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2024 International Conference on Optics, Electronics, and Communication Engineering, OECE 2024

作者： Wang, Dong Wu, Pianhui Big Data and Computing Institute Guangdong Baiyun University Guangdong Guangzhou510450 China School of Mechatornic Engineering Guangdong Polytechnic Normal University Guangdong Guangzhou510450 China

ISBN: (纸本)9781510685437

The fatigue detection method based on neural network has been widely applied in the field of land transportation. The accuracy varies by different methods and solutions. Disadvantages of current widely applied methods for fatigue detection have been exposed by rational review, e.g., cost-effective, potable implementation issues. Cascade width learning based detection method with outstanding features is a sound solution to overcome shortcomings of other traditional detection methods. Therefore, it is of great significance and value to research this method and present its academic value and applicable values. This paper introduces a cascade width learning based fatigue detection method. The paper looks forward to development of cascade width learning based fatigue detection method, both academic and applicable values of proposed method have been presented by rational evaluation based on rational discussion on experimental results, the results prove that proposed method has achieved 94.9% accuracy in 52.43ms, which suggests more accuracy and fast speed than other common methods including: combinations of LBP and SVM, ASM and Fuzzy, CNN and PERCLO. © 2024 SPIE.

关键词： Eye Material fatigue Machine learning Mouth Head Neural networks Education and training Signal detection Video Visualization

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A Review of Multimedia Video Services Based on Serverless Cloud computing

A Review of Multimedia Video Services Based on Serverless Cl...

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2023 IEEE International Symposium on Broadband Multimedia Systems and Broadcasting, BMSB 2023

作者： Su, Yue Sang, Liu Zhao, Weibo Li, Wei Yuan, Changqing China Academy of Information and Communications Technology Cloud Computing & Big Data Research Institute Beijing China Academy of Telecommunications Technology Beijing China

ISBN: (纸本)9798350321524

Cloud computing technology has achieved rapid growth in recent years. Serverless cloud computing has been applied in more and more scenarios due to its pay-as-you-go, event-driven, and flexible features. This article introduces the application of serverless cloud computing technology in multimedia video services, analyzes the key capabilities, and looks forward to the key development directions in the future. © 2023 IEEE.

关键词： Cloud computing

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A Novel Approach to Panel data Clustering: Integrating Feature Extraction and Weighted Distance Functions 4

A Novel Approach to Panel Data Clustering: Integrating Featu...

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4th International Conference on Artificial Intelligence and Computer Engineering, ICAICE 2023

作者： Ao, Xiqin Abisado, Mideth College of Computing and Information Technologies National University Manila Philippines Institute of Big Data and Artificial Intelligence Anhui Xinhua University Anhui China

ISBN: (纸本)9798400708831

The traditional clustering method for two-dimensional information is unsuitable for processing panel data. A weighted panel data clustering method based on feature extraction is proposed based on the investigation of multiple information features of panel data. The technique first defines a distance function that considers the absolute value of the indicator, the growth rate of adjacent time points, and the degree of fluctuation variation. Then, the indicator weights and time weights are aggregated into a comprehensive weighted distance through a linear model, and the clustering process of panel data is implemented based on the Ward clustering method. Finally, empirical analysis using consumption expenditure data of various regions in China shows that this clustering analysis method has better discrimination ability and can improve the accuracy of sample clustering. © 2023 ACM.

关键词： Feature extraction

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AlphaFold2 and its applications in the fields of biology and medicine

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Signal Transduction and Targeted Therapy 2023年第4期8卷 1630-1643页

作者： Zhenyu Yang Xiaoxi Zeng Yi Zhao Runsheng Chen West China Biomedical Big Data Center West China HospitalSichuan UniversityChengdu 610041China Key Laboratory of Intelligent Information Processing Advanced Computer Research CenterInstitute of Computing TechnologyChinese Academy of SciencesBeijing 100190China Key Laboratory of RNA Biology Center for Big Data Research in HealthInstitute of BiophysicsChinese Academy of SciencesBeijing 100101China Pingshan Translational Medicine Center Shenzhen Bay LaboratoryShenzhen 518118China

AlphaFold2(AF2)is an artificial intelligence(AI)system developed by DeepMind that can predict three-dimensional(3D)structures of proteins from amino acid sequences with atomic-level *** structure prediction is one of the most challenging problems in computational biology and chemistry,and has puzzled scientists for 50 *** advent of AF2 presents an unprecedented progress in protein structure prediction and has attracted much *** release of structures of more than 200 million proteins predicted by AF2 further aroused great enthusiasm in the science community,especially in the fields of biology and ***2 is thought to have a significant impact on structural biology and research areas that need protein structure information,such as drug discovery,protein design,prediction of protein function,et *** the time is not long since AF2 was developed,there are already quite a few application studies of AF2 in the fields of biology and medicine,with many of them having preliminarily proved the potential of *** better understand AF2 and promote its applications,we will in this article summarize the principle and system architecture of AF2 as well as the recipe of its success,and particularly focus on reviewing its applications in the fields of biology and *** of current AF2 prediction will also be discussed.

