Tiantian Wu

Zhengzhou University

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i-10 index

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Fucheng Wan

Minzu University of China

Fangtao Yang

Dalian University of Technology

Peijia Zhang

Zhengzhou University

Yu Wang

Xinxiang Medical University

Qiang Zhang

Hanzhong Central Hospital

Zihui Yao

Xinxiang Medical University

Sun Changqing

Zhengzhou University

Bo Hu

London School of Economics and Political Science

Lianke Wang

Zhengzhou University

Zhong Sheng-wen

Cooperative Institutions

Zhengzhou University

Minzu University of China

Beijing Microelectronics Technology Institute

Capital Normal University

Shanghai Jiao Tong University

Chinese Academy of Sciences

Huazhong University of Science and Technology

Beijing Normal University

Xinxiang Medical University

Sun Yat-sen University

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Negative emotions among Chinese primary and middle school students and association with screen time: A network analysis

Journal of Affective Disorders (2024)

Sun Changqing Bo Hu Peijia Zhang Tiantian Wu Lianke Wang

Association (psychology)

10.1016/j.jad.2024.11.030

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The research of the side-channel analysis method based on deep learning for trusted platform module

Journal of Physics Conference Series (2022)

Zhe Wang Hui Wang Yuning Yang Dejian Li Zhe Zhang

At present, the trusted platform module (TPM) has been widely used in electricity, finance, transportation, and other industries, and its security has attracted much attention. The research on the side-channel attack (SCA) can be conducive to improving the security design technology of trusted platform modules. The side channel attack on the trusted platform module is studied from the initial differential power analysis (DPA) to the machine learning method. This paper introduces the deep learning techniques in SCA and proposes a new SCA technique based on deep learning. Firstly, on basis of the characteristics of SCA on TPM, we improve the convolutional neural network (CNN) models, including ResNet, VGG, and Google Net. Then, for the SM4 cipher implemented with and without countermeasures, we implement some attack experiments by exploiting the SCA based on various deep learning models and compare the experimental results with the DPA attack. The experiment results show that under the same circumstance, the SCA based on the deep learning method is more effective. We compare the effects of different CNN models and hyper-parameters to provide the basis and data for further research.

10.1088/1742-6596/2358/1/012016

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An Integrated Model to Assess EFL Learners' Online Learning Behaviour

International Journal of Technology-Enhanced Education (2023)

Tiantian Wu

Bilibili is a widely popular video-sharing application in China. This study aims to develop a comprehensive model to investigate the behavior of Chinese English learners on Bilibili, based on the theory of planned behavior, technology acceptance model, past experience, and past behavior. Fifteen hypotheses were proposed and tested using smart partial least squares (smart PLS) with data collected from 223 participants. The findings revealed that learners' past experience and behavior influenced their subjective norms and perceived behavioral control of learning English in Bilibili. Perceived ease of use was found to be influenced by perceived usefulness. Subjective norms, perceived behavioral control, and perceived usefulness were identified as significant factors influencing learners' intention. However, attitude did not significantly influence intention. Furthermore, behavioral intention significantly impacted learners' actual behavior but perceived behavioral control did not. Future research could focus on refining the combination model in the online learning domain.

Technology Acceptance Model

10.4018/ijtee.323453

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C被覆は富LiMengカソード材料の低温性能を改善した。【JST・京大機械翻訳】

Dianyuan jishu (2016)

Tiantian Wu Xu Baohe Hu Wei Zhong Sheng-wen Chen Long

Source

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Depressive symptoms changes in the new-onset stroke patients: A cross-lagged panel network analysis

Journal of Affective Disorders (2025)

Peijia Zhang Sun Changqing Zhengqi Zhu Jianhang Miao Panpan Wang

Stroke

Depression

10.1016/j.jad.2025.02.071

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Research on Document Classification in the Field of Construction

Zhenyang Ren Fucheng Wan Hongzhi Yu Tiantian Wu

10.2991/iccia-19.2019.78

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Research on Recommendation system based on user portrait

Tiantian Wu Fangtao Yang Dongjiao Zhang Ao Zhu Fucheng Wan

One potential solution to the problem of information overload is the recommendation system, and the main task of recommendation system based on user portrait is to combine user and product, by mapping user portrait and product portrait, combining association rule mining and reordering algorithm, a personalized product recommendation list is obtained. Not only can help users find valuable information for themselves, but also can make the information displayed in front of interested users, so as to achieve a win-win situation between information consumers and information producers.

Portrait

Information Overload

10.1109/icaiis49377.2020.9194941

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Research on Edge Security Analysis Method Based on Decision Tree

2022 IEEE 4th International Conference on Power, Intelligent Computing and Systems (ICPICS) (2023)

Zhe Wang Hui Wang Dejian Li Jian Zhao Tianyu Yan

Based on the classification of ack, udp, and syn type abnormal traffic launched by worm programs, machine learning algorithms are used to achieve real-time classification of traffic generated by terminal devices, without affecting the normal business traffic of the terminal. After project evaluation and comparison of the performance of several classification and clustering models, the current model in the project is an algorithm implementation of decision tree type. Through experiments, it has been proven that the edge security analysis method based on decision trees is effective.

ID3 algorithm

Statistical classification

Traffic classification

Tree (set theory)

10.1109/icpics58376.2023.10235341

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Chinese shallow semantic parsing based on multilevel linguistic clues

Journal of Computational Methods in Sciences and Engineering (2020)

Fucheng Wan Fangtao Yang Tiantian Wu Dongjiao Zhang Lei Zhang

With rapid development of artificial intelligence and Chinese information processing technology, research related to natural language processing have reached the level of semantic understanding gradually, while Chinese Shallow Semantic Parsing is the key technique in the semantic understanding field. In this paper, a further improvement is conducted on the basic model of Chinese semantic role labeling for linear classification based on conditional random fields. In this paper, a method of combination of linguistic clues, combining with the existing linear sequence labeling algorithm and integrating some multilevel linguistic clues, such as morphology is related to syntax, in the model training to reconstruct and improve the Chinese semantic role labeling model of linear sequence. Through the experimental comparison and linguistic assistant analysis, this paper puts forward a targeted improvement method to significantly improve the accuracy of model labeling and proves that the integration of related linguistic clues in the semantic role labeling model based on linear sequence can improve the effect of model labeling.

Sequence labeling

Semantic role labeling

10.3233/jcm-194111

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Component Management Framework for Operating System Based on Microkernel Architecture

2022 China International Conference on Electricity Distribution (CICED) (2022)

Hui Wang Zeng Lin Dun Zhongqiang Yan Tianyu Zhao Xiaolong

Edge computing puts forward higher requirements on operating system in terms of security, real-time and scalability. Operating systems based on microkernel architecture can effectively meet these requirements. However, the current microkernel operating system lacks a general user-mode program organization and management mechanism, which makes it difficult to develop user-mode programs such as system services, device drivers and applications. To solve this problem, this paper proposes a system service dynamic construction framework based on dynamic loading and dynamic linking technology, proposes a capability-based component security mechanism, and proposes a cross-core IPC optimization method. Based on these mechanisms, an efficient, secure and flexible component management framework can be formed. We also developed a prototype system and verified it on a real hardware platform. The experimental data show that the component framework designed in this paper is efficient and secure.

Microkernel

Component (thermodynamics)

10.1109/ciced56215.2022.9929027

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