Finite Sample Properties for Closed Loop System Identification

In this paper, after closed loop system identification is reviewed, asymptotic analysis and finite sample analysis for closed loop system identification are studied respectively, corresponding to the infinite data and finite data. More specifically, within the framework of infinite data, the cost function is modified to its simplified form, and one optimal feedback controller is obtained based on our own derivations. The simplified cost function and optimal feedback controller are benefit for practical application. Furthermore, the asymptotic variance of that optimal feedback controller is also yielded from the point of asymptotic analysis. In the case of finite data, finite sample properties are constructed for closed loop system identification, then one difference between the sampled identification criterion and its corresponding expected criterion is derived as an explicit form, which can bound one guaranteed interval for the sampled identification criterion. Finally, one simulation example is used to prove the efficiency of our proposed theories.

Morphometric analysis of the His bundle (atrioventricular fascicle) in humans and other animal species, associated with electrophysiological variables. Histological and immunohistochemical study

His bundle is a part of the specialized electrical conduction system that, in the normal or anormal hearts, provides connection between the atrial and ventricular myocardial compartments. The aim of this study was to perform a morphometric analysis of the characteristics of His bundle and its association with predetermined electrophysiological variables in humans, dogs, horses, and pigs. We used five hearts of the species studied. Histological sections of 5 µm thickness were obtained and stained with hematoxylin-eosin and Masson's trichrome. We also used the desmin and PAS method for precise identification of cells. His bundle was longer in horses (2.85 x 0.82 mm) and pigs (1.77 x 0.44 mm) than in dogs (1.53 x 0.26 mm) and humans, which was the shortest (1.06 x 0.23 mm). In His bundle cells, the area and diameters were significantly larger in pigs and horses than in humans (p < 0.001) and dogs (p < 0.001). We have found two patterns of organization of the components of His bundle: Group I, with large cells and a high amount of collagen fibers in ungulates (pigs and horses); group II, with smaller cells and less amount of collagen fibers in humans and dogs. Documenting differences in cell size in His bundle allows us to obtain an additional, alternative identification criterion to commonly used ones such as anatomical location. Morphological characteristics of His bundle and its cells in the different species studied coincide with rapid or slow transmission of the electrical impulse when compared with the predetermined electrophysiological variables.

RESULTS DESIGNING AND ANALYSIS WHEN INTRODUCING NEW BEVERAGE IDENTIFICATION CRITERIA

Building a digital profile of food product with use of modern mathematical apparatus of basic matrices is a solution to the problem of designing innovative beverage recipes. In this regard, for the effective use of the food resource base, modeling and production of high-quality food products, there is an acute problem of developing a methodology for identifying food products using the full range of the currently available analytical base. The article discusses an algorithm for constructing a flexible experimental design for the new identification criteria development, taking into account the laboratory research peculiarities in the beverage industry. The application of software in experiment designing is considered and a practical example of integrated designing based on the construction of an identification criterion for wine materials is presented.

Ethnic categorisation, identity and perceptions of life among Swedish Samis

To what extent do Swedish Samis identify their ethnicity as Sami, Swedish, or both? How do they meet various criteria for being allowed to register as voters to the Sami Parliament? What factors predict ethnicities? These questions are studied in randomised samples from the electoral roll for the Sami Parliament. Applying Berry’s model of acculturation, four types are constructed—separated, assimilated, integrated, and marginalised. The findings show that the integrated represent the great majority of Samis. The two groups who tend to choose one of the identities—Sami or Swedish—represent less than one third when combined and are about equal in size. Those marginalised with weak ethnic identities represent 2%. Although all meet the self-identification criterion of being Sami, few meet each of some ‘objective’ criteria, e.g. being involved in reindeer herding, having Sami as the home language or having parents or grandparents with Sami as the home language. The main predictors of a stronger Sami identity are cultural symbolic behaviours and heredity. The main negative predictor of a stronger Swedish identity among Samis is the use of cultural symbolic behaviours, and the main positive predictor is a positive estimate on the Swedish public opinion’s interest in Samis. The findings are discussed in relation to Sami debates on indigeneity.

Gait Recognition via Deep Learning of the Center-of-Pressure Trajectory

The fact that every human has a distinctive walking style has prompted a proposal to use gait recognition as an identification criterion. Using end-to-end learning, I investigated whether the center-of-pressure (COP) trajectory is sufficiently unique to identify a person with high certainty. Thirty-six adults walked for 30 min on a treadmill equipped with a force platform that continuously recorded the positions of the COP. The raw two-dimensional signals were sliced into segments of two gait cycles. A set of 20,250 segments from 30 subjects was used to configure and train convolutional neural networks (CNNs). The best CNN classified a separate set containing 2250 segments with an overall accuracy of 99.9%. A second set of 4500 segments from the six remaining subjects was then used for transfer learning. Several small subsamples of this set were selected randomly and used to fine tune the pretrained CNNs. Training with two segments per subject was sufficient to achieve 100% accuracy. The results suggest that every person produces a unique trajectory of underfoot pressures while walking and that CNNs can learn the distinctive features of these trajectories. By applying a pretrained CNN (transfer learning), a couple of strides seem enough to learn and identify new gaits. However, these promising results should be confirmed in a larger sample under realistic conditions.

О КАЛИБРОВКЕ АВТОНОМНОЙ МОДЕЛИ ТУНДРОВОЙ БИОЛОГИЧЕСКОЙ ПОПУЛЯЦИИ ЛЕММИНГОВ

The paper presents an autonomous model of the biological population of lemmings of a phenomenological type, designed in complex studies of tundra communities. In the model, the dynamics of a population is described through a difference equation relating the population in two neighboring years that depends on three parameters of the biological and ecological genesis. The combination of parameter values included in the equation under consideration determines a class of one-dimensional unimodal mappings of a dynamical system in which the bifurcation properties, asymptotics, and stability of trajectories were analytically and numerically studied. In this paper the main focus is made on model identification criterion. The method of identification sets is proposed to be used for calibration of the model. The identification sets method is based on the approximation and visualization of small-dimensional projections of a multidimensional graph of the error function given in the space of three environmental and two population parameters. This paper describes a case study of model identification using data on the tundra lemming population on the Taimyr Peninsula. It is shown that in this case two biological and ecological parameters allow for stable location distribution.

A Novel Protection and Location Scheme for Pole-to-Pole Fault in MMC-MVDC Distribution Grid

Nowadays, the efficient and reliable protection and location schemes for MMC-MVDC (Modular Multilevel Converter-Medium Voltage Direct Current) grid are few. This paper is the first to propose a scheme to not only protect the feeders and the busbar, but locate the segments in MMC-MVDC grid. To improve the reliability, this paper analyzes the transient characteristics of the pole-to-pole fault and then obtains the characteristic frequency band. Based on S-transform, STCFB (S-transform characteristic frequency band) Phase of fault component is utilized to construct the identification criterion for faulty feeder and faulty segment. The whole scheme can be divided into three steps, namely, protection starting criterion, faulty feeder and busbar protection criterion, and faulty segment location criterion. Firstly, the current gradient method is utilized to quickly detect the fault and start the protection device. Secondly, the non-unit protection criterion on busbar and feeders is proposed according to STCFB Phase of the voltage and current fault component. Thirdly, according to the STCFB Phase on both sides of the feeder segment, the faulty segment can be located. A radial MMC-MVDC distribution network model was built in PSCAD/EMTDC software to evaluate the performance of the protection and location method. Simulation results for different cases demonstrate that the proposed scheme has high accuracy, good adaptability and reliability.