Chengzhang Zhu^1,2, Renmao Zhang¹, Yalong Xiao^1,2,*, Beiji Zou¹, Xian Chai¹, Zhangzheng Yang¹, Rong Hu³, Xuanchu Duan⁴

CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.1, pp. 1103-1128, 2024, DOI:10.32604/cmes.2024.048453

Abstract Automatic segmentation of medical images provides a reliable scientific basis for disease diagnosis and analysis. Notably, most existing methods that combine the strengths of convolutional neural networks (CNNs) and Transformers have made significant progress. However, there are some limitations in the current integration of CNN and Transformer technology in two key aspects. Firstly, most methods either overlook or fail to fully incorporate the complementary nature between local and global features. Secondly, the significance of integrating the multi-scale encoder features from the dual-branch network to enhance the decoding features is often disregarded in methods that combine CNN and Transformer. To address… More >

Zun-Di Huang¹, Zhen-Bin Zhou^1,2,3, Ning Chang¹, Zheng-Wei Chen^2,3,*, Su-Mei Wang^2,3,*

CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.1, pp. 975-996, 2024, DOI:10.32604/cmes.2024.047664

Abstract The safety and stability of high-speed maglev trains traveling on viaducts in crosswinds critically depend on their aerodynamic characteristics. Therefore, this paper uses an improved delayed detached eddy simulation (IDDES) method to investigate the aerodynamic features of high-speed maglev trains with different marshaling lengths under crosswinds. The effects of marshaling lengths (varying from 3-car to 8-car groups) on the train’s aerodynamic performance, surface pressure, and the flow field surrounding the train were investigated using the three-dimensional unsteady compressible Navier-Stokes (N-S) equations. The results showed that the marshaling lengths had minimal influence on the aerodynamic performance of the head and middle… More > Graphic Abstract

Qing Zhu^1,*, Linlin Gu^1,2, Huijie Lin^1,2

CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.1, pp. 577-591, 2024, DOI:10.32604/cmes.2023.043307

Abstract With the rapid development of electric power systems, load estimation plays an important role in system operation and planning. Usually, load estimation techniques contain traditional, time series, regression analysis-based, and machine learning-based estimation. Since the machine learning-based method can lead to better performance, in this paper, a deep learning-based load estimation algorithm using image fingerprint and attention mechanism is proposed. First, an image fingerprint construction is proposed for training data. After the data preprocessing, the training data matrix is constructed by the cyclic shift and cubic spline interpolation. Then, the linear mapping and the gray-color transformation method are proposed to… More >

KRISHAN KUMAR PATEL, RAJESH PUROHIT

Journal of Polymer Materials, Vol.36, No.1, pp. 23-37, 2019, DOI:10.32381/JPM.2019.36.01.3

Abstract Microwave (MV)-induced thermo-responsive shape memory thermoplastic polyurethane (SMTPU)/ MWCNT composites were prepared in micro-compounder. Composites containing different amount of multiwall Carbon nanotube (MWCNT) varying from 0 to 1.5 phr in SMTPU matrix were prepared. Maximum stretching strength, recovery force and tensile strength for 1.5 CNTPU (1.5 phr MWCNT in SMTPU matrix) was increased by 120%, 100% and 24% respectively as compared to SMTPU. MV-induced shape memory is a novel approach for fast, clean and remote heating during operation. MWCNT is strong absorber of microwave irradiation so that SMTPU/ MWCNTs nanocomposites successfully triggered by microwave. More >

RAFAT SABA^*, MOHD. KASHIF AZIZ, GHULAM MUSTAFA, ARPIT SRIVASTAVA, SHEKHAR SRIVASTAVA^*

Journal of Polymer Materials, Vol.38, No.1-2, pp. 153-166, 2021, DOI:10.32381/JPM.2021.38.1-2.12

Abstract We have synthesized Schiff’s base of Fe₃ O₄ @chitosan with 4,4'-diselenobisbenzaldehyde (Fe₃O₄ @CSSe) composite and used it as acatalyst for the oxidation of sulfides, having some advantageous properties such as eco-friendly, cost-effective and highly efficient magnetic biocatalyst of selenium. The synthesized schiff’s base was characterized by different physical characterization techniques such as Fourier transform infrared spectroscopy (FT-IR), X-ray diffraction (XRD), Vibrating sample magnetometer (VSM)and Dynamic light scattering (DLS). Further, we used the resulting schiff’s base as a catalyst in the presence of a green oxidant (H₂ O₂ ) to oxidize sulfides to corresponding sulfoxides at room temperature. It has been… More >