关键词： system fields Fold

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Construction of user Portrait System Based on information warehouse under big data 2

Construction of user Portrait System Based on information wa...

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2022 2nd International Conference on Artificial Intelligence, big data and Algorithms, CAIBDA 2022

作者： Fang, Yaxin Liu, Zhonglin Li, Changbao Pan, Shuang North China Institute of Computing Technology Big Data Analysis Department Beijing100083 China

ISBN: (纸本)9783800760268

With the continuous development of Internet technology, the scale of data volume shows an explosive growth *** this case, the traditional user portrait system will have problems such as insufficient data storage and slow calculation. Based on this, this paper designs a user portrait technology based on information warehouse under big data. Through the data acquisition module, the distributed information collection is carried out to complete data acquisition, data cleaning and zoning. Through the data warehouse hierarchical operation, the data is accumulated and summarized, and complex tasks are resolved into multiple simple tasks. It is convenient to locate problems, improve the reusability of calculation results, and decouple original data and statistical data. Through user portrait management platform module, the labels are classified, customized[For the labels of statistical classes are distributed and aggregated through spark. For the labels of mining classes, K-means algorithm is used to build a multi-level user portrait model. The storage of portrait data and the screening of multi label combination are realized through the user clustering module. The experimental results show that the system is suitable for the construction of user portrait in the case of large amount of data[The advantages of the system are lower delay and stable accuracy. © VDE VERLAG GMBH ∙ Berlin ∙ Offenbach.

关键词： big data

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ELLIPTIC EQUATION WITH CRITICAL EXPONENT AND DIPOLE POTENTIAL: EXISTENCE AND DECAY ESTIMATES

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Acta Mathematica Scientia 2025年第2期45卷 636-658页

作者： Yu SU Zhisu LIU Senli LIU School of Mathematics and Big Data Anhui University of Science and TechnologyHuainan 232001China School of Mathematics and Physics China University of GeosciencesWuhan 430074China Institute for Advanced Marine Research China University of GeosciencesGuangzhou 511462China College of Mathematics and Computing Science Hunan University of Science and TechnologyXiangtan 411201China

The paper is concerned with a class of elliptic equation with critical exponent and Dipole *** precisely,we make use of the refined Sobolev inequality with Morrey norm to obtain the existence and decay properties of n... 详细信息

关键词： Dipole potential decay estimation Hardy Sobolev critical exponent Henon Sobolev critical exponent

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Remaining Useful Life Prediction of Degraded Systems Based on Multiple Performance Indicators Constructed by Multiple Features

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IEEE Sensors Journal 2025年第11期25卷 19613-19631页

作者： Wu, Bin Shi, Hui Zeng, Jianchao Zhang, Xiaohong Wang, Zhijian Wang, Zuolu Taiyuan University of Science and Technology School of Electronic Information Engineering Taiyuan030024 China North University of China institute for Big Data and Visual Computing Taiyuan030051 China University of Huddersfield Centre for Efficiency and Performance Engineering HuddersfieldHD1 3DH United Kingdom

The health status assessment of industrial equipment is critical to fault prediction and health management technologies. To fully reflect system degradation and accurately predict the remaining useful life (RUL) of a system, the construction of multiple performance indicators is important. Thus, a new state-space model and RUL prediction method is proposed herein based on multiple indicators, considering the three correlation relationships among features and degradation indicators. First, according to the extracted and selected feature signals, various relationships such as the correlations among multiple features, multiple features and indicators, and multiple indicators are analyzed. Then an intuitive multi-indicator state-space model is established considering the three correlations and the identified degradation patterns. On this basis, three failure modes of the system are defined according to the multi-indicator complex correlation conditions, and the corresponding probability density function of the system RUL is calculated. Finally, the PHM2012 Challenge and XJTU-SY datasets are used as examples for experimental verification. Compared with other prediction methods, the proposed method can intuitively reflect the correlation between features and indicators, to solve the problem caused by the hidden random correlation. © 2001-2012 IEEE.

