Vol.124, No.3, 2020-Table of Contents
- OPEN ACCESS EDITORIAL
- Introduction to the Special Issue on Recent Developments of Isogeometric Analysis and Its Applications in Structural Optimization
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CMES-Computer Modeling in Engineering & Sciences, Vol.124, No.3, pp. 783-785, 2020, DOI:10.32604/cmes.2020.013234
(This article belongs to this Special Issue: Recent Developments of Isogeometric Analysis and its Applications in Structural Optimization) - Abstract This article has no abstract. More
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- OPEN ACCESS ARTICLE
- Isogeometric Analysis and Shape Optimization of Holed Structures via the Patch Removing Technique
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CMES-Computer Modeling in Engineering & Sciences, Vol.124, No.3, pp. 787-806, 2020, DOI:10.32604/cmes.2020.09936
(This article belongs to this Special Issue: Recent Developments of Isogeometric Analysis and its Applications in Structural Optimization) - Abstract In this study, a patch removing based Isogeometric analysis (PR-IGA) method is proposed to conduct the holed structural analysis with only one parametric domain, in which there are also no trimmed elements. The theoretical foundation of this novel patch removing approach is that any holed structure can be obtained by removing sub-patches (i.e., the holes) from an intact base patch. Since the parametric domains of these patches are all meshed by rectangular grids, the elements in the resulted holed structural parametric domain could all be untrimmed rectangles under certain mapping conditions. To achieve the special condition, a systematic technique consisting… More
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- OPEN ACCESS ARTICLE
- Interpolating Isogeometric Boundary Node Method and Isogeometric Boundary Element Method Based on Parameter Space
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CMES-Computer Modeling in Engineering & Sciences, Vol.124, No.3, pp. 807-824, 2020, DOI:10.32604/cmes.2020.010936
(This article belongs to this Special Issue: Recent Developments of Isogeometric Analysis and its Applications in Structural Optimization) - Abstract In this paper, general interpolating isogeometric boundary node method (IIBNM) and isogeometric boundary element method (IBEM) based on parameter space are proposed for 2D elasticity problems. In both methods, the integral cells and elements are defined in parameter space, which can reproduce the geometry exactly at all the stages. In IIBNM, the improved interpolating moving leastsquare method (IIMLS) is applied for field approximation and the shape functions have the delta function property. The Lagrangian basis functions are used for field approximation in IBEM. Thus, the boundary conditions can be imposed directly in both methods. The shape functions are defined in… More
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- OPEN ACCESS ARTICLE
- Fractional Analysis of Thin Film Flow of Non-Newtonian Fluid
- CMES-Computer Modeling in Engineering & Sciences, Vol.124, No.3, pp. 825-845, 2020, DOI:10.32604/cmes.2020.011073
- Abstract Modeling and analysis of thin film flow with respect to magneto hydro dynamical effect has been an important theme in the field of fluid dynamics, due to its vast industrial applications. The analysis involves studying the behavior and response of governing equations on the basis of various parameters such as thickness of the film, film surface profile, shear stress, liquid velocity, volumetric flux, vorticity, gravity, viscosity among others, along with different boundary conditions. In this article, we extend this analysis in fractional space using a homotopy based scheme, considering the case of a Non-Newtonian Pseudo-Plastic fluid for lifting and drainage… More
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Downloads:1455
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- OPEN ACCESS ARTICLE
- Predicting Human Mobility via Long Short-Term Patterns
- CMES-Computer Modeling in Engineering & Sciences, Vol.124, No.3, pp. 847-864, 2020, DOI:10.32604/cmes.2020.010240
- Abstract Predicting human mobility has great significance in Location based Social Network applications, while it is challenging due to the impact of historical mobility patterns and current trajectories. Among these challenges, historical patterns tend to be crucial in the prediction task. However, it is difficult to capture complex patterns from long historical trajectories. Motivated by recent success of Convolutional Neural Network (CNN)-based methods, we propose a Union ConvGRU (UCG) Net, which can capture long short-term patterns of historical trajectories and sequential impact of current trajectories. Specifically, we first incorporate historical trajectories into hidden states by a shared-weight layer, and then utilize… More
