Jiawei Zhang^*, Qing Wang, Hongchun Huang, Haige Wang, Guodong Ji, Meng Cui, Hongyuan Zhang

FDMP-Fluid Dynamics & Materials Processing, Vol.19, No.9, pp. 2305-2314, 2023, DOI:10.32604/fdmp.2023.026304

Abstract Formation pressure is the key parameter for the analysis of wellbore safety. With increasing drilling depth, however, the behavior of this variable becomes increasingly complex. In this work, a 3D model of the formation pressure under uncertainty is presented. Moreover a relevant algorithm is elaborated. First, the logging data of regional key drilling wells are collected and a one-dimensional formation pressure profile along the well depth is determined. Then, a 3D model of regional formation pressure of the hierarchical group layer is defined by using the Kriging interpolation algorithm relying on a support vector machine (SVM) and the formation pressure… More >

Shiwei Qin, Zili Dai^*

CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.3, pp. 3157-3172, 2023, DOI:10.32604/cmes.2023.026874

Abstract High-resolution underwater digital elevation models (DEMs) are important for water and soil conservation, hydrological analysis, and river channel dredging. In this work, the underwater topography of the Panjing River in Shanghai, China, was measured by an unmanned surface vessel. Five different interpolation methods were used to generate the underwater DEM and their precision and applicability for different underwater landforms were analyzed through cross-validation. The results showed that there was a positive correlation between the interpolation error and the terrain surface roughness. The five interpolation methods were all appropriate for the survey area, but their accuracy varied with different surface roughness.… More >

S. Vidhya^1,*, V. Kalaivani²

Computer Systems Science and Engineering, Vol.45, No.3, pp. 2673-2692, 2023, DOI:10.32604/csse.2023.027724

Abstract In recent decades, the cloud computing contributes a prominent role in health care sector as the patient health records are transferred and collected using cloud computing services. The doctors have switched to cloud computing as it provides multiple advantageous measures including wide storage space and easy availability without any limitations. This necessitates the medical field to be redesigned by cloud technology to preserve information about patient’s critical diseases, electrocardiogram (ECG) reports, and payment details. The proposed work utilizes a hybrid cloud pattern to share Massachusetts Institute of Technology-Beth Israel Hospital (MIT-BIH) resources over the private and public cloud. The stored… More >

Bich Nguyen¹, Binh Nguyen¹, Hai Tran², Vuong Pham¹, Le Nhi Lam Thuy¹, Pham The Bao^1,*

CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 2431-2441, 2023, DOI:10.32604/cmc.2023.029618

Abstract 3-dimension (3-D) printing technology is growing strongly with many applications, one of which is the garment industry. The application of human body models to the garment industry is necessary to respond to the increasing personalization demand and still guarantee aesthetics. This paper proposes a method to construct 3-D human models by applying deep learning. We calculate the location of the main slices of the human body, including the neck, chest, belly, buttocks, and the rings of the extremities, using pre-existing information. Then, on the positioning frame, we find the key points (fixed and unaltered) of these key slices and update… More >

Yun Fen Yong^1,*, Chee Keong Tan¹, Ian Kim Teck Tan², Su Wei Tan¹

CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 1801-1818, 2023, DOI:10.32604/cmc.2023.032710

Abstract A robust radio map is essential in implementing a fingerprint-based indoor positioning system (IPS). However, the offline site survey to manually construct the radio map is time-consuming and labour-intensive. Various interpolation techniques have been proposed to infer the virtual fingerprints to reduce the time and effort required for offline site surveys. This paper presents a novel fingerprint interpolator using a multi-path loss model (M-PLM) to create the virtual fingerprints from the collected sample data based on different signal paths from different access points (APs). Based on the historical signal data, the poor signal paths are identified using their standard deviations.… More >

