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2,312 results on '"Wang, Yuxiang"'

51. Preparation of Plant Protein Fiber and Its Application in the Food Field: A Review of Recent Research

Author

WANG Yuxiang, ZHENG Zhaojun, LIU Yuanfa

Subjects
plant protein fiber, preparation, application, plant-based meat, Food processing and manufacture, TP368-456
Abstract

Most natural plant protein molecules are spherical, and the excessively compact structure limits the nutrition and functionality of plant proteins. Spherical plant protein molecules can be transformed into plant protein fiber by various techniques such as molecular self-assembly, screw extrusion, shearing, wet spinning, electrospinning and solution blow spinning. Plant protein fiber is characterized by a high aspect ratio, clear molecular orientation, high mechanical strength, and strong functionality, and can be directly eaten, used as food additives or used to encapsulate active substances, which greatly expands the application of plant proteins in the food field and improves the added value of plant proteins. However, the addition of poisonous and harmful chemical reagents, and the morphological defects, poor stability, low yield and high production cost of plant protein fiber limit its wide popularization and industrial production. This article reviews the techniques for the preparation of plant protein fiber and its application in the food field, analyzes its advantages, disadvantages and limitations, and proposes future directions.

Published
2023
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52. Remaining Useful Life Prediction of IGBT Modules Across Working Conditions Based on ProbSparse Self-Attention

Author

ZHONG Zhiwei, WANG Yuxiang, HUANG Yixiang, XIAO Dengyu, XIA Pengcheng, LIU Chengliang

Subjects
insulated gate bipolar transistor(igbt) module, transient thermal resistance, remaining useful life (rul) prediction, probsparse self-attention, transfer learning, Engineering (General). Civil engineering (General), TA1-2040, Chemical engineering, TP155-156, Naval architecture. Shipbuilding. Marine engineering, VM1-989
Abstract

In order to improve the accuracy of remaining useful life (RUL) prediction of insulated gate bipolar transistor(IGBT) modules across working conditions to enhance their reliability, an RUL prediction method based on the ProbSparse self-attention mechanism and transfer learning was proposed based on the transient thermal resistance features of IGBT modules under different working conditions. An accelerated aging test bench of the IGBT module was designed ang built to perform power cycling experiments in different temperature ranges, and state data of full life-time under different working conditions were collected. Transient thermal resistance change data during the IGBT module degradation were calculated, and the transient thermal features that can accurately reflect the aging state of the IGBT module were extracted and selected. These features were used to predict the RUL of IGBT modules across different working conditions based on the proposed method. The experimental result shows that the accuracy of the proposed RUL prediction method of IGBT modules across working conditions outperforms other compared methods. Particularly, the RUL prediction accuracy during the early degradation stage has been significantly improved.

Published
2023
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53. COVID-19 Fake News Detection Using Bidirectional Encoder Representations from Transformers Based Models

Author

Wang, Yuxiang, Zhang, Yongheng, Li, Xuebo, and Yu, Xinyao

Subjects
Computer Science - Computation and Language
Abstract

Nowadays, the development of social media allows people to access the latest news easily. During the COVID-19 pandemic, it is important for people to access the news so that they can take corresponding protective measures. However, the fake news is flooding and is a serious issue especially under the global pandemic. The misleading fake news can cause significant loss in terms of the individuals and the society. COVID-19 fake news detection has become a novel and important task in the NLP field. However, fake news always contain the correct portion and the incorrect portion. This fact increases the difficulty of the classification task. In this paper, we fine tune the pre-trained Bidirectional Encoder Representations from Transformers (BERT) model as our base model. We add BiLSTM layers and CNN layers on the top of the finetuned BERT model with frozen parameters or not frozen parameters methods respectively. The model performance evaluation results showcase that our best model (BERT finetuned model with frozen parameters plus BiLSTM layers) achieves state-of-the-art results towards COVID-19 fake news detection task. We also explore keywords evaluation methods using our best model and evaluate the model performance after removing keywords.

