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Intelligent Sports data Measurement Based on Multi data Fusion

Intelligent Sports Data Measurement Based on Multi Data Fusi...

引用

2023 International conference on Power, Electrical Engineering, Electronics and control, PEEEC 2023

作者： Cai, Yanli Wuhan Qingchuan University Hubei Wuhan430012 China

ISBN: (纸本)9798350329124

data fusion technology is an information processing discipline that just emerged in the 1990s, and its application range is very wide, while target tracking and recognition is still the most important subject of data fusion technology research. And with the development of sports research, it has become an inevitable trend to pursue the accuracy of intelligent sports data measurement. In order to obtain accurate sports data, motion capture technology is an important means to obtain sports data. For this reason, based on the systematic analysis of the current human motion modeling and simulation research methods, this paper proposes a multi-data fusion-based intelligent New ideas for sports data measurement. With the help of a variety of modern signal analysis and processing methods, the feature extraction and motion pattern classification of EMG signals in the process of human movement are studied in detail. Compared with the image-based method, the accuracy of sports target tracking is further improved. In order to meet the requirement of similarity retrieval from large-scale database, the similarity measure of different human body movements and postures is defined. Display and manage human movement data and evaluation results, so as to facilitate the storage and query of historical movement records. © 2023 IEEE.

关键词： Sports

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Do You Behave Always the Same? A process Mining Approach

Do You Behave Always the Same? A Process Mining Approach

引用

4th International conference on process Mining (ICPM)

作者： Di Federico, Gemma Burattin, Andrea Tech Univ Denmark Lyngby Denmark

ISBN: (纸本)9783031278143;9783031278150

Human behavior could be represented in the form of a process. Existing process modeling notations, however, are not able to faithfully represent these very flexible and unstructured processes. Additional non-process aware perspectives should be considered in the representation. control-flow and data dimensions should be combined to build a robust model which can be used for analysis purposes. The work in this paper proposes a new hybrid model in which these dimensions are combined. An enriched conformance checking approach is described, based on the alignment of imperative and declarative process models, which also supports data dimensions from a statistical viewpoint.

关键词： Behavioral research

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Dynamics modeling and analysis of a down-hole drill string multibody system based on the absolute coordinate formulation 7

Dynamics modeling and analysis of a down-hole drill string m...

引用

7th International conference on Downhole Measurement and control, ICDMC 2024

作者： Fang, Chao Li, HaiQuan Liu, Wei Xu, ZhaoHui Liao, MaoLin Fan, JinChao Lin, ZiLi Pang, HaiBo National Engineering Research Center for Oil&Gas Drilling and Completion Technology Beijing102206 China CNPC Engineering Technology R&D Co. Ltd. Beijing102206 China University of Science and Technology Beijing Beijing100102 China

Drilling system dynamics is the basis of studying the interaction between components in drilling process, which needs to solve many difficult problems such as geometric nonlinear dynamics of drill string, contact between drill string and wellbore, solving timeliness and so on. The existing research on establishing dynamic unit of local drilling tool structure has low solution efficiency, and it is difficult to meet the requirements of directional trajectory control and drilling speed increase analysis efficiently. Dynamics model of a downhole drill string system is established by using the multibody system dynamics method in this study. The natural coordinate formulation and the absolute nodal coordinate formulation are adopted to describe the rigid parts and the flexible beams, respectively. The presented model can be used to analyze the dynamic characteristics of the drill string system and the interaction between the drill string and the environment such as the wellbore and rocks in the drilling process. Finally, through comparative analysis with on-site test data, the correctness of the multibody dynamic model of the drill string system established in this paper was preliminarily verified. © 2024 Institute of Physics Publishing. All rights reserved.

关键词： Drill strings

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A comprehensive data analysis for aggregate capacity forecasting in Vehicle-to-Grid applications

A comprehensive data analysis for aggregate capacity forecas...

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2024 International conference on control, Automation and Diagnosis, ICCAD 2024

作者： Patanè, Luca Sapuppo, Francesca Xibilia, Maria Gabriella Napoli, Giuseppe Università Degli Studi Di Messina Dipartimento Di Ingegneria Messina Italy Messina Italy

ISBN: (纸本)9798350361025

The integration of electric vehicles (EVs) into the Vehicle-to-Grid (V2G) framework necessitates accurate forecasting of the aggregated available capacity (AAC). This paper introduces a method for extracting AAC values from generic mobility data and other readily available data sources obtaining a comprehensive dataset that encompasses geographical information through GPS coordinates, meteorological data, and the consideration of national holidays and weekends. Different predictive models based on machine learning, such as Neural Networks, Long Short-Term Memory networks, Tree Ensembles, and Gaussian process Regressors were implemented. The application of such models on different multidimensional datasets seeks to enhance the precision of capacity predictions, explaining and modeling the complex dependencies within the input data and the target available capacity, ultimately improving the efficiency and reliability of V2G systems. As the prevalence of EVs continues to rise, the proposed methodology offers a valuable tool for grid operators, energy planners, and stakeholders to optimize the integration of EVs into the broader energy landscape and facilitates the strategic planning of aggregator hub locations. © 2024 IEEE.

