Physicomathematical models of seeds and errors in calculating the volume of an electro terminator filled with seeds

Denmukhammadiev, Aktam; Pardaev, Abror; Begmatov, M; Abdirakhmonov, I.; Akhmedov, M.Sh.

doi:10.1051/e3sconf/202126401053

Cited by 3 publications

(3 citation statements)

References 12 publications

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“…We have studied external and internal influences that adversely affect a multi-story building [16], the physical and mathematical models of seeds (as bulk material), and the errors in calculating the volume of the electroterminator filled with these seeds were studied [17] and a physical and electronic model of an infrared emitter for drying winding insulation was studied to create an intelligent heating control system and. winding insulation drying [18].…”

Section: Resultsmentioning

confidence: 99%

Electronic-physical model that determines thermal conductivity of walls made of various materials

Denmukhammadiev,

Pardaev,

Kucharov

et al. 2023

E3S Web of Conf.

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The article analyzes data on creating an electronic-physical model designed to determine the thermal conductivity of walls from various loose or solid materials used in the agricultural sector and construction. At the end of 2022 and the beginning of 2023, during the abnormally cold winter days observed in the Republic of Uzbekistan, accidents were observed at many construction sites and in heating networks. In response to this, by the government's decision, practical work was carried out to cover buildings' outer part (facade) with special basalt material. The studies of one-dimensional heat transfer in a compound cylinder carried out in a stationary mode at a constant thermal conductivity of the material, are analyzed. In these studies, heat conduction equations were studied with the results of heat transfer simulations developed using the Ansys software. The electronic-physical model proposed in the article allows you to quickly and accurately measure the heat and thermal diffusivity of walls made of various materials. It will be possible to intelligently control the electronic-physical model using thermal sensors. The article contains detailed engineering calculations and illustrative materials. Internet data was analyzed, and specific conclusions were drawn. The prerequisites for the creation of an intelligent system for measuring the temperature and thermal conductivity of walls from various bulk materials are made in the work.

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Section: Resultsmentioning

confidence: 99%

Electronic-physical model that determines thermal conductivity of walls made of various materials

Denmukhammadiev,

Pardaev,

Kucharov

et al. 2023

E3S Web of Conf.

Self Cite

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“…The problems of filling a volume with periodic spherical dispersed particles of the same radius were studied by the authors as a mathematical model [19]. The study of the calculation model and the detection of errors when filling containers of various shapes with fine-grained cotton seeds are considered in the article [20]. Here, the authors note the possibility of optimal design of various vessel shapes using mathematical and geometric models of bodies.…”

Section: Resultsmentioning

confidence: 99%

A priori data on pre-sowing treatment and primary experiments on electric heating of onion seeds

Denmukhammadiev,

Pardaev,

Sobirov

2023

E3S Web Conf.

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Currently, Uzbekistan is among the twenty most advanced countries in the cultivation of onions. The onion plant was interpreted as a symbol of life in ancient Greek mythologies. Onion is one of the most widely consumed foods in the world due to its essential health and preventive properties, as one of the most essential fruits in the kitchen in the daily diet. The article studies the methods of processing onions before planting based on an analysis of the countries of the world. The results of studies of the influence of various electrophysical parameters on onion seeds are presented analytically. The effective influence of the electric field strength on the health of seeds is explained. The authors also referred to the results and methods of scientific research conducted at NRU “TIIAME” and analyzed the electrical and mechanical properties of onion seeds based on specific experiments. In particular, we analyzed the mass of 1000 seeds, the filling factor of the cubic container, and the initial (primary) results of determining the electrical and thermal conductivity of soaked seeds. The article also provides information on the impact of alternating electric current on onion seeds, developed special electrodes for determining electrical resistance, and a methodology for conducting research experiments. An electrical circuit is presented that ensures the completeness of seed treatment. There are also materials on the positive effect of “electrically activated” water on the additional health of soaked onion seeds. It is shown that the necessary conditions have been created for the process of automated intelligent control of the temperature of soaked onion seeds.

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“…However, only using spectral features cannot fully characterize the fine local water information. Therefore, there are many methods to extract spatial information from remote sensing images based on mathematical models [18,19].…”

Section: Remote Sensing Imagementioning

confidence: 99%

Remote Sensing Image Water Body Recognition Algorithm Based on Deep Convolution Generating Network and Combined Features

Zhao

Feng

2022

Wireless Communications and Mobile Computing

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The application of remote sensing images in water body recognition has become an effective method for ecological environment detection and evaluation, which has the disadvantages of low efficiency due to the existence of interpretation marks and rich interpretation experience in the current water body environment recognition, and overreliance on human experience. In this paper, the water body recognition method is applied to remote sensing images by combining the deep convolution generation network and the combined features, which has the advantage of high recognition accuracy. In the convolutional neural network, a five-layer convolutional neural network is used to construct a remote sensing water information extraction model, the transfer learning idea is introduced, and the densely connected feature fusion structure is added, so as to achieve the purposes of accelerating the convergence speed of the neural network, reducing the requirements of the neural network on the scale of training data, and reducing the loss of spatial hierarchical information and small object information. Compared with SVM, DBN, and CNN models, the experimental results show that the recognition accuracy of the proposed method is as high as 95. 69% under the constraint of scale window, which has a wide range of application scenarios and practical significance.

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Physicomathematical models of seeds and errors in calculating the volume of an electro terminator filled with seeds

Cited by 3 publications

References 12 publications

Electronic-physical model that determines thermal conductivity of walls made of various materials

Electronic-physical model that determines thermal conductivity of walls made of various materials

A priori data on pre-sowing treatment and primary experiments on electric heating of onion seeds

Remote Sensing Image Water Body Recognition Algorithm Based on Deep Convolution Generating Network and Combined Features

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