Noisy image enhancements using deep learning techniques

This article explores the application of deep learning techniques to improve the accuracy of feature enhancements in noisy images. A multitasking convolutional neural network (CNN) learning model architecture has been proposed that is trained on a large set of annotated images. Various techniques have been used to process noisy images, including the use of data augmentation, the application of filters, and the use of image reconstruction techniques. As a result of the experiments, it was shown that the proposed model using deep learning methods significantly improves the accuracy of object recognition in noisy images. Compared to single-tasking models, the multi-tasking model showed the superiority of this approach in performing multiple tasks simultaneously and saving training time. This study confirms the effectiveness of using multitasking models using deep learning for object recognition in noisy images. The results obtained can be applied in various fields, including computer vision, robotics, automatic driving, and others, where accurate object recognition in noisy images is a critical component

Detection of heart pathology using deep learning methods

In the directions of modern medicine, a new area of processing and analysis of visual data is actively developing - a radio municipality - a computer technology that allows you to deeply analyze medical images, such as computed tomography (CT), magnetic resonance imaging (MRI), chest radiography (CXR), electrocardiography and electrocardiography. This approach allows us to extract quantitative texture signs from signals and distinguish informative features to describe the heart's pathology, providing a personified approach to diagnosis and treatment. Cardiovascular diseases (SVD) are one of the main causes of death in the world, and early detection is crucial for timely intervention and improvement of results. This experiment aims to increase the accuracy of deep learning algorithms to determine cardiovascular diseases. To achieve the goal, the methods of deep learning were considered used to analyze cardiograms. To solve the tasks set in the work, 50 patients were used who are classified by three indicators, 13 anomalous, 24 nonbeat, and 1 healthy parameter, which is taken from the MIT-BIH Arrhythmia database

Parasitic Effects of PWM-VSI Control Leading to Torque Harmonics in AC Drives

Precise torque control without pulsations is one of the major quality issues in pulse-width modulated voltage-source inverter (PWM-VSI) drives. Theoretically, it could be postulated that at frequencies of some kHz, the machine’s inertia absorbs switching frequency torque harmonics, and the resulting torque becomes smooth; though, in reality, parasitic effects in voltage source inverters may cause additional torque harmonics of low order. In particular, first, second and sixth torque harmonics are observed. Such torque harmonics are especially dangerous for normal drive operation, since they may be amplified by drive train resonances at corresponding rotational velocities. New parasitic effects in PWM-VSI control, leading to torque harmonic of low order, are described in the paper, and recommendations for their compensation are given

The Use of Phosphorus-Containing Waste and Algae to Produce Biofertilizer for Tomatoes

The current state of phosphorus-containing waste and the methods of its disposal remain relevant. The storage of phosphorus-containing waste sludge is carried out in sludge collectors, which occupy large areas. With the disposal of slags and sludge, as well as the elimination of sludge collectors, the harmful effect of waste on the soil will cease, and the possibility of using these areas for economic land use will appear. Many studies show the movement of phosphorus in soil and water, thus proving the difficulty of disposing of this waste. Of course, phosphorus slags and sludge are used in small quantities in the production of building materials, but this does not solve all the problems. In the south of Kazakhstan, there are warehouses for the waste from the production of phosphorus-containing fertilizers, which also require disposal. One of the ways of modern utilization of these wastes is their use in fertilizers for agriculture. However, since the phosphorus-containing waste has a high content of phosphorus, compared to nitrogen and potassium, this ratio can be changed with the addition of chlorella biomass. The purpose of the conducted study was to investigate the possibility of using a complex of phosphorus waste and algae, that is, the cultivation of chlorella at various concentrations of phosphorus-containing waste for further use of the suspension in watering the test plant. In the form of a test plant, tomato seeds were chosen, the cultivation of which in agriculture is economically profitable. When cultivated in closed ground, tomatoes lose their taste, which can be restored with the use of organic fertilizers. This article shows the results of the influence of various concentrations of phosphorus waste and green microalgae on the growth and development of Solanum lycopersicum

Use of Phytomeliorant Plants for Waste Water Purification

The use of phytomeliorant plants is one of the promising trends in environmental biotechnology to purify waste water. The study was carried out to understand the phytomeliorative qualities of plants of the indigenous flora of the Turkestan Region under controlled conditions and to develop a method for treating wastewater. It was established that the use of a three-stage treatment of municipal wastewater using phytomeliorant plants: Ceratophуllum demersum L., Potamogeton trichoides Cha. Et Schlecht., Potamogeton pectinatus L., Potamogeton natans L.; Cardamine densiflora N. Gontsch., Sium sizaroideum DC.; Veronica beccabunga L, Veronica anagallis aquatica L. and Azolla caroliniana Willd for 30 days of the controlled experiment reduces the content of organic and mineral ingredients to the MPC values. A method for phyto-meliorative wastewater treatment of one of the sanatoriums in the south of Kazakhstan was developed and carried out in multi-stage bioponds, where water was purified from mineral and organic compounds by 94.9 ± 8.3 – 98.9 ± 7.8% in 12 days. In this study, first of all, nitrogenous compounds were utilized, then there was an active absorption of mineral ions and residual organic matter by plants. In conclusion, significant purification of wastewater was achieved by using indigenous phytomeliorant plants in much shorter time period