关键词： Machine learning

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Research on the Development of New Energy Electric Vehicles Based on Factor analysis and Intervention Optimization of LSTM Model 2

Research on the Development of New Energy Electric Vehicles ...

引用

2nd IEEE International conference on control, Electronics and Computer Technology, ICCECT 2024

作者： Yang, Lijing Huang, Yuhan Shi, Hanlin Yuan, Zijing Yuan, Chun Wuhan University of Science and Technology Wuhan China

ISBN: (纸本)9798350380958

Given the two-carbon strategy, the new energy vehicle industry is expanding rapidly. This paper studies the problems related to the development of new energy electric vehicles in China through modeling analysis. In this paper, the random forest algorithm is first used to evaluate the main factors affecting the development of new energy electric vehicles in China, and then the principal component analysis algorithm is used to determine the impact of each factor. The survey results show that the number of public charging stations, the number of state-supported policies and the level of population consumption are dominant;Then, we collected the development data of China's new energy electric vehicle industry, and used the Logistic algorithm to create an EV prediction model to predict the progress of China's new energy electric vehicles in the next ten years. Further, this paper collects data on electric vehicles powered by new energy sources and analyze their impact on the established global conventional energy vehicle industry. Using the VAR model, this study assesses possible correlations between the production and sales of new energy electric vehicles in China and globally. Subsequently, the functional equation of domestic and global joint production and sales of new energy electric vehicles is derived. The influence of policies restrict the development of new sustainable energy electric vehicles on the development of new sustainable energy electric vehicles in China is analyzed. First, the data that is not affected by the policy restriction, which is selected, and the rationality of the model is verified by LSTM algorithm. An intervention analysis model is introduced to optimize the LSTM model while considering the policy constraints. Through this optimized fitting process, the fitting results are consistent with the actual results, and the impact of policy restrictions on the development of new electric vehicles in China can be quantified. © 2024 IEEE.

关键词： Factor analysis

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EFFECTIVE analysis OF LIQUID PIPELINE SYSTEM PERFORMANCE POST UPGRADE PROJECT 15

EFFECTIVE ANALYSIS OF LIQUID PIPELINE SYSTEM PERFORMANCE POS...

引用

2024 15th International Pipeline conference, IPC 2024

作者： Ma, Te Mansour, Vivianne Qiao, Sean Trans Mountain Corporation CalgaryAB Canada

ISBN: (纸本)9780791888568

It is difficult to analyze the performance of liquid transmission pipelines that transport products through a process called batching which allows multiple products, such as heavy crude oil, refined and semi-refined products to be transported in batches one after another. This is because the products delivered vary in batch content, batch size and batch position. A combination of operating data analysis and Hydraulic Pipeline Simulator modeling could be used to effectively analyze the pipeline system performance improvements following a pipeline system upgrade to justify the project’s economic benefits. The subject pipeline is a liquid transmission pipeline with approximately 1,150 km total length of pipe (nominal diameters of 610 mm / 762 mm / 914 mm) and twenty-three (23) pump stations. The pipeline delivers approximately 300,000 bbl/day of diverse types of crude products ranging from refined petroleum to heavy crude. In addition, the delivery batch lineups vary from day to day. A system upgrade project was completed to improve the system throughput. The upgrade included installing larger motors and Variable Frequency Drive (VFD) at 7 of the 23 pump stations. Following the system upgrade, a method for quantifying post-project benefits was derived for a pipeline system using batch delivery to determine the pipeline throughput improvement and pump power consumption saving. This paper showcases the analytical considerations and calculation methodologies involving pipeline operating SCADA (Supervisory control and data Acquisition) data analysis and Hydraulic Pipeline Simulator modeling as a combined approach. Both analytical approaches are utilized to evaluate the performance improvement of the subject pipeline system upgrade in terms of system throughput and power saving. It was concluded that the pipeline system throughput was improved up to 5% and annual energy savings of 18% was achieved post system upgrade. With the optimized analytical evaluation method, the pip

关键词： Crude oil

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Artificial Intelligence for Clinical Intensive Care in the Hospital: Opportunities and Challenges 14th

Artificial Intelligence for Clinical Intensive Care in the H...

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14th International conference on Digital Human modeling and Applications in Health, Safety, Ergonomics and Risk Management (DHM) Held as Part of the 25th International conference on Human-Computer Interaction (HCii)

作者： Brukamp, Kirsten Protestant Univ Ludwigsburg Res Grp Hlth Technol Eth Paulusweg 6 D-71638 Ludwigsburg Germany

ISBN: (纸本)9783031357473;9783031357480

Innovative technologies promise to substantially transform clinical health care. In particular, applications of artificial intelligence are currently emerging as part of medical devices. Clinical intensive care in the hospital has traditionally been a setting in which health care professionals are extensively supported by technical products. Post-operative care after cardiac surgery constitutes a highly relevant realm for evaluating novel approaches with medical devices. Technological innovations may include probability estimates for diagnosis and prognosis by an artificial intelligence analysis of data combinations from different sources, voice and gesture control, remote assessment of skin perfusion, as well as optimized representation and visualization of clinical data. A requirements analysis, using empirical methods of social science research, was conducted in order to include stakeholders' perspectives. Thereby, a participatory design was realized in the research and development processes. Ethical, legal, and social implications (ELSI) were specifically addressed to identify potentials for improving both acceptance and acceptability during future steps.

