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5th International Conference on Computer science and Management Technology, ICCSMT 2024

作者： Hu, Ruijie Faculty of Science and Technology Guangdong Provincial Key Laboratory of Interdisciplinary Research and Application for Data Science BNU-HKBU United International College Zhuhai China

ISBN: (纸本)9798400709999

With the rapid development of financial markets, stock price prediction, as a highly complex and challenging topic, has attracted more and more attention from academia and industry. This study aims to use multiple machine learning algorithms to predict stock market prices, especially exploring the advantages of deep learning models in capturing market nonlinear and time series characteristics. In this article, a machine learning model is used for contribution analysis, analyzing multiple features of stocks, performing a weighted combination analysis of features, and then using a convolutional neural network to perform feature extraction and analysis of stocks, and combining the attention mechanism for deep feature extraction, and finally use the long short-term memory network (LSTM) model to output the model to analyze and predict future stock trends. The experimental results show that combining deep learning analysis technology and factor screening machine can significantly improve the prediction accuracy of the model. At the same time, this article also compared the performance of different models in different market environments, and concluded that in markets with higher volatility, models based on deep learning are more stable. Ultimately, this research provides a new technical means for risk management and investment decisions in financial markets. © 2024 Copyright held by the owner/author(s). Publication rights licensed to ACM.

关键词： Convolutional neural networks

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Research on θ -Intuitionistic Fuzzy Homomorphism Theory

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Journal of Applied Mathematics and Physics 2024年第10期12卷 3579-3589页

作者： Yue Wang Yan Yan Xinru Shang College of Science North China University of Science and Technology Tangshan China Hebei Key Laboratory of Data Science and Application Tangshan China

Fuzzy homomorphism is an important research content of fuzzy group theory, different fuzzy mappings will produce different fuzzy homomorphisms. In this paper, the fuzzy homomorphism of groups is generalized. Firstly, the θ-intuitionistic fuzzy mapping is defined, and the θ-intuitionistic fuzzy homomorphism of groups is obtained. The properties of intuitionistic fuzzy subgroups and intuitionistic fuzzy normal subgroups are studied under the θ-intuitionistic fuzzy homomorphism of groups, and the fundamental theorem of θ-intuitionistic fuzzy homomorphism is proved.

关键词： -Intuitionistic Fuzzy Homomorphism Intuitionistic Fuzzy Subgroup Intuitionistic Fuzzy Normal Subgroup

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Current Status of Objectification of Four Diagnostic Methods on Constitution Recognition of Chinese Medicine

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Chinese Journal of Integrative Medicine 2022年第12期28卷 1137-1146页

作者： LI Cong-cong YAN Xin-sheng LIU Ming-hao TENG Gui-fa School of Information Science and Technology Hebei Agricultural UniversityBaodingHebei Province 071001China Hebei Key Laboratory of Agricultural Big Data BaodingHebei Province 071001China

Chinese medicine(CM)has thousands of years of experience in prevention of *** for CM,people's constitution is closely related to their health status,thus recognition of CM constitution is the fundamental and core contentof research on constitution *** development of technologies such as sensors,arificial intelligence and big data,objectification of the four diagnostic methods of CM has gradually matured,bringing changes in the mindset and innovations in technical means for recognition of CM *** paper presents a systematic review of the latest research trends in constitution recognition based on objectification of diagnostic methods in CM.

