scholarly journals Effect of bodyside-specific data processing on the results of fish morphometric studies

2018 ◽  
Author(s):  
Péter Takács ◽  
Árpád Ferincz ◽  
Ádám Staszny ◽  
Zoltán Vitál
Keyword(s):  
Data Processing ◽  
Specific Data

scholarly journals Facing the needs for clean bicycle data – a bicycle-specific approach of GPS data processing

2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Sven Lißner ◽  
Stefan Huber
Keyword(s):  
Data Processing ◽  
Gps Data ◽  
Data Set ◽  
Specific Data ◽  
Driving Mode ◽  
Mode Detection ◽  
Current State ◽  
Mode Recognition ◽  
Recorded Data ◽  
Gps Tracks

Abstract Background GPS-based cycling data are increasingly available for traffic planning these days. However, the recorded data often contain more information than simply bicycle trips. GPS tracks resulting from tracking while using other modes of transport than bike or long periods at working locations while people are still tracking are only some examples. Thus, collected bicycle GPS data need to be processed adequately to use them for transportation planning. Results The article presents a multi-level approach towards bicycle-specific data processing. The data processing model contains different steps of processing (data filtering, smoothing, trip segmentation, transport mode recognition, driving mode detection) to finally obtain a correct data set that contains bicycle trips, only. The validation reveals a sound accuracy of the model at its’ current state (82–88%).

A Meta-Mining Ontology Framework for Data Processing

2021 ◽  
Vol 12 (2) ◽  
pp. 37-56
Author(s):  
Man Tianxing ◽  
Nataly Zhukova ◽  
Alexander Vodyaho ◽  
Tin Tun Aung
Keyword(s):  
Data Mining ◽  
Data Processing ◽  
Data Streams ◽  
Specific Data ◽  
Ontology Merging ◽  
Knowledge Models ◽  
Task Requirements ◽  
Ontology Extraction ◽  
Merging Method ◽  
And Task

Extracting knowledge from data streams received from observed objects through data mining is required in various domains. However, there is a lack of any kind of guidance on which techniques can or should be used in which contexts. Meta mining technology can help build processes of data processing based on knowledge models taking into account the specific features of the objects. This paper proposes a meta mining ontology framework that allows selecting algorithms for solving specific data mining tasks and build suitable processes. The proposed ontology is constructed using existing ontologies and is extended with an ontology of data characteristics and task requirements. Different from the existing ontologies, the proposed ontology describes the overall data mining process, used to build data processing processes in various domains, and has low computational complexity compared to others. The authors developed an ontology merging method and a sub-ontology extraction method, which are implemented based on OWL API via extracting and integrating the relevant axioms.

The Urban and Rural Public Transit Demand Analysis in Hohhot

2014 ◽  
Vol 599-601 ◽  
pp. 2149-2152
Author(s):  
Cheng Bing Li ◽  
Yi Zhang ◽  
Rui Xue Guo
Keyword(s):  
Strategic Planning ◽  
Data Processing ◽  
Public Transportation ◽  
Logit Model ◽  
Public Transit ◽  
Influence Factors ◽  
Demand Analysis ◽  
Function Model ◽  
Specific Data ◽  
Urban And Rural Residents

This paper firstly briefly describes the basic situation of population, economy and transportation of Hohhot, and then analyzes the influence factors of Hohhot urban and rural residents and their characteristic attributes. Secondly, the topic brings the function model of the urban and rural public transit prediction, and uses the Logit model for specific data processing. and introduces its significance and the strategic planning. The author analysis this paper may help Hohhot development integration of urban and rural public transportation in the future.

scholarly journals Microservice-Oriented Platform for Internet of Big Data Analytics: A Proof of Concept

Sensors ◽  
2019 ◽  
Vol 19 (5) ◽  
pp. 1134 ◽  
Author(s):  
Zheng Li ◽  
Diego Seco ◽  
Alexis Sánchez Rodríguez
Keyword(s):  
Big Data ◽  
Resource Management ◽  
Data Processing ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Proof Of Concept ◽  
Tight Coupling ◽  
Specific Data ◽  
Numerous Data ◽  
Iot Devices

