scholarly journals Towards the Formal Modeling Methodology of WSN through the Transformation of SysML into DSPNs

Author(s):  
Amel Berrachedi ◽  
Malika Ioualalen ◽  
Ahmed Hammad
2019 ◽  
Author(s):  
Robin Glebes ◽  
Joshua Dustin ◽  
Jan-Anders Mansson

2011 ◽  
Vol 22 (11) ◽  
pp. 2698-2715 ◽  
Author(s):  
Fang-Xiong XIAO ◽  
Zhi-Qiu HUANG ◽  
Zi-Ning CAO ◽  
Li-Zhong TU ◽  
Yi ZHU

Author(s):  
Victor L. Shabanov ◽  
Marianna Ya Vasilchenko ◽  
Elena A. Derunova ◽  
Andrey P. Potapov

The aim of the work is to find relevant indicators for assessing the relationship between investments in fixed assets in agriculture, gross output of the industry, and agricultural exports using tools for modeling the impact of innovation and investment development on increasing production and export potential in the context of the formation of an export-oriented agricultural economy. The modeling methodology and the proposed estimating and forecasting tools for diagnosing and monitoring the state of sectoral and regional innovative agricultural systems are used to analyze the relationship between investments in fixed assets in agriculture, gross output of the industry, and agricultural exports based on the construction of the classification of Russian regions by factors that aggregate these features to diagnose incongruence problems and to improve institutional management in regional innovative export-oriented agrosystems. Based on the results of the factor analysis application, an underestimated role of indicators of investment in agriculture, the intensity and efficiency of agricultural production, were established. Based on the results of the cluster analysis, the established five groups of regions were identified, with significant differences in the level of investment in agriculture, the volume of production of the main types of agricultural products, and the export and exported food. The research results are of practical value for use in improving institutional management when planning reforms and transformations of regional innovative agrosystems.


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