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检索条件"任意字段=2019 International Conference on Modeling, Simulation and Big Data Analysis（MSBDA 2019）"

共 1293 条记录，以下是21-30 订阅

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cPSITRES: A collaborative system for analysis of big data on sea ice

cPSITRES: A collaborative system for analysis of Big Data on...

引用

IEEE international conference on big data (big data)

作者： Singh, Vinit Veerendraveer Sorensen, Scott Kambhamettu, Chandra Univ Delaware Video Image Modeling & Synth Lab Delaware OH 19716 USA Vis Syst Inc Riverside RI USA

ISBN: (纸本)9781728108582

analysis of sea ice image rasters presents exciting challenges to the computer vision community, and results from such visual analysis can offer novel insights to domain experts studying sea ice. In recent years, there is a surge in the production of geospatial data sets on sea ice along with the methods for their analysis. As numerous providers independently provision geospatial data sets, they are found in varying formats. Also, there is often limited collaboration between the infra-domain and inter-domain experts analyzing these data sets. To tackle these aforementioned challenges, we have developed the cPSITRES system using open-source technologies and libraries to serve cruise-based high-resolution spatiotemporal big data on sea ice along with relevant unstructured public data. The system enables its users to perform complex analysis on the provided data sets and also serves as a collaborative platform for the rapid discovery of open-source methods analyzing sea ice. We also showcase a few exemplary traditional and state-of-the-art computer vision methods liar the analysis of data provided by cPSITRES.

关键词： sea ice geospatial data image analysis big data analysis collaborative system

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Application of Cloud Computing in Information Management System in the Era of big data 2

Application of Cloud Computing in Information Management Sys...

引用

2nd international conference on Computational modeling, simulation and data analysis, CMSDA 2022

作者： Miao, Xianghui Liaoning Dalian China

ISBN: (纸本)9798350345759

Cloud computing can provide long-term maintenance technology for enterprise management planning, and improve the operational efficiency of enterprises without increasing energy consumption. Therefore, this paper studies how to improve the information management efficiency of small and medium-sized enterprises by introducing cloud computing technology to build software application system. Cloud computing enterprise management system of big data adopts Saas mode of cloud computing, cloud server is created by Alibaba Cloud, and virtual cluster is created by hadoop to realize distributed storage and calculation of enterprise information data. The application design adopts J2EE technology, java language and SSH framework to establish the system. In this paper, a storage resource pool is built in the virtual cluster, and then different servers are used as storage shared resource pools of different resources. Cloud platform can control and manage all virtual machines. © 2022 IEEE.

关键词： big data

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Federated Multimodal big data Storage & Analytics Platform for Additive Manufacturing

Federated Multimodal Big Data Storage & Analytics Platform f...

引用

IEEE international conference on big data (big data)

作者： Aggour, Kareem S. Kumar, Vijay S. Cuddihy, Paul Williams, Jenny Weisenberg Gupta, Vipul Dial, Laura Hanlon, Tim Gambone, Justin Vinciquerra, Joseph GE Res AI Knowledge & Big Data Niskayuna NY 12309 USA GE Res Struct Mat Niskayuna NY 12309 USA GE Res Addit Technol Niskayuna NY 12309 USA

ISBN: (纸本)9781728108582

Additive technologies are expected to revolutionize manufacturing across almost every industry, but there is a sizable gap between the current state of the technology and the maturity required for it to achieve widespread adoption. Advanced analytics are required to improve the reliability and repeatability of additive manufacturing, and those analytics require data. Large volumes of multimodal data are generated and used throughout the additive manufacturing lifecycle, from material design to part design and simulation, part printing to post-processing and inspection. To capture and link that diverse big data together, we have designed and developed a federated multimodal big data storage and analytics platform comprised of three tiers-a distributed polyglot data storage and analysis tier with different repositories for different data structures, a metadata knowledge graph tier for modeling the data and their relationships across the various repositories, and a user interface tier for visualizing, exploring and invoking analytics on the data. The platform has been used to integrate a collection of previously disparate steps to optimize the process parameters used to build a new additive material, enabling materials scientists and other non-software experts to capture, visualize and analyze the requisite data through a single user interface.