Guojun Zheng^1,2, Zhaomin Yan¹, Yang Xia^1,2, Ping Hu^1,2, Guozhe Shen^1,2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.134, No.3, pp. 1975-1995, 2023, DOI:10.32604/cmes.2022.021415

Abstract Peridynamics (PD) is a non-local mechanics theory that overcomes the limitations of classical continuum mechanics (CCM) in predicting the initiation and propagation of cracks. However, the calculation efficiency of PD models is generally lower than that of the traditional finite element method (FEM). Structural idealization can greatly improve the calculation efficiency of PD models for complex structures. This study presents a PD shell model based on the micro-beam bond via the homogenization assumption. First, the deformations of each endpoint of the micro-beam bond are calculated through the interpolation method. Second, the micro-potential energy of the axial, torsional, and bending deformations… More >

Ying Li¹, Longxiang Xu¹, Fangjun Mei¹, Shihui Ying^2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.134, No.1, pp. 657-672, 2023, DOI:10.32604/cmes.2022.021277

Abstract We propose new hybrid Lagrange neural networks called LaNets to predict the numerical solutions of partial differential equations. That is, we embed Lagrange interpolation and small sample learning into deep neural network frameworks. Concretely, we first perform Lagrange interpolation in front of the deep feedforward neural network. The Lagrange basis function has a neat structure and a strong expression ability, which is suitable to be a preprocessing tool for pre-fitting and feature extraction. Second, we introduce small sample learning into training, which is beneficial to guide the model to be corrected quickly. Taking advantages of the theoretical support of traditional… More >

Israa Ismail^1,*, Mohamed Meselhy Eltoukhy^1,2, Ghada Eltaweel¹

Computer Systems Science and Engineering, Vol.45, No.1, pp. 167-181, 2023, DOI:10.32604/csse.2023.028906

Abstract Super-resolution techniques are used to reconstruct an image with a high resolution from one or more low-resolution image(s). In this paper, we proposed a single image super-resolution algorithm. It uses the nonlocal mean filter as a prior step to produce a denoised image. The proposed algorithm is based on curvelet transform. It converts the denoised image into low and high frequencies (sub-bands). Then we applied a multi-dimensional interpolation called Lancozos interpolation over both sub-bands. In parallel, we applied sparse representation with over complete dictionary for the denoised image. The proposed algorithm then combines the dictionary learning in the sparse representation… More >

E. P. Kannan^1,*, S. S. Vinsley², T. V. Chithra³

Intelligent Automation & Soft Computing, Vol.34, No.3, pp. 1675-1691, 2022, DOI:10.32604/iasc.2022.022707

Abstract In this paper, Field-Programmable Gate Array (FPGA) implementation-based image demosaicing is carried out. The Newton Gregory interpolation algorithm is designed based on FPGA frame work. Interpolation is the method of assessing the value of a function for any in-between value of self-regulating variable, whereas the method of computing the value of the function outside the specified range is named extrapolation. The natural images are collected from Kodak image database and medical images are collected from UPOL (University of Phoenix Online) database. The proposed algorithm is executed on using Xilinx ISE (Integrated Synthesis Environment) Design Suite 14.2 and is confirmed on… More >

Yintong Wang^1,2,*, Yingjie Yang², Haiyan Chen³, Hao Zheng¹, Heyou Chang¹

Intelligent Automation & Soft Computing, Vol.34, No.1, pp. 371-388, 2022, DOI:10.32604/iasc.2022.027146

Abstract Handwritten Chinese recognition which involves variant writing style, thousands of character categories and monotonous data mark process is a long-term focus in the field of pattern recognition research. The existing methods are facing huge challenges including the complex structure of character/line-touching, the discriminate ability of similar characters and the labeling of training datasets. To deal with these challenges, an end-to-end residual attention handwritten Chinese paragraph text recognition method is proposed, which uses fully convolutional neural networks as the main structure of feature extraction and employs connectionist temporal classification as a loss function. The novel residual attention gate block is more… More >