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  • Open Access

    REVIEW

    A Review on Finite Element Alternating Methods for Analyzing 2D and 3D Cracks

    Jai Hak Park*

    Digital Engineering and Digital Twin, Vol.2, pp. 79-101, 2024, DOI:10.32604/dedt.2024.047280

    Abstract A finite element alternating method has been known as a very convenient and accurate method to solve two and three-dimensional crack problems. In this method, a general crack problem is solved by a superposition of two solutions. One is a finite element solution for a finite body without a crack, and the other is an analytical solution for a crack in an infinite body. Since a crack is not considered in a finite element model, generating a model is very simple. The method is especially very convenient for a fatigue crack growth simulation. Over the past 40 years, S. N.… More >

  • Open Access

    ARTICLE

    ADVANCES IN THERMODIFFUSION AND THERMOPHORESIS (SORET EFFECT) IN LIQUID MIXTURES

    Morteza Eslamian*

    Frontiers in Heat and Mass Transfer, Vol.2, No.4, pp. 1-20, 2011, DOI:10.5098/hmt.v2.4.3001

    Abstract Recent advances in thermodiffusion (Soret effect) in binary and higher multicomponent liquid mixtures are reviewed. The mixtures studied include the hydrocarbon, associating, molten metal and semiconductor, polymer, and DNA mixtures. The emphasis is placed on the theoretical works, particularly models based on the nonequilibrium thermodynamics, although other approaches such as the statistical, kinetic and hydrodynamic approaches are discussed as well. For each mixture, the major theoretical and experimental works are discussed and the research trends and challenges are addressed. Some of the challenges include a need for combining various methods to develop a comprehensive theoretical model or at least to… More >

  • Open Access

    ARTICLE

    NUMERICAL SIMULATION OF DROPLET IMPACT AND SOLIDIFICATION INCLUDING THERMAL SHRINKAGE IN A THERMAL SPRAY PROCESS

    Sina Alavi, Mohammad Passandideh-Fard*

    Frontiers in Heat and Mass Transfer, Vol.2, No.2, pp. 1-9, 2011, DOI:10.5098/hmt.v2.2.3007

    Abstract In this paper, a numerical study is performed to investigate the effects of thermal shrinkage on the deposition of molten particles on a substrate in a thermal spray process using the Volume-of-Fluid (VOF) method. Thermal shrinkage is a phenomenon caused by the variation of density during cooling and solidification of a molten metal. The Navier-Stokes equations along with the energy equation including phase change are solved using a 2D/axisymmetric mesh. The VOF method is used to track the free surface of molten particles, and an enthalpy-porosity formulation is used to model solidification. For the normal impact of tin particles in… More >

  • Open Access

    ARTICLE

    Maximum Correntropy Criterion-Based UKF for Loosely Coupling INS and UWB in Indoor Localization

    Yan Wang*, You Lu, Yuqing Zhou, Zhijian Zhao

    CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.3, pp. 2673-2703, 2024, DOI:10.32604/cmes.2023.046743

    Abstract Indoor positioning is a key technology in today’s intelligent environments, and it plays a crucial role in many application areas. This paper proposed an unscented Kalman filter (UKF) based on the maximum correntropy criterion (MCC) instead of the minimum mean square error criterion (MMSE). This innovative approach is applied to the loose coupling of the Inertial Navigation System (INS) and Ultra-Wideband (UWB). By introducing the maximum correntropy criterion, the MCCUKF algorithm dynamically adjusts the covariance matrices of the system noise and the measurement noise, thus enhancing its adaptability to diverse environmental localization requirements. Particularly in the presence of non-Gaussian noise,… More >

  • Open Access

    ARTICLE

    Enhancing Multicriteria-Based Recommendations by Alleviating Scalability and Sparsity Issues Using Collaborative Denoising Autoencoder

    S. Abinaya*, K. Uttej Kumar

    CMC-Computers, Materials & Continua, Vol.78, No.2, pp. 2269-2286, 2024, DOI:10.32604/cmc.2024.047167

    Abstract A Recommender System (RS) is a crucial part of several firms, particularly those involved in e-commerce. In conventional RS, a user may only offer a single rating for an item-that is insufficient to perceive consumer preferences. Nowadays, businesses in industries like e-learning and tourism enable customers to rate a product using a variety of factors to comprehend customers’ preferences. On the other hand, the collaborative filtering (CF) algorithm utilizing AutoEncoder (AE) is seen to be effective in identifying user-interested items. However, the cost of these computations increases nonlinearly as the number of items and users increases. To triumph over the… More >

  • Open Access

    ARTICLE

    Multi-Objective Equilibrium Optimizer for Feature Selection in High-Dimensional English Speech Emotion Recognition

