A trend extraction method based on logistic functions and envelopes

A method of step characteristic trend extraction based on logistic functions and envelopes (LFEs) is proposed in this paper. Compared with the existing trend extraction methods, the LFE method can determine the starting position of the step trend using a logistic function and extract the local trend using upper and lower envelopes. This method enhances the extraction accuracy and reduces the computation time. To verify the effectiveness of the LFE method, a simulated signal with a step trend feature was compared with the five-spot triple smoothing method, wavelet transform method and empirical mode decomposition-based method. All of these methods were applied to a real shock signal. The results demonstrate that the LFE method can reliably and accurately extract the trends with step characteristics based on less prior knowledge. Moreover, the proposed technique is suitable for industrial online applications.

Velocity Multistability vs. Ergodicity Breaking in a Biased Periodic Potential

Multistability, i.e., the coexistence of several attractors for a given set of system parameters, is one of the most important phenomena occurring in dynamical systems. We consider it in the velocity dynamics of a Brownian particle, driven by thermal fluctuations and moving in a biased periodic potential. In doing so, we focus on the impact of ergodicity—A concept which lies at the core of statistical mechanics. The latter implies that a single trajectory of the system is representative for the whole ensemble and, as a consequence, the initial conditions of the dynamics are fully forgotten. The ergodicity of the deterministic counterpart is strongly broken, and we discuss how the velocity multistability depends on the starting position and velocity of the particle. While for non-zero temperatures the ergodicity is, in principle, restored, in the low temperature regime the velocity dynamics is still affected by initial conditions due to weak ergodicity breaking. For moderate and high temperatures, the multistability is robust with respect to the choice of the starting position and velocity of the particle.

A Novel Approach to Damage Assessment in Structures Based on Artificial Neural Network Working Parallel With a Hybrid Stochastic Optimization

Artificial neural network (ANN) is the study of computer algorithms that can learn from experience to improve performance. ANN employs backpropagation (BP) algorithms using gradient descent (GD)-based learning methods to reduce the discrepancies between predicted and real targets. Even though these differences are considerably decreased after each iteration, the network may still face major risks of being entrapped in local minima if complex error surfaces contain too numerous the best local solutions. To overcome those drawbacks of ANN, numerous researchers have come up with solutions to local minimum prevention by choosing a beneficial starting position that relies on the global search capability of other algorithms. This strategy possibly assists the network in avoiding the first local minima. However, a network often has many local bests widely distributed. Hence, the solution of choosing good starting points may no further be beneficial because the particles are probably entrapped in other local optimal solutions throughout the process of looking for the global best. Therefore, in this work, a novel ANN working parallel with the stochastic search capacity of evolutionary algorithms, is proposed. Additionally, to increase the efficiency of the global search capacity, a hybrid of particle swarm optimization and genetic algorithm (PSOGA) is applied during the process of seeking the best solution, which effectively guarantees to assist the network of ANN in escaping from local minima. This strategy gains both benefits of GD techniques as well as the global search capacity of PSOGA that possibly solves the local minima issues thoroughly. The effectiveness of ANNPSOGA is assessed using both numerical models consisting of various damage cases (single and multiple damages) and a free-free steel beam with different damage levels calibrated in the laboratory. The results demonstrate that ANNPSOGA provides higher accuracy than traditional ANN, PSO, and other hybrid ANNs (even a higher level of noise is employed) and also considerably decreases calculational cost compared with PSO.

Searching of the Source of Educational Inequality

Various approaches to investigating the sources of inequality in education are discussed in the paper. It is noted that data on the representation of students from families with various parental status at levels of education do not give a full picture of what is happening. Full-fledged interpretation requires to turn to a much larger amount of information, primarily because an influence of the family and the environment during the period of primary socialization is of decisive importance for the formation of chances in the educational sphere. The social experience of the family, the models of social behavior based on it, the developed cultural patterns, strategies, and tactics are important. At the same time, the orientations towards education are not fixed once and for all; they can be transformed if the general situation changes (for example, economic) or a directed influence is made (for example, pedagogical). The formed orientations are, as it were, a starting position and later sets the direction and speed of possible reflection on certain influences. The pandemic and the resulting intensification of distance learning have sharply increased the importance of motivation and other students’ qualities, formed during the period of primary socialization: they are critical for academic success. The accompanying growth of inequality in education has actualized the search for its sources to find means to overcome or at least reduce it. Equalization of opportunities for young people from all social groups is especially important for the growth of human potential.