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- OPEN ACCESS ARTICLE
- Probabilistic Life Calculation Method of NdFeB Based on Brittle Fatigue Damage Model
- CMES-Computer Modeling in Engineering & Sciences, Vol.124, No.3, pp. 865-884, 2020, DOI:10.32604/cmes.2020.010720
- Abstract This paper proposes a probabilistic life calculation method of NdFeB based on brittle fatigue damage model. Firstly, Zhu-Wang-Tang (ZWT) constitutive model considering strain rate is established, and based on this, a numerical co-simulation model for NdFeB life calculation is constructed. The life distribution diagram of NdFeB under different stress levels is obtained after simulation. Secondly, a new model of brittle fatigue damage based on brittle damage mechanism is proposed. Then the parameters in the model are identified according to the life distribution diagram of NdFeB and the parameter distribution of the damage evolution model when applied to NdFeB is obtained.… More
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- OPEN ACCESS ARTICLE
- Numerical Simulation on Oil Spilling of Submarine Pipeline and Its Evolution on Sea Surface
- CMES-Computer Modeling in Engineering & Sciences, Vol.124, No.3, pp. 885-914, 2020, DOI:10.32604/cmes.2020.09810
- Abstract Due to the interaction and corrosion of the seawater, submarine pipelines are easy to be broken to spill oil. The special environment of subsea restricts the technical development of pipeline maintenance. Therefore, the study on the oil spilling model of submarine pipeline is very important for predicting the movement and diffusion of spilled oil, so that oil spilling traces and relating strategies can be determined. This paper aims to establish an oil spilling model of a submarine pipeline, study the movement characteristics of spilled oil in seawater by numerical simulation, and determine the traces, diffusion range, time to sea surface,… More
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- OPEN ACCESS ARTICLE
- A Differential Quadrature Based Approach for Volterra Partial Integro-Differential Equation with a Weakly Singular Kernel
- CMES-Computer Modeling in Engineering & Sciences, Vol.124, No.3, pp. 915-935, 2020, DOI:10.32604/cmes.2020.011218
- Abstract Differential quadrature method is employed by numerous researchers due to its numerical accuracy and computational efficiency, and is mentioned as potential alternative of conventional numerical methods. In this paper, a differential quadrature based numerical scheme is developed for solving volterra partial integro-differential equation of second order having a weakly singular kernel. The scheme uses cubic trigonometric B-spline functions to determine the weighting coefficients in the differential quadrature approximation of the second order spatial derivative. The advantage of this approximation is that it reduces the problem to a first order time dependent integro-differential equation (IDE). The proposed scheme is obtained in… More
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Downloads:1386
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- OPEN ACCESS ARTICLE
- Milling Parameters Optimization of Al-Li Alloy Thin-Wall Workpieces Using Response Surface Methodology and Particle Swarm Optimization
- CMES-Computer Modeling in Engineering & Sciences, Vol.124, No.3, pp. 937-952, 2020, DOI:10.32604/cmes.2020.010565
- Abstract To improve the milling surface quality of the Al-Li alloy thin-wall workpieces and reduce the cutting energy consumption. Experimental research on the milling processing of AA2195 Al-Li alloy thin-wall workpieces based on Response Surface Methodology was carried out. The single factor and interaction of milling parameters on surface roughness and specific cutting energy were analyzed, and the multi-objective optimization model was constructed. The Multiobjective Particle Swarm Optimization algorithm introducing the Chaos Local Search algorithm and the adaptive inertial weight was applied to determine the optimal combination of milling parameters. It was observed that surface roughness was mainly influenced by feed… More
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Downloads:1408
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- OPEN ACCESS ARTICLE
- Planar System-Masses in an Equilateral Triangle: Numerical Study within Fractional Calculus
- CMES-Computer Modeling in Engineering & Sciences, Vol.124, No.3, pp. 953-968, 2020, DOI:10.32604/cmes.2020.010236
