To date, intelligent algorithms for topology optimization have been extensively studied to reduce the cost of calculation. In the article, a feature pyramid network is built with physical constraints to accelerate the design of topology optimization. A model with physical constraints not only guarantees high precision but also has better physical performance than a model without physical constraints.
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Jiaxiang Luo1,2, Yu Li2, Weien Zhou2, Zhiqiang Gong2, Zeyu Zhang1, Wen Yao2,*
CMES-Computer Modeling in Engineering & Sciences, Vol.128, No.3, pp. 823-848, 2021, DOI:10.32604/cmes.2021.016737
(This article belongs to this Special Issue: Novel Methods of Topology Optimization and Engineering Applications)
Abstract Deep learning for topology optimization has been extensively studied to reduce the cost of calculation in recent years. However, the loss function of the above method is mainly based on pixel-wise errors from the image perspective, which cannot embed the physical knowledge of topology optimization. Therefore, this paper presents an improved deep learning model to alleviate the above difficulty effectively. The feature pyramid network (FPN), a kind of deep learning model, is trained to learn the inherent physical law of topology optimization itself, of which the loss function is composed of pixel-wise errors and physical constraints. Since the calculation of… More >
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D. A. Makhloof, A. R. Ibrahim, Xiaodan Ren*
CMES-Computer Modeling in Engineering & Sciences, Vol.128, No.3, pp. 849-874, 2021, DOI:10.32604/cmes.2021.016882
Abstract Due to the developments of computer science and technology in recent years, computer models and numerical
simulations for large and complicated structures can be done. Among the vast information and results obtained
from the analysis and simulations, the damage performance is of great importance since this damage might cause
enormous losses for society and humanity, notably in cases of severe damage occurring. One of the most effective
tools to handle the results about the damage performance of the structure is the damage index (DI) together
with the damage states, which are used to correlate the damage indices with the damage… More >
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REVIEW
Revathi Jothiramalingam1, Anitha Jude2, Duraisamy Jude Hemanth2,*
CMES-Computer Modeling in Engineering & Sciences, Vol.128, No.3, pp. 875-906, 2021, DOI: 10.32604/cmes.2021.016485
Abstract The 12-lead ECG aids in the diagnosis of myocardial infarction and is helpful in the prediction of cardiovascular
disease complications. It does, though, have certain drawbacks. For other electrocardiographic anomalies such as
Left Bundle Branch Block and Left Ventricular Hypertrophy syndrome, the ECG signal with Myocardial Infarction
is difficult to interpret. These diseases cause variations in the ST portion of the ECG signal. It reduces the clarity of
ECG signals, making it more difficult to diagnose these diseases. As a result, the specialist is misled into making an
erroneous diagnosis by using the incorrect therapeutic technique. Based on these concepts,… More >
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Ibrahim M. Almanjahie1,2,*, Javid Gani Dar3, Amer Ibrahim Al-Omari4, Aijaz Mir5
CMES-Computer Modeling in Engineering & Sciences, Vol.128, No.3, pp. 907-925, 2021, DOI:10.32604/cmes.2021.014896
(This article belongs to this Special Issue: Intelligent Computing for Engineering Applications)
Abstract Many researchers measure the uncertainty of a random variable using quantile-based entropy techniques. These
techniques are useful in engineering applications and have some exceptional characteristics than their distribution
function method. Considering order statistics, the key focus of this article is to propose new quantile-based
Mathai-Haubold entropy and investigate its characteristics. The divergence measure of the Mathai-Haubold is also
considered and some of its properties are established. Further, based on order statistics, we propose the residual
entropy of the quantile-based Mathai-Haubold and some of its property results are proved. The performance of
the proposed quantile-based Mathai-Haubold entropy is investigated by simulation… More >
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Sultan Alamri1,*, Kartini Nurfalah2, Kiki Adhinugraha3
CMES-Computer Modeling in Engineering & Sciences, Vol.128, No.3, pp. 927-948, 2021, DOI:10.32604/cmes.2021.014852
Abstract An indoor trajectory is the path of an object moving through corridors and stairs inside a building. There are various types of technologies that can be used to reconstruct the path of a moving object and detect its position. GPS has been used for reconstruction in outdoor environments, but for indoor environments, mobile devices with embedded sensors are used. An accelerometer sensor and a magnetometer sensor are used to detect human movement and reconstruct the trajectory on a single floor. In an indoor environment, there are many activities that will create the trajectory similar to an outdoor environment, such as… More >