关键词： Prediction models

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Informed Spectral Normalized Gaussian Processes for Trajectory Prediction 27

Informed Spectral Normalized Gaussian Processes for Trajecto...

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27th European Conference on Artificial Intelligence, ECAI 2024

作者： Schlauch, Christian Wirth, Christian Klein, Nadja Continental Automotive Technologies GmbH AI Lab Berlin Germany Humboldt-Universität zu Berlin Germany Karlsruhe Institute of Technology Scientific Computing Center Methods for Big Data Germany

ISBN: (纸本)9781643685489

Prior parameter distributions provide an elegant way to represent prior expert knowledge for informed learning. Previous work has shown that using such informative priors to regularize probabilistic deep learning (DL) models increases their performance and data efficiency. However, commonly used sampling-based approximations for probabilistic DL models can be computationally expensive, requiring multiple forward passes and longer training times. Promising alternatives are compute efficient last layer kernel approximations like spectral normalized Gaussian processes (SNGPs). We propose a novel regularization-based continual learning method for SNGPs, which enables the use of informative priors that represent prior knowledge learned from previous tasks. Our proposal builds upon well-established methods and requires no rehearsal memory or parameter expansion. We apply our informed SNGP model to the trajectory prediction problem in autonomous driving by integrating prior drivability knowledge. On two public datasets, we investigate its performance under diminishing training data and across locations, and thereby demonstrate an increase in data efficiency and robustness to location-transfers over non-informed and informed baselines. © 2024 The Authors.

关键词： Gaussian distribution

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Pushing AI to wireless network edge: an overview on integrated sensing, communication, and computation towards 6G

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Science China(Information Sciences) 2023年第3期66卷 7-25页

作者： Guangxu ZHU Zhonghao LYU Xiang JIAO Peixi LIU Mingzhe CHEN Jie XU Shuguang CUI Ping ZHANG Shenzhen Research Institute of Big Data Future Network of Intelligence Institute (FNii) The Chinese University of Hong Kong (Shenzhen) School of Science and Engineering (SSE) The Chinese University of Hong Kong (Shenzhen) State Key Laboratory of Advanced Optical Communication Systems and Networks School of Electronics Peking University Department of Electrical and Computer Engineering and Institute for Data Science and Computing University of Miami Peng Cheng Laboratory State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications

Pushing artificial intelligence(AI) from central cloud to network edge has reached board consensus in both industry and academia for materializing the vision of artificial intelligence of things(AIoT) in the sixth-generation(6G) era. This gives rise to an emerging research area known as edge intelligence, which concerns the distillation of human-like intelligence from the vast amount of data scattered at the wireless network edge. Typically, realizing edge intelligence corresponds to the processes of sensing, communication,and computation, which are coupled ingredients for data generation, exchanging, and processing, ***, conventional wireless networks design the three mentioned ingredients separately in a task-agnostic manner, which leads to difficulties in accommodating the stringent demands of ultra-low latency, ultra-high reliability, and high capacity in emerging AI applications like auto-driving and metaverse. This thus prompts a new design paradigm of seamlessly integrated sensing, communication, and computation(ISCC) in a taskoriented manner, which comprehensively accounts for the use of the data in downstream AI tasks. In view of its growing interest, this study provides a timely overview of ISCC for edge intelligence by introducing its basic concept, design challenges, and enabling techniques, surveying the state-of-the-art advancements, and shedding light on the road ahead.

关键词： sixth-generation (6G) edge intelligence artificial intelligence of things (AIoT) integrated sensing communication and computation (ISCC)

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Web-Based Optimization and Expansion of Multimodal High School Entrance Examination data Visualization 12

Web-Based Optimization and Expansion of Multimodal High Scho...

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12th International Conference of Information and Communication Technology, ICTech 2023

作者： Zhang, Wei Jian, Duan Wang, HongLiang Zhang, YongHong Shengyang Institute of Computing Technology University of Chinese Academy of Sciences Beijing China Shandong University Big Data Technology and Cognitive Intelligence Laboratory Beijing China

ISBN: (纸本)9798350332919

The reform of the new college entrance examination system makes students and their parents pay more attention to the feasibility and accuracy of the college entrance examination. The college entrance examination informatization can help the local admissions departments to mine and analyze the data rules from the massive college entrance examination data, and provide help and guidance for each link of volunteer application. Therefore, this paper, in order to comply with the development trend of the new college entrance examination information construction, proposes the optimization method of data visualization chart rendering and innovative combination of ideas to improve the Web rendering performance in order to enhance the interactive experience of users and the platform. © 2023 IEEE.

关键词： data visualization

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