Lu Zhang^1,*, Yuzhuo Wang¹, Zhiwei Yu¹, Rong Jiang¹, Liguo Zhao¹, Yingdong Song^1,2

The International Conference on Computational & Experimental Engineering and Sciences, Vol.30, No.3, pp. 1-2, 2024, DOI:10.32604/icces.2024.012701

Abstract Thermo-mechanical fatigue (TMF), as the main failure mode of hot components of an aeroengine, are increasingly investigated recently [1,2]. TMF crack growth is studied in a nickel-based powder metallurgy (PM) superalloy subjected to in-phase (IP) and out-of-phase (OP), as well as isothermal fatigue (IF) at peak temperature. The crack growth rate and path are evaluated for both coarse grain (CG) and fine grain (FG) structure, especially the effects of phase angle and polycrystalline microstructure. The results show that the TMF crack propagation is mainly transgranular in OP condition; while in IP condition, crack propagates intergranularly… More >

Dhia K. Suker, Ahmed R. Abdo^*, Khalid Abdulkhaliq M. Alharbi

Intelligent Automation & Soft Computing, Vol.39, No.5, pp. 929-947, 2024, DOI:10.32604/iasc.2024.056341 - 31 October 2024

Abstract This paper presents a deep learning Convolutional Neural Network (CNN) for predicting grain orientations from electron backscatter diffraction (EBSD) patterns. The proposed model consists of multiple neural network layers and has been trained on a dataset of EBSD patterns obtained from stainless steel 316 (SS316). Grain orientation changes when considering the effects of temperature and strain rate on material deformation. The deep learning CNN predicts material orientation using the EBSD method to address this challenge. The accuracy of this approach is evaluated by comparing the predicted crystal orientation with the actual orientation under different conditions, More >

Longgang Zhao¹, Seok-Won Lee^2,*

CMC-Computers, Materials & Continua, Vol.81, No.1, pp. 1855-1877, 2024, DOI:10.32604/cmc.2024.056215 - 15 October 2024

Abstract Although sentiment analysis is pivotal to understanding user preferences, existing models face significant challenges in handling context-dependent sentiments, sarcasm, and nuanced emotions. This study addresses these challenges by integrating ontology-based methods with deep learning models, thereby enhancing sentiment analysis accuracy in complex domains such as film reviews and restaurant feedback. The framework comprises explicit topic recognition, followed by implicit topic identification to mitigate topic interference in subsequent sentiment analysis. In the context of sentiment analysis, we develop an expanded sentiment lexicon based on domain-specific corpora by leveraging techniques such as word-frequency analysis and word embedding. More >

Menghan Zhang^1,2, Fangfang Shan^1,2,*, Mengyao Liu^1,2, Zhenyu Wang^1,2

CMC-Computers, Materials & Continua, Vol.81, No.1, pp. 1565-1580, 2024, DOI:10.32604/cmc.2024.056008 - 15 October 2024

Abstract With the emergence and development of social networks, people can stay in touch with friends, family, and colleagues more quickly and conveniently, regardless of their location. This ubiquitous digital internet environment has also led to large-scale disclosure of personal privacy. Due to the complexity and subtlety of sensitive information, traditional sensitive information identification technologies cannot thoroughly address the characteristics of each piece of data, thus weakening the deep connections between text and images. In this context, this paper adopts the CLIP model as a modality discriminator. By using comparative learning between sensitive image descriptions and… More >

Hui Liu¹, Xu Song^1,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.29, No.2, pp. 1-1, 2024, DOI:10.32604/icces.2024.011362

Abstract Because of its higher specific strength and better biocompatibility, commercially pure titanium (CP Ti) is widely used for product fabrication in the aerospace, medical, and other industries. Currently, different ways are adopted to strengthen CP Ti, such as solid-solution strengthening using oxygen or adding metal components to form alloys; however, the introduction of oxygen, other gases, or alloying elements reduces the corrosion resistance and biocompatibility. Herein, CP Ti with a low oxygen content was used to fabricate samples via a high-precision laser powder bed fusion process. Smaller laser beam diameter and thinner layer thickness lead More >

Sihui Tong¹, Boyuan Cao¹, Dongqing Tian², Qinwei Ma¹, Guangyan Liu^1,*, Li Shi², Libin Sun²

The International Conference on Computational & Experimental Engineering and Sciences, Vol.29, No.1, pp. 1-1, 2024, DOI:10.32604/icces.2024.010870

