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  • Open Access

    ARTICLE

    Attribute-Based Keyword Search over the Encrypted Blockchain

    Zhen Yang1, Hongao Zhang1, Haiyang Yu1,*, Zheng Li1, Bocheng Zhu1, Richard O. Sinnott2

    CMES-Computer Modeling in Engineering & Sciences, Vol.128, No.1, pp. 269-282, 2021, DOI:10.32604/cmes.2021.015210

    Abstract To address privacy concerns, data in the blockchain should be encrypted in advance to avoid data access from all users in the blockchain. However, encrypted data cannot be directly retrieved, which hinders data sharing in the blockchain. Several works have been proposed to deal with this problem. However, the data retrieval in these schemes requires the participation of data owners and lacks finer-grained access control. In this paper, we propose an attribute-based keyword search scheme over the encrypted blockchain, which allows users to search encrypted files over the blockchain based on their attributes. In addition, we build a file chain… More >

  • Open Access

    ARTICLE

    A Mortality Risk Assessment Approach on ICU Patients Clinical Medication Events Using Deep Learning

    Dejia Shi1, Hanzhong Zheng2,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.128, No.1, pp. 161-181, 2021, DOI:10.32604/cmes.2021.014917

    Abstract ICU patients are vulnerable to medications, especially infusion medications, and the rate and dosage of infusion drugs may worsen the condition. The mortality prediction model can monitor the real-time response of patients to drug treatment, evaluate doctors’ treatment plans to avoid severe situations such as inverse Drug-Drug Interactions (DDI), and facilitate the timely intervention and adjustment of doctor’s treatment plan. The treatment process of patients usually has a time-sequence relation (which usually has the missing data problem) in patients’ treatment history. The state-of-the-art method to model such time-sequence is to use Recurrent Neural Network (RNN). However, sometimes, patients’ treatment can… More >

  • Open Access

    ARTICLE

    A Numerical Model for Simulating Two-Phase Flow with Adaptive Mesh Refinement

    Yunxing Zhang, Shan Ma, Kangping Liao, Wenyang Duan*

    CMES-Computer Modeling in Engineering & Sciences, Vol.128, No.1, pp. 43-64, 2021, DOI:10.32604/cmes.2021.014847

    Abstract In this study, a numerical model for simulating two-phase flow is developed. The Cartesian grid with Adaptive Mesh Refinement (AMR) is adopted to reduce the computational cost. An explicit projection method is used for the time integration and the Finite Difference Method (FDM) is applied on a staggered grid for the discretization of spatial derivatives. The Volume of Fluid (VOF) method with Piecewise-Linear Interface Calculation (PLIC) is extended to the AMR grid to capture the gas-water interface accurately. A coarse-fine interface treatment method is developed to preserve the flux conservation at the interfaces. Several two-dimensional (2D) and three-dimensional (3D) benchmark… More >

  • Open Access

    ARTICLE

    DEM Simulations of Resistance of Particle to Intruders during Quasistatic Penetrations

    Shaomin Liang, Lu Liu, Shunying Ji*

    CMES-Computer Modeling in Engineering & Sciences, Vol.128, No.1, pp. 145-160, 2021, DOI:10.32604/cmes.2021.016403

    Abstract Based on the discrete element method and hydrostatics theory, an improved Archimedes principle is proposed to study the rules pertaining to resistance changes during the penetration process of an intruder into the particulate materials. The results illustrate the fact that the lateral contribution to the resistance is very small, while the tangential force of the lateral resistance originates from friction effects. Conversely, the resistance of particulate materials on the intruder mainly occurs at the bottom part of the intruding object. Correspondingly, the factors that determine the resistance of the bottom part of the intruding object and the rules pertaining to… More >

  • Open Access

    ARTICLE

    A Pseudo-Spectral Scheme for Systems of Two-Point Boundary Value Problems with Left and Right Sided Fractional Derivatives and Related Integral Equations

    I. G. Ameen1, N. A. Elkot2, M. A. Zaky3,*, A. S. Hendy4,5, E. H. Doha2

    CMES-Computer Modeling in Engineering & Sciences, Vol.128, No.1, pp. 21-41, 2021, DOI:10.32604/cmes.2021.015310

    Abstract We target here to solve numerically a class of nonlinear fractional two-point boundary value problems involving left- and right-sided fractional derivatives. The main ingredient of the proposed method is to recast the problem into an equivalent system of weakly singular integral equations. Then, a Legendre-based spectral collocation method is developed for solving the transformed system. Therefore, we can make good use of the advantages of the Gauss quadrature rule. We present the construction and analysis of the collocation method. These results can be indirectly applied to solve fractional optimal control problems by considering the corresponding Euler–Lagrange equations. Two numerical examples… More >