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Rina Okuyama1, Naoto Mitsume2, Hideki Fujii1, Hideaki Uchida1,*
CMES-Computer Modeling in Engineering & Sciences, Vol.128, No.3, pp. 949-965, 2021, DOI:10.32604/cmes.2021.015773
Abstract As the number of automobiles continues to increase year after year, the associated problem of traffic congestion has become a serious societal issue. Initiatives to mitigate this problem have considered methods for optimizing traffic volumes in wide-area road networks, and traffic-flow simulation has become a focus of interest as a technique for advance characterization of such strategies. Classes of models commonly used for traffic-flow simulations include microscopic models based on discrete vehicle representations, macroscopic models that describe entire traffic-flow systems in terms of average vehicle densities and velocities, and mesoscopic models and hybrid (or multiscale) models incorporating both microscopic and… More >
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Ying Wang*, Haoran Shi, Shibo Ren
CMES-Computer Modeling in Engineering & Sciences, Vol.128, No.3, pp. 967-983, 2021, DOI:10.32604/cmes.2021.015792
Abstract The corrosion of reinforcement in the concrete will cause the effective cross-sectional area of reinforcement to be weakened and the performance of reinforcement to change and lead to the degradation of the bond behavior between reinforcement and concrete, which can seriously affect the mechanical properties of the structural elements. Therefore, it is of great practical significance to accurately simulate the corrosion morphology and the corrosion products of reinforcement. This paper improves the previous cellular automata models and establishes a new cellular automata model framework for simulating the random pitting corrosion process of reinforcement in concrete. This model defines the detailed… More >
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Chaowei Lin1,#, Feifei Lee1,#,*, Jiawei Cai1, Hanqing Chen1, Qiu Chen2,*
CMES-Computer Modeling in Engineering & Sciences, Vol.128, No.3, pp. 985-1006, 2021, DOI:10.32604/cmes.2021.014522
Abstract Scene recognition is a fundamental task in computer vision, which generally includes three vital stages, namely feature extraction, feature transformation and classification. Early research mainly focuses on feature extraction, but with the rise of Convolutional Neural Networks (CNNs), more and more feature transformation methods are proposed based on CNN features. In this work, a novel feature transformation algorithm called Graph Encoded Local Discriminative Region Representation (GEDRR) is proposed to find discriminative local representations for scene images and explore the relationship between the discriminative regions. In addition, we propose a method using the multi-head attention module to enhance and fuse convolutional… More >
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Jianchen Wu1, Yujie Guo1,*, Fangli Wang1,2
CMES-Computer Modeling in Engineering & Sciences, Vol.128, No.3, pp. 1007-1031, 2021, DOI:10.32604/cmes.2021.016475
Abstract Spacecraft flexible appendages may experience thermally induced vibrations (TIV) under sudden heating loads, which in consequence will be unable to complete their intended missions. Isogeometric analysis (IGA) utilizes, in an isoparametric concept, the same high order and high continuity non-uniform rational B-splines (NURBS) to represent both the geometry and the physical field of the structure. Compared to the traditional Lagrange polynomial based finite element method where only C0-continuity across elements can be achieved, IGA is geometrically exact and naturally fulfills the C1-continuity requirement of Euler–Bernoulli (EB) beam elements, therefore, does not need extra rotational degrees-of-freedom. In this paper, we present… More >
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Abidhan Bardhan1, Priyadip Manna1, Vinay Kumar1, Avijit Burman1, Bojan Žlender2, Pijush Samui1,*
CMES-Computer Modeling in Engineering & Sciences, Vol.128, No.3, pp. 1033-1067, 2021, DOI:10.32604/cmes.2021.015885
Abstract In many civil engineering projects, Piled Raft Foundations (PRFs) are usually preferred where the incoming load from the superstructures is very high. In geotechnical engineering practice, the settlement of soil layers is a critical issue for the serviceability of the structures. Thus, assessment of risk associated with the structures corresponding to the maximum allowable settlement of soils needs to be carried out in the design phase. In this study, reliability analysis of PRF based on settlement criteria is performed using a high-performance hybrid soft computing model. The new approach is an integration of the artificial neural network (ANN) and a… More >
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ARTICLE
Liping Yan1,*, Wei-Chiang Hong2
CMES-Computer Modeling in Engineering & Sciences, Vol.128, No.3, pp. 1069-1102, 2021, DOI:10.32604/cmes.2021.016499
