Vol.131, No.1, 2022-Table of Contents

On the Cover


Aiming to reduce noise pollution level, this work proposes a novel method of rationalizing the layout design of sound-absorption materials adhered to structural surfaces. The isogeometric boundary element method is applied to perform acoustic analysis directly from the Computer-Aided Design models which are built by Catmull-Clark subdivision surfaces. Based on the acoustic simulation and sensitivity analysis results, we employ the density-based topology optimization method to optimize the distribution of sound-absorption materials. A car model is used in the numerical example to demonstrate the effectiveness of the present method.
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  • Noise Pollution Reduction through a Novel Optimization Procedure in Passive Control Methods
  • Abstract This paper proposes a novel optimization framework in passive control techniques to reduce noise pollution. The geometries of the structures are represented by Catmull-Clark subdivision surfaces, which are able to build gap-free Computer-Aided Design models and meanwhile tackle the extraordinary points that are commonly encountered in geometric modelling. The acoustic fields are simulated using the isogeometric boundary element method, and a density-based topology optimization is conducted to optimize distribution of sound-absorbing materials adhered to structural surfaces. The approach enables one to perform acoustic optimization from Computer-Aided Design models directly without needing meshing and volume parameterization, thereby avoiding the geometric errors… More
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  • Study of Effect of Boundary Conditions on Patient-Specific Aortic Hemodynamics
  • Abstract Cardiovascular computational fluid dynamics (CFD) based on patient-specific modeling is increasingly used to predict changes in hemodynamic parameters before or after surgery/interventional treatment for aortic dissection (AD). This study investigated the effects of flow boundary conditions (BCs) on patient-specific aortic hemodynamics. We compared the changes in hemodynamic parameters in a type A dissection model and normal aortic model under different BCs: inflow from the auxiliary and truncated structures at aortic valve, pressure control and Windkessel model outflow conditions, and steady and unsteady inflow conditions. The auxiliary entrance remarkably enhanced the physiological authenticity of numerical simulations of flow in the ascending… More
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  • Comparative Study on Deformation Prediction Models of Wuqiangxi Concrete Gravity Dam Based on Monitoring Data
  • Abstract The deformation prediction models of Wuqiangxi concrete gravity dam are developed, including two statistical models and a deep learning model. In the statistical models, the reliable monitoring data are firstly determined with Lahitte criterion; then, the stepwise regression and partial least squares regression models for deformation prediction of concrete gravity dam are constructed in terms of the reliable monitoring data, and the factors of water pressure, temperature and time effect are considered in the models; finally, according to the monitoring data from 2006 to 2020 of five typical measuring points including J23 (on dam section ), J33 (on dam section… More
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  • Mu-Net: Multi-Path Upsampling Convolution Network for Medical Image Segmentation
  • Abstract Medical image segmentation plays an important role in clinical diagnosis, quantitative analysis, and treatment process. Since 2015, U-Net-based approaches have been widely used for medical image segmentation. The purpose of the U-Net expansive path is to map low-resolution encoder feature maps to full input resolution feature maps. However, the consecutive deconvolution and convolutional operations in the expansive path lead to the loss of some high-level information. More high-level information can make the segmentation more accurate. In this paper, we propose MU-Net, a novel, multi-path upsampling convolution network to retain more high-level information. The MU-Net mainly consists of three parts: contracting… More
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  • An Approach for Quantifying the Influence of Seepage Dissolution on Seismic Performance of Concrete Dams
  • Abstract Many concrete dams seriously suffer from long-term seepage dissolution, and the induced mechanical property deterioration of concrete may significantly affect the structural performance, especially the seismic safety. An approach is presented in this paper to quantify the influence of seepage dissolution on seismic performance of concrete dams. To connect laboratory test with numerical simulation, dissolution tests are conducted for concrete specimens and using the cumulative relative leached calcium as an aging index, a deterioration model is established to predict the mechanical property of leached concrete in the first step. A coupled seepage-calcium dissolution-migration model containing two calculation modes is proposed… More
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  • Influence of Soil Heterogeneity on the Behavior of Frozen Soil Slope under Freeze-Thaw Cycles
  • Abstract Soil slope stability in seasonally frozen regions is a challenging problem for geotechnical engineers. The freeze-thaw process of soil slope caused by the temperature fluctuation increases the difficulty in predicting the slope stability because the soil property is influenced by the freeze-thaw cycle. In addition, the frozen soil, which has ice crystal, ice lens and experienced freeze-thaw process, could present stronger heterogeneity. Previous research has not investigated the combined effect of soil heterogeneity and freeze-thaw cycle. This paper studies the influence of soil heterogeneity on the stability of frozen soil slope under freeze-thaw cycles. The local average subdivision (LAS) is… More