Published
2021

68. Identifying modulation formats using integrated clustering algorithm

Author

Zhang, Wenbo, Ye, Jinmei, Yue, Zixian, Wang, Yuxiang, Zhang, Xulun, Zhang, Xiaoguang, and Xi, Lixia

Subjects
Electrical Engineering and Systems Science - Signal Processing
Abstract

Modulation format identification (MFI) is crucial in next-generation optical networks such as cognitive optical networks. An integrated-clustering-algorithm-based MFI scheme in a coherent optical communication system is proposed herein. Numerical simulations are performed to test the performance of the scheme on the platform of a polarization domain multiplexing system at a symbol rate of 28 Gbaud. Simulations show that the MFI scheme can achieve an accuracy of 100% for five modulation formats considered in this study when the optical signal-to-noise ratio values are lower than the 7% forward error correction threshold. Tolerances to residual chromatic dispersion (CD) are discussed, and the results show that the proposed scheme can perform well as the residual CD changes over a wide range of values. Moreover, by selecting a number of key blocks, the proposed scheme is less complex than other clustering-based MFI schemes.

Published
2021

70. Comparison of the evolutionary patterns of DNA repeats in ancient and young invertebrate species flocks of Lake Baikal

Author

Wang Yuxiang, T. E. Peretolchina, E. V. Romanova, and D. Y. Sherbakov

Subjects
dna repeats, lake baikal, phylogeny, baicaliidae, amphipods, evolution of repeats, repeatome, Genetics, QH426-470
Abstract

DNA repeat composition of low coverage (0.1–0.5) genomic libraries of four amphipods species endemic to Lake Baikal (East Siberia) and four endemic gastropod species of the fam. Baicaliidae have been compared to each other. In order to do so, a neighbor joining tree was inferred for each quartet of species (amphipods and mollusks) based on the ratio of repeat classes shared in each pair of species. The topology of this tree was compared to the phylogenies inferred for the same species from the concatenated protein-coding mitochondrial nucleotide sequences. In all species analyzed, the fraction of DNA repeats involved circa half of the genome. In relatively more ancient amphipods (most recent common ancestor, MRCA, existed approximately sixty millions years ago), the most abundant were species-specific repeats, while in much younger Baicaliidae (MRCA equal to ca. three millions years) most of the DNA repeats were shared among all four species. If the presence/absence of a repeat is regarded as a separate independent trait, and the ratio of shared to total numbers of repeats in a species pair is used as the measure of distance, the topology of the NJ tree is the same as the quartet phylogeny inferred for the mitogenomes protein coding nucleotide sequences. Meanwhile, in each group of species, a substantial number of repeats were detected pointing to the possibility of non-neutral evolution or a horizontal transfer between species occupying the same biotope. These repeats were shared by non-sister groups while being absent in the sister genomes. On the other hand, in such cases some traits of ecological significance were also shared.

Published
2023
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75. A Comprehensive Survey and Experimental Comparison of Graph-Based Approximate Nearest Neighbor Search

Author

Wang, Mengzhao, Xu, Xiaoliang, Yue, Qiang, and Wang, Yuxiang

Subjects
Computer Science - Information Retrieval, Computer Science - Databases
Abstract

Approximate nearest neighbor search (ANNS) constitutes an important operation in a multitude of applications, including recommendation systems, information retrieval, and pattern recognition. In the past decade, graph-based ANNS algorithms have been the leading paradigm in this domain, with dozens of graph-based ANNS algorithms proposed. Such algorithms aim to provide effective, efficient solutions for retrieving the nearest neighbors for a given query. Nevertheless, these efforts focus on developing and optimizing algorithms with different approaches, so there is a real need for a comprehensive survey about the approaches' relative performance, strengths, and pitfalls. Thus here we provide a thorough comparative analysis and experimental evaluation of 13 representative graph-based ANNS algorithms via a new taxonomy and fine-grained pipeline. We compared each algorithm in a uniform test environment on eight real-world datasets and 12 synthetic datasets with varying sizes and characteristics. Our study yields novel discoveries, offerings several useful principles to improve algorithms, thus designing an optimized method that outperforms the state-of-the-art algorithms. This effort also helped us pinpoint algorithms' working portions, along with rule-of-thumb recommendations about promising research directions and suitable algorithms for practitioners in different fields., Comment: 28 pages, 21 figures, 24 tables, conference