(This article belongs to this Special Issue: Hybrid Intelligent Methods for Forecasting in Resources and Energy Field)
Abstract The timely and effective investment risk assessment and forecasting are of great significance to ensure the investment safety and sustainable development of wind energy along the Belt and Road. In order to obtain the scientific
and real-time forecasting result, this paper constructs a novel hybrid intelligent model based on improved cloud
model combined with GRA-TOPSIS and MBA-WLSSVM. Firstly, the factors influencing investment risk of wind
energy along the Belt and Road are identified from three dimensions: endogenous risk, exogenous risk and process
risk. Through the fuzzy threshold method, the final input index system is selected. Secondly, the risk evaluation
method… More >
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Ming-Chih Chen, Yin-Ting Cheng*, Ru-Wei Chen
CMES-Computer Modeling in Engineering & Sciences, Vol.128, No.3, pp. 1103-1119, 2021, DOI:10.32604/cmes.2021.015589
(This article belongs to this Special Issue: Hybrid Intelligent Methods for Forecasting in Resources and Energy Field)
Abstract This work presents a fall detection system based on artificial intelligence. The system incorporates miniature wearable devices for fall detection. Fall detection is achieved by integrating a three-axis gyroscope and a three-axis accelerometer. The system gathers the differential data collected by the gyroscope and accelerometer, applies artificial intelligence algorithms for model training and constructs an effective model for fall detection. To provide easy wearing and effective position detection, it is designed as a small device attached to the user’s waist. Experiment results have shown that the accuracy of the proposed fall detection model is up to 98%, demonstrating the effectiveness… More >
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ARTICLE
Taekyun Kim1,*, Dae San Kim2, Dmitry V. Dolgy3, Si-Hyeon Lee1, Jongkyum Kwon4,*
CMES-Computer Modeling in Engineering & Sciences, Vol.128, No.3, pp. 1121-1132, 2021, DOI:10.32604/cmes.2021.016532
(This article belongs to this Special Issue: Trend Topics in Special Functions and Polynomials: Theory, Methods, Applications and Modeling)
Abstract We introduce the higher-order type 2 Bernoulli numbers and polynomials of the second kind. In this paper, we
investigate some identities and properties for them in connection with central factorial numbers of the second
kind and the higher-order type 2 Bernoulli polynomials. We give some relations between the higher-order type 2
Bernoulli numbers of the second kind and their conjugates. More >
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ARTICLE
Ke Song1,*, Paul Liu2, Dongquan Liu3
CMES-Computer Modeling in Engineering & Sciences, Vol.128, No.3, pp. 1133-1150, 2021, DOI:10.32604/cmes.2021.016008
(This article belongs to this Special Issue: Computer Methods in Bio-mechanics and Biomedical Engineering)
Abstract A novel beamforming algorithm named Delay Multiply and Sum (DMAS), which excels at enhancing the resolution and contrast of ultrasonic image, has recently been proposed. However, there are nested loops in this algorithm, so the calculation complexity is higher compared to the Delay and Sum (DAS) beamformer which is widely used in industry. Thus, we proposed a simple vector-based method to lower its complexity. The key point is to transform the nested loops into several vector operations, which can be efficiently implemented on many parallel platforms, such as Graphics Processing Units (GPUs), and multi-core Central Processing Units (CPUs). Consequently, we… More >
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ARTICLE
Haishan Lu, Shuguang Gong*, Jianping Zhang, Guilan Xie, Shuohui Yin
CMES-Computer Modeling in Engineering & Sciences, Vol.128, No.3, pp. 1151-1178, 2021, DOI:10.32604/cmes.2021.016165
(This article belongs to this Special Issue: Novel Methods of Topology Optimization and Engineering Applications)
Abstract We proposed an improved graphics processing unit (GPU) acceleration approach for three-dimensional structural topology optimization using the element-free Galerkin (EFG) method. This method can effectively eliminate the race condition under parallelization. We established a structural topology optimization model by combining the EFG method and the solid isotropic microstructures with penalization model. We explored the GPU parallel algorithm of assembling stiffness matrix, solving discrete equation, analyzing sensitivity, and updating design variables in detail. We also proposed a node pair-wise method for assembling the stiffness matrix and a node-wise method for sensitivity analysis to eliminate race conditions during the parallelization. Furthermore, we… More >
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ARTICLE
Jun Yan1,3, Qi Xu1, Zhirui Fan1, Zunyi Duan2,*, Hongze Du1, Dongling Geng1
CMES-Computer Modeling in Engineering & Sciences, Vol.128, No.3, pp. 1179-1196, 2021, DOI:10.32604/cmes.2021.016950