HEXAPOD MOVEMENT ALGORITHMS TO AVOID INTERFERENCE. ANGULAR MOVEMENT

This paper considers the possibility of using a stepping robot - hexapod for research, monitoring the condition of technical dry channels, enclosed spaces and more. Compared to existing designs used today, the hexapod has a list of advantages that make it a more versatile tool, namely: autonomy, due to the power supply installed at work, design features that ensure its increased patency on uneven surfaces. Instead, this type of work requires the development of complex algorithms for movement than in the case of wheeled or tracked machines, ie. hexapod is a platform that moves the limbs, which in turn move with the help of servos. Therefore, the movement of the platform is provided by the control of each servo. In addition, environmental information is additionally processed from rangefinders, limb con-tact sensors with the surface, cameras, accelerometers, etc. Particular attention is paid to robot rotation algorithms, as the proposed scope imposes restrictions on the ability to maneuver freely in space. An algorithm for rotating robots in confined spaces based on limb state matrices has been developed, which greatly simplifies the practical implementation and allows to easily change the type of stroke during the hexapod operation. It is also proposed to introduce a buffer state matrix, which allows you to remember the last position of the limbs of the robot in case of its failure, after the elimination of which, it is possible to continue moving from any last state. Or return to the starting position and change the route. The versatility of the algorithm allows its use not only in the development of the software part of the hesapod, but also for other types of walking robots. Since the developed algorithm allows you to easily modify the types of moves at each iteration of the step. In the future, it is planned to test this algorithm on a model of a hexapod and supplement it with the necessary components for vertical movement, which is very important for passability in this area of application.

Mice identify subgoal locations through an action-driven mapping process

Mammals instinctively explore and form mental maps of their spatial environments. Models of cognitive mapping in neuroscience mostly depict map-learning as a process of random or biased diffusion. In practice, however, animals explore spaces using structured, purposeful, sensory-guided actions. Here we test the hypothesis that executing specific exploratory actions is a key strategy for building a cognitive map. Previous work has shown that in arenas with obstacles and a shelter, mice spontaneously learn efficient multi-step escape routes by memorizing allocentric subgoal locations. We thus used threat-evoked escape to probe the relationship between ethological exploratory behavior and allocentric spatial memory. Using closed-loop neural manipulations to interrupt running movements during exploration, we found that blocking runs targeting an obstacle edge abolished subgoal learning. In contrast, blocking other movements while sparing edge-directed runs had no effect on memorizing subgoals. Finally, spatial analyses suggest that the decision to use a subgoal during escape takes into account the mouse's starting position relative to the layout of the environment. We conclude that mice use an action-driven learning process to identify subgoals and that these subgoals are then integrated into a map-based planning process. We suggest a conceptual framework for spatial learning that is compatible with the successor representation from reinforcement learning and sensorimotor enactivism from cognitive science.

Leg Dominance and OSB12 Kick Start Performance in Young Competitive Swimmers

The purpose of this study was to examine differences in starting and kick-plate positions, pointing to an effect on kick-start performance with the dominant and non-dominant feet placed on the front edge of the OSB12 starting block. The sample included 20 female competitive swimmers whose average age was 16.1 ± 0.6 years. To assess swimmers’ lower body explosive strength and determine leg dominance, a triple hop distance test was administered. We determined the swimmers’ preferred starting position on a starting block in terms of the kick-plate setting and body position on the starting block. The results of our study demonstrate the importance of leg dominance and positioning on the OSB12 starting block. After the preferred starting position was determined, the optimal position for the kick start was selected. When the dominant leg was placed on the front edge of the starting block (p < 0.05; Cohen’s d—large effect), swimmers produced shorter block times and times to 2 and 5 m. For most of the tested swimmers, the optimal basic position on the starting block included neutral- and rear-weighted positions with the kick plate set to positions 3–4 and the right leg placed on the front edge of the OSB12 starting block.