关键词： Chinese medicine constitution recognition four diagnostic methods objectification machine learning deep learning

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Design and development of immersive 3D virtual simulation experiment teaching platform for internet of things

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Multimedia Tools and applications 2024年 1-15页

作者： Li, Yanan Li, Congcong Wang, Yijin Teng, Guifa College of Information Science & amp Technology Hebei Agricultural University No.289 Lingyusi Street Hebei Province Baoding071001 China Hebei Key Laboratory of Agricultural Big Data No.289 Lingyusi Street Hebei Province Baoding071001 China

The learning content of the Internet of Things (IoT) professional courses is closely related to reality, and has the characteristics of comprehensiveness, intersection and application. In order to solve the limitations of traditional practice teaching methods in time and space, and enhance the interaction of practice teaching, this project took the Internet of Things technology and application in virtual smart city as the research object, combined with advanced information technology, based on Bloom’s teaching objectives, a 3D virtual simulation experiment teaching platform composed of virtual equipment, and integrated data management and analysis services was established. The platform constructs a number of IoT 3D virtual simulation scenarios that emphasize professional technology and reflect the cutting-edge technology to create an immersive teaching environment. In addition, the platform contains multiple comprehensive experimental projects for exploratory research-based professional courses. Through the innovative experimental mode of integrating games, competitions, breakthroughs, explorations and flipped experiments, students’ interest in learning can be enhanced, and the overall quality of students’ practical ability, innovative spirit and learning ability can be improved. © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature 2024.

关键词： Virtual environments

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Microwave excited hyperthermy and catalysis of heterostructured Au/Cu–BTA for effective bacteria killing by accelerating charge separation

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Rare Metals 2024年第10期43卷 5186-5201页

作者： Wen-Jing Zhang Li-Guo Jin Shui-Lin Wu Chao-Feng Wang Yu-Feng Zheng Zhao-Yang Li Zhen-Duo Cui Hui Jiang Sheng-Li Zhu Xiang-Mei Liu School of Materials Science and Engineering the Key Laboratory of Advanced Ceramics and Machining Technology by the Ministry of Education of ChinaTianjin UniversityTianjin 300072China Biomedical Materials Engineering Research Center Hubei Key Laboratory of Polymer MaterialsMinistry-of-Education Key Laboratory for the Green Preparation and Application of Functional MaterialsSchool of Materials Science&EngineeringHubei UniversityWuhan 430062China School of Materials Science and Engineering Peking UniversityBeijing 100871China School of Health Science and Biomedical Engineering Hebei University of TechnologyTianjin 300401China

Deep tissue infections caused by pathogenic bacteria seriously threat the lives of *** this study a smart heterostructured Au/Cu-BTA(BTA=1,2,4,5-benzenetetramine)with microwave(MW)response is synthesized via NaBH_(4)reduction of HAuCl_(4)on the ***/Cu-BTA exhibits excellent hyperthermy and dynamics under MW *** MW thermal mechanism of Au/Cu-BTA is attributed to the excellen dielectric loss and polarization of the heterogeneous ***,the surface energy levels of the Cu-BTA interface alleviate the difficulty of electron hopping through multistage ***,MW can excite Cu-BTA to produce free ***,Au nanoparticles rapidly increase electron transfer and inhibit electron-hole ***,the yields of reactive oxygen species can be enhanced for MW dynamic therapy Consequently,under 10 min of MW irradiation,Au/Cu-BTA killed 99.998%±0.001% of Gram-positive Staphylococcus aureus,99.966%±0.014% of methicillin-resistant Staphylococcus aureus,and 96.871%±0.831% of Gram-negative Pseudomonas *** effective MW bacteria-killing strategy designed in this study shows significant potential for application in the MW-responsive treatment of deep tissue infections without antibiotics.

关键词： Microwave therapy Antibacterial Antiinfection

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Quantification and Validation for Degree of Understanding in M2M Semantic Communications 24

Quantification and Validation for Degree of Understanding in...