    Liya Yue1, Pei Hu2, Shu-Chuan Chu3, Jeng-Shyang Pan3,4,*

    CMC-Computers, Materials & Continua, Vol.78, No.2, pp. 1957-1975, 2024, DOI:10.32604/cmc.2024.046962

    Abstract Speech emotion recognition (SER) uses acoustic analysis to find features for emotion recognition and examines variations in voice that are caused by emotions. The number of features acquired with acoustic analysis is extremely high, so we introduce a hybrid filter-wrapper feature selection algorithm based on an improved equilibrium optimizer for constructing an emotion recognition system. The proposed algorithm implements multi-objective emotion recognition with the minimum number of selected features and maximum accuracy. First, we use the information gain and Fisher Score to sort the features extracted from signals. Then, we employ a multi-objective ranking method to evaluate these features and… More >

  • Open Access

    ARTICLE

    Ash Detection of Coal Slime Flotation Tailings Based on Chromatographic Filter Paper Sampling and Multi-Scale Residual Network

    Wenbo Zhu1, Neng Liu1, Zhengjun Zhu2,*, Haibing Li1, Weijie Fu1, Zhongbo Zhang1, Xinghao Zhang1

    Intelligent Automation & Soft Computing, Vol.38, No.3, pp. 259-273, 2023, DOI:10.32604/iasc.2023.041860

    Abstract The detection of ash content in coal slime flotation tailings using deep learning can be hindered by various factors such as foam, impurities, and changing lighting conditions that disrupt the collection of tailings images. To address this challenge, we present a method for ash content detection in coal slime flotation tailings. This method utilizes chromatographic filter paper sampling and a multi-scale residual network, which we refer to as MRCN. Initially, tailings are sampled using chromatographic filter paper to obtain static tailings images, effectively isolating interference factors at the flotation site. Subsequently, the MRCN, consisting of a multi-scale residual network, is… More >

  • Open Access

    ARTICLE

    Enhanced Steganalysis for Color Images Using Curvelet Features and Support Vector Machine

    Arslan Akram1,2, Imran Khan1, Javed Rashid2,3, Mubbashar Saddique4,*, Muhammad Idrees4, Yazeed Yasin Ghadi5, Abdulmohsen Algarni6

    CMC-Computers, Materials & Continua, Vol.78, No.1, pp. 1311-1328, 2024, DOI:10.32604/cmc.2023.040512

    Abstract Algorithms for steganography are methods of hiding data transfers in media files. Several machine learning architectures have been presented recently to improve stego image identification performance by using spatial information, and these methods have made it feasible to handle a wide range of problems associated with image analysis. Images with little information or low payload are used by information embedding methods, but the goal of all contemporary research is to employ high-payload images for classification. To address the need for both low- and high-payload images, this work provides a machine-learning approach to steganography image classification that uses Curvelet transformation to… More >

  • Open Access

    ARTICLE

    Binary Archimedes Optimization Algorithm for Computing Dominant Metric Dimension Problem

    Basma Mohamed1,*, Linda Mohaisen2, Mohammed Amin1

    Intelligent Automation & Soft Computing, Vol.38, No.1, pp. 19-34, 2023, DOI:10.32604/iasc.2023.031947

    Abstract In this paper, we consider the NP-hard problem of finding the minimum dominant resolving set of graphs. A vertex set B of a connected graph G resolves G if every vertex of G is uniquely identified by its vector of distances to the vertices in B. A resolving set is dominating if every vertex of G that does not belong to B is a neighbor to some vertices in B. The dominant metric dimension of G is the cardinality number of the minimum dominant resolving set. The dominant metric dimension is computed by a binary version of the Archimedes optimization… More >

  • Open Access

    ARTICLE

    A Novel Method for Aging Prediction of Railway Catenary Based on Improved Kalman Filter

    Jie Li1,3,*, Rongwen Wang2, Yongtao Hu1,3, Jinjun Li1

    Structural Durability & Health Monitoring, Vol.18, No.1, pp. 73-90, 2024, DOI:10.32604/sdhm.2023.044023

    Abstract The aging prediction of railway catenary is of profound significance for ensuring the regular operation of electrified trains. However, in real-world scenarios, accurate predictions are challenging due to various interferences. This paper addresses this challenge by proposing a novel method for predicting the aging of railway catenary based on an improved Kalman filter (KF). The proposed method focuses on modifying the priori state estimate covariance and measurement error covariance of the KF to enhance accuracy in complex environments. By comparing the optimal displacement value with the theoretically calculated value based on the thermal expansion effect of metals, it becomes possible… More > Graphic Abstract

    A Novel Method for Aging Prediction of Railway Catenary Based on Improved Kalman Filter

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