- Abstract In this work, a system of three masses on the vertices of equilateral triangle is investigated. This system is known in the literature as a planar system. We first give a description to the system by constructing its classical Lagrangian. Secondly, the classical Euler-Lagrange equations (i.e., the classical equations of motion) are derived. Thirdly, we fractionalize the classical Lagrangian of the system, and as a result, we obtain the fractional Euler-Lagrange equations. As the final step, we give the numerical simulations of the fractional model, a new model which is based on Caputo fractional derivative. More
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Cited by:25
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- OPEN ACCESS ARTICLE
- A Novel Analytical Technique of the Fractional Bagley-Torvik Equations for Motion of a Rigid Plate in Newtonian Fluids
- CMES-Computer Modeling in Engineering & Sciences, Vol.124, No.3, pp. 969-983, 2020, DOI:10.32604/cmes.2020.010942
- Abstract The current paper is concerned with a modified Homotopy perturbation technique. This modification allows achieving an exact solution of an initial value problem of the fractional differential equation. The approach is powerful, effective, and promising in analyzing some classes of fractional differential equations for heat conduction problems and other dynamical systems. To crystallize the new approach, some illustrated examples are introduced. More
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Views:1925
Downloads:1743
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- OPEN ACCESS ARTICLE
- Subinterval Decomposition-Based Interval Importance Analysis Method
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CMES-Computer Modeling in Engineering & Sciences, Vol.124, No.3, pp. 985-1000, 2020, DOI:10.32604/cmes.2020.09006
(This article belongs to this Special Issue: Novel Methods for Reliability Evaluation and Optimization of Complex Mechanical Structures) - Abstract The importance analysis method represents a powerful tool for quantifying the impact of input uncertainty on the output uncertainty. When an input variable is described by a specific interval rather than a certain probability distribution, the interval importance measure of input interval variable can be calculated by the traditional non-probabilistic importance analysis methods. Generally, the non-probabilistic importance analysis methods involve the Monte Carlo simulation (MCS) and the optimization-based methods, which both have high computational cost. In order to overcome this problem, this study proposes an interval important analytical method avoids the time-consuming optimization process. First, the original performance function is… More
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Downloads:1691
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- OPEN ACCESS ARTICLE
- Effect of Data Augmentation of Renal Lesion Image by Nine-layer Convolutional Neural Network in Kidney CT
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CMES-Computer Modeling in Engineering & Sciences, Vol.124, No.3, pp. 1001-1015, 2020, DOI:10.32604/cmes.2020.010753
(This article belongs to this Special Issue: Recent Advances on Deep Learning for Medical Signal Analysis (RADLMSA)) - Abstract Artificial Intelligence (AI) becomes one hotspot in the field of the medical images analysis and provides rather promising solution. Although some research has been explored in smart diagnosis for the common diseases of urinary system, some problems remain unsolved completely A nine-layer Convolutional Neural Network (CNN) is proposed in this paper to classify the renal Computed Tomography (CT) images. Four group of comparative experiments prove the structure of this CNN is optimal and can achieve good performance with average accuracy about 92.07 ± 1.67%. Although our renal CT data is not very large, we do augment the training data by… More
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Downloads:1818
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- A Hybrid Deep Learning Architecture for the Classification of Superhero Fashion Products: An Application for Medical-Tech Classification
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CMES-Computer Modeling in Engineering & Sciences, Vol.124, No.3, pp. 1017-1033, 2020, DOI:10.32604/cmes.2020.010943
(This article belongs to this Special Issue: Recent Advances on Deep Learning for Medical Signal Analysis (RADLMSA)) - Abstract Comic character detection is becoming an exciting and growing research area in the domain of machine learning. In this regard, recently, many methods are proposed to provide adequate performance. However, most of these methods utilized the custom datasets, containing a few hundred images and fewer classes, to evaluate the performances of their models without comparing it, with some standard datasets. This article takes advantage of utilizing a standard publicly dataset taken from a competition, and proposes a generic data balancing technique for imbalanced dataset to enhance and enable the in-depth training of the CNN. In addition, to classify the superheroes… More