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24th IEEE International Conference on Communication Technology, ICCT 2024

作者： Xia, Linhan Cai, Jiaxin Hou, Ricky Yuen-Tan Jeong, Seon-Phil BNU-HKBU United International College Guangdong Provincial Key Laboratory of Interdisciplinary Research and Application for Data Science Zhuhai China

ISBN: (纸本)9798350363760

With the development of Artificial Intelligence (AI) and Internet of Things (IoT) technologies, network communications based on the Shannon-Nyquist theorem gradually reveal their limitations due to the neglect of semantic information in the transmitted content. Semantic communication (SemCom) provides a solution for extracting information meanings from the transmitted content. The semantic information can be successfully interpreted by a receiver with the help of a shared knowledge base (KB). This paper proposes a two-stage hierarchical qualification and validation model for natural language-based machine-to-machine (M2M) SemCom. The approach can be applied in various applications, such as autonomous driving and edge computing. In the proposed model, we quantitatively measure the degree of understanding (DoU) between two communication parties at the word and sentence levels. The DoU is validated and ensured at each level before moving to the next step. The model's effectiveness is verified through a series of experiments, and the results show that the quantification and validation method proposed in this paper can significantly improve the DoU of inter-machine SemCom. © 2024 IEEE.

关键词： Latent semantic analysis

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Can bidirectional encoder become the ultimate winner for downstream applications of foundation models? 2

Can bidirectional encoder become the ultimate winner for dow...

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2nd International Conference on Foundation and Large Language Models, FLLM 2024

作者： Yang, Lewen Zhou, Xuanyu Fan, Juao Xie, Xinyi Zhu, Shengxin BNU-HKBU United International College Guangdong Provincial Key Laboratory of Interdisciplinary Research and Application for Data Science Zhuhai China

ISBN: (纸本)9798350354799

Over the past few decades, Artificial Intelligence(AI) has progressed from the initial machine learning stage to the deep learning stage, and now to the stage of foundational models. Foundational models have the characteristics of pre-training, transfer learning, and self-supervised learning, and pre-trained models can be fine-tuned and applied to various downstream tasks. Under the framework of foundational models, models such as Bidirectional Encoder Representations from Transformers(BERT) and Generative Pre-trained Transformer(GPT) have greatly advanced the development of natural language processing(NLP), especially the emergence of many models based on BERT. BERT broke through the limitation of only using one-way methods for language modeling in pre-training by using a masked language model. It can capture bidirectional context information to predict the masked words in the sequence, this can improve the feature extraction ability of the model. This makes the model very useful for downstream tasks, especially for specialized applications. The model using the bidirectional encoder can better understand the domain knowledge and be better applied to these downstream tasks. So we hope to help understand how this technology has evolved and improved model performance in various natural language processing tasks under the background of foundational models and reveal its importance in capturing context information and improving the model's performance on downstream *** article analyzes one-way and bidirectional models based on GPT and BERT and compares their differences based on the purpose of the model. It also briefly analyzes BERT and the improvements of some models based on BERT. The model's performance on the Stanford Question Answering dataset(SQuAD) and General Language Understanding Evaluation(GLUE) was compared. © 2024 IEEE.

关键词： Self-supervised learning

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Dynamic updating approximations of local multigranulation neighborhood covering rough sets

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Soft Computing 2025年第6期29卷 2531-2550页

作者： Shi, Qi Zhang, Yan-Lan School of Computer Science Minnan Normal University Fujian Zhangzhou363000 China Key Laboratory of Data Science and Intelligence Application Fujian Province University Fujian Zhangzhou363000 China

The lower and upper approximations in rough set theory are important for dealing with uncertain knowledge. The covering rough set is an important part of the rough set theory and is suitable for dealing with numerical data. With the development of information technology, the information is constantly updated and changed in various information systems, and it is crucial to efficiently obtain the lower and upper approximations in dynamic environments. In this paper, the matrix-based methods for updating the approximate operators of local multigranulation neighborhood covering rough sets when objects are added or deleted are mainly investigated. Firstly, the local multigranulation neighborhood covering rough set model is introduced. Then, we analyze the relationships between the prior matrices and the updating matrices when objects change. Meanwhile, the dynamic updating processes for lower and upper approximations are proposed. The time complexity analyses of algorithms theoretically prove the efficiency of dynamic algorithms compared with static ones. To illustrate the effectiveness of the proposed dynamic algorithms, six datasets from the UCI are employed for comparative experiments. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2025.

