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Piecewise Polynomial Aggregation as Preprocessing for Data Numerical Modeling

B S Dobronets, O A Popova
2018 Journal of Physics, Conference Series  
The authors show that their approach to data aggregation allows reducing the level of data uncertainty and significantly increasing the efficiency of numerical calculations.  ...  To demonstrate the degree of the correspondence of the proposed methods to reality, the authors developed a theoretical framework and considered numerical examples devoted to time series aggregation.  ...  In each case, a time series of distributions would offer a more informative representation than other forms of aggregated time series.  ... 
doi:10.1088/1742-6596/1015/3/032028 fatcat:r5omtrwfrvd6zd2n5aymdb3sw4

An adaptive process planning approach of rapid prototyping and manufacturing

G.Q. Jin, W.D. Li, L. Gao
2013 Robotics and Computer-Integrated Manufacturing  
for the internal area of the layer to simplify computing processes and speed up fabrication.  ...  In addition, based on the developed build time and geometrical accuracy analysis models, adaptive algorithms were designed to generate an adaptive speed of the RP/M nozzle/print head for the contour tool-paths  ...  quality during RP/M, and zigzag tool-paths for the internal area of the model to simplify computing and fabrication processes. (3) An adaptive speed algorithm for RP/M-used to control the speed of the  ... 
doi:10.1016/j.rcim.2012.07.001 fatcat:k6owjrskwbe6vmz7fteybn337i

Recurrent Auto-Encoder Model for Large-Scale Industrial Sensor Signal Analysis [chapter]

Timothy Wong, Zhiyuan Luo
2018 Communications in Computer and Information Science  
The proposed method can be applied in large-scale industrial processes for sensors signal analysis purpose, where clusters of the vector representations can reflect the operating states of the industrial  ...  The change of time series features over time can be summarised as a smooth trajectory path.  ...  It has concluded that Dynamic Time Warping (DTW) can be an effective benchmark for unidimensional time series data representation.  ... 
doi:10.1007/978-3-319-98204-5_17 fatcat:tnanvgdmjfe3thpoztfqviyf4u

Exploring Distance Based Approaches for Reducing Sensor Data in Defect Related Prognosis

Selvine G. Mathias, Daniel Grossmann, Tapanta Bhanja
2021 Procedia Computer Science  
Vibration data consists of batches of time series which if accumulated over a period of time is a huge collection of numeric data.  ...  Abstract Vibration data consists of batches of time series which if accumulated over a period of time is a huge collection of numeric data.  ...  In [13] , the authors propose a technique to process raw time-series data using deep learning where signal processing techniques for noise reduction and feature extraction (time and frequency domain)  ... 
doi:10.1016/j.procs.2021.03.076 fatcat:ue5mbtyt2nahxl2uz2h3ulfhtm

Mathematical modeling of an inductive link for optimizing efficiency

Hussnain Ali, Talha J Ahmad, Shoab A Khan
2009 2009 IEEE Symposium on Industrial Electronics & Applications  
Aim of the analysis is to facilitate the designers in their design process as mathematical relationships for different models and their comparison has never been reported earlier in literature.  ...  Design of an optimized RF transcutaneous link through inductive coils is an arduous design process which involves complex mathematical modeling to search for optimized design parameters.  ...  First step in the design and analysis of an inductive link requires simplified circuit representation of the inductive link.  ... 
doi:10.1109/isiea.2009.5356338 fatcat:yexw6dfrsrd4zjb27jxkjywwru

Editor's introduction

Luc Bauwens, Wolfgang Polasek, Herman K. van Dijk
1996 Journal of Econometrics  
The purpose of the recently established International Society for Bayesian Analysis (ISBA) ~ is: To fi~ster the study of Baye:~ian statistical and decision analysis, its relation to other methodologies  ...  ic, industrial, and social problems.  ...  The paper shows an alternative for modelling nonstationary vector time series without pre-adjustments of the nonstationarity in the data.  ... 
doi:10.1016/0304-4076(95)01764-x fatcat:dglo7z7dsjc47o3azeanixbmre

Time Series Management Systems: A Survey

Soren Kejser Jensen, Torben Bach Pedersen, Christian Thomsen
2017 IEEE Transactions on Knowledge and Data Engineering  
) for times series management.  ...  The collection of time series data increases as more monitoring and automation are being deployed.  ...  of industrial machinery, analysis of time series collected from scientific experiments, embedded storage for Internet of things (IoT) devices, and more.  ... 
doi:10.1109/tkde.2017.2740932 fatcat:3phn7rowfbhsxdzjwcvfgcjigu

Data Series Management (Dagstuhl Seminar 19282)