Regime-sanctioned oligarchs

No oligarchic system, similar to those in Ukraine or Russia, developed in Belarus after 1991, but the formation of a group of prominent regime-linked businessmen has accelerated in recent years. They owe their influence to informal concessions from the regime to do business in selected sectors of the economy. They often do not take over state property but act as intermediaries, earning a hefty commission for doing so. They also operate in the criminal sphere, primarily involving the large-scale smuggling of goods into Russia and the European Union. This article aims to show the evolution and specifics of big business in Belarus. The growing capital potential of big Belarusian businessmen, estimated at a dozen or so, and their rising influence on the economic decisions made by the authorities while maintaining total political loyalty, make it justified to call at least some of them oligarchs. The system emerging in Belarus bears certain similarities to some post-Soviet oligarchic systems while having its own distinctive features. The accumulated capital and contacts give at least some of the emerging Belarusian oligarchs a good starting position for taking a front seat in a possible future political transformation, should the conditions arise for that to begin.

Champion Position Analysis in Short Track Speed Skating Competitions From 2007 to 2019

Purpose: Short track speed skating is a racing sport with racing tactics are equally crucial to speed and technical skating skills. Therefore, to investigate the relationship between starting and finishing positions for elite skaters and subsequently, explore pacing patterns for champions are necessary.Methods: To investigate a pattern of effective tactical positioning strategy, Kendall’s tau-b correlations between starting and finishing position were calculated, with 500 m races having the most positive correlation (0.347, P &lt; 0.05).Results: Furthermore, starting position distributions of winners in each round, as well as the fluctuations in champion starting positions across rounds were analyzed. Our findings showed that skaters on the first track were inclined to win the rounds in 500, 1,000, and 1,500 m (28, 28, and 22%, respectively), and the differences between starting and finishing positions for champions were minimized in semi-finals. Meanwhile, the pacing patterns were gaining more fluctuations by the increase of race distances for champions, as the average standard deviation of lap rankings equaled 0.90, 1.15, and 2.21 for 500, 1,000, and 1,500 m races, respectively.Conclusion: In conclusion, elite skaters should adopt flexible tactics at the lowest cost of energy consumption. The overall variability of lap ranking in long-distance races were distinctly higher than it in short distance.

How do users interact with Virtual Geographic Environments? Users’ behavior evaluation in urban participatory planning

For the past twenty years, the adoption of Virtual Geographic Environments is thriving. This democratization is due to numerous new opportunities offered by this medium. However, in participatory urban planning these interactive 3D geovisualizations are still labeled as very advanced means, and are only scarcely used. The involvement of citizens in urban decision-making is indeed carefully planned ahead to limit off-topic feedback. A better comprehension of Virtual Geographic Environments, and more specifically of users’ strategic behaviors while interacting with this medium could enhance participants’ contributions. The users’ strategic behavior was assessed in this article through an experimental study. A total of 107 participants completed online tasks about the identification of 3D scenes’ footprints, the comparison of buildings’ heights, and the visibility of objects through the scenes. The interactions of the participants were recorded (i.e. pressed keys, pointing device interactions), as well as the camera positions adopted to complete specific tasks. The results show that: (1) users get more efficient throughout the study; (2) interruptions in 3D manipulation appear to highlight difficulties in interacting with the virtual environments; (3) users tend to centralize their positions within the scene, notably around their starting position; (4) the type of task strongly affects the behavior of users, limiting or broadening their explorations. The results of this experimental study are a valuable resource that can be used to improve the design of future urban planning projects involving Virtual Geographic Environments, e.g. with the creation of personalized 3D tools.