Home / Journals / CMES / Vol.125, No.1, 2020
Table of Content
  • Open Access

    REVIEW

    Nanomechanics and Ultrastructure of Bone: A Review

    Mohammad Maghsoudi-Ganjeh, Xiaodu Wang*, Xiaowei Zeng*
    CMES-Computer Modeling in Engineering & Sciences, Vol.125, No.1, pp. 1-32, 2020, DOI:10.32604/cmes.2020.012123
    Abstract In this review, a brief presentation is first given to the hierarchical structure and mechanical behavior of bone. Then, the recent advancements in nanoscale characterization of bone ultrastructure and ingredients are discussed based on an extensive quantity of references in the literature.Moreover, computational and analytical bone mechanics at ultrastructure levels are critically reviewed with the growing body of knowledge in the field. The computational and analytical models are summarized in several categories for ease of understanding bone nanomechanics and their applicability/limitations. This review is expected to provide a well-informed foundation for the researchers interested in interrogating the complex biomechanical response… More >

  • Open Access

    ARTICLE

    Online AUV Path Replanning Using Quantum-Behaved Particle Swarm Optimization with Selective Differential Evolution

    Hui Sheng Lim1,*, Christopher K. H. Chin1, Shuhong Chai1, Neil Bose1,2
    CMES-Computer Modeling in Engineering & Sciences, Vol.125, No.1, pp. 33-50, 2020, DOI:10.32604/cmes.2020.011648
    Abstract This paper presents an online AUV (autonomous underwater vehicle) path planner that employs path replanning approach and the SDEQPSO (selective differential evolution-hybridized quantum-behaved particle swarm optimization) algorithm to optimize an AUV mission conducted in an unknown, dynamic and cluttered ocean environment. The proposed path replanner considered the effect of ocean currents in path optimization to generate a Pareto-optimal path that guides the AUV to its target within minimum time. The optimization was based on the onboard sensor data measured from the environment, which consists of a priori unknown dynamic obstacles and spatiotemporal currents. Different sensor arrangements for the forward-looking sonar… More >

  • Open Access

    ARTICLE

    Modelling Strategy and Parametric Study of Metal Gaskets for Automotive Applications

    Fabio Bruzzone, Cristiana Delprete, Carlo Rosso*
    CMES-Computer Modeling in Engineering & Sciences, Vol.125, No.1, pp. 51-64, 2020, DOI:10.32604/cmes.2020.011023
    Abstract This paper is focused on finite element simulation of cylinder head gaskets. Finite element codes support several methodologies, each of which has its own strengths and weaknesses. One of the key points lies in the influence of the gasket geometry on its final behaviour. Such a contribution can come from the detailed modelling of the gasket or by defining a global non-linear behaviour in which material and geometry non-linearities are summarised. Two approaches were used to simulate the gasket behaviour. The first one consists in using a 2D approach, which allows to model through-thickness non-linear behaviour of gasket. The second… More >

  • Open Access

    ARTICLE

    Ziegler–Nichols Customization for Quadrotor Attitude Control under Empty and Full Loading Conditions

    Ivan Paulo Canal1,*, Manuel Martin Pérez Reimbold2, Maurício de Campos2
    CMES-Computer Modeling in Engineering & Sciences, Vol.125, No.1, pp. 65-75, 2020, DOI:10.32604/cmes.2020.010741
    Abstract An aircraft quadrotor is a complex control system that allows for great flexibility in flight. Controlling multirotor aerial systems such as quadrotors is complex because the variables involved are not always available, known, and accurate. The inclusion of payload changes the dynamic characteristics of the aircraft, making it necessary to adapt the control system for this situation. Among the various control methods that have been investigated, proportional-integralderivative (PID) control offers good results and simplicity of application; however, achieving stability and high performance is challenging, with the most critical task being tuning the controller gains. The Ziegler–Nichols (ZN) theory was used… More >

  • Open Access

    ARTICLE

    Periodic Lattice Porous Structure Produced by Selective Laser Melting: Process, Experiment and Numerical Simulation Analysis

    Jianrui Zhang1,2, Min Chi1, Bo Qian1,*, Zhijun Qiu2
    CMES-Computer Modeling in Engineering & Sciences, Vol.125, No.1, pp. 77-94, 2020, DOI:10.32604/cmes.2020.010518
    Abstract To accurately perform the coupled simulation of temperature field and stress field of complex parts and porous structures under the optimal manufacturing process parameters, three kinds of porous structures with different complexity were designed in this paper. Firstly, ANSYS additive software was used to conduct the stress/deformation simulation of the whole structure under different scanning strategies. Secondly, the optimal scanning strategy for different porous structures was determined, then the experimental preparation was performed, and mechanical properties of compression were tested and studied. The results show that the elastic modulus and yield strength increase with the increase of pole diameter/wall thickness.… More >

