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  • Open Access


    Web Page Recommendation Using Distributional Recurrent Neural Network

    Chaithra1,*, G. M. Lingaraju2, S. Jagannatha3

    Computer Systems Science and Engineering, Vol.45, No.1, pp. 803-817, 2023, DOI:10.32604/csse.2023.028770

    Abstract In the data retrieval process of the Data recommendation system, the matching prediction and similarity identification take place a major role in the ontology. In that, there are several methods to improve the retrieving process with improved accuracy and to reduce the searching time. Since, in the data recommendation system, this type of data searching becomes complex to search for the best matching for given query data and fails in the accuracy of the query recommendation process. To improve the performance of data validation, this paper proposed a novel model of data similarity estimation and clustering method to retrieve the… More >

  • Open Access


    Novel Quantum Algorithms to Minimize Switching Functions Based on Graph Partitions

    Peng Gao*, Marek Perkowski, Yiwei Li, Xiaoyu Song

    CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 4545-4561, 2022, DOI:10.32604/cmc.2022.020483

    Abstract After Google reported its realization of quantum supremacy, Solving the classical problems with quantum computing is becoming a valuable research topic. Switching function minimization is an important problem in Electronic Design Automation (EDA) and logic synthesis, most of the solutions are based on heuristic algorithms with a classical computer, it is a good practice to solve this problem with a quantum processer. In this paper, we introduce a new hybrid classic quantum algorithm using Grover’s algorithm and symmetric functions to minimize small Disjoint Sum of Product (DSOP) and Sum of Product (SOP) for Boolean switching functions. Our method is based… More >

  • Open Access


    Cross-Layer Hidden Markov Analysis for Intrusion Detection

    K. Venkatachalam1, P. Prabu2, B. Saravana Balaji3, Byeong-Gwon Kang4, Yunyoung Nam4,*, Mohamed Abouhawwash5,6

    CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 3685-3700, 2022, DOI:10.32604/cmc.2022.019502

    Abstract Ad hoc mobile cloud computing networks are affected by various issues, like delay, energy consumption, flexibility, infrastructure, network lifetime, security, stability, data transition, and link accomplishment. Given the issues above, route failure is prevalent in ad hoc mobile cloud computing networks, which increases energy consumption and delay and reduces stability. These issues may affect several interconnected nodes in an ad hoc mobile cloud computing network. To address these weaknesses, which raise many concerns about privacy and security, this study formulated clustering-based storage and search optimization approaches using cross-layer analysis. The proposed approaches were formed by cross-layer analysis based on intrusion… More >

  • Open Access


    Determination of Cup to Disc Ratio Using Unsupervised Machine Learning Techniques for Glaucoma Detection

    R. Praveena*, T. R. GaneshBabu

    Molecular & Cellular Biomechanics, Vol.18, No.2, pp. 69-86, 2021, DOI:10.32604/mcb.2021.014622

    Abstract The cup nerve head, optic cup, optic disc ratio and neural rim configuration are observed as important for detecting glaucoma at an early stage in clinical practice. The main clinical indicator of glaucoma optic cup to disc ratio is currently determined manually by limiting the mass screening was potential. This paper proposes the following methods for an automatic cup to disc ratio determination. In the first part of the work, fundus image of the optic disc region is considered. Clustering means K is used automatically to extract the optic disc whereas K-value is automatically selected by algorithm called hill climbing.… More >

  • Open Access


    QRDPSO: A New Optimization Method for Swarm Robot Searching and Obstacle Avoidance in Dynamic Environments

    Mehiar, D.A.F., Azizul, Z.H.*, Loo, C.K.

    Intelligent Automation & Soft Computing, Vol.26, No.3, pp. 447-454, 2020, DOI:10.32604/iasc.2020.013921

    Abstract In this paper we show how the quantum-based particle swarm optimization (QPSO) method is adopted to derive a new derivation for robotics application in search and rescue simulations. The new derivation, called the Quantum Robot Darwinian PSO (QRDPSO) is inspired from another PSO-based algorithm, the Robot Darwinian PSO (RDPSO). This paper includes comprehensive details on the QRDPSO formulation and parameters control which show how the swarm overcomes communication constraints to avoid obstacles and achieve optimal solution. The results show the QRDPSO is an upgrade over RDPSO in terms of convergence speed, trajectory control, obstacle avoidance and connectivity performance of the… More >

