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Optical heat generation and control at the nanoscale play a key role in many applications, such as photothermal therapy, photocatalysis, thermophotovoltaics, etc. Adjusting the photoheating temperature can be easily performed by tuning the intensity of the incident light. However, fine tuning of the temperature of nanostructures at a fixed light intensity still remains a challenging task. In this work, we propose a tunable optical nanoheater that consists of a titanium oxynitride (TiON) plasmonic antenna placed on top of a silicon cylinder. It has been experimentally shown that, at a fixed intensity of 5 MW/cm², a change in the photoheating temperature up to 100 ^◦C can be achieved. The underlying approach is based on the controlled oxidation of TiON. This allows for flexible tailoring the permittivity of TiON. As a result, the photoheating temperature can be tuned, which is associated with the modification of the absorption cross-section of plasmonic nanostructure.

A method of adaptive quantization of discrete wavelet transform coefficients in the JPEG2000 standard, based on the algorithm of search and identification of small image structures, which are distinguished by human vision, is proposed. The method of image block classification by structure features and the identification algorithm of coefficients of block transformation in sub-bands of the discrete wavelet transform are described. A description of the adaptive quantization algorithm and recommendations on tuning the quantizer parameters for high image sharpness are given. Experimental estimates of the efficiency of compression of photorealistic images with different detail are provided, which allow conclusions about the advantages of the new method in comparison with analogues to be drawn and recommendations for its further development in intelligent video systems to be given.

We analyses the issues with processing data obtained from a 3d X-ray microtomograph when dealing with problem diagnosis and classification of defects in radio-electronic devices. It is proposed to use neural network methods and regularizing splines for solving the problem. A comparative analysis of neural network and spline methods is carried out in solving problems of recovering heavily noisy signals. The effectiveness of the proposed approach is studied by numerical simulation methods and in the processing of real data.

In this paper, the maximum detection range of the various chessboard corners detection algorithms is compared. The requirements to the minimum square size for detecting the internal corners of a chessboard are determined. Formulae for determining the maximum distance to a chessboard of a known size and the smallest detectable size of a chessboard for a given distance are proposed

A method is proposed for fast selection of bandwidths of kernel functions in the nonparametric estimation of a two-dimensional random variable with dependent components. The method is based on the results of the analysis of the asymptotic properties of the Rosenblatt-Parsen kernel probability density estimation. The properties of a fast algorithm for bandwidth selecting in the considered nonparametric estimation of the probability density are investigated.

A model of the formation of a hyperspectral image by a space-scanning system due to the translational motion of the unmanned aerial vehicle on which it is installed is considered. The relationship between the angular deviation of the aircraft roll and the nature of geometric distortions of the hyperspectral image lines formed is determined. An algorithm of correction of introduced distortions according to the data of the inertial navigation system is presented. The results of modeling and processing of real images reveal acceptable correction quality and computational simplicity of the developed algorithm.

A new method of high-precision positioning of mobile objects moving along program trajectories, based on the processing of satellite navigation measurements using robust filtering algorithms, has been proposed. The method is based on the possibility of approximating (in particular, using electronic maps) the program trajectory of an object with a set of trajectory intervals with known analytical dependencies of navigation parameters, as well as the use of robust stochastic filtering methods that take into account the characteristic dynamics of the object and the uncertain nature of the type of interference distributions of Doppler and code satellite measurements. Integration of electronic map information providing high accuracy of trajectory binding and algorithms of robust nonlinear filtering of satellite measurements optimal by the criterion of the minimum nonlinear function of measurement mismatch determined by the class of interference distributions of Doppler and code measurements has been carried out. This makes it possible to significantly reduce computing costs, while significantly improving the accuracy of object positioning. The effectiveness of the proposed method is illustrated by a numerical example.

It is found that, for some non-autonomous methods of navigation in space, there are autonomous methods “symmetrical” to them, in which all measurements are carried out only from the board of the spacecraft whose position is determined. In this case, the measurement results obtained in the corresponding non-autonomous methods are reproduced. Since the instant of obtaining the same type of measurements, processing in both "symmetric" methods is carried out according to identical algorithms. Two pairs of such methods are considered. The difference in the degree of "symmetry" and the possibility of using intermediate data for processing observations are discussed.

A single-position hybrid method of bearing-free passive location of a moving source of pulsed periodic radio signal emission is proposed. The method takes into account temporal and energy measurements. The method is valid for all directions of target motion along both straight-line and curvilinear trajectories. No current estimation of the Doppler frequency is required; the time shift and relative power generated by the period evolution and signal level at the observation point serve as measured parameters. Issues related to determining the range and other parameters of motion, computational correctness, and accuracy characteristics are considered. Practical considerations and a numerical example are provided.

The previously developed methodology for constructing automated process control systems for the production of coaxial communication cables extends to solving the problems of synthesizing digital controlled systems for automating technological processes for the manufacture of radio frequency cables, including data cables, on which structured cable wiring systems are built for the implementation of local computer systems. The methodology of a new approach to optimizing the control of multilevel "bottom-up" systems, implemented on in-loop and inter-loop digital controllers, providing global optimization by generalized indicators of control quality, is described. These criteria, in contrast to typical optimization criteria, make it possible to achieve the best performance characteristics of the manufactured cable products, which is ensured by the optimal tuning of digital regulators according to the simulation model of the controlled system.