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1,575 results on '"Tang, Xuan"'

61. Research on the evaluation method of rock brittleness characteristics based on stress-strain curve

Author

Tang Xuan and He Yi

Subjects
stress-strain curve, fragility, rock type, stress state, brittle cracking stage, 97m80, Mathematics, QA1-939
Abstract

In this study, not only the variability of the internal texture of rocks is considered in the in-depth investigation of the brittle fracture properties of rocks, but also the effects of different stress states and temperature factors on the fragility of rocks are focused on. Through experimental studies and data analysis of various types of rocks under different stress conditions and temperature environments, this study found that the plasticity of marble is positively related to stress. Under other stress states of 5, 15, 25, and 35 MPa, the stress-strain curves become flatter with increasing stress. Under uniaxial stress condition, the fragile strengths of different rocks are sandstone, red sandstone, granite, marble, chert, and cement mortar in that order. Whereas, under triaxial stress condition, the fragility of the rock samples was in the order of fine-grained granite, coarse-grained granite, sandstone, tuff, and marble. It was further found that the rock specimens after different high-temperature water-cooling treatments exhibited four different stages of brittle fracture, and the peak of the first stage of the rock was higher as the temperature decreased. The inclination of the peak was inversely proportional to the temperature. This study provides an essential scientific basis for the in-depth understanding of the brittle fracture characteristics of rocks and their engineering applications.

Published
2024
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62. A Cross-Platform Benchmark for Interval Computation Libraries

Author

Tang, Xuan, Ferguson, Zachary, Schneider, Teseo, Zorin, Denis, Kamil, Shoaib, Panozzo, Daniele, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Wyrzykowski, Roman, editor, Dongarra, Jack, editor, Deelman, Ewa, editor, and Karczewski, Konrad, editor

Published
2023
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63. Developing a Core Competency for Educarists in Guangdong, China

Author

Tang, Xuan and Mohamed Zainal, Siti Rohaida Binti

Subjects
Professional development -- Surveys -- Analysis, Early childhood education -- Surveys -- Analysis, Infants -- Surveys -- Training, Business
Abstract

Purpose: This study aims to explore the core competency of Educarists in early childhood education (ECE) in Guangdong, China. The objective of this core competency model is to enhance their professional development and subsequently to improve the quality of learning for both infants and toddlers during their early education stage. Design/methodology/approach: The study employs a mixed-methods research design comprising document review and analysis, interview techniques, and a questionnaire survey. Data are collected from recruitment information on Educarists. In adiditon, series of interview were conducted to gauge the internal perspective of the core competency. In addition, this study also applied the questionnaire survey among the Educarists in Guangdong, China. The questionnaire is to identify the factors that influence the professional development of Educarists and their competencies. Both approaches were designed to achieve the objective of this study which is to develop the core competency of Educarists in ECE. Findings: The findings highlight the importance of love, patience, good communication skills, and a passion for working with children, as well as a solid understanding of child development and the ability to design appropriate activities and adapt to individual needs. A competency model for Educarists is proposed, categorized into foundational, intermediate, and advanced competencies. These findings can assist the designing the training programs as well as to design of high-quality early childhood education programs in China. Research limitations/implications: The study is limited to the context of Guangdong, China, and its findings may need to be more generalizable to other regions or countries. Future research could replicate the study in other contexts to enhance the generalizability of the findings. Practical implications: The proposed competency model can serve as a framework for identifying the critical competencies required for Educarists in ECE, which can aid in recruitment, training, and performance evaluation. This study's results can also inform policy decisions and promote the overall improvement of the quality of early childhood education in China. Originality/value: This study can guide the development of training programs and professional development for Educarists, as well as the design and implementation of high-quality early childhood education programs in China. The study's findings can also serve as a foundation for future research in the field of early childhood education. Keywords: Educarists, Early Childhood Education, Core Competency Model, Human Resource Management., 1. Introduction In response to China's rapidly growing population and the evolution of the early childhood education (ECE) system, the role of Educarists has emerged to provide education and care [...]

