Lingling Chen^1,2,*, Tong Liu¹, Zhuo Gong¹, Ding Wang¹

Computer Systems Science and Engineering, Vol.48, No.2, pp. 321-339, 2024, DOI:10.32604/csse.2023.037865

Abstract Human pose estimation is a basic and critical task in the field of computer vision that involves determining the position (or spatial coordinates) of the joints of the human body in a given image or video. It is widely used in motion analysis, medical evaluation, and behavior monitoring. In this paper, the authors propose a method for multi-view human pose estimation. Two image sensors were placed orthogonally with respect to each other to capture the pose of the subject as they moved, and this yielded accurate and comprehensive results of three-dimensional (3D) motion reconstruction that helped capture their multi-directional poses.… More >

Arafat A. Bhuiyan^a,1, A. K. M. Sadrul Islam^a, M. Ruhul Amin^b

Frontiers in Heat and Mass Transfer, Vol.3, No.3, pp. 1-9, 2012, DOI:10.5098/hmt.v3.3.3006

Abstract This numerical analysis presents the airside performance of a wavy fin-and-tube heat exchanger having 4 row configurations considering steady, incompressible and 3D flow using Commercial CFD Code ANSYS CFX 12.0. Results are presented in the form of friction factor (f), Colburn factor (j) and efficiency index (j/f). The numerical procedure has been validated by comparison with published numerical and experimental results and good agreement has been observed. A series of numerical calculations have been carried out in order to analyze the influence of various geometric characteristics on different fields as well as on the heat transfer and pressure drop and… More >

Muhammad Akbar¹, Huali Pan^1,*, Jiangcheng Huang², Bilal Ahmed³, Guoqiang Ou¹

CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.3, pp. 2835-2863, 2024, DOI:10.32604/cmes.2024.046993

Abstract The present work aims to assess earthquake-induced earth-retaining (ER) wall displacement. This study is on the dynamics analysis of various earth-retaining wall designs in hollow precast concrete panels, reinforcement concrete facing panels, and gravity-type earth-retaining walls. The finite element (FE) simulations utilized a 3D plane strain condition to model full-scale ER walls and numerous nonlinear dynamics analyses. The seismic performance of different models, which includes reinforcement concrete panels and gravity-type and hollow precast concrete ER walls, was simulated and examined using the FE approach. It also displays comparative studies such as stress distribution, deflection of the wall, acceleration across the… More >

Yuchun Li^1,4, Mengxing Huang^1,*, Yu Zhang², Zhiming Bai³

CMC-Computers, Materials & Continua, Vol.78, No.2, pp. 1649-1668, 2024, DOI:10.32604/cmc.2023.046883

Abstract The precise and automatic segmentation of prostate magnetic resonance imaging (MRI) images is vital for assisting doctors in diagnosing prostate diseases. In recent years, many advanced methods have been applied to prostate segmentation, but due to the variability caused by prostate diseases, automatic segmentation of the prostate presents significant challenges. In this paper, we propose an attention-guided multi-scale feature fusion network (AGMSF-Net) to segment prostate MRI images. We propose an attention mechanism for extracting multi-scale features, and introduce a 3D transformer module to enhance global feature representation by adding it during the transition phase from encoder to decoder. In the… More >

Yanmei Li^1,*, Jinghong Tang¹, Weiwu Ding¹, Jian Luo², Naveed Ahmad³, Rajesh Kumar⁴

CMC-Computers, Materials & Continua, Vol.78, No.1, pp. 713-733, 2024, DOI:10.32604/cmc.2023.046872

Abstract Alzheimer’s disease (AD) is a complex, progressive neurodegenerative disorder. The subtle and insidious onset of its pathogenesis makes early detection of a formidable challenge in both contemporary neuroscience and clinical practice. In this study, we introduce an advanced diagnostic methodology rooted in the Med-3D transfer model and enhanced with an attention mechanism. We aim to improve the precision of AD diagnosis and facilitate its early identification. Initially, we employ a spatial normalization technique to address challenges like clarity degradation and unsaturation, which are commonly observed in imaging datasets. Subsequently, an attention mechanism is incorporated to selectively focus on the salient… More >

