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  • Open Access

    ARTICLE

    CLEC: Combination Locality Based Erasure Code for Permissioned Blockchain Storage

    Jiabin Wu1,3, Boai Yang2, Yang Liu1, Fang Liu3,*, Nong Xiao1, Shuo Li4

    CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 5137-5150, 2022, DOI:10.32604/cmc.2022.028305

    Abstract Building a new decentralized domain name system based on blockchain technology is helping to solve problems, such as load imbalance and over-dependence on the trust of the central node. However, in the existing blockchain storage system, the storage overhead is very high due to its full-replication data storage mechanism. The total storage consumption for each block is up to O(n) with n nodes. Erasure code applied to blockchains can significantly reduce the storage overhead, but also greatly lower the read performance. In this study, we propose a novel coding scheme for blockchain storage, Combination Locality based Erasure Code for Permissioned… More >

  • Open Access

    ARTICLE

    A Fast Tongue Detection and Location Algorithm in Natural Environment

    Lei Zhu1, Guojiang Xin1,2,*, Xin Wang1, Changsong Ding1,2, Hao Liang1,2, Qilei Chen3

    CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 4727-4742, 2022, DOI:10.32604/cmc.2022.028187

    Abstract The collection and extraction of tongue images has always been an important part of intelligent tongue diagnosis. At present, the collection of tongue images generally needs to be completed in a sealed, stable light environment, which is not conducive to the promotion of extensive tongue image and intelligent tongue diagnosis. In response to the problem, a new algorithm named GCYTD (GELU-CA-YOLO Tongue Detection) is proposed to quickly detect and locate the tongue in a natural environment, which can greatly reduce the restriction of the tongue image collection environment. The algorithm is based on the YOLO (You Only Look Once) V4-tiny… More >

  • Open Access

    ARTICLE

    Trustworthy Explainable Recommendation Framework for Relevancy

    Saba Sana*, Mohammad Shoaib

    CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 5887-5909, 2022, DOI:10.32604/cmc.2022.028046

    Abstract Explainable recommendation systems deal with the problem of ‘Why’. Besides providing the user with the recommendation, it is also explained why such an object is being recommended. It helps to improve trustworthiness, effectiveness, efficiency, persuasiveness, and user satisfaction towards the system. To recommend the relevant information with an explanation to the user is required. Existing systems provide the top-k recommendation options to the user based on ratings and reviews about the required object but unable to explain the matched-attribute-based recommendation to the user. A framework is proposed to fetch the most specific information that matches the user requirements based on… More >

  • Open Access

    ARTICLE

    Design of Multi-Valued Logic Circuit Using Carbon Nano Tube Field Transistors

    S. V. Ratankumar1,2, L. Koteswara Rao1,*, M. Kiran Kumar3

    CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 5283-5298, 2022, DOI:10.32604/cmc.2022.027975

    Abstract The design of a three-input logic circuit using carbon nanotube field effect transistors (CNTFETs) is presented. Ternary logic must be an exact replacement for dual logic since it performs straightforwardly in digital devices, which is why this design is so popular, and it also reduces chip area, both of which are examples of circuit overheads. The proposed module we have investigated is a triple-logic-based one, based on advanced technology CNTFETs and an emphasis on minimizing delay times at various values, as well as comparisons of the design working with various load capacitances. Comparing the proposed design with the existing design,… More >

  • Open Access

    ARTICLE

    Truncation and Rounding-Based Scalable Approximate Multiplier Design for Computer Imaging Applications

    S. Rooban1,*, A. Yamini Naga Ratnam1, M. V. S. Ramprasad2, N. Subbulakshmi3, R. Uma Mageswari4

    CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 5169-5184, 2022, DOI:10.32604/cmc.2022.027974

    Abstract Advanced technology used for arithmetic computing application, comprises greater number of approximate multipliers and approximate adders. Truncation and Rounding-based Scalable Approximate Multiplier (TRSAM) distinguish a variety of modes based on height (h) and truncation (t) as TRSAM (h, t) in the architecture. This TRSAM operation produces higher absolute error in Least Significant Bit (LSB) data shift unit. A new scalable approximate multiplier approach that uses truncation and rounding TRSAM (3, 7) is proposed to increase the multiplier accuracy. With the help of foremost one bit architecture, the proposed scalable approximate multiplier approach reduces the partial products. The proposed approximate TRSAM… More >

  • Open Access

    ARTICLE

    A Constant Gain and Miniaturized Antipodal Vivaldi Antenna for 5G Communication Applications