Published
2021

85. Semantic Guided and Response Times Bounded Top-k Similarity Search over Knowledge Graphs

Author

Wang, Yuxiang, Khan, Arijit, Wu, Tianxing, Jin, Jiahui, and Yan, Haijiang

Subjects
Computer Science - Databases
Abstract

Recently, graph query is widely adopted for querying knowledge graphs. Given a query graph $G_Q$, the graph query finds subgraphs in a knowledge graph $G$ that exactly or approximately match $G_Q$. We face two challenges on graph query: (1) the structural gap between $G_Q$ and the predefined schema in $G$ causes mismatch with query graph, (2) users cannot view the answers until the graph query terminates, leading to a longer system response time (SRT). In this paper, we propose a semantic-guided and response-time-bounded graph query to return the top-k answers effectively and efficiently. We leverage a knowledge graph embedding model to build the semantic graph $SG_Q$, and we define the path semantic similarity ($pss$) over $SG_Q$ as the metric to evaluate the answer's quality. Then, we propose an A* semantic search on $SG_Q$ to find the top-k answers with the greatest $pss$ via a heuristic $pss$ estimation. Furthermore, we make an approximate optimization on A* semantic search to allow users to trade off the effectiveness for SRT within a user-specific time bound. Extensive experiments over real datasets confirm the effectiveness and efficiency of our solution.

Published
2019

87. The discovery of three-dimensional Van Hove singularity

Author

Wu, Wenbin, Shi, Zeping, Ozerov, Mykhaylo, Du, Yuhan, Wang, Yuxiang, Ni, Xiao-Sheng, Meng, Xianghao, Jiang, Xiangyu, Wang, Guangyi, Hao, Congming, Wang, Xinyi, Zhang, Pengcheng, Pan, Chunhui, Pan, Haifeng, Sun, Zhenrong, Yang, Run, Xu, Yang, Hou, Yusheng, Yan, Zhongbo, Zhang, Cheng, Lu, Hai-Zhou, Chu, Junhao, and Yuan, Xiang

Published
2024
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92. Using Augmented Mean Arterial Pressure to Identify High Mortality Risk Patients With Moderate Aortic Stenosis

Author

Chao, Chieh-Ju, Agasthi, Pradyumma, Girardo, Marlene, Barry, Timothy, Seri, Amith R., Brown, Lisa, Wraith, Rachel E., Shanbhag, Anusha, Wang, Yuxiang, Chen, Yi-Chieh, Lester, Steven J., Alsidawi, Said, Freeman, William K., Naqvi, Tasneem Z., Eleid, Mackram, Fortuin, David, Pollak, Peter, El Sabbagh, Abdallah, Sell-Dottin, Kristen, Majdalany, David, Larsen, Carolyn, Holmes, David R., Oh, Jae K., Appleton, Christopher P., and Arsanjani, Reza

Published
2023
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99. Universal materials model of deep-learning density functional theory Hamiltonian

Author

Wang, Yuxiang, primary, Li, Yang, additional, Tang, Zechen, additional, Li, He, additional, Yuan, Zilong, additional, Tao, Honggeng, additional, Zou, Nianlong, additional, Bao, Ting, additional, Liang, Xinghao, additional, Chen, Zezhou, additional, Xu, Shanghua, additional, Bian, Ce, additional, Xu, Zhiming, additional, Wang, Chong, additional, Si, Chen, additional, Duan, Wenhui, additional, and Xu, Yong, additional

Published
2024
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