SORAYA SEGHIER^1,2,*, MOHAMMED BELBACHIR¹

Journal of Polymer Materials, Vol.38, No.3-4, pp. 205-218, 2021, DOI:10.32381/JPM.2021.38.3-4.3

Abstract In the present paper, we report the synthesis of a new amino polymer made of oxazolidinone using an efficient ecocatalyst called Maghnite-H⁺. The synthesis process contains two steps: the first consists to the preparation of an amino oxiran 3-(oxiran-ylmethyl) oxazolidin- 2-one (OMO) by a substitution reaction of epichlorhydrin by 2-oxazolidinone, the second step concerns a green polymerization of the resultant oxiran by a ring opening reaction catalysed by Maghnite-H⁺. The polymer have been successfully prepared and characterized by various techniques, such as ¹H NMR, ¹³C NMR, IR, which were used to elucidate the structural characteristics of the resulting polymers. The… More >

THIRUMALAISAMY SURYAPRABHA^A, CHUNGHYUN CHOI^A, ZUBAIR AHMED CHANDIO^B, LAWRENCE ROBERT MSALILWA^B, TAEGWANG YUN^C,*, JUN YOUNG CHEONG^B,*, BYUNGIL HWANG^A,*

Journal of Polymer Materials, Vol.40, No.3-4, pp. 191-204, 2023, DOI:10.32381/JPM.2023.40.3-4.5

Abstract Magnetorheological fluids (MRFs) is a smart fluid system that exhibits swift and reversible alterations in their rheological characteristics when exposed to an external magnetic field. MRFs are used for applications in various areas, including automotive systems, robotics, aerospace, and civil engineering. The performance of MRFs depends on the behavior of the dispersed magnetic particles, necessitating thoughtful consideration of particle traits to optimize fluid performance. Carbonyl Iron Powders (CIPs), high purity iron (>98%) reduced from penta carbonyl iron, are widely employed in MRFs due to their exceptional magnetic characteristics. Nevertheless, the innate surfaces of CIPs tend to conglomerate, leading to compromises… More >

He Wang^1,*, Ying He²

FDMP-Fluid Dynamics & Materials Processing, Vol.20, No.4, pp. 889-899, 2024, DOI:10.32604/fdmp.2023.042728

Abstract Magnetohydrodynamic (MHD) induction pumps are contactless pumps able to withstand harsh environments. The rate of fluid flow through the pump directly affects the efficiency and stability of the device. To explore the influence of induction pump settings on the related delivery speed, in this study, a numerical model for coupled electromagnetic and flow field effects is introduced and used to simulate liquid metal lithium flow in the induction pump. The effects of current intensity, frequency, coil turns and coil winding size on the velocity of the working fluid are analyzed. It is shown that the first three parameters have a… More >

Changfeng Feng¹, Chunping Wang², Dongdong Zhang¹, Renke Kou¹, Qiang Fu^1,*

CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 3993-4013, 2024, DOI:10.32604/cmc.2024.048351

Abstract Transformer-based models have facilitated significant advances in object detection. However, their extensive computational consumption and suboptimal detection of dense small objects curtail their applicability in unmanned aerial vehicle (UAV) imagery. Addressing these limitations, we propose a hybrid transformer-based detector, H-DETR, and enhance it for dense small objects, leading to an accurate and efficient model. Firstly, we introduce a hybrid transformer encoder, which integrates a convolutional neural network-based cross-scale fusion module with the original encoder to handle multi-scale feature sequences more efficiently. Furthermore, we propose two novel strategies to enhance detection performance without incurring additional inference computation. Query filter is designed… More >

Bhawna Goyal¹, Ayush Dogra², Dawa Chyophel Lepcha¹, Rajesh Singh³, Hemant Sharma⁴, Ahmed Alkhayyat⁵, Manob Jyoti Saikia^6,*

CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 4317-4342, 2024, DOI:10.32604/cmc.2024.047256

Abstract Multimodal medical image fusion has attained immense popularity in recent years due to its robust technology for clinical diagnosis. It fuses multiple images into a single image to improve the quality of images by retaining significant information and aiding diagnostic practitioners in diagnosing and treating many diseases. However, recent image fusion techniques have encountered several challenges, including fusion artifacts, algorithm complexity, and high computing costs. To solve these problems, this study presents a novel medical image fusion strategy by combining the benefits of pixel significance with edge-preserving processing to achieve the best fusion performance. First, the method employs a cross-bilateral… More >