Anthony Bagnall, Richard L. Cole, Themis Palpanas, Kostas Zoumpatianos, Michael Wagner
2019 Dagstuhl Reports  
The analysis of time series is becoming increasingly prevalent across scientific disciplines and industrial applications.  ...  Additionally, support for data series data sources, i.e., time focused database systems, and federated query processing for data series in general will be desirable.  ... 
doi:10.4230/dagrep.9.7.24 dblp:journals/dagstuhl-reports/BagnallCPZ19 fatcat:pxi472vlgnazzbsfk5ti73twza

Twin-Control Approach [chapter]

Mikel Armendia, Aitor Alzaga, Flavien Peysson, Dirk Euhus
2019 Twin-Control  
Conclusions Twin-Control ( is a new concept for machining process performance optimization, covering ICT-related features like Digital Twin, condition monitoring, fleet data management  ...  In addition, the industrial evaluation approach is also introduced. In the next chapters of the book, the presented features will be defined in detail.  ...  Information about event types and the time stamps of their occurrence will be used to analyse the time series data and thus finding dependencies between different alarms.  ... 
doi:10.1007/978-3-030-02203-7_2 fatcat:ljxros74tvf3powu2qcv5n3dhm

Symbolic signal processing and system analysis

Miroslav Lutovac, Dejan Tosic
2003 Facta universitatis - series Electronics and Energetics  
We present a new software in MATLAB and Mathematica for symbolic signal processing and system analysis.  ...  Built on a solid foundation of filter design and spectral analysis techniques, this toolbox contains powerful tools for algorithm development, signal and linear system analysis, and time-series data modeling  ...  solution sets, (c) students who want more efficient, and practical learning, and (d) industry designers responsible for products with short time-to-market.  ... 
doi:10.2298/fuee0303423l fatcat:o4wyeedoyrg43h7wuf35ofllfm

A patent time series processing component for technology intelligence by trend identification functionality

Hongshu Chen, Guangquan Zhang, Donghua Zhu, Jie Lu
2014 Neural computing & applications (Print)  
In order to capture the hidden trend turning points and improve the framework of existing technology intelligence, this paper proposes a patent time series processing component with trend identification  ...  Technology intelligence indicates the concept and applications that transform data hidden in patents or scientific literatures into technical insight for technology strategy-making support.  ...  Acknowledgements The author Hongshu Chen acknowledges the support from the China Scholarship Council (2011603004) and top-up scholarship from University of Technology,  ... 
doi:10.1007/s00521-014-1616-y fatcat:gb3koxmkdngyji22qbxp5bolne


Boris Alekseyevich Kucherov, Vladimir Mikhailovich Artyushenko
2017 Acta Polytechnica CTU Proceedings  
These issues are discussed by the example of the planning department which solves the tasks of allocation of control facilities for spacecraft (a subset of satellite range scheduling problem),  ...  Directions to increase the efficiency of reaction of the planning department's specialists to change the current situation by visual and sound notification of various events are marked.  ...  Possibility to view collected data in summary table for selected time interval was implemented to use in creating reports and further analysis of the data.  ... 
doi:10.14311/app.2017.12.0056 fatcat:t2rwonptzjg4pexqeg5wc5ypem

Research on Management Efficiency and Dynamic Relationship in Intelligent Management of Tourism Engineering Based on Industry 4.0

Tianchen Hou, Huihua Chen
2022 Computational Intelligence and Neuroscience  
This study aims to solve the problems of low efficiency of dynamic relationship analysis and low data utilization in traditional intelligent management methods of tourism engineering.  ...  According to the human behavior data analysis model and convolution neural network algorithm, this study formulates the real-time management data scheme of tourism engineering and better extracts the characteristic  ...  Acknowledgments is work was supported by the study on the high-quality development path of promoting the integration of culture and tourism in the Yellow River Basin in Henan Province (212400410104).  ... 
doi:10.1155/2022/5831062 pmid:35103056 pmcid:PMC8800595 fatcat:gkbcgllqazaqjpvmw5363caega

Page 509 of Management Science Vol. 6, Issue 4 [page]

1960 Management Science  
., Simulation of a simplified job shop, 311. Berman, Simeon M., GRENANDER and ROSENBLATT’S Statistical Analysis of Stationary Time Series: Book Re- view, 503. Bowman, E.  ...  ., McKEAN’S Efficiency in Government through Systems Analysis with Emphasis on Water Resource De- velopment: Book Review, 356.  ... 

DSCo-NG: A Practical Language Modeling Approach for Time Series Classification [chapter]

Daoyuan Li, Tegawendé F. Bissyandé, Jacques Klein, Yves Le Traon
2016 Lecture Notes in Computer Science  
The abundance of time series data in various domains and their high dimensionality characteristic are challenging for harvesting useful information from them.  ...  data) and generic (so that it can be applied to various domains) approach for time series classification.  ...  Acknowledgment The authors would like to thank Paul Wurth S.A. and Luxembourg Ministry of Economy for sponsoring this research work.  ... 
doi:10.1007/978-3-319-46349-0_1 fatcat:r74kcumiifhrlph3rrge4qqt7y
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