THE WORKS OF SPIRIDON MIKHAILOV (YANDUSH) IN THE ASPECT OF SOME HISTORICAL ETHNOLOGY PROBLEMS

S.M. Mikhailov (Yandush) distinguished two ethnographic groups and two dialects of the Chuvash ethnos. The scientist attributed the population of Kozmodemyansky and the northern part of Yadrinsky uyezds to the upper (Virjal) Chuvash, and that of Tsivisky and Cheboksary uyezds of Kazan province – to the lower (Anatri) ones. Starting with the works of G.I. Komissarov, a third (middle-level) group began to be allocated from the lower group. According to the scientist, the Chuvash, being a separate community of Turkic-speaking peoples, used to live in Zakamye, where they had migrated from Siberia. He developed the Turkic-Bulgarian theory of the Chuvash language origin and the main ethnographic groups (middle lower and lower) of the Chuvash ethnos. He considered the upper dialect to be a mixed group, in whose culture, in addition to Turkic-Bulgar elements he found many elements of the Finno-Ugrians (the mountain Mari and the Mordvins-Erzya), and partly Kazan Tatars. Prior to annexation of the Chuvash Region to the Moscow state, two ethnographic groups of the mountain Chuvash functioned on the right bank of the Volga – the upper and the middle lower. After settling the southern steppe regions, in the process of cultural dialogue with the Mishar Tatars, a third ethnographic group was formed, known to the middle lower Chuvash as the khirti “steppe”. In Modern times, the geographical location of the ethnographic groups of the Chuvash ethnos contributed to penetration of the ideas of the European-Russian Enlightenment in the Chuvash Region (from the western territories to the eastern and southern ones). In the 1950s of the XX century the ideas of the Chuvash enlightenment were first formulated by S.M. Mikhailov, and later they began to spread in the academic circles of the entire Volga region. His works remain a valuable source for identifying the adaptive scheme of the ethnos, which the Chuvash built by localizing the “evil” principle outside of themselves, their society, ethnos.

An Investigation of Adaptive Radius for the Covariance Localization in Ensemble Data Assimilation

The covariance matrix estimated from the ensemble data assimilation always suffers from filter collapse because of the spurious correlations induced by the finite ensemble size. The localization technique is applied to ameliorate this issue, which has been suggested to be effective. In this paper, an adaptive scheme for Schur product covariance localization is proposed, which is easy and efficient to implement in the ensemble data assimilation frameworks. A Gaussian-shaped taper function is selected as the localization taper function for the Schur product in the adaptive localization scheme, and the localization radius is obtained adaptively through a certain criterion of correlations with the background ensembles. An idealized Lorenz96 model with an ensemble Kalman filter is firstly examined, showing that the adaptive localization scheme helps to significantly reduce the spurious correlations in the small ensemble with low computational cost and provides accurate covariances that are similar to those derived from a much larger ensemble. The investigations of adaptive localization radius reveal that the optimal radius is model-parameter-dependent, vertical-level-dependent and nearly flow-dependent with weather scenarios in a realistic model; for example, the radius of model parameter zonal wind is generally larger than that of temperature. The adaptivity of the localization scheme is also illustrated in the ensemble framework and shows that the adaptive scheme has a positive effect on the assimilated analysis as the well-tuned localization.

High-Order Adaptive Scheme for Reactive Transport in Heterogeneous Porous Media

Subsurface sequestration of carbon dioxide, contaminant transport, and enhanced oil recovery processes often involve complex reaction dynamics. The rock-fluid interactions span a very wide range of length and time scales, and it is important for the numerical solutions to resolve these scales properly. To address these challenges, we extend the adaptive transport scheme for the simulation of reactive transport in heterogeneous porous media developed previously (Deucher and Tchelepi, 2021) to account for (a) higher-order approximation of the convective fluxes and (b) coupling with a chemical solver connected to geochemical databases. The numerical results demonstrate that adaptivity is more effective when a higher-order approximation of the fluxes is used. This is because of lower levels of numerical dispersion compared with low-order approximations, which helps resolve the displacement fronts more accurately. As a result, the regions that experience significant concentration and saturation gradients are more confined, and that leads to improvements in the computational efficiency of the adaptive scheme. The robustness of the approach is demonstrated using a highly heterogeneous two-phase case with multiple wells and a variable total liquid-rate. Due to the modularity of the adaptive scheme, coupling with a chemical solver module is straightforward. The scheme is tested for a three-dimensional case that considers injection of carbonated water in a reservoir matrix of calcite. The results show that the adaptive scheme leads to an accurate representation of the reference concentration distributions of the six reactive components throughout the simulation and leads to a large reduction in the number of cell updates required to achieve the solution.

An adaptive scheme for degradation suppression in Lidar based SLAM

Purpose With the booming development of computer, optical and sensing technologies and cybernetics, the technical research in unmanned vehicle has been advanced to a new era. This trend arouses great interest in simultaneous localization and mapping (SLAM). Especially, light detection and ranging (Lidar)-based SLAM system has the characteristics of high measuring accuracy and insensitivity to illumination conditions, which has been widely used in industry. However, SLAM has some intractable problems, including degradation under less structured or uncontrived environment. To solve this problem, this paper aims to propose an adaptive scheme with dynamic threshold to mitigate degradation. Design/methodology/approach We propose an adaptive strategy with a dynamic module is proposed to overcome degradation of point cloud. Besides, a distortion correction process is presented in the local map to reduce the impact of noise in the iterative optimization process. Our solution ensures adaptability to environmental changes. Findings Experimental results on both public data set and field tests demonstrated that the algorithm is robust and self-adaptive, which achieved higher localization accuracy and lower mapping error compared with existing methods. Originality/value Unlike other popular algorithms, we do not rely on multi-sensor fusion to improve the localization accuracy. Instead, the pure Lidar-based method with dynamic threshold and distortion correction module indeed improved the accuracy and robustness in localization results.

Mamdani-Type Fuzzy-Based Adaptive Nonhomogeneous Synchronization

The aim of this work is the design of an adaptive controller based on Mamdani-type fuzzy inference systems. The input control is constructed with saturation functions’ fuzzy-equivalents, which works as the adaptive scheme of the controller. This control law is designed to stabilize the error system to synchronize a pair of chaotic nonhomogeneous piecewise systems. Finally, an illustrative example as numerical evidence is developed.

A Frequency Adaptive Scheme Based on Newton Structure of PRRC for LCL-Type Inverter Connected with Weak Grid

Repetitive control (RC) is gradually used in inverters tied with weak grid. To achieve the zero steady-state error tracking of inverter current and compensate the harmonic distortion caused by frequency fluctuation, a frequency adaptive (FA) control scheme for LCL-type inverter connected with weak grid is proposed. This scheme adopts a proportional resonance (PR) controller in parallel with RC (PRRC) to overcome the disadvantages caused by RC inherent one-cycle time delay. A fractional delay (FD) filter based on the Newton structure is proposed to approximate the fraction item of fs/f, where fs and f are sample frequency and grid frequency, respectively. The structure of the proposed FD filter is relatively simple; moreover, coefficients of the filter maintain constant so as not to need online tuning even when grid frequency fluctuates, which decreases the computational burden considerably. The feasibility and effectiveness of the proposed FA control scheme, named as Newton-FAPRRC, are all verified by the simulation and experimental results.