关键词： Innovative technologies Artificial intelligence Health care Intensive care Hospital Empirical methods of social science research Requirements analysis Ethical legal and social implications (ELSI)

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Research on Production Quality control Based on Sampling Inspection Model and Expected Cost Optimization Algorithm 3

Research on Production Quality Control Based on Sampling Ins...

引用

3rd International conference on data Analytics, Computing and Artificial Intelligence, ICDACAI 2024

作者： Lin, Yuguwen Xia, Zihan Wuhan University Wuhan China Shanghai Maritime University Shanghai China

ISBN: (纸本)9798331519032

This study explores production quality control based on a sampling inspection model and an expected cost optimization algorithm. First, a sampling inspection model is established, assuming the defect rate follows a binomial distribution. Using z-tests or t-tests, hypotheses are formulated to check whether the defect rate of a batch of parts exceeds the specified threshold. By determining the sample size and conducting power analysis, the model controls Type I errors (rejecting a good batch) and Type ii errors (accepting a defective batch), and simulates the sampling process to decide whether to accept a batch. Next, a cost optimization model is proposed to optimize production inspection and handling decisions. Through dynamic programming and expected cost analysis, the impact of different inspection strategies on total production costs and product quality is quantified. The study simulates six different production conditions. Finally, by comparing the total costs and defect rates of 16 different combinations of inspection and disassembly strategies, the optimal strategy is determined. These strategies include whether to inspect part 1, part 2, and the final product, as well as whether to disassemble defective products. This analysis allows for determining the optimal sample size, accurately screening qualified batches, improving inspection efficiency, reducing misjudgments, and lowering inspection costs and time investment. © 2024 IEEE.

关键词： Dynamic programming

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Temperature control System for Biological Liquefaction of Dead Livestock and Poultry Based on Fuzzy Neural Network PID 4

Temperature Control System for Biological Liquefaction of De...

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4th IEEE International conference on Information Technology, Big data and Artificial Intelligence, ICIBA 2024

作者： Li, Hualong Huang, Xiang Wu, Liqin Yang, Xuanjiang Li, Miao Anhui Agricultural University Anhui China Chinese Academy of Sciences Institute of Intelligent Machinery Hefei Institute of Materials Science Anhui China Anhui University of Science and Technology Anhui China

ISBN: (纸本)9798350363586

At present, the efficient bio-liquefaction technology of dead livestock and poultry has become an important technical means for the harmless treatment of dead livestock and poultry because of its advantages of high value-added liquid amino acid fertilizer. How to achieve the precise control of temperature in the process of efficient bio-liquefaction of dead livestock and poultry is a difficult problem that needs to be solved urgently. In this study, a temperature control system for the bio-liquefaction of dead livestock and poultry based on fuzzy neural network PID was proposed. The fuzzy neural network algorithm blurs inputs, models rules, and fuzzy reasoning through fuzzy set theory to simulate human fuzzy reasoning ability to achieve the modeling and control of complex systems. analysis showed that the temperature control was effective. The temperature change amplitude was ± 2. The experimental results showed that the system had the characteristics of simple structure, small static error, and fast dynamic response speed. An effective technical means for the precise control of temperature in the process of efficient bio-liquefaction of dead livestock and poultry is provided in this study, which has a wide range of application prospects. © 2024 IEEE.

关键词： Livestock

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DMFDT: data Management Framework for Digital Twin 25th

DMFDT: Data Management Framework for Digital Twin

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25th IFIP WG 5.5 Working conference on Virtual Enterprises (PRO-VE)

作者： Ali, Zeeshan Poursoltan, Milad Traore, Mamadou Kaba Univ Bordeaux IMS Lab CNRS UMR 5218 Talence France

ISBN: (纸本)9783031717451;9783031717437;9783031717420

Digital Twin (DT) provides a digital representation of a real-world entity (process or product) that is continuously synchronized with a specified frequency. In this regard, DT utilizes a set of models that capture the various aspects of the real system to provide a deeper understanding and analysis of its real counterpart. The data within the DT holds paramount significance and serves as the foundation for model updating, refining, interoperability, validity, usability, etc. Accordingly, DT requires rigorous data management throughout its entire life cycle. This paper explores data knowledge areas related to DT (i.e., data governance, architecture, modeling, integration, interoperability, quality, uncertainty, visualization, and security) and also highlights their best practices, and proposes a data Management Framework for Digital Twin (DMFDT) to facilitate a better understanding of the DT data related requirements and proven practices. Validation and application of the DMFDT is done through the high-level DT architecture and a case study of the proposed framework is also presented by a DT developed to study the mobility system at the University of Bordeaux in France.

关键词： Digital Twin Framework Digital Twin Architecture data Management Framework data Requirements data Life-Cycle

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