The ubiquitous Internet of Things (IoT) devices nowadays are generating various and numerous data from everywhere at any time. Since it is not always necessary to centralize and analyze IoT data cumulatively (e.g., the Monte Carlo analytics and Convergence analytics demonstrated in this article), the traditional implementations of big data analytics (BDA) will suffer from unnecessary and expensive data transmissions as a result of the tight coupling between computing resource management and data processing logics. Inspired by software-defined infrastructure (SDI), we propose the “microservice-oriented platform” to break the environmental monolith and further decouple data processing logics from their underlying resource management in order to facilitate BDA implementations in the IoT environment (which we name “IoBDA”). Given predesigned standard microservices with respect to specific data processing logics, the proposed platform is expected to largely reduce the complexity in and relieve inexperienced practices of IoBDA implementations. The potential contributions to the relevant communities include (1) new theories of a microservice-oriented platform on top of SDI and (2) a functional microservice-oriented platform for IoBDA with a group of predesigned microservices.

Instrumental and Experimental Considerations

2018 ◽  
Author(s):  
Eaton E. Lattman ◽  
Thomas D. Grant ◽  
Edward H. Snell
Keyword(s):  
Data Processing ◽  
Two Dimensional ◽  
Specific Data ◽  
One Dimensional ◽  
Dimensional Image ◽  
Two Dimensional Image ◽  
Data Processing Software ◽  
Processing Software

Thic chapter describes some of the processes that are often carried out within specific data processing software associated with an instrument but are invisible to the user. It is useful to be aware of them. These include dealing with detector artifacts and limitations, and the integration of the signal from a two-dimensional image to produce a one-dimensional scattering profile, among other steps.

Research on Recovery of Computer Data Based on Windows System

2014 ◽  
Vol 608-609 ◽  
pp. 603-606
Author(s):  
Min Zhou
Keyword(s):  
Data Processing ◽  
File System ◽  
Software Tools ◽  
Data Recovery ◽  
Computer Data ◽  
Specific Data ◽  
Storage Format

This paper researches the computer data recovery in FAT Windows file system, analyzed the storage format and file data operations (such as formatting, partition and delete), specific to the data processing and the data recovery, summarizes the method of data recovery and commonly used software tools, and gives the specific data recovery examples.

Processor Specific Data Processing Device (DPD) Design For Energy Efficient Data Center

2014 ◽  
Vol 1 (1) ◽  
pp. 1-12
Author(s):  
Diya Garg ◽  
◽  
Harkinder Kaur ◽  
Aditi Goyal ◽  
Bishwajeet Pandey ◽  
...  
Keyword(s):  
Data Processing ◽  
Data Center ◽  
Energy Efficient ◽  
Specific Data ◽  
Efficient Data ◽  
Processing Device

scholarly journals TXM-Sandbox: an open-source software for transmission X-ray microscopy data analysis

2022 ◽  
Vol 29 (1) ◽  
Author(s):  
Xianghui Xiao ◽  
Zhengrui Xu ◽  
Feng Lin ◽  
Wah-Keat Lee
Keyword(s):  
Data Analysis ◽  
Data Processing ◽  
Chemical Information ◽  
Graphic User Interface ◽  
Specific Data ◽  
X Ray ◽  
Primary Image ◽  
Material Sciences ◽  
Microscopy Data ◽  
Processing Steps

A transmission X-ray microscope (TXM) can investigate morphological and chemical information of a tens to hundred micrometre-thick specimen on a length scale of tens to hundreds of nanometres. It has broad applications in material sciences and battery research. TXM data processing is composed of multiple steps. A workflow software has been developed that integrates all the tools required for general TXM data processing and visualization. The software is written in Python and has a graphic user interface in Jupyter Notebook. Users have access to the intermediate analysis results within Jupyter Notebook and have options to insert extra data processing steps in addition to those that are integrated in the software. The software seamlessly integrates ImageJ as its primary image viewer, providing rich image visualization and processing routines. As a guide for users, several TXM specific data analysis issues and examples are also presented.

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