In this article, the research presents a general overview of deep learning-based AVSS (audio-visual source separation) systems. AVSS has achieved exceptional results in a number of areas, including decreasing noise levels, boosting speech recognition, and improving audio quality. The advantages and disadvantages of each deep learning model are discussed throughout the research as it reviews various current experiments on AVSS. The TCD TIMIT dataset (which contains top-notch audio and video recordings created especially for speech recognition tasks) and the Voxceleb dataset (a sizable collection of brief audio-visual clips with human speech) are just a couple of the useful datasets summarized in the paper that can be used to test AVSS systems. In its basic form, this review aims to highlight the growing importance of AVSS in improving the quality of audio signals.
In this paper the analysis of the corrosion basic types destructions on an example of buildings constructions is carried out and the basic requirements to materials for designs in construction are defined. A classification of corrosion damage is proposed, which became a prerequisite for selecting the main indicators of materials that maximally affect the quality and durability. The main methods for determining the main indicators of corrosion damage are identified.
Most studies on deep beams have been made with reinforced concrete deep beams, only a few studies investigate the response of prestressed deep beams, while, to the best of our knowledge, there is not a study that investigates the response of full scale (T-section) prestressed deep beams with large web openings. An experimental and numerical study was conducted in order to investigate the shear strength of ordinary reinforced and partially prestressed full scale (T-section) deep beams that contain large web openings in order to investigate the prestressing existence effects on the deep beam responses and to better understand the effects of prestressing locations and opening depth to beam depth ratio on the deep beam performance and b
... Show MoreCurrently, one of the topical areas of application of machine learning methods is the prediction of material characteristics. The aim of this work is to develop machine learning models for determining the rheological properties of polymers from experimental stress relaxation curves. The paper presents an overview of the main directions of metaheuristic approaches (local search, evolutionary algorithms) to solving combinatorial optimization problems. Metaheuristic algorithms for solving some important combinatorial optimization problems are described, with special emphasis on the construction of decision trees. A comparative analysis of algorithms for solving the regression problem in CatBoost Regressor has been carried out. The object of
... Show MoreSingle long spiral tube column pressure swing adsorption (PSA) unit, 25 mm diameter, and 6 m length was constructed to study the separation of water from ethanol at azeotropic concentration of 95 wt%. The first three meters of the column length acted as a vaporizer and the remaining length acted as an adsorber filled by commercial 3A zeolite. The effect of pressure, temperature and feed flow rate on the product ethanol purity, process recovery and productivity were studied. The results showed that ethanol purity increased with temperature and pressure and decreased with feed flow rate. The purity decreased with increasing productivity. The purity range was 98.9 % to 99.6 %, the recovery range was 0.82 to 0.92 and the productivity range w
... Show MoreThe research demonstrates new species of the games by applying separation axioms via sets, where the relationships between the various species that were specified and the strategy of winning and losing to any one of the players, and their relationship with the concepts of separation axioms via sets have been studied.