  • Open Access


    Modified Viterbi Scoring for HMM‐Based Speech Recognition

    Jihyuck Joa, Han‐Gyu Kimb, In‐Cheol Parka, Bang Chul Jungc, Hoyoung Yooc

    Intelligent Automation & Soft Computing, Vol.25, No.2, pp. 351-358, 2019, DOI:10.31209/2019.100000096

    Abstract A modified Viterbi scoring procedure is presented in this paper based on Dijkstra’s shortest-path algorithm. In HMM-based speech recognition systems, the Viterbi scoring plays a significant role in finding the best matching model, but its computational complexity is linearly proportional to the number of reference models and their states. Therefore, the complexity is serious in implementing a high-speed speech recognition system. In the proposed method, the Viterbi scoring is translated into the searching of a minimum path, and the shortest-path algorithm is exploited to decrease the computational complexity while preventing the recognition accuracy from deteriorating. In addition, a two-phase comparison… More >

  • Open Access


    On Multi-Thread Crawler Optimization for Scalable Text Searching

    Guang Sun1, Huanxin Xiang2, Shuanghu Li1,*

    Journal on Big Data, Vol.1, No.2, pp. 89-106, 2019, DOI:10.32604/jbd.2019.07235

    Abstract Web crawlers are an important part of modern search engines. With the development of the times, data has exploded and humans have entered a “big data era”. For example, Wikipedia carries the knowledge from all over the world, records the real-time news that occurs every day, and provides users with a good database of data, but because of the large amount of data, it puts a lot of pressure on users to search. At present, single-threaded crawling data can no longer meet the requirements of text crawling. In order to improve the performance and program versatility of single-threaded crawlers, a… More >

  • Open Access


    Network Embedding-Based Anomalous Density Searching for Multi-Group Collaborative Fraudsters Detection in Social Media

    Chengzhang Zhu1, 2, Wentao Zhao2, *, Qian Li1, Pan Li2, Qiaobo Da3

    CMC-Computers, Materials & Continua, Vol.60, No.1, pp. 317-333, 2019, DOI:10.32604/cmc.2019.05677

    Abstract Detecting collaborative fraudsters who manipulate opinions in social media is becoming extremely important in order to provide reliable information, in which, however, the diversity in different groups of collaborative fraudsters presents a significant challenge to existing collaborative fraudsters detection methods. These methods often detect collaborative fraudsters as the largest group of users who have the strongest relation with each other in the social media, consequently overlooking the other groups of fraudsters that are with strong user relation yet small group size. This paper introduces a novel network embedding-based framework NEST and its instance BEST to address this issue. NEST detects… More >

  • Open Access


    Fast Searching Algorithm for Candidate Satellite-node Set in NLMG

    Yufeng Nie1, Ying Liu2, Yuantong Gu3, Xiangkuo Fan1

    CMES-Computer Modeling in Engineering & Sciences, Vol.45, No.1, pp. 31-56, 2009, DOI:10.3970/cmes.2009.045.031

    Abstract The Node-based Local Mesh Generation (NLMG) algorithm, which is free of mesh inconsistency, is one of core algorithms in the Node-based Local Finite Element Method (NLFEM) to achieve the seamless link between mesh generation and stiffness matrix calculation, and the seamless link helps to improve the parallel efficiency of FEM. Furthermore, the key to ensure the efficiency and reliability of NLMG is to determine the candidate satellite-node set of a central node quickly and accurately. This paper develops a Fast Local Search Method based on Uniform Bucket (FLSMUB) and a Fast Local Search Method based on Multilayer Bucket (FLSMMB), and… More >

  • Open Access


    Researching the Link Between the Geometric and Rènyi Discord for Special Canonical Initial States Based on Neural Network Method

    Xiaoyu Li1, Qinsheng Zhu2,*, Qingyu Meng2, Caishu You1, Mingzheng Zhu1, Yong Hu2, Yiming Huang1,3, Hao Wu2, Desheng Zheng4

    CMC-Computers, Materials & Continua, Vol.60, No.3, pp. 1087-1095, 2019, DOI:10.32604/cmc.2019.06060

    Abstract Quantum correlation which is different to the entanglement and classical correlation plays important role in quantum information field. In our setup, neural network method is adopted to simulate the link between the Rènyi discord (α = 2) and the geometric discord (Bures distance) for special canonical initial states in order to show the consistency of physical results for different quantification methods. Our results are useful for studying the differences and commonalities of different quantizing methods of quantum correlation. More >

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