  • Open Access

    ARTICLE

    The Research of Automatic Classification of Ultrasound Thyroid Nodules

    Yanling An1, Shaohai Hu1,*, Shuaiqi Liu2,3, Jie Zhao2,3,*, Yu-Dong Zhang4

    CMES-Computer Modeling in Engineering & Sciences, Vol.128, No.1, pp. 203-222, 2021, DOI:10.32604/cmes.2021.015159

    Abstract This paper proposes a computer-aided diagnosis system which can automatically detect thyroid nodules (TNs) and discriminate them as benign or malignant. The system firstly uses variational level set active contour with gradients and phase information to complete automatic extraction of the boundaries of thyroid nodules images. Then according to thyroid ultrasound images and clinical diagnostic criteria, a new feature extraction method based on the fusion of shape, gray and texture is explored. Due to the imbalance of thyroid sample classes, this paper introduces a weight factor to improve support vector machine, offering different classes of samples with different weights. Finally,… More >

  • Open Access

    ARTICLE

    Improved Prediction and Understanding of Glass-Forming Ability Based on Random Forest Algorithm

    Chenjing Su1, Xiaoyu Li1,*, Mengru Li2, Qinsheng Zhu2, Hao Fu2, Shan Yang3

    Journal of Quantum Computing, Vol.3, No.2, pp. 79-87, 2021, DOI:10.32604/ jqc.2021.016651

    Abstract As an ideal material, bulk metallic glass (MG) has a wide range of applications because of its unique properties such as structural, functional and biomedical materials. However, it is difficult to predict the glass-forming ability (GFA) even given the criteria in theory and this problem greatly limits the application of bulk MG in industrial field. In this work, the proposed model uses the random forest classification method which is one of machine learning methods to solve the GFA prediction for binary metallic alloys. Compared with the previous SVM algorithm models of all features combinations, this new model is successfully constructed… More >

  • Open Access

    ARTICLE

    A Bi-Histogram Shifting Contrast Enhancement for Color Images

    Lord Amoah1,2,*, Ampofo Twumasi Kwabena3

    Journal of Quantum Computing, Vol.3, No.2, pp. 65-77, 2021, DOI:10.32604/jqc.2021.020734

    Abstract Recent contrast enhancement (CE) methods, with a few exceptions, predominantly focus on enhancing gray-scale images. This paper proposes a bihistogram shifting contrast enhancement for color images based on the RGB (red, green, and blue) color model. The proposed method selects the two highest bins and two lowest bins from the image histogram, performs an equalized number of bidirectional histogram shifting repetitions on each RGB channel while embedding secret data into marked images. The proposed method simultaneously performs both right histogram shifting (RHS) and left histogram shifting (LHS) in each histogram shifting repetition to embed and split the highest bins while… More >

  • Open Access

    ARTICLE

    Malware Detection Based on Multidimensional Time Distribution Features

    Huizhong Sun1, Guosheng Xu1,*, Hewei Yu2, Minyan Ma3, Yanhui Guo1, Ruijie Quan4

    Journal of Quantum Computing, Vol.3, No.2, pp. 55-63, 2021, DOI:10.32604/jqc.2021.017365

    Abstract Language detection models based on system calls suffer from certain false negatives and detection blind spots. Hence, the normal behavior sequences of some malware applications for a short period can become malicious behavior within a certain time window. To detect such behaviors, we extract a multidimensional time distribution feature matrix on the basis of statistical analysis. This matrix mainly includes multidimensional time distribution features, multidimensional word pair correlation features, and multidimensional word frequency distribution features. A multidimensional time distribution model based on neural networks is built to detect the overall abnormal behavior within a given time window. Experimental evaluation is… More >

  • Open Access

    ARTICLE

    New Quantum Private Comparison Using Hyperentangled GHZ State

    Jerrel Gianni1, Zhiguo Qu2,*

    Journal of Quantum Computing, Vol.3, No.2, pp. 45-54, 2021, DOI:10.32604/jqc.2021.019675

    Abstract In this paper, we propose a new protocol designed for quantum private comparison (QPC). This new protocol utilizes the hyperentanglement as the quantum resource and introduces a semi-honest third party (TP) to achieve the objective. This protocol’s quantum carrier is a hyperentangled three-photon GHZ state in 2 degrees of freedom (DOF), which could have 64 combinations. The TP can decide which combination to use based on the shared key information provided from a quantum key distribution (QKD) protocol. By doing so, the security of the protocol can be improved further. Decoy photon technology is also used as another means of… More >

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