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Training to perform robotic surgery is time-consuming with uncertain metrics of the level of achieved skill. We tested the feasibility of using muscle co-contraction as a metric to quantify robotic surgical skill in a virtual simulation environment. We recruited six volunteers with varying skill levels in robotic surgery. The volunteers performed virtual tasks using a robotic console while we recorded their muscle activity. A co-contraction metric was then derived from the activity of pairs of opposing hand muscles and compared to the scores assigned by the training software. We found that muscle-based metrics were more sensitive than motion-based scores in quantifying the different levels of skill between simulated tasks and in novices vs. experts across different tasks. Therefore, muscle-based metrics may help quantify in general terms the level of robotic surgical skill and could potentially be used for biofeedback to increase the rate of learning.

The final aim of our research is to develop a braincomputer interface (BCI) for olfaction. Our research program relies on modern olfactory displays and advanced processing of electroencephalography (EEG) and respiratory data in order to develop methods for robust olfactory BCI systems. Here we present the initial results from 17 subjects of our ongoing study. Applying k-nearest neighbors algorithm (k-NN) classification methods we achieve up to 79.9% accuracy for within subject classification of EEG signals for odor pairs. We propose some methods for further improvement of classification algorithm. EEG classification for different olfactory stimuli is the first step in this research, followed by the development of odor-imagery BCIs and odor-based neurofeedback.

The system of non-contact ultrasonic testing of polymer composite materials by the shadow method system is described. Frequency dependence of the integral informative parameter is presented for different values of time points of integration. Possibility to operate simultaneously on two working frequencies is shown.

The system of contactless ultrasonic testing of polymer composite materials by the shadow method system is described. The results of testing various samples and types of detected defects are presented. The spectra of the signal and noise are calculated by discrete Fourier transforming. Frequency separation method is used for noise filtration, signal-component separation and for calculation of signal envelope.

The manufacturing technology of p++-Si/SiO x /Ni memristor structures was developed. The SiO x functional layer was obtained by the processing of thermal silicon oxide in hydrogen electron-cyclotron resonance (ECR) plasma. Varying plasma processing parameters made it possible to obtain n++-Si/SiO x /Ni memristor structures with the $x$ coefficient ranging from 1.79 to 2.0 and the oxide layer thickness from 14 to 20 nm. All obtained structures exhibited bipolar reversible resistive switching. Minimal forming voltages (≈7 V) were obtained for the samples with $x = 1.79-1.83$ . In addition, all of the obtained memristors demonstrated a sufficiently large ratio of currents in low- and high-resistance states (memory window) amounting to 3 - 4 orders of magnitude.

The paper considers a simulation model of electrochemical electrical energy storage based on the known electrical characteristics. A peculiar feature of the model is the use of parametric dependencies obtained by the regression analysis according to the available experimental data. The model implements a change in the voltage and internal resistance depending on the charge depth, as well as a change in the battery capacity depending on the ambient temperature. The article shows the implementation of the mathematical model in the MATLAB/Simulink environment and presents the results of the validity check of the proposed model under various external influences. It presents the results of model experiments to determine the change in the degree of charge, voltage, and the amount of stored energy over time at the specified values of the charge current. The model can be useful for modeling interconnected power systems with energy storage to simulate changes in the parameters of electric circuits due to the battery charge/discharge process, as well as under the influence of the ambient temperature.

Industry 4.0. with its inherent complexity of technologies, digitalization and intellectualization encourages universities to look for new innovative approaches in education to provide students with advanced professional competencies. Formula Student Electric is an international student competition consisting in the development of racing cars followed by competitive races. However, accidents can happen not only on the track, but also in the garage. A big problem is charging batteries due to the complexity of controlling such a long process. The market lacks ready-made solutions meeting the requirements of the regulations. We developed a schematic diagram of the charger and designed a simplified model of the CC / CV charging process in Simulink. Theoretical calculations show that the charging time of a battery with a capacity of 100 Ah and a maximum voltage of 42 V, in the case of 30 A, took 3 hours 32 minutes to 100% and 1 hour 47 minutes to 50%, at in the case of 20 A - 5 hours 15 minutes and 2 hours 40 minutes, respectively. We selected the charger components. We designed a 3D model of the rack in the SolidWorks software for the safe use of the charger.

