Mathematical and Computer Modelling
Penghui Zheng1, 2, Youwen Tian1, 2, Ruiyao Shi1, 2
COMPUTER MODELLING & NEW TECHNOLOGIES 2016 20(3) 7-11
1College of Information and Electrical Engineering, Shenyang Agricultural University
2Agricultural Information Engineering Technology Research Center of Liaoning Province Shenyang City, Liaoning province, China
A detecting way based on Android platform was proposed in order to detect greenhouse crop disease degree in real time. This way employed the camera in mobile phone to acquire crop disease leaf image in the greenhouse. Firstly, the detection system was built by the Eclipse based on the Android development environment. The iterative threshold segmentation algorithm was used to separate the crop disease leaf area from background. And the fuzzy C-means cluster algorithm was adopted to extract the disease spots. After analyzed the impact of different fuzzy weighted index m value, the value of m was selected 2 for the disease spots segmentation. After that the crop disease degree was determined based on the relevant standards and the total disease index of greenhouse was got based on disease index calculation standards. Finally, the calculating data could upload to the network server and was used management cloud achieved synchronous computer terminal query. The experimental results show that the detecting way could non-destructed measure the disease index of leaf diseases with non-destructive and exact in greenhouse.
Cuilian You, Lijuan Yan
COMPUTER MODELLING & NEW TECHNOLOGIES 2016 20(3) 12-16
College of Mathematics and Information Science, Hebei University, Baoding 071000, China
Uncertain sequence is a sequence of uncertain variables indexed by integers. In this paper, a new kind of
sequence convergence that complete convergence was presented. Then, the relationships among complete
convergence, convergence in p-distance, convergence in measure, convergence in distribution, convergence
uniformly almost surely and convergence almost surely were investigated.
Amir Mokhtar Hannane, Hadria Fizazi
COMPUTER MODELLING & NEW TECHNOLOGIES 2016 20(3) 17-23
COMPUTER MODELLING & NEW TECHNOLOGIES 2016 20(3) 24-31
Network & Information Center, East China Normal University, Shanghai, 200062, China
We give direct detailed proofs for the connection between powerdomains and logic models which can be made about nondetermin- istic computations. In the proceeding of proofs, we prove some algebraic properties of them at the same time. Meanwhile, we take up some trick for constructing the finite branching tree, which can also be used into the other areas.
N Vihrov, V Nikiforov, J Polugina, S Sokolov, A Nyrkov, V Gaskarov, A Zhilenkov
COMPUTER MODELLING & NEW TECHNOLOGIES 2016 20(3) 32-34
Kairat Bostanbekov1,2, Daniyar Nurseitov2
COMPUTER MODELLING & NEW TECHNOLOGIES 2016 20(3) 35-41
1International University of Information Technologies (IUIT), Almaty, Kazakhstan
2Kazakh National Research Technical University (KazNRTU), Almaty, Kazakhstan
This article describes the development of a multifunctional geoinformation system RANDOM (Risk Assessment of Nature Detriment due to Oil spill Migration), realizing a multiprocessor calculation of probabilistic risk models to assess the negative impact of the oil spill on the biota of the North Caspian. The urgency of the problems associated with the development of oil fields in a very vulnerable shallow part of the Caspian Sea, where a major accident could have disastrous consequences. This article describes the development process from design to implementation to testing. The system is designed on the basis of service-oriented architecture (SOA), which allows for easy, flexible integration of services, and access them via the Internet. Through the use of SOA, the system can be expanded and upgraded. In this approach, the services may be located on physically different servers. Described in detail the process of parallel processing of large data set, shows the comparative tests on performance calculations. Tests have shown the benefit of using a supercomputer, it enables us to obtain a risk assessment for an adequate time. This system is designed for professionals in the field of ecology and mathematical modeling and subsoil oil fields on the continental shelf of the seas and oceans. RANDOM system as the final result of the decision of risk assessment tasks includes a series of calculation modules based on the methods of probability theory, computational mathematics, hydrodynamics, oil chemistry, marine biology, mathematical modeling and geoinformatics.