  • Open Access

    ARTICLE

    Short-Term Traffic Flow Prediction Based on LSTM-XGBoost Combination Model

    Xijun Zhang*, Qirui Zhang
    CMES-Computer Modeling in Engineering & Sciences, Vol.125, No.1, pp. 95-109, 2020, DOI:10.32604/cmes.2020.011013
    Abstract According to the time series characteristics of the trajectory history data, we predicted and analyzed the traffic flow. This paper proposed a LSTMXGBoost model based urban road short-term traffic flow prediction in order to analyze and solve the problems of periodicity, stationary and abnormality of time series. It can improve the traffic flow prediction effect, achieve efficient traffic guidance and traffic control. The model combined the characteristics of LSTM (Long Short-Term Memory) network and XGBoost (Extreme Gradient Boosting) algorithms. First, we used the LSTM model that increases dropout layer to train the data set after preprocessing. Second, we replaced the… More >

  • Open Access

    ARTICLE

    Prediction of Intrinsically Disordered Proteins with a Low Computational Complexity Method

    Jia Yang1, Haiyuan Liu1,*, Hao He2
    CMES-Computer Modeling in Engineering & Sciences, Vol.125, No.1, pp. 111-123, 2020, DOI:10.32604/cmes.2020.010347
    Abstract The prediction of intrinsically disordered proteins is a hot research area in bio-information. Due to the high cost of experimental methods to evaluate disordered regions of protein sequences, it is becoming increasingly important to predict those regions through computational methods. In this paper, we developed a novel scheme by employing sequence complexity to calculate six features for each residue of a protein sequence, which includes the Shannon entropy, the topological entropy, the sample entropy and three amino acid preferences including Remark 465, Deleage/Roux, and Bfactor(2STD). Particularly, we introduced the sample entropy for calculating time series complexity by mapping the amino… More >

  • Open Access

    ARTICLE

    Deep Residual Network Based on Image Priors for Single Image Super Resolution in FFA Images

    G. R. Hemalakshmi*, D. Santhi, V. R. S. Mani, A. Geetha, N. B. Prakash
    CMES-Computer Modeling in Engineering & Sciences, Vol.125, No.1, pp. 125-143, 2020, DOI:10.32604/cmes.2020.011331
    Abstract Diabetic retinopathy, aged macular degeneration, glaucoma etc. are widely prevalent ocular pathologies which are irreversible at advanced stages. Machine learning based automated detection of these pathologies facilitate timely clinical interventions, preventing adverse outcomes. Ophthalmologists screen these pathologies with fundus Fluorescein Angiography Images (FFA) which capture retinal components featuring diverse morphologies such as retinal vasculature, macula, optical disk etc. However, these images have low resolutions, hindering the accurate detection of ocular disorders. Construction of high resolution images from these images, by super resolution approaches expedites the diagnosis of pathologies with better accuracy. This paper presents a deep learning network for Single… More >

  • Open Access

    ARTICLE

    Simulation Analysis on Mechanical Property Characterization of Carbon Nanotubes Reinforced Epoxy Composites

    Dan Li1, Li Ding1, Zhengang Liu2, Qiang Li3, Kaiyun Guo1, Hailin Cao1,4,*
    CMES-Computer Modeling in Engineering & Sciences, Vol.125, No.1, pp. 145-171, 2020, DOI:10.32604/cmes.2020.010822
    Abstract Carbon nanotube (CNT)-reinforced composites have ultra-high elastic moduli, low densities, and fibrous structures. This paper presents the multi-scale finite element modeling of CNT-reinforced polymer composites from micro- to macro-scales. The nanocomposites were modeled using representative volume elements (RVEs), and finite element code was written to simulate the modeling and loading procedure and obtain equivalent mechanical properties of the RVEs with various volume fractions of CNTs, which can be used directly in the follow-up simulation studies on the macroscopic model of CNT-reinforced nanocomposites. When using the programming to simulate the deformation and fracture process of the CNT-reinforced epoxy composites, the mechanical… More >

  • Open Access

    ARTICLE

    The Efficient Finite Element Methods for Time-Fractional Oldroyd-B Fluid Model Involving Two Caputo Derivatives

