Zhengyuan Pei¹, Yasushi Koito^2,*

Frontiers in Heat and Mass Transfer, Vol.22, No.5, pp. 1381-1397, 2024, DOI:10.32604/fhmt.2024.056624 - 30 October 2024

Abstract Extended experiments were conducted on the oscillation characteristics of merged liquid slugs in a horizontally oriented polymer pulsating heat pipe (PHP). The PHP’s serpentine channel comprised 14 parallel channels with a width of 1.3 and a height of 1.1 . The evaporator and condenser sections were 25 and 50 long, respectively, and the adiabatic section in between was 75 mm long. Using a plastic 3D printer and semi-transparent filament made from acrylonitrile butadiene styrene, the serpentine channel was printed directly onto a thin polycarbonate sheet to form the PHP. The PHP was charged with hydrofluoroether-7100.… More >

Ali M. H. Al-Obaidy^*, Ekhlas M. Fayyadh, Amer M. Al-Dabagh

Frontiers in Heat and Mass Transfer, Vol.22, No.5, pp. 1421-1442, 2024, DOI:10.32604/fhmt.2024.055063 - 30 October 2024

Abstract High heat dissipation is required for miniaturization and increasing the power of electronic systems. Pool boiling is a promising option for achieving efficient heat dissipation at low wall superheat without the need for moving parts. Many studies have focused on improving heat transfer efficiency during boiling by modifying the surface of the heating element. This paper presents an experimental investigation on improving pool boiling heat transfer using an open microchannel. The primary goal of this work is to investigate the impact of the channel geometry characteristics on boiling heat transfer. Initially, rectangular microchannels were prepared… More > Graphic Abstract

Weigang Jin¹, Lei Chen^2,*, Shencong Zheng², Yuqi Jiang², Yifei Li², Hongkun Chen²

Energy Engineering, Vol.121, No.11, pp. 3161-3179, 2024, DOI:10.32604/ee.2024.054068 - 21 October 2024

Abstract Investigating flexibility and stability boosting transmission expansion planning (TEP) methods can increase the renewable energy (RE) consumption of the power systems. In this study, we propose a bi-level TEP method for voltage-source-converter-based direct current (VSC-DC), focusing on flexibility and stability enhancement. First, we established the TEP framework of VSC-DC, by introducing the evaluation indices to quantify the power system flexibility and stability. Subsequently, we propose a bi-level VSC-DC TEP model: the upper-level model acquires the optimal VSC-DC planning scheme by using the improved moth flame optimization (IMFO) algorithm, and the lower-level model evaluates the flexibility More >

Shuang Kang¹, Yinchao He^1,2, Wenwen Li^1,*, Sen Liu²

CMC-Computers, Materials & Continua, Vol.81, No.1, pp. 933-949, 2024, DOI:10.32604/cmc.2024.056614 - 15 October 2024

Abstract To address the issues of low accuracy and high false positive rate in traditional Otsu algorithm for defect detection on infrared images of wind turbine blades (WTB), this paper proposes a technique that combines morphological image enhancement with an improved Otsu algorithm. First, mathematical morphology’s differential multi-scale white and black top-hat operations are applied to enhance the image. The algorithm employs entropy as the objective function to guide the iteration process of image enhancement, selecting appropriate structural element scales to execute differential multi-scale white and black top-hat transformations, effectively enhancing the detail features of defect… More >

Tao Zhou^1,3, Yunfeng Pan^1,3,*, Huiling Lu², Pei Dang^1,3, Yujie Guo^1,3, Yaxing Wang^1,3

CMC-Computers, Materials & Continua, Vol.80, No.3, pp. 4813-4832, 2024, DOI:10.32604/cmc.2024.054685 - 12 September 2024

Abstract Multimodal lung tumor medical images can provide anatomical and functional information for the same lesion. Such as Positron Emission Computed Tomography (PET), Computed Tomography (CT), and PET-CT. How to utilize the lesion anatomical and functional information effectively and improve the network segmentation performance are key questions. To solve the problem, the Saliency Feature-Guided Interactive Feature Enhancement Lung Tumor Segmentation Network (Guide-YNet) is proposed in this paper. Firstly, a double-encoder single-decoder U-Net is used as the backbone in this model, a single-coder single-decoder U-Net is used to generate the saliency guided feature using PET image and… More >