关键词： additive manufacturing semantics knowledge graphs polyglot data storage Spark

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modeling Dynamic Spatial-Temporal Cluster Relationships

Modeling Dynamic Spatial-Temporal Cluster Relationships

引用

IEEE international conference on big data (big data)

作者： Portugal, Ivens Alencar, Paulo Cowan, Donald Univ Waterloo Waterloo ON Canada

ISBN: (纸本)9781728108582

Spatial-temporal data refers to potentially massive amounts of data gathered across both space and time. Spatial-temporal data analysis helps uncover the value that this type of data holds to domains such as transportation operations, traffic management, service demand, and trip planning. Specifically, cluster analysis groups data into sets known as clusters such that elements inside a cluster are more similar to each other than elements in other dusters. Cluster analysis has been successfully applied in domains such as transportation, ecology, medicine, and astronomy. However, current duster analysis techniques limit themselves to static cluster analysis, thereby missing the identification of interesting insights and patterns related to the evolution of clusters over time. In this paper, we clarify the concept of dynamic clusters and support new forms of duster analyses by introducing, describing, and formalizing duster relationships that represent important events, such as split or merge, that a cluster may go through from its start to its end. These relationships provide a foundation for investigating cluster evolution and providing novel insights for better operational and business decision making.

关键词： Cluster analysis spatial-temporal data spatial-temporal relationships

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analysis of Vessel Behaviors in Costal Waterways Using big AIS data 4

Analysis of Vessel Behaviors in Costal Waterways Using Big A...

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4th IEEE international conference on Cloud Computing and big data analysis (ICCCBDA)

作者： Tang, Guolei Cao, Qiankai Li, Xiang Dalian Univ Technol DLUT State Key Lab Coastal & Offshore Engn Dalian Peoples R China

ISBN: (纸本)9781728114101

Enhancing traffic safety and obtaining vessel messages in complicated and varied marine environment has become the focus of attention. Therefore, Automatic Identification System (AIS) is utilized to get the vessel behaviors. In this article, we develop the vessel behavior analysis framework based on JPPF parallel processing framework to get spatial-temporal characteristics of vessel behavior in costal waterways. At last, 1 billion AIS data from Tianjin port in China are input into the proposed framework and vessel behaviors can be obtained, which can serve for vessel traffic simulation, safe navigation of vessel, supervision of the maritime sector and macroscopic dispatch of the country.

关键词： waterways AIS data vessel behavior JPPF

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Accurate marking method of network attacking information based on big data analysis

Accurate marking method of network attacking information bas...

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international conference on Intelligent Transportation, big data & Smart City (ICITBS)

作者： Li Peng Min Xiao-cui Guangzhou Huali Sci & Technol Vocat Coll Guangzhou 511325 Guangdong Peoples R China

ISBN: (纸本)9781728113074

In the open network environment, the network offensive information is implanted in big data environment, so it is necessary to carry out accurate location marking of network offensive information, to realize network attack detection, and to implement the process of accurate location marking of network offensive information. Combined with big data analysis method, the location of network attack nodes is realized, but when network attacks cross in series, the performance of attack information tagging is not good. An accurate marking technique for network attack information is proposed based on big data fusion tracking recognition. The adaptive learning model combined with big data is used to mark and sample the network attack information, and the feature analysis model of attack information chain is designed by extracting the association rules. This paper classifies the data types of the network attack nodes, and improves the network attack detection ability by the task scheduling method of the network attack information nodes, and realizes the accurate marking of the network attacking information. simulation results show that the proposed algorithm can effectively improve the accuracy of marking offensive information in open network environment, the efficiency of attack detection and the ability of intrusion prevention is improved, and it has good application value in the field of network security defense.

关键词： network attack information marking big data

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A big-data Approach to Defining Breathing Signatures for Identifying Respiratory Disease

A Big-Data Approach to Defining Breathing Signatures for Ide...

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IEEE international conference on big data (big data)

作者： Rahman, Abrar Weiner, Yonathan Swanson, Hailey Slepian, Rebecca Abdullah, Anusheh Slepian, Marvin J. Univ Calif Berkeley 101 Durant Hall Berkeley CA 94720 USA Worcester Polytech Inst WPI 100 Inst Rd Worcester MA 01609 USA Univ Arizona 1501 N Campbell Ave Tucson AZ 85724 USA Univ Calif Davis 1 Shields Ave Davis CA 95616 USA

ISBN: (纸本)9781728108582

This project seeks to use wearable sensors to develop a novel method for measuring respiratory activity in human subjects. This is the first stage of an ongoing project under the Arizona Center for Accelerated Biomedical Innovation (ACABI) [1]. The ultimate ambition of this effort is to develop a baseline digital breathing signature for a particular individual, so that medical professionals equipped with big-data analysis tools can use deviations from one's signature to differentiate between conventional breathing and abnormal breathing patterns, such as splinting and Kussmaul respirations.