    An Chen*
    CMES-Computer Modeling in Engineering & Sciences, Vol.125, No.1, pp. 173-195, 2020, DOI:10.32604/cmes.2020.011871
    Abstract In this paper, we consider the numerical schemes for a timefractional Oldroyd-B fluid model involving the Caputo derivative. We propose two efficient finite element methods by applying the convolution quadrature in time generated by the backward Euler and the second-order backward difference methods. Error estimates in terms of data regularity are established for both the semidiscrete and fully discrete schemes. Numerical examples for two-dimensional problems further confirm the robustness of the schemes with first- and second-order accurate in time. More >

  • Open Access

    ARTICLE

    A Novel Binary Firey Algorithm for the Minimum Labeling Spanning Tree Problem

    Mugang Lin1,2,*, Fangju Liu3, Huihuang Zhao1,2, Jianzhen Chen1,2
    CMES-Computer Modeling in Engineering & Sciences, Vol.125, No.1, pp. 197-214, 2020, DOI:10.32604/cmes.2020.09502
    Abstract Given a connected undirected graph G whose edges are labeled, the minimum labeling spanning tree (MLST) problem is to find a spanning tree of G with the smallest number of different labels. The MLST is an NP-hard combinatorial optimization problem, which is widely applied in communication networks, multimodal transportation networks, and data compression. Some approximation algorithms and heuristics algorithms have been proposed for the problem. Firey algorithm is a new meta-heuristic algorithm. Because of its simplicity and easy implementation, it has been successfully applied in various fields. However, the basic firefly algorithm for the MLST problem is proposed in this… More >

  • Open Access

    ARTICLE

    Exploring the Abnormal Brain Regions and Abnormal Functional Connections in SZ by Multiple Hypothesis Testing Techniques

    Lan Yang1, Shun Qi2,3,#, Chen Qiao1,*, Yanmei Kang1
    CMES-Computer Modeling in Engineering & Sciences, Vol.125, No.1, pp. 215-237, 2020, DOI:10.32604/cmes.2020.010796
    (This article belongs to this Special Issue: Data Science and Modeling in Biology, Health, and Medicine)
    Abstract Schizophrenia (SZ) is one of the most common mental diseases. Its main characteristics are abnormal social behavior and inability to correctly understand real things. In recent years, the magnetic resonance imaging (MRI) technique has been popularly utilized to study SZ. However, it is still a great challenge to reveal the essential information contained in the MRI data. In this paper, we proposed a biomarker selection approach based on the multiple hypothesis testing techniques to explore the difference between SZ and healthy controls by using both functional and structural MRI data, in which biomarkers represent both abnormal brain functional connectivity and… More >

  • Open Access

    ARTICLE

    Performance Analysis of Intelligent CR-NOMA Model for Industrial IoT Communications

    Yinghua Zhang1,2, Jian Liu1, Yunfeng Peng1, Yanfang Dong2, Changming Zhao3,*
    CMES-Computer Modeling in Engineering & Sciences, Vol.125, No.1, pp. 239-257, 2020, DOI:10.32604/cmes.2020.010778
    (This article belongs to this Special Issue: Intelligent Models for Security and Resilience in Cyber Physical Systems)
    Abstract Aiming for ultra-reliable low-latency wireless communications required in industrial internet of things (IIoT) applications, this paper studies a simple cognitive radio non-orthogonal multiple access (CR-NOMA) downlink system. This system consists of two secondary users (SUs) dynamically interfered by the primary user (PU), and its performance is characterized by the outage probability of the SU communications. This outage probability is calculated under two conditions where, a) the transmission of PU starts after the channel state information (CSI) is acquired, so the base station (BS) is oblivious of the interference, and b) when the BS is aware of the PU interference, and… More >

  • Open Access

    ARTICLE

    Effect of Hole Density and Confining Pressure on Mechanical Behavior of Porous Specimens: An Insight from Discrete Element Modeling

    Yuanchao Zhang1, Zhiyuan Xia2,*, Yujing Jiang1, Miao Chen3, Jiankang Liu1, Qian Yin4
    CMES-Computer Modeling in Engineering & Sciences, Vol.125, No.1, pp. 259-280, 2020, DOI:10.32604/cmes.2020.011076
    (This article belongs to this Special Issue: Modeling and Simulation of Fluid flows in Fractured Porous Media: Current Trends and Prospects)
    Abstract Hole-like defects are very common in natural rock or coal mass, and play an important role in the failure and mechanical behaviors of rock or coal mass. In this research, multi-holed coal specimens are constructed numerically and calibrated based on UDEC-GBM models. Then, the strength, deformation and failure behavior of the porous specimens are analyzed, with consideration of hole density (P) and confining pressure (σ3). The simulation results are highly consistent with those available experiment results, and show that the compressive strength decreases exponentially with the increasing hole density. The strength loss is mainly caused by the reduction of cohesion… More >

