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  • Open Access

    ARTICLE

    ELM-Based Shape Adaptive DCT Compression Technique for Underwater Image Compression

    M. Jamuna Rani1,*, C. Vasanthanayaki2

    Computer Systems Science and Engineering, Vol.45, No.2, pp. 1953-1970, 2023, DOI:10.32604/csse.2023.028713 - 03 November 2022

    Abstract Underwater imagery and transmission possess numerous challenges like lower signal bandwidth, slower data transmission bit rates, Noise, underwater blue/green light haze etc. These factors distort the estimation of Region of Interest and are prime hurdles in deploying efficient compression techniques. Due to the presence of blue/green light in underwater imagery, shape adaptive or block-wise compression techniques faces failures as it becomes very difficult to estimate the compression levels/coefficients for a particular region. This method is proposed to efficiently deploy an Extreme Learning Machine (ELM) model-based shape adaptive Discrete Cosine Transformation (DCT) for underwater images. Underwater More >

  • Open Access

    ARTICLE

    Modified 2 Satisfiability Reverse Analysis Method via Logical Permutation Operator

    Siti Zulaikha Mohd Jamaludin1, Mohd. Asyraf Mansor2, Aslina Baharum3,*, Mohd Shareduwan Mohd Kasihmuddin1, Habibah A. Wahab4, Muhammad Fadhil Marsani1

    CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 2853-2870, 2023, DOI:10.32604/cmc.2023.032654 - 31 October 2022

    Abstract The effectiveness of the logic mining approach is strongly correlated to the quality of the induced logical representation that represent the behaviour of the data. Specifically, the optimum induced logical representation indicates the capability of the logic mining approach in generalizing the real datasets of different variants and dimensions. The main issues with the logic extracted by the standard logic mining techniques are lack of interpretability and the weakness in terms of the structural and arrangement of the 2 Satisfiability logic causing lower accuracy. To address the issues, the logical permutation serves as an alternative… More >

  • Open Access

    ARTICLE

    Earth Pressure of the Trapdoor Problem Using Three-Dimensional Discrete Element Method

    Qizhi Chen1, Chuli Xu1, Baoping Zou1,*, Zhanyou Luo2, Changjie Xu3, Xu Long4,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.135, No.2, pp. 1503-1520, 2023, DOI:10.32604/cmes.2022.022823 - 27 October 2022

    Abstract Load transformation from the yielding part of the soil to the adjacent part is known as the soil arching effect, which plays an important role in the design of various geotechnical infrastructures. Terzaghi’s trapdoor test was an important milestone in the development of theories on soil arching. The research on earth pressure of the trapdoor problem is presented in this paper using the three-dimensional (3D) discrete element method (DEM). Five 3D trapdoor models with different heights are established by 3D DEM software PFC 3D. The variation of earth pressure on the trapdoor with the downward… More >

  • Open Access

    ARTICLE

    An Algorithm to Reduce Compression Ratio in Multimedia Applications

    Dur-e-Jabeen1,*, Tahmina Khan2, Rumaisa Iftikhar1, Ali Akbar Siddique1, Samiya Asghar1

    CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 539-557, 2023, DOI:10.32604/cmc.2023.032393 - 22 September 2022

    Abstract In recent years, it has been evident that internet is the most effective means of transmitting information in the form of documents, photographs, or videos around the world. The purpose of an image compression method is to encode a picture with fewer bits while retaining the decompressed image’s visual quality. During transmission, this massive data necessitates a lot of channel space. In order to overcome this problem, an effective visual compression approach is required to resize this large amount of data. This work is based on lossy image compression and is offered for static color… More >

  • Open Access

    ARTICLE

    Constructing Representative Collective Signature Protocols Using The GOST R34.10-1994 Standard

    Tuan Nguyen Kim1,*, Duy Ho Ngoc2, Nikolay A. Moldovyan3

    CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 1475-1491, 2023, DOI:10.32604/cmc.2023.029253 - 22 September 2022

    Abstract The representative collective digital signature, which was suggested by us, is built based on combining the advantages of group digital signature and collective digital signature. This collective digital signature schema helps to create a unique digital signature that deputizes a collective of people representing different groups of signers and may also include personal signers. The advantage of the proposed collective signature is that it can be built based on most of the well-known difficult problems such as the factor analysis, the discrete logarithm and finding modulo roots of large prime numbers and the current digital… More >

