It is estimated that more than 9% of the Russian population is hearing impaired, and the development of dactyl recognition systems is becoming critical to facilitate their social communication. The introduction of dactyl recognition systems will improve communication for these people, providing them with equal opportunities and improving their quality of life. The research focused on learning the characters of the dactyl alphabet, as well as developing a labeled dataset and training a neural network for gesture recognition. The aim of the work is to create tools capable of recognizing the signs of the Russian dactyl alphabet. Within the framework of this research the method of computer vision was applied. The process of gesture recognition consists of the following steps: first the camera captures the video stream, after the images of hands are preprocessed. Then a pre-trained neural network analyzes these images and extracts important features. Next, gesture classification takes place, where the model determines whether the sign belongs to a certain letter of the alphabet. Finally, the recognition results are interpreted into a suitable symbol associated with the gesture. During the research process, the signs of the dactyl alphabet and interaction features of people with auditory impairment were studied and a dataset of more than 25000 trained data was also created. A model was developed and trained based on the most appropriate architecture for the task of the work. The model was tested and optimized to improve its accuracy. The results of this work can be used in the creation of devices to compensate for poor hearing, providing people with hearing impairment comfort in society.

Keywords: computer vision, sign recognition, dactyl classification, transfer learning, Russian dactyl alphabet, deep learning, computerization, software, assistive technology, convolutional neural networks

During the harvesting of crops, a significant amount of straw residues is formed, which can be used as raw material for subsequent processing. To assess the volume of straw suitable for processing for various needs of the agro-industrial complex, it is proposed to apply the Lotka-Volterra method. Using this method, it is possible to predict the formation of straw residues depending on the initial indicators during harvesting.

Keywords: straw residues, processing of straw raw materials, modeling, Lotka-Volterra method

A widespread technology with deep litter floor with broilers. Promising material for bedding are the straw materials. However, straw, held a simple reduction, does not meet the zootechnical requirements, in particular the recommended length of the cut should be 50 mm to 150 mm. Thus, there arises the problem of fractionation straw, obtained at harvest crops as waste. We carried out an analysis of the different types of fractional chopped straw with nodal connections without them. Studies have been conducted on the behavior of these types in an air classifier with a velocity change .

Keywords: The straw residues fractionation aerodinomicheskie performance, fly speed

In the article we research application of culmiferous waste products of in the capacity of fractionated culmiferous litter on poultry plants at the low-ground content animal. For definition of optimal parameters of processing the initial culmiferous material exposed machining by a microwave radiation and was researched on micro and nano level for revealing qualitative changes of a structural surface.

Keywords: culmiferous bedding, microwave radiation, structural surface, the energy of the microwaves, capillary condensation, "pin" structure, scanning probe microscope.