Shigeki Kaneko¹, Naoto Mitsume², Shinobu Yoshimura^1,*

Digital Engineering and Digital Twin, Vol.2, pp. 33-48, 2024, DOI:10.32604/dedt.2023.044279

Abstract In an integrated coal gasification combined cycle plant, cooling pipes are installed in the gasifier reactor and water cooling is executed to avoid reaching an excessively high temperature. To accelerate the design, it is necessary to develop an analysis system that can simulate the cooling operation within the practical computational time. In the present study, we assumed the temperature fields of the cooled object and the cooling water to be governed by the three-dimensional (3D) heat equation and the one-dimensional (1D) convection-diffusion equation, respectively. Although some existing studies have employed similar modeling, the applications have been limited to simple-shaped structures.… More >

Bingzhu Wang^1,*, Xiangrui Ye^2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.2, pp. 1401-1425, 2024, DOI:10.32604/cmes.2024.047364

Abstract A novel three-dimensional-fiber reinforced soft pneumatic actuator (3D-FRSPA) inspired by crab claw and human hand structure that can bend and deform independently in each segment is proposed. It has an omni-directional bending configuration, and the fibers twined symmetrically on both sides to improve the bending performance of FRSPA. In this paper, the static and kinematic analysis of 3D-FRSPA are carried out in detail. The effects of fiber, pneumatic chamber and segment length, and circular air chamber radius of 3D-FRSPA on the mechanical performance of the actuator are discussed, respectively. The soft mobile robot composed of 3D-FRSPA has the ability to… More >

Duong Q. Nguyen¹, Thinh D. Le³, Phuong D. Nguyen³, Nga T. K. Le², H. Nguyen-Xuan^3,*

CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.2, pp. 2197-2214, 2024, DOI:10.32604/cmes.2023.043992

Abstract Facial wound segmentation plays a crucial role in preoperative planning and optimizing patient outcomes in various medical applications. In this paper, we propose an efficient approach for automating 3D facial wound segmentation using a two-stream graph convolutional network. Our method leverages the Cir3D-FaIR dataset and addresses the challenge of data imbalance through extensive experimentation with different loss functions. To achieve accurate segmentation, we conducted thorough experiments and selected a high-performing model from the trained models. The selected model demonstrates exceptional segmentation performance for complex 3D facial wounds. Furthermore, based on the segmentation model, we propose an improved approach for extracting… More > Graphic Abstract

MINJI PARK¹, CHULHWAN BANG², WON-SOO YUN³, YUN-MI JEONG^3,*

Oncology Research, Vol.32, No.2, pp. 273-282, 2024, DOI:10.32604/or.2023.044362

Abstract Fucoidan, a sulfate polysaccharide obtained from brown seaweed, has various bioactive properties, including anti-inflammatory, anti-cancer, anti-viral, anti-oxidant, anti-coagulant, anti-thrombotic, anti-angiogenic, and anti-Helicobacter pylori properties. However, the effects of low-molecular-weight fucoidan (LMW-F) on melanoma cell lines and three dimensional (3D) cell culture models are not well understood. This study aimed to investigate the effects of LMW-F on A375 human melanoma cells and cryopreserved biospecimens derived from patients with advanced melanoma. Ultrasonic wave was used to fragment fucoidan derived from Fucus vesiculosus into smaller LMW-F. MTT and live/dead assays showed that LMW-F inhibited cell proliferation in both A375 cells and patient-derived melanoma… More >

S. Kannan^1,*, S. Anusuya²

CMC-Computers, Materials & Continua, Vol.77, No.3, pp. 3835-3851, 2023, DOI:10.32604/cmc.2023.042465

Abstract Gliomas, the most prevalent primary brain tumors, require accurate segmentation for diagnosis and risk assessment. In this paper, we develop a novel deep learning-based method, the Dynamic Hierarchical Attention for Improved Segmentation and Survival Prognosis (DHA-ISSP) model. The DHA-ISSP model combines a three-band 3D convolutional neural network (CNN) U-Net architecture with dynamic hierarchical attention mechanisms, enabling precise tumor segmentation and survival prediction. The DHA-ISSP model captures fine-grained details and contextual information by leveraging attention mechanisms at multiple levels, enhancing segmentation accuracy. By achieving remarkable results, our approach surpasses 369 competing teams in the 2020 Multimodal Brain Tumor Segmentation Challenge. With… More >