

    A Hybrid Security Framework for Medical Image Communication

    Walid El-Shafai1,2, Hayam A. Abd El-Hameed3, Ashraf A. M. Khalaf3, Naglaa F. Soliman4, Amel A. Alhussan5,*, Fathi E. Abd El-Samie1

    CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 2713-2730, 2022, DOI:10.32604/cmc.2022.028739 - 16 June 2022

    Abstract Authentication of the digital image has much attention for the digital revolution. Digital image authentication can be verified with image watermarking and image encryption schemes. These schemes are widely used to protect images against forgery attacks, and they are useful for protecting copyright and rightful ownership. Depending on the desirable applications, several image encryption and watermarking schemes have been proposed to moderate this attention. This framework presents a new scheme that combines a Walsh Hadamard Transform (WHT)-based image watermarking scheme with an image encryption scheme based on Double Random Phase Encoding (DRPE). First, on the More >

  • Open Access

    ARTICLE

    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 - 16 June 2022

    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

    ARTICLE

    Errorless Underwater Channel Selection Scheme Using Forward Error Rectification and Modulation

    A. Herald1,*, C. Vennila2

    Intelligent Automation & Soft Computing, Vol.34, No.2, pp. 753-768, 2022, DOI:10.32604/iasc.2022.025362 - 03 May 2022

    Abstract Acoustic and optical communication are the best options for data transmission in underwater communication. This paper presents the simulation model of an underwater wireless optical communication channel using the Errorless Channel Selection Using Forward Error Rectification and Modulation Progression (ECFM). The suitable modulation methods are used to encode and transfer the packets properly, the data is encoded in differential phase shift key mode at the phase of the light wave carrier. In addition, to send and receive data, an error rectification method is developed in the transport layer, which improves network speed. In addition, we More >

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