Floating car data processing model based on Hadoop-GIS tools

Bayesian method was introduced and leaded into the vehicle fault data processing. The parameter estimation and the selection of the optimal distribution model based on Bayesian method were studied, and an example was given. The references are provided for the application of Bayesian method in the large complicated systems, such as vehicle equipments.

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Analytical challenges of untargeted GC-MS-based metabolomics and the critical issues in selecting the data processing strategy

F1000Research ◽

10.12688/f1000research.11823.1 ◽

2017 ◽

Vol 6 ◽

pp. 967 ◽

Cited By ~ 11

Author(s):

Ting-Li Han ◽

Yang Yang ◽

Hua Zhang ◽

Kai P. Law

Keyword(s):

Quality Control ◽

Data Processing ◽

Epidemiological Study ◽

Internal Standard ◽

Analytical Techniques ◽

Experimental Conditions ◽

Data Set ◽

Raw Data ◽

Model Based ◽

Critical Issues

Background: A challenge of metabolomics is data processing the enormous amount of information generated by sophisticated analytical techniques. The raw data of an untargeted metabolomic experiment are composited with unwanted biological and technical variations that confound the biological variations of interest. The art of data normalisation to offset these variations and/or eliminate experimental or biological biases has made significant progress recently. However, published comparative studies are often biased or have omissions. Methods: We investigated the issues with our own data set, using five different representative methods of internal standard-based, model-based, and pooled quality control-based approaches, and examined the performance of these methods against each other in an epidemiological study of gestational diabetes using plasma. Results: Our results demonstrated that the quality control-based approaches gave the highest data precision in all methods tested, and would be the method of choice for controlled experimental conditions. But for our epidemiological study, the model-based approaches were able to classify the clinical groups more effectively than the quality control-based approaches because of their ability to minimise not only technical variations, but also biological biases from the raw data. Conclusions: We suggest that metabolomic researchers should optimise and justify the method they have chosen for their experimental condition in order to obtain an optimal biological outcome.

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Model-based object recognition by wave-oriented data processing

10.1117/12.213105 ◽

1995 ◽

Cited By ~ 1

Author(s):

Lawrence Carin ◽

Leopold B. Felsen ◽

Chi Tran

Keyword(s):

Object Recognition ◽

Data Processing ◽

Model Based

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An Analysis of an Area’s Vulnerability to the Emergence of Land-Use Conflicts

Land ◽

10.3390/land10111173 ◽

2021 ◽

Vol 10 (11) ◽

pp. 1173

Author(s):

Iwona Cieślak ◽

Andrzej Biłozor

Keyword(s):

Land Use ◽

Data Processing ◽

Spatial Planning ◽

Statistical Data ◽

Statistical Data Processing ◽

Land Use Conflict ◽

Gis Tools ◽

Land Use Conflicts ◽

Surrounding Space ◽

Data Processing Methods

The optimization of space is the priority goal of spatial planning. Spatial planning policies have numerous objectives, including the prevention of land-use conflicts. Conflicts arise whenever two entities have contradictory expectations regarding the surrounding space. In the process of spatial development, humans impart new characteristics to space, which, under specific circumstances, can give rise to land-use conflict. The elements of space that are particularly vulnerable to conflict include boundary points, property boundaries, density of development, or the shared use of infrastructure. The main aim of this study was to develop a procedure for evaluating the risk of land-use conflict based on the characteristic attributes of space. The proposed procedure for assessing the accumulation of conflict-generating traits in space was developed with the use of databases, GIS tools, and statistical data processing methods.

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