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2,571 results on '"Guo, Jingjing"'

1. MSSC-BiMamba: Multimodal Sleep Stage Classification and Early Diagnosis of Sleep Disorders with Bidirectional Mamba

Author

Zhang, Chao, Cui, Weirong, and Guo, Jingjing

Subjects
Computer Science - Artificial Intelligence
Abstract

Monitoring sleep states is essential for evaluating sleep quality and diagnosing sleep disorders. Traditional manual staging is time-consuming and prone to subjective bias, often resulting in inconsistent outcomes. Here, we developed an automated model for sleep staging and disorder classification to enhance diagnostic accuracy and efficiency. Considering the characteristics of polysomnography (PSG) multi-lead sleep monitoring, we designed a multimodal sleep state classification model, MSSC-BiMamba, that combines an Efficient Channel Attention (ECA) mechanism with a Bidirectional State Space Model (BSSM). The ECA module allows for weighting data from different sensor channels, thereby amplifying the influence of diverse sensor inputs. Additionally, the implementation of bidirectional Mamba (BiMamba) enables the model to effectively capture the multidimensional features and long-range dependencies of PSG data. The developed model demonstrated impressive performance on sleep stage classification tasks on both the ISRUC-S3 and ISRUC-S1 datasets, respectively containing data with healthy and unhealthy sleep patterns. Also, the model exhibited a high accuracy for sleep health prediction when evaluated on a combined dataset consisting of ISRUC and Sleep-EDF. Our model, which can effectively handle diverse sleep conditions, is the first to apply BiMamba to sleep staging with multimodal PSG data, showing substantial gains in computational and memory efficiency over traditional Transformer-style models. This method enhances sleep health management by making monitoring more accessible and extending advanced healthcare through innovative technology., Comment: 10 pages

Published
2024

2. Tracking Knowledge Evolution in Cloud Health Care Research: Knowledge Map and Common Word Analysis

Author

Gu, Dongxiao, Yang, Xuejie, Deng, Shuyuan, Liang, Changyong, Wang, Xiaoyu, Wu, Jiao, and Guo, Jingjing

Subjects
Computer applications to medicine. Medical informatics, R858-859.7, Public aspects of medicine, RA1-1270
Abstract

BackgroundWith the continuous development of the internet and the explosive growth in data, big data technology has emerged. With its ongoing development and application, cloud computing technology provides better data storage and analysis. The development of cloud health care provides a more convenient and effective solution for health. Studying the evolution of knowledge and research hotspots in the field of cloud health care is increasingly important for medical informatics. Scholars in the medical informatics community need to understand the extent of the evolution of and possible trends in cloud health care research to inform their future research. ObjectiveDrawing on the cloud health care literature, this study aimed to describe the development and evolution of research themes in cloud health care through a knowledge map and common word analysis. MethodsA total of 2878 articles about cloud health care was retrieved from the Web of Science database. We used cybermetrics to analyze and visualize the keywords in these articles. We created a knowledge map to show the evolution of cloud health care research. We used co-word analysis to identify the hotspots and their evolution in cloud health care research. ResultsThe evolution and development of cloud health care services are described. In 2007-2009 (Phase I), most scholars used cloud computing in the medical field mainly to reduce costs, and grid computing and cloud computing were the primary technologies. In 2010-2012 (Phase II), the security of cloud systems became of interest to scholars. In 2013-2015 (Phase III), medical informatization enabled big data for health services. In 2016-2017 (Phase IV), machine learning and mobile technologies were introduced to the medical field. ConclusionsCloud health care research has been rapidly developing worldwide, and technologies used in cloud health research are simultaneously diverging and becoming smarter. Cloud–based mobile health, cloud–based smart health, and the security of cloud health data and systems are three possible trends in the future development of the cloud health care field.

Published
2020
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22. Gated Deeper Models are Effective Factor Learners

Author

Guo, Jingjing

Subjects
Quantitative Finance - Pricing of Securities, Computer Science - Machine Learning
Abstract

Precisely forecasting the excess returns of an asset (e.g., Tesla stock) is beneficial to all investors. However, the unpredictability of market dynamics, influenced by human behaviors, makes this a challenging task. In prior research, researcher have manually crafted among of factors as signals to guide their investing process. In contrast, this paper view this problem in a different perspective that we align deep learning model to combine those human designed factors to predict the trend of excess returns. To this end, we present a 5-layer deep neural network that generates more meaningful factors in a 2048-dimensional space. Modern network design techniques are utilized to enhance robustness training and reduce overfitting. Additionally, we propose a gated network that dynamically filters out noise-learned features, resulting in improved performance. We evaluate our model over 2,000 stocks from the China market with their recent three years records. The experimental results show that the proposed gated activation layer and the deep neural network could effectively overcome the problem. Specifically, the proposed gated activation layer and deep neural network contribute to the superior performance of our model. In summary, the proposed model exhibits promising results and could potentially benefit investors seeking to optimize their investment strategies., Comment: 7 pages

Published
2023

24. Federated Learning: Bridging Data Privacy and Model Accuracy on JointCloud

Author

Guo, Jingjing, Yi, Bo, Wang, Xingwei, Zhang, Jiaxin, Lv, Enliang, Zhang, Kaimin, Qiu, Lin, Goos, Gerhard, Series 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, Huang, De-Shuang, editor, Zhang, Xiankun, editor, and Zhang, Qinhu, editor

Published
2024
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25. Preparation and Performance Test of Electrophoretic Particles Modified by Nano TiO2

Author

Guo, Jingjing, Zhang, Chunxiu, Liao, Ruijuan, Fang, Yi, Feng, Yuguang, Song, Xiaoli, Zhang, Ao, Yang, Yonggang, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Li, Yong, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Oneto, Luca, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zamboni, Walter, Series Editor, Zhang, Junjie James, Series Editor, Tan, Kay Chen, Series Editor, Song, Huihui, editor, Xu, Min, editor, Yang, Li, editor, Zhang, Linghao, editor, and Yan, Shu, editor

Published
2024
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38. Preparation and anticorrosion property of MXene@PANI based PU composite coating

Author

GUO Jingjing, WANG Qiguan, WANG Feifei, and WANG Sumin

Subjects
polyaniline, ti3c2tx, composite, polyurethane, anticorrosion performance, Materials of engineering and construction. Mechanics of materials, TA401-492
Abstract

In order to enhance the physical barrier performance of polyaniline(PANI)/polyurethane(PU) coating against corrosive medium, the introduction of two-dimensional material in the coating is one of the effective methods. PU coating matrix was synthesized from 2, 4-diisocyanate (TDI) and 3, 3′-dichloro-4, 4′-diamino diphenylmethane(MOCA), and MXene@PANI was synthesized by intercalation reaction of PANI with Ti3C2Tx.Then protective coating of MXene@PANI/PU was obtained by adding MXene@PANI into PU. The results show that when the mass ratio of MXene/PANI is 1∶1, no obvious corrosion occurs on the surface of the MXene@PANI/PU coating after 60 days of salt spraying. The corrosion current is 3.709×10-9 A·cm-2, and the impedance modulus is 1.93×108 Ω·cm2. The reason is that MXene improves the electrochemical activity of PANI and thus enhances the electrochemical anticorrosion performance of PANI. On the other hand, MXene nanoplates as a two-dimensional barrier can prevent the corrosive medium from entering into the coating, which improves the long-term protective performance of the coating.

Published
2023
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