关键词： big-data breathing signatures pattern mining respirations Forced Vital Capacity lung performance data modeling classification

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Research On The Effectiveness Of Campus Recruitment Based On big data

Research On The Effectiveness Of Campus Recruitment Based On...

引用

international conference on Smart Grid and Electrical Automation (ICSGEA)

作者： Zhang, Ying Luo, Xuanping Zhong, Chen Cai, Xinghua Gao, Xiang Jiangxi Sci & Technol Normal Univ Nanchang Jiangxi Peoples R China

ISBN: (纸本)9781728144634

To improve the effectiveness of the campus recruitment fair, through the analysis of the effective statistics of the campus recruitment fair, the quantitative evaluation of the effectiveness of the campus recruitment fair was carried out, and a method for evaluating the effectiveness of the campus recruitment fair based on big data analysis was proposed. The effective statistical analysis model of big data statistics, combined with sample regression analysis method, analyzes the effective data big data of campus recruitment fairs in campus recruitment meeting, constructs the decision objective function of campus recruitment fair effectiveness evaluation, and adopts the method of convergence rule evaluation for campus. Quantitative regression analysis of the effectiveness of job fairs, using descriptive statistical analysis results for big data mining and relevance description. The statistical feature of the extracted campus job fairs uses the average mutual information clustering method for pattern recognition and feature screening. The effectiveness evaluation of campus recruitment fair based on big data analysis is realized. The simulation results show that the confidence level of the campus recruitment fair effectiveness evaluation is higher and the evaluation results are accurate and reliable.

关键词： big data analysis campus recruitment study effect evaluation feature extraction

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Fire Evacuation Design and Fire Risk Assessment for a Stadium

Fire Evacuation Design and Fire Risk Assessment for a Stadiu...

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international conference on Intelligent Transportation, big data & Smart City (ICITBS)

作者： Yao Hao-wei Zhang Dong-sheng Liang Dong Zhengzhou Univ Light Ind Sch Bldg Environm Engn Zhengzhou 450002 Henan Peoples R China Sun Yat Sen Univ Guangdong Prov Key Lab Fire Sci & Technol Guangzhou 510006 Guangdong Peoples R China

ISBN: (纸本)9781728113074

In order to realize the fire risk assessment of A stadium, this paper establishes the fire scene model of the stadium, and takes the fire model simulation analysis to the stadium. The composition and structure of the stadium, the division of safety zones, evacuation and other aspects are analyzed. The model is established and the fire simulation experiment is carried out. The design requirements are given. Finally, the simulation data are obtained, and improvement suggestions for A venues are given through data. Fire risk assessment plays an important guiding role in improving the fire safety level of the stadium.

关键词： Stadium fire safety fire scenario model analysis

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modeling and Finite Element analysis of Left Cover of Motorcycle Engine 4

Modeling and Finite Element Analysis of Left Cover of Motorc...

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4th IEEE international conference on Cloud Computing and big data analysis (ICCCBDA)

作者： Zheng, Bin Huang, Chi Zhang, Jing-Dong Panzhihua Univ Inst Transportat & Automobile Engn Panzhihua Peoples R China

ISBN: (纸本)9781728114101

Motorcycle engine is the key part of the motorcycle and its performance directly influences the power and economy of the motorcycle. The left cover of motorcycle engine is the important part of the motorcycle engine, and its static and dynamic characteristics directly affect the performance of the motorcycle engine. The paper is mainly aimed at the left cover of the motorcycle engine, which is an aluminum alloy die casting. The three dimensional simplified model of left cover of the motorcycle engine was built by using the PRO/E software. Based on the three dimensional simplified models, the ANSYS software is used to carry out the static and modal analysis of the motorcycle engine left cover. The results show that the design and manufacture of the left cover of the motorcycle engine can be effectively solved by combining the PRO/E software and the finite element analysis of ANSYS software. The results can offer some references for the design and manufacture of the left cover of the motorcycle engine.

关键词： motorcycle engine left cover three dimension modeling static analysis modal analysis

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