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Downloads:1851
Cited by:8
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- OPEN ACCESS ARTICLE
- Coverless Text Hiding Method Based on Improved Evaluation Index and One-Bit Embedding
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CMES-Computer Modeling in Engineering & Sciences, Vol.124, No.3, pp. 1035-1048, 2020, DOI:10.32604/cmes.2020.010450
(This article belongs to this Special Issue: Information Hiding and Multimedia Security) - Abstract In the field of information hiding, text is less redundant, which leads to less space to hide information and challenging work for researchers. Based on the Markov chain model, this paper proposes an improved evaluation index and onebit embedding coverless text steganography method. In the steganography process, this method did not simply take the transition probability as the optimization basis of the steganography model, but combined it with the sentence length in the corresponding nodes in the model to gauge sentence quality. Based on this, only two optimal conjunctions of the current words are retained in the method to generate… More
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Views:2066
Downloads:1751
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- OPEN ACCESS ARTICLE
- Validating the Correct Wearing of Protection Mask by Taking a Selfie: Design of a Mobile Application “CheckYourMask” to Limit the Spread of COVID-19
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CMES-Computer Modeling in Engineering & Sciences, Vol.124, No.3, pp. 1049-1059, 2020, DOI:10.32604/cmes.2020.011663
(This article belongs to this Special Issue: Computer Modelling of Transmission, Spread, Control and Diagnosis of COVID-19) - Abstract In a context of a virus that is transmissive by sputtering, wearing masks appear necessary to protect the wearer and to limit the propagation of the disease. Currently, we are facing the 2019–2020 coronavirus pandemic. Coronavirus disease 2019 (COVID-19) is an infectious disease with first symptoms similar to the flu. The symptom of COVID-19 was reported first in China and very quickly spreads to the rest of the world. The COVID-19 contagiousness is known to be high by comparison with the flu. In this paper, we propose a design of a mobile application for permitting everyone having a smartphone and… More
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Downloads:16396
Cited by:3
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- OPEN ACCESS ARTICLE
- An Efficient Content-Based Image Retrieval System Using kNN and Fuzzy Mathematical Algorithm
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CMES-Computer Modeling in Engineering & Sciences, Vol.124, No.3, pp. 1061-1083, 2020, DOI:10.32604/cmes.2020.010198
(This article belongs to this Special Issue: Security Enhancement of Image Recognition System in IoT based Smart Cities) - Abstract The implementation of content-based image retrieval (CBIR) mainly depends on two key technologies: image feature extraction and image feature matching. In this paper, we extract the color features based on Global Color Histogram (GCH) and texture features based on Gray Level Co-occurrence Matrix (GLCM). In order to obtain the effective and representative features of the image, we adopt the fuzzy mathematical algorithm in the process of color feature extraction and texture feature extraction respectively. And we combine the fuzzy color feature vector with the fuzzy texture feature vector to form the comprehensive fuzzy feature vector of the image according to… More
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Views:1844
Downloads:1587
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- OPEN ACCESS ARTICLE
- Thermodynamics of Molten Pool Predicted by Computational Fluid Dynamics in Selective Laser Melting of Ti6Al4V: Surface Morphology Evolution and Densification Behavior
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CMES-Computer Modeling in Engineering & Sciences, Vol.124, No.3, pp. 1085-1098, 2020, DOI:10.32604/cmes.2020.010927
(This article belongs to this Special Issue: Design & simulation in Additive Manufacturing) - Abstract The three-dimensional physical model of the randomly packed powder material irradiated by the laser beam was established, taking into account the transformation of the material phase, the melt spreading and the interaction of the free surface of the molten pool and the recoiling pressure caused by the material evaporation during the selective laser melting. Influence of the processing parameters on the thermal behavior, the material evaporation, the surface morphology and the densification behavior in the connection region of the molten pool and the substrate was studied. It was shown that the powder material underwent the transformation from the partial melting… More