    Amruta S. Dixit1, Sumit Kumar1,*, Shabana Urooj2

    CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 4909-4921, 2022, DOI:10.32604/cmc.2022.027862

    Abstract This paper proposes a stable gain and a compact Antipodal Vivaldi Antenna (AVA) for a 38 GHz band of 5G communication. A novel compact AVA is designed to provide constant gain, high front to back ratio (FBR), and very high efficiency. The performance of the proposed AVA is enhanced with the help of a dielectric lens (DL) and corrugations. A rectangular-shaped DL is incorporated in conventional AVA (CAVA) to enhance its gain up to 1 dBi and the bandwidth by 1.8 GHz. Next, the rectangular corrugations are implemented in CAVA with lens (CAVA-L) to further improve the gain and bandwidth. The proposed… More >

  • Open Access

    ARTICLE

    CNN Based Multi-Object Segmentation and Feature Fusion for Scene Recognition

    Adnan Ahmed Rafique1, Yazeed Yasin Ghadi2, Suliman A. Alsuhibany3, Samia Allaoua Chelloug4,*, Ahmad Jalal1, Jeongmin Park5

    CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 4657-4675, 2022, DOI:10.32604/cmc.2022.027720

    Abstract Latest advancements in vision technology offer an evident impact on multi-object recognition and scene understanding. Such scene-understanding task is a demanding part of several technologies, like augmented reality-based scene integration, robotic navigation, autonomous driving, and tourist guide. Incorporating visual information in contextually unified segments, convolution neural networks-based approaches will significantly mitigate the clutter, which is usual in classical frameworks during scene understanding. In this paper, we propose a convolutional neural network (CNN) based segmentation method for the recognition of multiple objects in an image. Initially, after acquisition and preprocessing, the image is segmented by using CNN. Then, CNN features are… More >

  • Open Access

    ARTICLE

    Research on Tibetan Speech Recognition Based on the Am-do Dialect

    Kuntharrgyal Khysru1,*, Jianguo Wei1,2, Jianwu Dang3

    CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 4897-4907, 2022, DOI:10.32604/cmc.2022.027591

    Abstract In China, Tibetan is usually divided into three major dialects: the Am-do, Khams and Lhasa dialects. The Am-do dialect evolved from ancient Tibetan and is a local variant of modern Tibetan. Although this dialect has its own specific historical and social conditions and development, there have been different degrees of communication with other ethnic groups, but all the abovementioned dialects developed from the same language: Tibetan. This paper uses the particularity of Tibetan suffixes in pronunciation and proposes a lexicon for the Am-do language, which optimizes the problems existing in previous research. Audio data of the Am-do dialect are expanded… More >

  • Open Access

    ARTICLE

    Sika Deer Behavior Recognition Based on Machine Vision

    He Gong1,3,4, Mingwang Deng1, Shijun Li1,2,6,*, Tianli Hu1,3,4, Yu Sun1,3,4, Ye Mu1,3,4, Zilian Wang1, Chang Zhang1, Thobela Louis Tyasi5

    CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 4953-4969, 2022, DOI:10.32604/cmc.2022.027457

    Abstract With the increasing intensive and large-scale development of the sika deer breeding industry, it is crucial to assess the health status of the sika deer by monitoring their behaviours. A machine vision–based method for the behaviour recognition of sika deer is proposed in this paper. Google Inception Net (GoogLeNet) is used to optimise the model in this paper. First, the number of layers and size of the model were reduced. Then, the 5 × 5 convolution was changed to two 3 × 3 convolutions, which reduced the parameters and increased the nonlinearity of the model. A 5 × 5 convolution… More >

  • Open Access

    ARTICLE

    Real-Time Demand Response Management for Controlling Load Using Deep Reinforcement Learning

    Yongjiang Zhao, Jae Hung Yoo, Chang Gyoon Lim*

    CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 5671-5686, 2022, DOI:10.32604/cmc.2022.027443

    Abstract With the rapid economic growth and improved living standards, electricity has become an indispensable energy source in our lives. Therefore, the stability of the grid power supply and the conservation of electricity is critical. The following are some of the problems facing now: 1) During the peak power consumption period, it will pose a threat to the power grid. Enhancing and improving the power distribution infrastructure requires high maintenance costs. 2) The user's electricity schedule is unreasonable due to personal behavior, which will cause a waste of electricity. Controlling load as a vital part of incentive demand response (DR) can… More >

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