The increasingly sophisticated design of modern vehicles affects the technological processes of assembly, repair and maintenance. When assessing the vehicle maintainability, nuances may arise at the operation stage that were not taken into account in the design, especially for new and modernized models. So, problems may arise associated with the non-optimal organization of the repair technological processes or with their injury hazard. Therefore, there is a need for feedback from the manufacturer, who has effective tools for checking and adjusting processes. An algorithm for the technological process of assessing maintainability has been developed, which includes a sequence of actions by designers and technologists and then checking the corrected process in the service center. The use of simulation and virtual reality tools allows to achieve one of the main tasks of any enterprise - ensuring the safe labor of workers, preventing injuries at the workplace. On the other hand, the correct organization of labor increases the productivity of workers and saves time significantly. Simulation of the technological process of removing the crankcase protection has been carried out. We took into account the anthropological parameters of real workers. As a result of optimization experiments, the parameters of the lift were selected, they will reduce the load on all muscle groups, thereby preventing the occurrence of occupational diseases.

This paper presents the architecture, design features and a description about the use of the geographic information system in university campus management. The system architecture is based on the standards of the international organization Open Geospatial Consortium using software products that meet the requirements of free software. This development is intended to manage socio-economic processes in the heterogeneous information environment of Tomsk State University of Control Systems and Radio Electronics.

As part of the electrical equipment modernization, we propose a continuous temperature control system for a chamber resistance furnace. A furnace model is developed in the VisSim software package, which takes into account the heterogeneity of the furnace as a control object and includes 3 heat transfer circuits. System delays caused mainly by the delay of the thermocouple are also taken into account. Calculations of the accuracy of temperature stabilization for relay and digital controllers are performed. The relay control method shows large temperature fluctuations on the heating element, which significantly reduces the service life of the heating elements. The implementation of pulse control using a PID controller based on a temperature controller allows increasing the accuracy of temperature maintenance in all modes to a level of ± 0.2 ° C.

The system of non-contact ultrasonic testing of polymer composite materials by the through-transmission method system is described. Envelopes of fundamental and higher harmonics are investigated by discrete Fourier transformation. The model of ratio of polynomials is used for describing spectra of time signals. The quadrature components are found by modified Prony method. The spatial resolving power is investigated.

Twin study is one of the major parts of human brain research that reveals the importance of environmental and genetic influences on different aspects of brain behavior and disorders. Accurate characterization of identical and fraternal twins allows us to infer on the genetic influence in a population. In this paper, we propose a novel pair-wise classification pipeline to identify the zygosity of twin pairs using the resting state functional magnetic resonance images (rs-fMRI). The new feature representation is utilized to efficiently construct brain network for each subject. Specifically, we project the fMRI signal to a set of cosine series basis and use the projection coefficients as the compact and discriminative feature representation of noisy fMRI. The pair-wise relation is encoded by a set of twin-wise correlations between functional brain networks across brain regions. We further employ hill climbing variable selection to identify the most genetically affected brain regions. The proposed framework has been applied to 208 twin pairs in Human Connectome Project (HCP) and we achieved 92.23(±4.43)% classification accuracy.

Radio frequency fingerprinting enhances security and privacy of wireless networks and communications by learning and extracting unique characteristics embedded in transmitted signals. Deep learning-based approaches learn radio fingerprints without hand-engineering features. One persisting drawback in deep learning methods is they identify only devices that are previously observed in a training set: if a radio signal from a new, unseen, device is passed through the classifier, the source device will be classified as one of the known devices. We propose a novel approach that facilitates new class detection without retraining a neural network, and perform extensive analysis of the proposed model both in terms of model parameters and real-world datasets. We accomplish this by first breaking down a longer transmission burst into smaller slices, and assessing classifier confidence on a new transmission based on per slice statistics: our approach detects a new device with 76% accuracy, while reducing the classification accuracy of 500 previously seen devices by no more than 10%.

We explore the resistance of deep learning methods for radio fingerprinting to MAC ID spoofing. We demonstrate that classifying transmission slices enables classification of a transmission with a fixed-length input deep classifier, enhances shift-invariance, and, most importantly, makes the classifier resistant to MAC ID spoofing. This is a consequence of the fact that the classifier does not learn to use the MAC ID to classifying among transmissions, but relies on other inherent discriminating signals, e.g., device imperfections. We demonstrate this via experiments on transmissions generated using two protocols, namely, WiFi and ADS-B.

A special permutation group of polar codes based on $N$ /4-cyclic shift is designed and analyzed for practical use. A permutation-transformation equivalence is firstly introduced to transfer the effect of permutation on the codeword side to the uncoded side. Then, we introduce the $N$ /4-cyclic shift permutation and analyze the conditions under which it can permute a codeword to another for polar codes that even do not fully respect partial order. We also reveal that the value assignment of frozen bits should follow specific rules related to the permutation pattern. Finally, a novel polar-specific implicit indication method is presented by applying the $N$ /4-cyclic shift permutation group to the practical wireless communication scenarios such as Physical Broadcasting Channel (PBCH) of a cellular network, which significantly simplifies the detection algorithm.