  • Open Access

    ARTICLE

    An Emotion Analysis Method Using Multi-Channel Convolution Neural Network in Social Networks

    Xinxin Lu1,*, Hong Zhang2
    CMES-Computer Modeling in Engineering & Sciences, Vol.125, No.1, pp. 281-297, 2020, DOI:10.32604/cmes.2020.010948
    (This article belongs to this Special Issue: Recent Advances on Deep Learning for Medical Signal Analysis (RADLMSA))
    Abstract As an interdisciplinary comprehensive subject involving multidisciplinary knowledge, emotional analysis has become a hot topic in psychology, health medicine and computer science. It has a high comprehensive and practical application value. Emotion research based on the social network is a relatively new topic in the field of psychology and medical health research. The text emotion analysis of college students also has an important research significance for the emotional state of students at a certain time or a certain period, so as to understand their normal state, abnormal state and the reason of state change from the information they wrote. In… More >

  • Open Access

    ARTICLE

    Least-Square Support Vector Machine and Wavelet Selection for Hearing Loss Identification

    Chaosheng Tang1, Deepak Ranjan Nayak2, Shuihua Wang1,3,4,*
    CMES-Computer Modeling in Engineering & Sciences, Vol.125, No.1, pp. 299-313, 2020, DOI:10.32604/cmes.2020.011069
    (This article belongs to this Special Issue: Recent Advances on Deep Learning for Medical Signal Analysis (RADLMSA))
    Abstract Hearing loss (HL) is a kind of common illness, which can significantly reduce the quality of life. For example, HL often results in mishearing, misunderstanding, and communication problems. Therefore, it is necessary to provide early diagnosis and timely treatment for HL. This study investigated the advantages and disadvantages of three classical machine learning methods: multilayer perceptron (MLP), support vector machine (SVM), and least-square support vector machine (LS-SVM) approach and made a further optimization of the LS-SVM model via wavelet entropy. The investigation illustrated that themultilayer perceptron is a shallowneural network,while the least square support vector machine uses hinge loss function… More >

  • Open Access

    REVIEW

    Importance of Features Selection, Attributes Selection, Challenges and Future Directions for Medical Imaging Data: A Review

    Nazish Naheed1, Muhammad Shaheen1, Sajid Ali Khan1, Mohammed Alawairdhi2,*, Muhammad Attique Khan3,*
    CMES-Computer Modeling in Engineering & Sciences, Vol.125, No.1, pp. 315-344, 2020, DOI:10.32604/cmes.2020.011380
    (This article belongs to this Special Issue: Recent Advances on Deep Learning for Medical Signal Analysis (RADLMSA))
    Abstract In the area of pattern recognition and machine learning, features play a key role in prediction. The famous applications of features are medical imaging, image classification, and name a few more. With the exponential growth of information investments in medical data repositories and health service provision, medical institutions are collecting large volumes of data. These data repositories contain details information essential to support medical diagnostic decisions and also improve patient care quality. On the other hand, this growth also made it difficult to comprehend and utilize data for various purposes. The results of imaging data can become biased because of… More >

  • Open Access

    ARTICLE

    A Multi-View Gait Recognition Method Using Deep Convolutional Neural Network and Channel Attention Mechanism

    Jiabin Wang*, Kai Peng
    CMES-Computer Modeling in Engineering & Sciences, Vol.125, No.1, pp. 345-363, 2020, DOI:10.32604/cmes.2020.011046
    (This article belongs to this Special Issue: Recent Advances on Deep Learning for Medical Signal Analysis (RADLMSA))
    Abstract In many existing multi-view gait recognition methods based on images or video sequences, gait sequences are usually used to superimpose and synthesize images and construct energy-like template. However, information may be lost during the process of compositing image and capture EMG signals. Errors and the recognition accuracy may be introduced and affected respectively by some factors such as period detection. To better solve the problems, a multi-view gait recognition method using deep convolutional neural network and channel attention mechanism is proposed. Firstly, the sliding time window method is used to capture EMG signals. Then, the back-propagation learning algorithm is used… More >

  • Open Access

    ARTICLE

    PDNet: A Convolutional Neural Network Has Potential to be Deployed on Small Intelligent Devices for Arrhythmia Diagnosis