Analysis of dynamic properties and movement safety of bogies with diagonal links and rubber-metal vibration absorbers between the rubbing elements of freight cars

This article aims to study experimentally the dynamic properties and traffic safety actions for gondola cars with bogies with diagonal links, operated on the territory of the Republic of Kazakhstan. The main results obtained during tests of gondola cars on bogie with diagonal links when they move along straight and curved sections as well as on switches are presented. The estimation of: dynamics coefficients, stability margin coefficients against derailment, lateral forces transmitted from the wheel to the rail, ratio of frame forces to a static load from the wheelset on the rails, and accelerations are made. The paper analyses the simulation of a polymer layer of rubber vibration absorber, to be installed between the rubbing surfaces, such as the link side of frame axle unit, and host unit is open-bearing, with lateral support of the three-piece freight car bogies, operating on the territory of the Commonwealth of Independent States. The model developed in this article consists of a rheological model of a Maxwell cell, a Fancher spring and an element which has the function of non-linearity. The simulation model can be used to study the characteristics of vibration dampers, gaskets and other power elements that have polymer properties and are installed at other types of transport and not only

Study of the Process of Destruction of Harmful Microorganisms in Water

In this scientific work, the problem of studying the process of destruction of microorganisms in water by an Etro-03 device based on electric corona discharge is considered. In the research, a special Etro-03 ozonator device was developed for clearing water of biological pollutants. Testing of the installation was carried out in order to disinfect surface water in the Kapshagai reservoir. During the research, various harmful microorganisms were found in the composition of the primary water that did not meet the maximum permissible concentration (MPC). For example, coliphages, coli-indices, and the number of microbes in general came across in large numbers. During the technological process, various amounts of ozone (O3) were released into the water, the amount and effective economic indicators of which were determined. In the same way, the effective time of the decontamination process was determined. During the research process, an algorithm of theoretical calculations was developed, and a mathematical model was given to bring 1m3 of surface water as the indicator for which sanitary rules and norms are approved

Оцінка виявлення хвороб рослин шляхом глибокого навчання

Plant disease and pest detection machines were originally used in agriculture and have, to some extent, replaced traditional visual identification. Plant diseases and pests are important determinants of plant productivity and quality. Plant diseases and pests can be identified using digital image processing. According to the difference in the structure of the network, this study presents research on the detection of plant diseases and pests based on three aspects of the classification network, detection network, and segmentation network in recent years, and summarizes the advantages and disadvantages of each method. A common data set is introduced and the results of existing studies are compared. This study discusses possible problems in the practical application of plant disease and pest detection based on deep learning. Conventional image processing algorithms or manual descriptive design and classifiers are often used for traditional computer vision-based plant disease and pest detection. This method usually uses various characteristics of plant diseases and pests to create an image layout and selects a useful light source and shooting angle to produce evenly lit images. The purpose of this work is to identify a group of pests and diseases of domestic and garden plants using a mobile application and display the final result on the screen of a mobile device. In this work, data from 38 different classes were used, including diseased and healthy leaf images of 13 plants from plantVillage. In the experiment, Inception v3 tends to consistently improve accuracy with an increasing number of epochs with no sign of overfitting and performance degradation. Keras with Theano backend used to teach architecturesМашини для виявлення хвороб рослин і шкідників спочатку використовувалися в сільському господарстві та певною мірою замінили традиційну візуальну ідентифікацію. Хвороби та шкідники рослин є важливими факторами, що визначають продуктивність і якість рослин. За допомогою цифрової обробки зображень можна ідентифікувати хвороби та шкідників рослин. Відповідно до різниці в структурі мережі, ця стаття представляє дослідження щодо виявлення хвороб рослин і шкідників на основі трьох аспектів мережі класифікації, мережі виявлення та мережі сегментації за останні роки, а також узагальнює переваги та недоліки кожного з методів. Представлено загальний набір даних і порівняно результати існуючих досліджень. У цьому дослідженні обговорюються можливі проблеми в практичному застосуванні виявлення хвороб рослин і шкідників на основі глибокого навчання. Звичайні алгоритми обробки зображень або ручний описовий дизайн і класифікатори часто використовуються для традиційного комп’ютерного зору на основі виявлення хвороб рослин і шкідників. Цей метод зазвичай використовує різні характеристики хвороб рослин і шкідників для створення компонування зображення та вибирає корисне джерело світла та кут зйомки для створення рівномірно освітлених зображень. Метою роботи є ідентифікація групи шкідників і хвороб домашніх і городніх рослин за допомогою мобільного додатку та відображення кінцевого результату на екрані мобільного пристрою. У цій роботі були використані дані з 38 різних класів, включаючи зображення хворих і здорових листків 13 рослин з plantVillage. В експерименті Inception v3 має тенденцію до постійного підвищення точності зі збільшенням кількості епох без ознак переобладнання та погіршення продуктивності. Keras із серверною частиною Theano використовується для навчання архітектур