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- OPEN ACCESS ARTICLE
- Design and Manufacture of Bionic Porous Titanium Alloy Spinal Implant Based on Selective Laser Melting (SLM)
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CMES-Computer Modeling in Engineering & Sciences, Vol.124, No.3, pp. 1099-1117, 2020, DOI:10.32604/cmes.2020.09619
(This article belongs to this Special Issue: Design & simulation in Additive Manufacturing) - Abstract In order to meet the clinical requirements of spine surgery, this paper proposed the exploratory research of computer-aided design and selective laser melting (SLM) fabrication of a bionic porous titanium spine implant. The structural design of the spinal implant is based on CT scanning data to ensure correct matching, and the mechanical properties of the implant are verified by simulation analysis and laser selective melting experiment. The surface roughness of the spinal implant manufactured by SLM without post-processing is Ra 15 μm, and the implant is precisely jointed with the photosensitive resin model of the upper and lower spine. The… More
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- A Reinforcement Learning System for Fault Detection and Diagnosis in Mechatronic Systems
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CMES-Computer Modeling in Engineering & Sciences, Vol.124, No.3, pp. 1119-1130, 2020, DOI:10.32604/cmes.2020.010986
(This article belongs to this Special Issue: Machine Learning based Methods for Mechanics) - Abstract With the increasing demand for the automation of operations and processes in mechatronic systems, fault detection and diagnosis has become a major topic to guarantee the process performance. There exist numerous studies on the topic of applying artificial intelligence methods for fault detection and diagnosis. However, much of the focus has been given on the detection of faults. In terms of the diagnosis of faults, on one hand, assumptions are required, which restricts the diagnosis range. On the other hand, different faults with similar symptoms cannot be distinguished, especially when the model is not trained by plenty of data. In… More
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Downloads:2751
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- Soft Tissue Deformation Model Based on Marquardt Algorithm and Enrichment Function
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CMES-Computer Modeling in Engineering & Sciences, Vol.124, No.3, pp. 1131-1147, 2020, DOI:10.32604/cmes.2020.09735
(This article belongs to this Special Issue: Computer Methods in Bio-mechanics and Biomedical Engineering) - Abstract In order to solve the problem of high computing cost and low simulation accuracy caused by discontinuity of incision in traditional meshless model, this paper proposes a soft tissue deformation model based on the Marquardt algorithm and enrichment function. The model is based on the element-free Galerkin method, in which Kelvin viscoelastic model and adjustment function are integrated. Marquardt algorithm is applied to fit the relation between force and displacement caused by surface deformation, and the enrichment function is applied to deal with the discontinuity in the meshless method. To verify the validity of the model, the Sensable Phantom Omni… More
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Views:2200
Downloads:1786
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- OPEN ACCESS ARTICLE
- Threshold-Based Adaptive Gaussian Mixture Model Integration (TA-GMMI) Algorithm for Mapping Snow Cover in Mountainous Terrain
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CMES-Computer Modeling in Engineering & Sciences, Vol.124, No.3, pp. 1149-1165, 2020, DOI:10.32604/cmes.2020.010932
(This article belongs to this Special Issue: Intelligent Models for Security and Resilience in Cyber Physical Systems) - Abstract Snow cover is an important parameter in the fields of computer modeling, engineering technology and energy development. With the extensive growth of novel hardware and software compositions creating smart, cyber physical systems’ (CPS) efficient end-to-end workflows. In order to provide accurate snow detection results for the CPS’s terminal, this paper proposed a snow cover detection algorithm based on the unsupervised Gaussian mixture model (GMM) for the FY-4A satellite data. At present, most snow cover detection algorithms mainly utilize the characteristics of the optical spectrum, which is based on the normalized difference snow index (NDSI) with thresholds in different wavebands. These… More
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Views:2172
Downloads:1796
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