Published
2023

86. Chitosan-derived carbon aerogel nanocomposite as an active electrode material for high-performance supercapacitors

Author

Le Hong Quan, Ung Thi Dieu Thuy, Pham Viet Nam, Nguyen Van Chi, Tang Xuan Duong, and Nguyen Van Hoa

Subjects
Chitosan, Chitosan-derived carbon, Aerogel nanocomposites, Supercapacitor, Materials of engineering and construction. Mechanics of materials, TA401-492
Abstract

The valorization of shrimp wastes to develop advanced materials brings economic and environmental advantages. This paper presents a facile and eco-friendly synthesis of shrimp chitosan-derived carbon (CCS) and CCS/NiO@Ni(OH)2 (CSSN) aerogel nanocomposite for supercapacitor application, in which NiO and Ni(OH)2 nanoparticles were tightly attached to the porous surface of CCS aerogel. As a result, CCSN-300 aerogel carbonized at 300 °C has high porosity and electrical conductivity and demonstrates its potential as an active electrode material for supercapacitors. The CCSN-300 aerogel material electrode exhibits a high capacitance of 316 mAh g−1 at 1.0 A g−1. Furthermore, the CCS//CCSN-300 device had a capacitance of 209 F g−1 at 1.0 A g−1 and over 84% remaining after the 10,000 cycles. Moreover, it has a high energy density of 65 Wh kg−1 at a power density of 1500 W kg−1. The results demonstrate that chitosan-derived carbon composites hold great promise in high application efficiency for energy storage.

Published
2023
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87. Joint Learning of Discriminative Low-dimensional Image Representations Based on Dictionary Learning and Two-layer Orthogonal Projections

Author

Wei, Xian, Shen, Hao, Li, Yuanxiang, Tang, Xuan, Jin, Bo, Zhao, Lijun, and Murphey, Yi Lu

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

There are some inadequacies in the language description of this paper that require further improvement. This paper is based on a revision of a conference paper. It is now necessary to further explain the difference between the contributions of the two papers., Comment: Some inappropriate descriptions have been found in this paper

Published
2019

88. 1D-Convolutional Capsule Network for Hyperspectral Image Classification

Author

Zhang, Haitao, Meng, Lingguo, Wei, Xian, Tang, Xiaoliang, Tang, Xuan, Wang, Xingping, Jin, Bo, and Yao, Wei

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

Recently, convolutional neural networks (CNNs) have achieved excellent performances in many computer vision tasks. Specifically, for hyperspectral images (HSIs) classification, CNNs often require very complex structure due to the high dimension of HSIs. The complex structure of CNNs results in prohibitive training efforts. Moreover, the common situation in HSIs classification task is the lack of labeled samples, which results in accuracy deterioration of CNNs. In this work, we develop an easy-to-implement capsule network to alleviate the aforementioned problems, i.e., 1D-convolution capsule network (1D-ConvCapsNet). Firstly, 1D-ConvCapsNet separately extracts spatial and spectral information on spatial and spectral domains, which is more lightweight than 3D-convolution due to fewer parameters. Secondly, 1D-ConvCapsNet utilizes the capsule-wise constraint window method to reduce parameter amount and computational complexity of conventional capsule network. Finally, 1D-ConvCapsNet obtains accurate predictions with respect to input samples via dynamic routing. The effectiveness of the 1D-ConvCapsNet is verified by three representative HSI datasets. Experimental results demonstrate that 1D-ConvCapsNet is superior to state-of-the-art methods in both the accuracy and training effort.

Published
2019

94. Learning Extremely Lightweight and Robust Model with Differentiable Constraints on Sparsity and Condition Number

Author

Wei, Xian, Xu, Yangyu, Huang, Yanhui, Lv, Hairong, Lan, Hai, Chen, Mingsong, Tang, Xuan, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Avidan, Shai, editor, Brostow, Gabriel, editor, Cissé, Moustapha, editor, Farinella, Giovanni Maria, editor, and Hassner, Tal, editor

Published
2022
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