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  • Remote Sensing Image Retrieval Based on 3D-Local Ternary Pattern (LTP) Features and Non-subsampled Shearlet Transform (NSST) Domain Statistical Features
  • Abstract With the increasing popularity of high-resolution remote sensing images, the remote sensing image retrieval (RSIR) has always been a topic of major issue. A combined, global non-subsampled shearlet transform (NSST)-domain statistical features (NSSTds) and local three dimensional local ternary pattern (3D-LTP) features, is proposed for high-resolution remote sensing images. We model the NSST image coefficients of detail subbands using 2-state laplacian mixture (LM) distribution and its three parameters are estimated using Expectation-Maximization (EM) algorithm. We also calculate the statistical parameters such as subband kurtosis and skewness from detail subbands along with mean and standard deviation calculated from approximation subband, and… More
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  • An Experimental and Numerical Study on the Ballistic Performance of Multi-Layered Moderately-Thick Metallic Targets against 12.7-mm Projectiles
  • Abstract The main goal of this work is to study the ballistic performance of multi-layered moderately-thick metallic targets. Several target configurations have been considered in this work, with various types of interlayer connection (spaced, contacted and adhesive) and the number of layers (four and eight), and the influence of target configurations on ballistic performance has been studied experimentally and numerically. In the experiments, the targets were impacted by 12.7-mm projectiles at a velocity around 820 m/s. The experimental results show that, with similar total thickness, the contacted and adhesive targets exhibit better ballistic performance than the monolithic targets, and the four-layered targets… More
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  • Seismic Performance of Assembled Shear Wall with Defective Sleeve Connection
  • Abstract In this paper, three kinds of shear walls with full sleeve grouting, fully defective sleeve and partially defective are designed for finite element analysis to analyze the influence of defects on the seismic performance of shear walls. The research shows that at the beginning of loading (5 s), the three models begin to appear compressive damage at the bottom of the wall in all three models. The damage of the defect-free model develops rapidly, and the damage of the fully defective model is basically the same as that of the partially defective model. With the gradual increase of displacement control (15 s),… More
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  • A Novel Feature Aggregation Approach for Image Retrieval Using Local and Global Features
  • Abstract The current deep convolution features based on retrieval methods cannot fully use the characteristics of the salient image regions. Also, they cannot effectively suppress the background noises, so it is a challenging task to retrieve objects in cluttered scenarios. To solve the problem, we propose a new image retrieval method that employs a novel feature aggregation approach with an attention mechanism and utilizes a combination of local and global features. The method first extracts global and local features of the input image and then selects keypoints from local features by using the attention mechanism. After that, the feature aggregation mechanism… More
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  • k-Order Fibonacci Polynomials on AES-Like Cryptology
  • Abstract The Advanced Encryption Standard (AES) is the most widely used symmetric cipher today. AES has an important place in cryptology. Finite field, also known as Galois Fields, are cornerstones for understanding any cryptography. This encryption method on AES is a method that uses polynomials on Galois fields. In this paper, we generalize the AES-like cryptology on 2 × 2 matrices. We redefine the elements of k-order Fibonacci polynomials sequences using a certain irreducible polynomial in our cryptology algorithm. So, this cryptology algorithm is called AES-like cryptology on the k-order Fibonacci polynomial matrix. More
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  • A Lightweight and Robust User Authentication Protocol with User Anonymity for IoT-Based Healthcare
  • Abstract With the rise of the Internet of Things (IoT), the word “intelligent medical care” has increasingly become a major vision. Intelligent medicine adopts the most advanced IoT technology to realize the interaction between patients and people, medical institutions, and medical equipment. However, with the openness of network transmission, the security and privacy of information transmission have become a major problem. Recently, Masud et al. proposed a lightweight anonymous user authentication protocol for IoT medical treatment, claiming that their method can resist various attacks. However, through analysis of the protocol, we observed that their protocol cannot effectively resist privileged internal attacks,… More
  •   Views:731       Downloads:554       Cited by:2        Download PDF
  • Improving Date Fruit Classification Using CycleGAN-Generated Dataset