Abstract Graphite materials serve critical roles as moderators, reflectors and core structural components in high-temperature gas-cooled nuclear reactors. These materials may experience a variety of loads during the reactor operation, including thermal, radiation, fatigue and dynamic loads, potentially leading to crack initiation and propagation. Consequently, it is imperative to investigate the fracture properties of graphite materials. Currently, there exists a dearth of comprehensive studies on the fracture toughness of graphite materials with varying grain sizes, especially regarding dynamic fracture toughness. This study introduces a novel approach utilizing a digital-image-correlation-based virtual extensometer to analyze crack propagation in… More >

Gonghui Deng, Dunzhi Wu, Weizhen Chen^*

CMC-Computers, Materials & Continua, Vol.80, No.2, pp. 1985-2003, 2024, DOI:10.32604/cmc.2024.052174 - 15 August 2024

Abstract The task of food image recognition, a nuanced subset of fine-grained image recognition, grapples with substantial intra-class variation and minimal inter-class differences. These challenges are compounded by the irregular and multi-scale nature of food images. Addressing these complexities, our study introduces an advanced model that leverages multiple attention mechanisms and multi-stage local fusion, grounded in the ConvNeXt architecture. Our model employs hybrid attention (HA) mechanisms to pinpoint critical discriminative regions within images, substantially mitigating the influence of background noise. Furthermore, it introduces a multi-stage local fusion (MSLF) module, fostering long-distance dependencies between feature maps at… More >

Adel A. Rezk^1,2,*, Mohamed M. El-Malky³, Heba I. Mohamed^4,*, Hossam S. El-Beltagi^1,5

Phyton-International Journal of Experimental Botany, Vol.93, No.7, pp. 1733-1748, 2024, DOI:10.32604/phyton.2024.052739 - 30 July 2024

Abstract Twenty-four rice genotypes were examined to assess genetic variability, heritability, and correlations for seven-grain quality traits, eight nutritional elements, and protein. ANOVA revealed significant differences for the quality traits studied. For every trait under study, the phenotypic coefficient of variation was higher than the correspondence genotypic coefficient of variation. Heritability in a broad sense varied from 29.75% for grain length to 98.31% for the elongation trait. Hulling percentage recovery had a highly significant positive correlation with milling and head rice percentage. Consequently, milling percentage had a highly positive correlation with head rice percentage. In amylose… More >

Pengcheng Li^1,2,#, Tianze Zhu^1,#, Yunyun Wang^1,2, Shuangyi Yin¹, Xinjie Zhu¹, Minggang Ji¹, Wenye Rui¹, Houmiao Wang¹, Zefeng Yang^1,2,*, Chenwu Xu^1,2,*

Phyton-International Journal of Experimental Botany, Vol.93, No.7, pp. 1441-1453, 2024, DOI:10.32604/phyton.2024.052219 - 30 July 2024

Abstract The nutritional composition and overall quality of maize kernels are largely determined by the key chemical components: protein, oil, and starch. Nevertheless, the genetic basis underlying these nutritional quality traits during grain filling remains poorly understood. In this study, the concentrations of protein, oil, and starch were studied in 204 recombinant inbred lines resulting from a cross between DH1M and T877 at four different stages post-pollination. All the traits exhibited considerable phenotypic variation. During the grain-filling stage, the levels of protein and starch content generally increased, whereas oil content decreased, with significant changes observed between… More >

Abida Aziz¹, Shafiqa Bano¹, Mubshar Hussain², Muhammad Farooq Azhar³, Ghulam Yasin³, Naila Hadayat⁴, Iqra Arooj⁵, Abeer Hashem⁶, Ajay Kumar⁷, Elsayed Fathi Abd_Allah⁸, Qamar uz Zaman^9,10,*

Phyton-International Journal of Experimental Botany, Vol.93, No.7, pp. 1647-1665, 2024, DOI:10.32604/phyton.2024.050974 - 30 July 2024

Abstract Wheat (Triticum aestivum L.) exhibits a greater capacity for cadmium (Cd) absorption compared to other cereal crops, leading to elevated daily Cd intake, and posing a significant threat to public health. For the mitigation of Cd stress in sustainable and environmentally friendly way, a pot study was designed by using exogenous application of various biostimulants, i.e., Nigella sativa and Ocimum sanctum extracts: 0%, 10%, and 20% in combination with the chelating agent ethylenediaminetetraacetic acid (EDTA) using 0 and 5 mg kg under various levels of Cd stress (i.e., 0, 5, 10, and 15 mg kg soil). Results revealed… More > Graphic Abstract