(This article belongs to this Special Issue: Novel Methods of Topology Optimization and Engineering Applications)
Abstract This study investigates structural topology optimization of thermoelastic structures considering two kinds of objectives of minimum structural compliance and elastic strain energy with a specified available volume constraint. To explicitly express the configuration evolution in the structural topology optimization under combination of mechanical and thermal load conditions, the moving morphable components (MMC) framework is adopted. Based on the characteristics of the MMC framework, the number of design variables can be reduced substantially. Corresponding optimization formulation in the MMC topology optimization framework and numerical solution procedures are developed for several numerical examples. Different optimization results are obtained with structural compliance and… More >
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ARTICLE
Lianxiong Chen1, Hui Liu1,*, Xihua Chu1,2, Jiao Wang3
CMES-Computer Modeling in Engineering & Sciences, Vol.128, No.3, pp. 1197-1218, 2021, DOI:10.32604/cmes.2021.016894
(This article belongs to this Special Issue: Novel Methods of Topology Optimization and Engineering Applications)
Abstract Functional graded cellular structure (FGCS) usually shows superior mechanical behavior with low density and high stiffness. With the development of additive manufacturing, functional graded cellular structure gains its popularity in industries. In this paper, a novel approach for designing functionally graded cellular structure is proposed based on a subdomain parameterized level set method (PLSM) under local volume constraints (LVC). In this method, a subdomain level set function is defined, parameterized and updated on each subdomain independently making the proposed approach much faster and more cost-effective. Additionally, the microstructures on arbitrary two adjacent subdomains can be connected perfectly without any additional… More >
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ARTICLE
Mailing Zhao1, Jun Ye1,2,*
CMES-Computer Modeling in Engineering & Sciences, Vol.128, No.3, pp. 1219-1230, 2021, DOI:10.32604/cmes.2021.016871
(This article belongs to this Special Issue: Advances in Neutrosophic and Plithogenic Sets for Engineering and Sciences: Theory, Models, and Applications (ANPSESTMA))
Abstract In the complexity and indeterminacy of decision making (DM) environments, orthopair neutrosophic number set (ONNS) presented by Ye et al. can be described by the truth and falsity indeterminacy degrees. Then, ONNS demonstrates its advantages in the indeterminate information expression, aggregations, and DM problems with some indeterminate ranges. However, the existing research lacks some similarity measures between ONNSs. They are indispensable mathematical tools and play a crucial role in DM, pattern recognition, and clustering analysis. Thus, it is necessary to propose some similarity measures between ONNSs to supplement the gap. To solve the issue, this study firstly proposes the p-indeterminate… More >
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ARTICLE
Yanyan Zhang1, Xiangjin Ran2,*
CMES-Computer Modeling in Engineering & Sciences, Vol.128, No.3, pp. 1231-1245, 2021, DOI:10.32604/cmes.2021.016866
(This article belongs to this Special Issue: Swarm Intelligence and Applications in Combinatorial Optimization)
Abstract In the network security field, the network intrusion detection system (NIDS) is considered one of the critical issues
in the detection accuracy and missed detection rate. In this paper, a method of two-step network intrusion detection
on the basis of GoogLeNet Inception and deep convolutional neural networks (CNNs) models is proposed.
The proposed method used the GoogLeNet Inception model to identify the network packets’ binary problem.
Subsequently, the characteristics of the packets’ raw data and the traffic features are extracted. The CNNs model
is also used to identify the multiclass intrusions by the network packets’ features. In the experimental results,… More >
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ARTICLE
Ravi Shanker Dubey1, Dumitru Baleanu2,3, Manvendra Narayan Mishra1,*, Pranay Goswami4
CMES-Computer Modeling in Engineering & Sciences, Vol.128, No.3, pp. 1247-1263, 2021, DOI:10.32604/cmes.2021.015224
(This article belongs to this Special Issue: Mathematical Aspects of Computational Biology and Bioinformatics)
Abstract Diabetes is a burning issue in the whole world. It is the imbalance between body glucose and insulin. The study of this imbalance is very much needed from a research point of view. For this reason, Bergman gave an important model named-Bergman minimal model. In the present work, using Caputo-Fabrizio (CF) fractional derivative, we generalize Bergman’s minimal blood glucose-insulin model. Further, we modify the old model by including one more component known as diet D(t), which is also essential for the blood glucose model. We solve the modified model with the help of Sumudu transform and fixed-point iteration procedures. Also,… More >