  • Open Access

    ARTICLE

    A Consistent Time Level Implementation Preserving Second-Order Time Accuracy via a Framework of Unified Time Integrators in the Discrete Element Approach

    Tao Xue1, Yazhou Wang2, Masao Shimada2, David Tae2, Kumar Tamma2,*, Xiaobing Zhang1,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.134, No.3, pp. 1469-1487, 2023, DOI:10.32604/cmes.2022.021616 - 20 September 2022

    Abstract In this work, a consistent and physically accurate implementation of the general framework of unified second-order time accurate integrators via the well-known GSSSS framework in the Discrete Element Method is presented. The improved tangential displacement evaluation in the present implementation of the discrete element method has been derived and implemented to preserve the consistency of the correct time level evaluation during the time integration process in calculating the algorithmic tangential displacement. Several numerical examples have been used to validate the proposed tangential displacement evaluation; this is in contrast to past practices which only seem to… More >

  • Open Access

    ARTICLE

    A Fixed-Point Iterative Method for Discrete Tomography Reconstruction Based on Intelligent Optimization

    Luyao Yang1,#, Hao Chen2,#, Haocheng Yu1, Jin Qiu1,*, Shuxian Zhu1,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.134, No.1, pp. 731-745, 2023, DOI:10.32604/cmes.2022.020656 - 24 August 2022

    Abstract Discrete Tomography (DT) is a technology that uses image projection to reconstruct images. Its reconstruction problem, especially the binary image (0–1 matrix) has attracted strong attention. In this study, a fixed point iterative method of integer programming based on intelligent optimization is proposed to optimize the reconstructed model. The solution process can be divided into two procedures. First, the DT problem is reformulated into a polyhedron judgment problem based on lattice basis reduction. Second, the fixed-point iterative method of Dang and Ye is used to judge whether an integer point exists in the polyhedron of More >

  • Open Access

    ARTICLE

    Discrete GWO Optimized Data Aggregation for Reducing Transmission Rate in IoT

    S. Siamala Devi1, K. Venkatachalam2, Yunyoung Nam3,*, Mohamed Abouhawwash4,5

    Computer Systems Science and Engineering, Vol.44, No.3, pp. 1869-1880, 2023, DOI:10.32604/csse.2023.025505 - 01 August 2022

    Abstract The conventional hospital environment is transformed into digital transformation that focuses on patient centric remote approach through advanced technologies. Early diagnosis of many diseases will improve the patient life. The cost of health care systems is reduced due to the use of advanced technologies such as Internet of Things (IoT), Wireless Sensor Networks (WSN), Embedded systems, Deep learning approaches and Optimization and aggregation methods. The data generated through these technologies will demand the bandwidth, data rate, latency of the network. In this proposed work, efficient discrete grey wolf optimization (DGWO) based data aggregation scheme using… More >

  • Open Access

    ARTICLE

    Optimized Deep Learning Methods for Crop Yield Prediction

    K. Vignesh1,*, A. Askarunisa2, A. M. Abirami3

    Computer Systems Science and Engineering, Vol.44, No.2, pp. 1051-1067, 2023, DOI:10.32604/csse.2023.024475 - 15 June 2022

    Abstract Crop yield has been predicted using environmental, land, water, and crop characteristics in a prospective research design. When it comes to predicting crop production, there are a number of factors to consider, including weather conditions, soil qualities, water levels and the location of the farm. A broad variety of algorithms based on deep learning are used to extract useful crops for forecasting. The combination of data mining and deep learning creates a whole crop yield prediction system that is able to connect raw data to predicted crop yields. The suggested study uses a Discrete Deep… More >

  • Open Access

    ARTICLE

    A Novel Radial Basis Function Neural Network Approach for ECG Signal Classification

    S. Sathishkumar1,*, R. Devi Priya2

    Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 129-148, 2023, DOI:10.32604/iasc.2023.023817 - 06 June 2022

    Abstract Electrocardiogram (ECG) is a diagnostic method that helps to assess and record the electrical impulses of heart. The traditional methods in the extraction of ECG features is inneffective for avoiding the computational abstractions in the ECG signal. The cardiologist and medical specialist find numerous difficulties in the process of traditional approaches. The specified restrictions are eliminated in the proposed classifier. The fundamental aim of this work is to find the R-R interval. To analyze the blockage, different approaches are implemented, which make the computation as facile with high accuracy. The information are recovered from the… More >

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