关键词： Knowledge based systems

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Robust and Trustworthy data Sharing Framework Leveraging On-Chain and Off-Chain Collaboration

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Computers, Materials & Continua 2024年第2期78卷 2159-2179页

作者： Jinyang Yu Xiao Zhang Jinjiang Wang Yuchen Zhang Yulong Shi Linxuan Su Leijie Zeng School of Computer Science Northwestern Polytechnical UniversityXi’an710072China MIIT Key Laboratory of Big Data Storage and Management Northwestern Polytechnical UniversityXi’an710072China National Engineering Laboratory for Integrated Aero-Space-Ground-Ocean Big Data Application Technology Northwestern Polytechnical UniversityXi’an710072China

The proliferation of Internet of Things(IoT)systems has resulted in the generation of substantial data,presenting new challenges in reliable storage and trustworthy *** distributed storage systems are hindered by centralized management and lack traceability,while blockchain systems are limited by low capacity and high *** address these challenges,the present study investigates the reliable storage and trustworthy sharing of IoT data,and presents a novel system architecture that integrates on-chain and off-chain data manage *** architecture,integrating blockchain and distributed storage technologies,provides high-capacity,high-performance,traceable,and verifiable data storage and *** on-chain system,built on Hyperledger Fabric,manages metadata,verification data,and permission information of the raw *** off-chain system,implemented using IPFS Cluster,ensures the reliable storage and efficient access to massive files.A collaborative storage server is designed to integrate on-chain and off-chain operation interfaces,facilitating comprehensive data *** provide a unified access interface for user-friendly system *** testing validates the system’s reliability and stable *** proposed approach significantly enhances storage capacity compared to standalone blockchain *** reliability tests consistently yield positive *** average upload and download throughputs of roughly 20 and 30 MB/s,respectively,the system’s throughput surpasses the blockchain system by a factor of 4 to 18.

关键词： On-chain and off-chain collaboration blockchain distributed storage system hyperledger fabric IPFS cluster

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Graphite Growth and Shrinkage Formation During Solidification of CGI 75

Graphite Growth and Shrinkage Formation During Solidificatio...

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75th World Foundry Congress, WFC 2024

作者： Liu, Jinhai Fu, Binguo Xue, Haitao Zhao, Xuebo Zhang, Guixian Liu, Hongchen School of Materials Science and Engineering Hebei University of Technology Tianjin300401 China Key Laboratory of Research and Application of Glass Rubber and Plastic Mold Materials in Hebei Province Hebei Huanghua061100 China

The morphology and evolution of the graphite have an important impact on the mechanical properties and shrinkage tendency of the compacted graphite cast iron (CGI). Compared to gray cast iron and ductile iron, there is relatively little understanding of the graphite precipitation behavior during the solidification process of CGI. Therefore, the precipitation and evolution behavior of graphite during the solidification process of hypoeutectic, eutectic, and hypereutectic CGI was systematically investigated based on thermal analysis, liquid quenching experiments, and metallographic analysis. Results demonstrate that the thermal analysis curve characteristics of three types of CGI are significantly different from the ideal curves. The closer the composition of hypoeutectic CGI is to the eutectic point, the higher the vermicularity and the smaller the shrinkage tendency. The primary graphite precipitated during solidification of hypereutectic CGI is spherical or exploded shaped, and the further away from the eutectic point, the larger the volume fraction of graphite balls, the lower the vermicularity, and there is theaustenite dendrite precipitation before eutectic reaction, which increases the probability of shrinkage porosity in hypereutectic CGI. The solidification of eutectic CGI is prone to the formation of a large amount of vermicular graphite, with a higher vermicularity and the smallest shrinkage tendency. The tendency of eutectic CGI to produce leakage is relatively small. © 2024 75th World Foundry Congress, WFC 2024. All rights reserved.

关键词： Quenching

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