  • Abstract Dates are an important part of human nutrition. Dates are high in essential nutrients and provide a number of health benefits. Date fruits are also known to protect against a number of diseases, including cancer and heart disease. Date fruits have several sizes, colors, tastes, and values. There are a lot of challenges facing the date producers. One of the most significant challenges is the classification and sorting of dates. But there is no public dataset for date fruits, which is a major limitation in order to improve the performance of convolutional neural networks (CNN) models and avoid the overfitting… More
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  • Experimental and Numerical Study on Mechanical Properties of Z-pins Reinforced Composites Adhesively Bonded Single-Lap Joints
  • Abstract The mechanical properties of Z-pins reinforced composites adhesively bonded single-lap joints (SLJs) under un-directional tension loading are investigated by experimental and numerical methods. Three kinds of joint configurations, including SLJs with three/two rows of Z-pins and “I” array of Z-pins, are investigated by tension test. The failure modes and mechanism of reinforced joints with different Z-pins numbers and alignment are analyzed, and the comparison is performed for the failure strengths of no Z-pins and Z-pins reinforced joints. According to experimental results, failure modes of three kinds of joints are all mixed failure. It turns out that the Z-pins are pulled… More
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  • A New Approach to Vague Soft Bi-Topological Spaces
  • Abstract Fuzzy soft topology considers only membership value. It has nothing to do with the non-membership value. So an extension was needed in this direction. Vague soft topology addresses both membership and non-membership values simultaneously. Sometimes vague soft topology (single structure) is unable to address some complex structures. So an extension to vague soft bi-topology (double structure) was needed in this direction. To make this situation more meaningful, a new concept of vague soft bi-topological space is introduced and its structural characteristics are attempted with a new definition. In this article, new concept of vague soft bi-topological space (VSBTS) is initiated… More
  •   Views:471       Downloads:450       Cited by:2        Download PDF
  • LF-CNN: Deep Learning-Guided Small Sample Target Detection for Remote Sensing Classification
  • Abstract Target detection of small samples with a complex background is always difficult in the classification of remote sensing images. We propose a new small sample target detection method combining local features and a convolutional neural network (LF-CNN) with the aim of detecting small numbers of unevenly distributed ground object targets in remote sensing images. The k-nearest neighbor method is used to construct the local neighborhood of each point and the local neighborhoods of the features are extracted one by one from the convolution layer. All the local features are aggregated by maximum pooling to obtain global feature representation. The classification… More
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  • Machine Learning Enhanced Boundary Element Method: Prediction of Gaussian Quadrature Points
  • Abstract This paper applies a machine learning technique to find a general and efficient numerical integration scheme for boundary element methods. A model based on the neural network multi-classification algorithm is constructed to find the minimum number of Gaussian quadrature points satisfying the given accuracy. The constructed model is trained by using a large amount of data calculated in the traditional boundary element method and the optimal network architecture is selected. The two-dimensional potential problem of a circular structure is tested and analyzed based on the determined model, and the accuracy of the model is about 90%. Finally, by incorporating the… More
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  • Research on Normal Pythagorean Neutrosophic Set Choquet Integral Operator and Its Application
  • Abstract We first propose the normal Pythagorean neutrosophic set (NPNS) in this paper, which synthesizes the distribution of the incompleteness, indeterminacy, and inconsistency of the Pythagorean neutrosophic set (PNS) and normal fuzzy number. We also define some properties of NPNS. For solving the decision-making problem of the non-strictly independent and interacting attributes, two kinds of NPNS Choquet integral operators are proposed. First, the NPNS Choquet integral average (NPNSCIA) operator and the NPNS Choquet integral geometric (NPNSCIG) operator are proposed. Then, their calculating formulas are derived, their properties are discussed, and an approach for solving the interacting multi-attribute decision making based on… More
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  • Spectral Matching Classification Method of Multi-State Similar Pigments Based on Feature Differences
  • Abstract The properties of the same pigments in murals are affected by different concentrations and particle diameters, which cause the shape of the spectral reflectance data curve to vary, thus influencing the outcome of matching calculations. This paper proposes a spectral matching classification method of multi-state similar pigments based on feature differences. Fast principal component analysis (FPCA) was used to calculate the eigenvalue variance of pigment spectral reflectance, then applied to the original reflectance values for parameter characterization. We first projected the original spectral reflectance from the spectral space to the characteristic variance space to identify the spectral curve. Secondly, the… More
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