    Fei Yang1,2,#, Xiaoqing Zhang1,*,#, Yong Zhu3
    CMES-Computer Modeling in Engineering & Sciences, Vol.125, No.1, pp. 365-382, 2020, DOI:10.32604/cmes.2020.010798
    (This article belongs to this Special Issue: Recent Advances on Deep Learning for Medical Signal Analysis (RADLMSA))
    Abstract Heart arrhythmia is a group of irregular heartbeat conditions and is usually detected by electrocardiograms (ECG) signals. Over the past years, deep learning methods have been developed to classify different types of heart arrhythmias through ECG based on computer-aided diagnosis systems (CADs), but these deep learning methods usually cannot trade-off between classification performance and parameters of deep learning methods. To tackle this problem, this work proposes a convolutional neural network (CNN) model named PDNet to recognize different types of heart arrhythmias efficiently. In the PDNet, a convolutional block named PDblock is devised, which is comprised of a pointwise convolutional layer… More >

  • Open Access

    ARTICLE

    Robust Design Optimization and Improvement by Metamodel

    Shufang Song*, Lu Wang, Yuhua Yan
    CMES-Computer Modeling in Engineering & Sciences, Vol.125, No.1, pp. 383-399, 2020, DOI:10.32604/cmes.2020.09588
    (This article belongs to this Special Issue: Novel Methods for Reliability Evaluation and Optimization of Complex Mechanical Structures)
    Abstract The robust design optimization (RDO) is an effective method to improve product performance with uncertainty factors. The robust optimal solution should be not only satisfied the probabilistic constraints but also less sensitive to the variation of design variables. There are some important issues in RDO, such as how to judge robustness, deal with multi-objective problem and black-box situation. In this paper, two criteria are proposed to judge the deterministic optimal solution whether satisfies robustness requirment. The robustness measure based on maximum entropy is proposed. Weighted sum method is improved to deal with the objective function, and the basic framework of… More >

  • Open Access

    ARTICLE

    Research on Trajectory Tracking Method of Redundant Manipulator Based on PSO Algorithm Optimization

    Shifu Xu*, Yanan Jiang
    CMES-Computer Modeling in Engineering & Sciences, Vol.125, No.1, pp. 401-415, 2020, DOI:10.32604/cmes.2020.09608
    (This article belongs to this Special Issue: Novel Methods for Reliability Evaluation and Optimization of Complex Mechanical Structures)
    Abstract Aiming at the problem that the trajectory tracking performance of redundant manipulator corresponding to the target position is difficult to optimize, the trajectory tracking method of redundant manipulator based on PSO algorithm optimization is studied. The kinematic diagram of redundant manipulator is created, to derive the equation of motion trajectory of redundant manipulator end. Pseudo inverse Jacobi matrix is used to solve the problem of manipulator redundancy. Based on the tracking ellipse of redundant manipulator, the tracking shape of redundant manipulator is determined with the overall tracking index as the second index, and the optimization method of tracking index is… More >

  • Open Access

    ARTICLE

    Multiple Images Steganography of JPEG Images Based on Optimal Payload Distribution

    Yang Pei1,2, Xiangyang Luo1,2,*, Yi Zhang2, Liyan Zhu2
    CMES-Computer Modeling in Engineering & Sciences, Vol.125, No.1, pp. 417-436, 2020, DOI:10.32604/cmes.2020.010636
    (This article belongs to this Special Issue: Information Hiding and Multimedia Security)
    Abstract Multiple images steganography refers to hiding secret messages in multiple natural images to minimize the leakage of secret messages during transmission. Currently, the main multiple images steganography algorithms mainly distribute the payloads as sparsely as possible in multiple cover images to improve the detection error rate of stego images. In order to enable the payloads to be accurately and efficiently distributed in each cover image, this paper proposes a multiple images steganography for JPEG images based on optimal payload redistribution. Firstly, the algorithm uses the principle of dynamic programming to redistribute the payloads of the cover images to reduce the… More >

  • Open Access

    ARTICLE

    Topp-Leone Odd Fréchet Generated Family of Distributions with Applications to COVID-19 Data Sets

    Sanaa Al-Marzouki1, Farrukh Jamal2, Christophe Chesneau3,*, Mohammed Elgarhy4
    CMES-Computer Modeling in Engineering & Sciences, Vol.125, No.1, pp. 437-458, 2020, DOI:10.32604/cmes.2020.011521
    (This article belongs to this Special Issue: Computer Modelling of Transmission, Spread, Control and Diagnosis of COVID-19)
    Abstract Recent studies have pointed out the potential of the odd Fréchet family (or class) of continuous distributions in fitting data of all kinds. In this article, we propose an extension of this family through the so-called “Topp-Leone strategy”, aiming to improve its overall flexibility by adding a shape parameter. The main objective is to offer original distributions with modifiable properties, from which adaptive and pliant statistical models can be derived. For the new family, these aspects are illustrated by the means of comprehensive mathematical and numerical results. In particular, we emphasize a special distribution with three parameters based on the… More >

Share Link

WeChat scan