Sheng Xiang¹, Junhao Ma¹, Qunli Shang¹, Xianbao Wang^1,*, Defu Chen^1,2

CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.1, pp. 713-731, 2024, DOI:10.32604/cmes.2024.052759 - 20 August 2024

Abstract Effective small object detection is crucial in various applications including urban intelligent transportation and pedestrian detection. However, small objects are difficult to detect accurately because they contain less information. Many current methods, particularly those based on Feature Pyramid Network (FPN), address this challenge by leveraging multi-scale feature fusion. However, existing FPN-based methods often suffer from inadequate feature fusion due to varying resolutions across different layers, leading to suboptimal small object detection. To address this problem, we propose the Two-layer Attention Feature Pyramid Network (TA-FPN), featuring two key modules: the Two-layer Attention Module (TAM) and the… More > Graphic Abstract

Meijing Li^*, Runqing Huang, Xianxian Qi

CMC-Computers, Materials & Continua, Vol.80, No.2, pp. 2283-2299, 2024, DOI:10.32604/cmc.2024.053630 - 15 August 2024

Abstract Chinese Clinical Named Entity Recognition (CNER) is a crucial step in extracting medical information and is of great significance in promoting medical informatization. However, CNER poses challenges due to the specificity of clinical terminology, the complexity of Chinese text semantics, and the uncertainty of Chinese entity boundaries. To address these issues, we propose an improved CNER model, which is based on multi-feature fusion and multi-scale local context enhancement. The model simultaneously fuses multi-feature representations of pinyin, radical, Part of Speech (POS), word boundary with BERT deep contextual representations to enhance the semantic representation of text… More >

Zhibo Yang, Xiaohan Huang, Bingdong Wang, Bin Hu, Zhenyong Zhang^*

CMC-Computers, Materials & Continua, Vol.80, No.2, pp. 3001-3019, 2024, DOI:10.32604/cmc.2024.053369 - 15 August 2024

Abstract With the widespread use of machine learning (ML) technology, the operational efficiency and responsiveness of power grids have been significantly enhanced, allowing smart grids to achieve high levels of automation and intelligence. However, tree ensemble models commonly used in smart grids are vulnerable to adversarial attacks, making it urgent to enhance their robustness. To address this, we propose a robustness enhancement method that incorporates physical constraints into the node-splitting decisions of tree ensembles. Our algorithm improves robustness by developing a dataset of adversarial examples that comply with physical laws, ensuring training data accurately reflects possible More >

Kexin Wang^*, Yingdong Gou, Dingrui Xue^*, Jiancheng Liu, Wanlong Qi, Gang Hou, Bo Li

CMC-Computers, Materials & Continua, Vol.80, No.2, pp. 2941-2962, 2024, DOI:10.32604/cmc.2024.052893 - 15 August 2024

Abstract The collective Unmanned Weapon System-of-Systems (UWSOS) network represents a fundamental element in modern warfare, characterized by a diverse array of unmanned combat platforms interconnected through heterogeneous network architectures. Despite its strategic importance, the UWSOS network is highly susceptible to hostile infiltrations, which significantly impede its battlefield recovery capabilities. Existing methods to enhance network resilience predominantly focus on basic graph relationships, neglecting the crucial higher-order dependencies among nodes necessary for capturing multi-hop meta-paths within the UWSOS. To address these limitations, we propose the Enhanced-Resilience Multi-Layer Attention Graph Convolutional Network (E-MAGCN), designed to augment the adaptability of More >

Zhuoyifan Zhang¹, Lu Zhang², Liang Wang³, Haoming Wu^2,*

CMC-Computers, Materials & Continua, Vol.80, No.2, pp. 3405-3420, 2024, DOI:10.32604/cmc.2024.052144 - 15 August 2024

Abstract Research on neural radiance fields for novel view synthesis has experienced explosive growth with the development of new models and extensions. The NeRF (Neural Radiance Fields) algorithm, suitable for underwater scenes or scattering media, is also evolving. Existing underwater 3D reconstruction systems still face challenges such as long training times and low rendering efficiency. This paper proposes an improved underwater 3D reconstruction system to achieve rapid and high-quality 3D reconstruction. First, we enhance underwater videos captured by a monocular camera to correct the image quality degradation caused by the physical properties of the water medium… More >